CRANberries

Fri, 06 Nov 2026

New package streetlamp with initial version 0.2.0
Package: streetlamp
Title: Panel Econometrics for the Effect of Police Stop and Search on Recorded Crime
Version: 0.2.0
Description: Builds an area-by-month panel of recorded crime in England and Wales from the data.police.uk bulk archive <https://data.police.uk/data/archive/>, attaches stop and search intensity as a treatment variable, and provides a panel-econometrics toolkit for evaluating policing interventions: two-way fixed effects, event studies, difference-in-differences with staggered adoption, synthetic control, spatial spillover and displacement models, and stop-crime elasticities by offence type. Area boundaries are read from the Office for National Statistics Open Geography Portal <https://geoportal.statistics.gov.uk/>, Census 2021 population from the 'Nomis' API <https://www.nomisweb.co.uk/api/v01/help>, and notes of re-supplied and missing force data from the data.police.uk change log <https://data.police.uk/changelog/>. Every panel carries a contract recording provenance, coverage, geography vintage and treatment definition; every estimator names its identifying assumption and [...truncated...]
License: MIT + file LICENSE
URL: https://github.com/BlackThrive/streetlamp, https://blackthrive.github.io/streetlamp/
BugReports: https://github.com/BlackThrive/streetlamp/issues
Depends: R (>= 4.1.0)
Imports: cli, did, digest, dplyr, fixest, generics, ggplot2 (>= 3.5.0), grDevices, grid, httr2, rlang (>= 1.1.0), sf, spdep, stats, tibble, tidyr, tools, utils, withr
Suggests: didimputation, httptest2, knitr, rmarkdown, spelling, strucchange, Synth, testthat (>= 3.0.0), vdiffr
VignetteBuilder: knitr
Encoding: UTF-8
Language: en-GB
NeedsCompilation: no
Packaged: 2026-10-22 18:13:20 UTC; musta
Author: Mustapha Wasseja [aut, cre], Souci Frissa [aut], Sarah Hamed [aut], Black Thrive Global [cph, fnd]
Maintainer: Mustapha Wasseja <muswaseja@gmail.com>
Repository: CRAN
Date/Publication: 2026-11-06 17:10:02 UTC

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New package chiplot with initial version 0.1.0
Package: chiplot
Title: Chi-Plots for Assessing Bivariate and Multivariate Dependence
Version: 0.1.0
Description: Graphical methods for assessing dependence. The chi-plot of Fisher and Switzer (1985) <doi:10.1093/biomet/72.2.253> and (2001) <doi:10.1198/000313001317098248> supplements a scatterplot of two variables, producing characteristic patterns for different forms of association. Its multivariate extension (Fisher and Lee, 2026) uses generalized orthants and data depth to explore whether a multivariate distribution factorizes into independent blocks of variables, with permutation tests and guidelines. Functions are provided for single chi-plots, a scatterplot matrix with chi-plots above the diagonal, multivariate chi-plots for a given partition of the variables, and a search over all partitions. Computation-intensive parts are written in C.
License: GPL (>= 2)
Encoding: UTF-8
Depends: R (>= 4.0.0)
Imports: graphics, grDevices, stats
Suggests: fda.usc
LazyData: true
NeedsCompilation: yes
Packaged: 2026-10-23 04:35:39 UTC; Nick
Author: Nicholas I. Fisher [aut, cre, cph], Alan J. Lee [aut], ValueMetrics Australia [cph]
Maintainer: Nicholas I. Fisher <nif@valuemetrics.com.au>
Repository: CRAN
Date/Publication: 2026-11-06 17:10:11 UTC

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New package SITSAR with initial version 1.0.0
Package: SITSAR
Title: Information Theory, Geometry and Statistics for Synthetic Aperture Radar Data
Version: 1.0.0
Description: Statistical models, information-theoretic measures and image analysis tools for Synthetic Aperture Radar (SAR) and polarimetric SAR (PolSAR) data. It implements intensity models (Gamma, generalized Gamma and G0I) and matrix models (scaled complex Wishart, G0 polarimetric and the compound truncated Poisson and compound geometric complex Wishart laws), maximum likelihood and expectation-maximization estimation, closed-form Shannon entropies with their asymptotic variances, entropy-based hypothesis tests and change detection, entropy-based image segmentation by (stochastic) expectation-maximization, stochastic distances and a family of divergence-based classifiers (Kullback-Leibler, Jeffreys, Bhattacharyya and Renyi) for Gaussian vector features and complex Wishart matrix features. The main tools are 'R6' classes and the classifiers are available as a 'parsnip' model, so they can be used inside 'tidymodels' workflows. Methods are described in Ferreira, Coelho and Nascimento (2021) <doi [...truncated...]
License: MIT + file LICENSE
URL: https://github.com/jodavid/SITSAR, https://jodavid.github.io/SITSAR/
BugReports: https://github.com/jodavid/SITSAR/issues
Depends: R (>= 4.1.0)
Imports: generics, graphics, grDevices, parsnip (>= 1.0.0), R6 (>= 2.5.0), rlang, stats, tibble, utils
Suggests: dials, knitr, recipes, rmarkdown, rsample, testthat (>= 3.0.0), tune, workflows, yardstick
VignetteBuilder: knitr
Encoding: UTF-8
Language: en-US
LazyData: true
LazyDataCompression: xz
NeedsCompilation: no
Packaged: 2026-10-22 21:11:02 UTC; jodavid
Author: Jodavid Ferreira [aut, cre] , Abraao Nascimento [aut]
Maintainer: Jodavid Ferreira <jodavid@protonmail.com>
Repository: CRAN
Date/Publication: 2026-11-06 16:20:02 UTC

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New package phylorug with initial version 0.1.0
Package: phylorug
Title: Visualize Clade Recovery and Support Across Phylogenetic Trees
Version: 0.1.0
Description: Generates rug plot visualizations directly on tree nodes to illustrate clade recovery and support from multiple phylogenetic and phylogenomic analyses. As modern studies routinely employ diverse datasets and inference techniques producing potentially conflicting trees, 'phylorug' simplifies the comparison among these trees by consolidating clade recovery and support on a reference tree.
License: MIT + file LICENSE
URL: https://github.com/mdrifathahamed/phylorug, https://mdrifathahamed.github.io/phylorug/
BugReports: https://github.com/mdrifathahamed/phylorug/issues
Depends: R (>= 4.1.0)
Imports: ape, graphics, grDevices, phangorn, stats, tools, utils
Suggests: knitr, mockery, rmarkdown, testthat (>= 3.0.0)
Encoding: UTF-8
LazyData: true
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-10-23 08:02:53 UTC; 1
Author: Md Rifath Ahamed [aut, cre, cph] , J. Salvador Arias [aut] , Sergei Tarasov [aut]
Maintainer: Md Rifath Ahamed <rifathahamed777@gmail.com>
Repository: CRAN
Date/Publication: 2026-11-06 16:50:02 UTC

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New package gpqyouden with initial version 0.1.0
Package: gpqyouden
Title: Generalized Pivotal Quantity Inference for the Youden Index
Version: 0.1.0
Description: Monte Carlo simulation study of generalized pivotal quantity (GPQ) based confidence intervals for the Youden index and its optimal cut-point, following Lai, Tian and Schisterman (2012) <doi:10.1016/j.csda.2010.11.023>.
License: MIT + file LICENSE
URL: https://github.com/jolmedilla/gpqyouden
BugReports: https://github.com/jolmedilla/gpqyouden/issues
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: parallel, kableExtra, dplyr, tidyr, stats, utils
Suggests: foreach, doParallel, roxygen2, testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-10-23 08:19:56 UTC; juanjo
Author: Juan Jose Olmedilla Arregui [aut, cre]
Maintainer: Juan Jose Olmedilla Arregui <juanjo@olmedilla.com>
Repository: CRAN
Date/Publication: 2026-11-06 16:50:08 UTC

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New package form.model with initial version 0.3.2
Package: form.model
Title: Neutral Versioned Form Definitions and Workbook Layouts
Version: 0.3.2
Description: Loads explicit YAML resources describing versioned forms, fields, declarative constraints, reference requirements, and workbook layouts. Checks model definitions against an installed YAML schema and consistency rules, and provides value-like inspection APIs. Does not validate submitted data or connect to external services.
License: LGPL-2.1
URL: https://ultreia-io.github.io/form.model/, https://github.com/ultreia-io/form.model
BugReports: https://github.com/ultreia-io/form.model/issues
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: yaml (>= 2.3.10)
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-10-23 05:23:05 UTC; tchemit
Author: Tony Chemit [aut, cre]
Maintainer: Tony Chemit <dev@tchemit.fr>
Repository: CRAN
Date/Publication: 2026-11-06 16:40:21 UTC

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New package rplam with initial version 1.0.2
Package: rplam
Title: Robust Estimators for Partially Linear Additive Models
Version: 1.0.2
Description: Robust estimation for partially linear additive models based on B-splines. The package implements a robust proposal that combines robust linear MM-regression estimators, which use an initial S-estimator followed by an M-estimation step with fixed scale, and B-spline approximations. The M-estimation step uses Tukey's bisquare function. The least-squares counterpart is also implemented. See Boente and Martínez (2023) <doi:10.1016/j.csda.2022.107611> for more details. The package also provides robust and least-squares estimators for additive models, that is, when the covariates enter only the nonparametric component of the model.
License: GPL-3
Imports: fda, stats, robustbase
Suggests: knitr, rmarkdown
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2026-10-22 22:59:37 UTC; alejandra
Author: Alejandra Mercedes Martinez [aut, cre]
Maintainer: Alejandra Mercedes Martinez <ale_m_martinez@hotmail.com>
Repository: CRAN
Date/Publication: 2026-11-06 12:30:02 UTC

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New package mzimp with initial version 0.1.0
Package: mzimp
Title: Zero-Inflated Mixed Poisson Regression for Multivariate Count Data
Version: 0.1.0
Description: Fits and selects zero-inflated mixed Poisson models for multivariate count regression. Supports multiple mixing distributions and variance specifications for flexible marginal modeling, while allowing dependence in the structural-zero components and latent mixing intensities to be modeled separately through copulas. The methodology is described in Nguyen (2026) <doi:10.48550/arXiv.2608.12732>.
License: GPL (>= 3)
Encoding: UTF-8
Imports: Rcpp, numDeriv, MASS, statmod, VineCopula, codetools, mvtnorm, pbivnorm, pkgload, ps, randtoolbox
LinkingTo: Rcpp, RcppArmadillo
Suggests: knitr, rmarkdown, PLNmodels
NeedsCompilation: yes
Packaged: 2026-10-23 02:05:50 UTC; AD
Author: Quang Huy Nguyen [aut, cre, cph]
Maintainer: Quang Huy Nguyen <huynqtkt@neu.edu.vn>
Repository: CRAN
Date/Publication: 2026-11-06 13:00:07 UTC

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New package EpiExposure with initial version 0.1.0
Package: EpiExposure
Title: Exposure-Lag-Response Modeling for Plant Disease Epidemiology
Version: 0.1.0
Description: Supports modeling and interpretation of environmental exposure-lag-response relationships in plant disease epidemiology using distributed lag non-linear models (DLNMs). Provides functions for defining complete exposure profiles, evaluating model identifiability, summarizing lag-specific and period-specific effects, performing sensitivity analyses, simulating environmental exposure scenarios, predicting plant disease outcomes, quantifying yield and economic losses, and evaluating individual and ensemble models. Supports harmonized frequentist and Bayesian modeling workflows. Builds on the framework implemented in the 'dlnm' package and described by Gasparrini (2011) <doi:10.18637/jss.v043.i08>.
Depends: R (>= 4.1)
Imports: dlnm, stats, glmmTMB, brms, spaMM, rlang, mgcv, nlme, ggplot2, scales
Suggests: dplyr, tidyr, purrr, tidyselect, INLA, knitr, rmarkdown, testthat (>= 3.0.0), pkgdown, readxl, patchwork, metR, bdlnm, cowplot, future, sn, future.apply
Additional_repositories: https://inla.r-inla-download.org/R/stable
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
LazyDataCompression: xz
VignetteBuilder: knitr
URL: https://github.com/tomazrg/EpiExposure, https://tomazrg.github.io/EpiExposure/
BugReports: https://github.com/tomazrg/EpiExposure/issues
NeedsCompilation: no
Packaged: 2026-10-23 03:10:21 UTC; RTomaz
Author: Ricardo Gomes Tomaz [aut, cre] , Emerson M. Del Ponte [aut] , Felipe Dalla Lana [aut]
Maintainer: Ricardo Gomes Tomaz <ricardogomesagro@gmail.com>
Repository: CRAN
Date/Publication: 2026-11-06 13:00:22 UTC

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New package drasR with initial version 0.1.0
Package: drasR
Title: Drift-Aware Risk-Guaranteed Acceptance Sampling
Version: 0.1.0
Description: Implements drift-aware risk-guaranteed acceptance sampling methods for adaptive lot disposition. The package provides tools for classical acceptance sampling, producer-risk and consumer-risk assessment, exponentially weighted moving average drift monitoring, adaptive tightening policies, decision fragility analysis, and safety-cost Pareto frontier construction. Classical binomial acceptance-plan design is described in the NIST/SEMATECH e-Handbook of Statistical Methods <https://www.itl.nist.gov/div898/handbook/pmc/section2/pmc232.htm>. Exponentially weighted moving averages follow Roberts (1959) <doi:10.1080/00401706.1959.10489860>. The methods are intended for simulation studies, supplier quality monitoring, and audit-oriented inspection decision support.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: stats, graphics, utils
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
URL: https://github.com/zerish12/drasR
BugReports: https://github.com/zerish12/drasR/issues
LazyData: true
NeedsCompilation: no
Packaged: 2026-10-23 00:17:04 UTC; muhammadzahirkhan
Author: Muhammad Zahir Khan [aut, cre]
Maintainer: Muhammad Zahir Khan <zahirstat007@gmail.com>
Repository: CRAN
Date/Publication: 2026-11-06 12:30:07 UTC

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New package DielectricWaterR with initial version 0.2.0
Package: DielectricWaterR
Title: Auditing and Exploring Dielectric Measurements of Water
Version: 0.2.0
Description: Imports, audits, compares and visualises dielectric measurements of water under fuel contamination and ageing. Provides descriptive summaries, frequency-response comparisons, confidence intervals based on physical-unit means, and training and testing splits that keep observations from the same experimental unit together. Experimental-unit safeguards address pseudoreplication concerns discussed by Hurlbert (1984) <doi:10.2307/1942661>. Grouped splitting is consistent with the structured-data validation principles discussed by Roberts et al. (2017) <doi:10.1111/ecog.02881>. Student t confidence intervals use the standard mean-interval formula described in the NIST/SEMATECH e-Handbook of Statistical Methods <https://www.itl.nist.gov/div898/handbook/eda/section3/eda352.htm>. Experimental-unit identifiers are supplied by the user and are not inferred from material labels. This research prototype does not provide validated contaminant prediction or causal inference.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: readxl, ggplot2, dplyr, tidyr, rlang, stats
Suggests: testthat
NeedsCompilation: no
Packaged: 2026-10-23 01:25:21 UTC; muhammadzahirkhan
Author: Muhammad Zahir Khan [aut, cre], Luqman Abidoye [aut]
Maintainer: Muhammad Zahir Khan <zahirstat007@gmail.com>
Repository: CRAN
Date/Publication: 2026-11-06 12:40:14 UTC

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New package causalMed with initial version 0.1.3
Package: causalMed
Title: Parametric G-Formula for Longitudinal Mediation and Total Effects
Version: 0.1.3
Description: Causal mediation analysis for longitudinal data with time-varying exposures, mediators and confounders, covering both interventional (Lin et al. (2017) <doi:10.1002/sim.7426>) and natural (Zheng and van der Laan (2017) <doi:10.1515/jci-2016-0006>) direct and indirect effects. Estimation uses the parametric g-formula (Robins (1986) <doi:10.1016/0270-0255(86)90088-6>), which is also exposed directly so that counterfactual means or risks can be estimated under static, dynamic or time-varying hypothetical interventions.
Depends: R (>= 3.5.1)
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Imports: data.table, nnet, future, future.apply, progressr
Suggests: gfoRmula, Hmisc, knitr, rmarkdown, survival, testthat
URL: https://github.com/adayim/causalMed, https://adayim.github.io/causalMed/
BugReports: https://github.com/adayim/causalMed/issues
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-10-22 22:57:47 UTC; alim
Author: Alimu Dayimu [aut, cre] , Xingling Guo [aut]
Maintainer: Alimu Dayimu <ad938@cam.ac.uk>
Repository: CRAN
Date/Publication: 2026-11-06 12:30:14 UTC

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New package bigcurve with initial version 0.6.0
Package: bigcurve
Title: Adaptive Densification of Lines for Map Projections
Version: 0.6.0
Description: Densify lines adaptively, as required by the curvature a map projection imposes on them. Edges are read as great circle arcs, and vertices are inserted along them only where the projected curve deviates from a straight chord by more than a tolerance measured on the map, following the adaptive resampling method of the 'd3-geo' 'JavaScript' library described in Bostock (2016) <https://github.com/d3/d3-geo>. Projections are computed with the 'PROJ' coordinate transformation library (<https://proj.org/>), so any coordinate reference system it supports can be a target. Inputs can be coordinate matrices, segment meshes or vertex pool topology from 'wkpool', and edges shared by neighbouring polygons receive identical new vertices.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: stats
URL: https://github.com/hypertidy/bigcurve, https://hypertidy.github.io/bigcurve/
BugReports: https://github.com/hypertidy/bigcurve/issues
Suggests: geographiclib, knitr, maps, PROJ, rmarkdown, s2, testthat (>= 3.0.0), textures, wk, wkpool (>= 0.4.0)
VignetteBuilder: knitr
LinkingTo: cpp11
SystemRequirements: PROJ (>= 8.0.0): libproj-dev (deb), proj-devel (rpm), proj (brew)
NeedsCompilation: yes
Packaged: 2026-10-23 00:34:54 UTC; mdsumner
Author: Michael D. Sumner [aut, cre, cph], Simon Wotherspoon [ctb] , Mike Bostock [ctb, cph]
Maintainer: Michael D. Sumner <mdsumner@gmail.com>
Repository: CRAN
Date/Publication: 2026-11-06 12:40:09 UTC

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Wed, 04 Nov 2026

New package ggindex with initial version 0.1.0
Package: ggindex
Title: Numbered Focus Points for 'ggplot2' Scatter Plots
Version: 0.1.0
Description: A 'ggplot2' geom that highlights selected points of a scatter plot with numbered markers and lists their descriptions in a legend keyed by the same numbers, as on an annotated map.
License: MIT + file LICENSE
URL: https://github.com/discindo/ggindex, https://discindo.github.io/ggindex/
BugReports: https://github.com/discindo/ggindex/issues
Depends: R (>= 4.1)
Imports: ggplot2 (>= 4.0.0), grid, scales
Suggests: quarto, sf, testthat (>= 3.0.0), vdiffr
VignetteBuilder: quarto
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-10-22 18:30:47 UTC; novica
Author: Teofil Nakov [aut] , Novica Nakov [aut, cre] , Discindo [cph]
Maintainer: Novica Nakov <nnovica@gmail.com>
Repository: CRAN
Date/Publication: 2026-11-04 22:10:02 UTC

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New package F2Adonis2 with initial version 0.1.1
Package: F2Adonis2
Title: PERMANOVA using the F2 Statistic
Version: 0.1.1
Language: en-US
Description: Implements the F2 statistic of Anderson et al. (2017) <doi:10.1111/anzs.12176> for permutational multivariate analysis of variance (PERMANOVA) on dissimilarity matrices. The F2 statistic uses group-specific dispersion estimates, so group centroids can be compared when dispersions differ and group sizes are unequal. P-values are obtained by permutation, bootstrap, or bias-adjusted bootstrap. The formula interface follows 'adonis2()' in the 'vegan' package.
License: GPL-2
Encoding: UTF-8
Imports: stats, vegan (>= 2.7-3)
Depends: R (>= 4.1.0)
LazyData: true
Suggests: knitr, rmarkdown, dplyr, ggplot2, onewaytests, yarrr, combinat, kableExtra, testthat (>= 3.0.0)
VignetteBuilder: knitr
URL: https://github.com/LakviruPerera/F2Adonis2
BugReports: https://github.com/LakviruPerera/F2Adonis2/issues
NeedsCompilation: no
Packaged: 2026-10-22 16:37:49 UTC; lakud
Author: Lakviru Perera [aut, cre, cph] , Mark Greenwood [aut]
Maintainer: Lakviru Perera <korathotagelaperera@montana.edu>
Repository: CRAN
Date/Publication: 2026-11-04 22:20:02 UTC

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New package SCMs with initial version 0.1.1
Package: SCMs
Title: Specification Curve Analysis for Synthetic Control Methods
Version: 0.1.1
Author: Zubin Jelveh [aut, cre]
Maintainer: Zubin Jelveh <zjelveh@umd.edu>
License: GPL-3
URL: https://github.com/zjelveh/SCMs
BugReports: https://github.com/zjelveh/SCMs/issues
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: CVXR (>= 1.9.0), ECOSolveR, dplyr (>= 1.0.7), foreach (>= 1.5.1), ggplot2 (>= 3.3.3), gtable, kernlab, cowplot, optimx, data.table, methods, parallel, purrr (>= 0.3.4), R6, stats, stringr (>= 1.4.0), tibble (>= 3.1.2), tidyr (>= 1.1.3), utils, doParallel, glmnet, gridtext, gridExtra, generics
Description: Estimates synthetic control models while exposing the implementation choices that define the synthetic counterfactual: how matching variables are constructed, how predictor weights are set, which constraints the donor weights satisfy (simplex, lasso, ridge, penalized), whether an intercept is included, and which outcome model corrects for bias (OLS, ridge, lasso, augmented synthetic control). Runs specification-curve analysis over a grid of these choices (Simonsohn, Simmons and Nelson (2020) <doi:10.1038/s41562-020-0912-z>), with placebo-in-space and bootstrap inference for single specifications and placebo inference for the curve as a whole, and uses 'xgboost' models with SHAP values (Lundberg and Lee (2017) <doi:10.48550/arXiv.1705.07874>) to show which choices drive the estimates. Methods follow Abadie, Diamond and Hainmueller (2010) <doi:10.1198/jasa.2009.ap08746>, Abadie (2021) <doi:10.1257/jel.20191450>, Ben-Michael, Feller and Rothstein (2021) <doi:10. [...truncated...]
Suggests: testthat (>= 3.0.0), clarabel, broom, xgboost, knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-10-22 14:38:28 UTC; zjelveh
Repository: CRAN
Date/Publication: 2026-11-04 21:40:13 UTC

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New package rplatypus with initial version 0.2.1
Package: rplatypus
Title: Computer Vision for Medical Imaging
Version: 0.2.1
Description: Semantic segmentation and object detection for medical images, from a folder of pictures to a trained model and a figure, in a handful of lines or one configuration file. Architectures, losses and training run on 'PyTorch' through 'pyplatypus', a 'Python' package which is installed and isolated automatically; nothing has to be set up by hand. R keeps the parts that make an analysis fast - reading and combining masks, drawing boxes, plotting, comparing models.
License: MIT + file LICENSE
URL: https://github.com/maju116/rplatypus, https://maju116.github.io/rplatypus/
BugReports: https://github.com/maju116/rplatypus/issues
SystemRequirements: Python (>= 3.10). Not a prerequisite the user installs: the package declares what it needs through 'reticulate' and 'uv' provisions an isolated environment on first use, leaving any system Python untouched.
Encoding: UTF-8
Depends: R (>= 4.1)
Imports: ggplot2, grDevices, parallel, rlang, reticulate (>= 1.41), tools, utils
Suggests: callr, jsonlite, knitr, pkgload, png, RNifti, rmarkdown, testthat (>= 3.0.0), withr, yaml
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-10-22 17:27:58 UTC; maju116
Author: Michal Maj [aut, cre]
Maintainer: Michal Maj <michalmaj116@gmail.com>
Repository: CRAN
Date/Publication: 2026-11-04 22:00:02 UTC

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New package kpqc with initial version 0.1.0
Package: kpqc
Title: Korean Post-Quantum Cryptography Algorithms
Version: 0.1.0
Copyright: see file COPYRIGHTS
Description: Provides synchronous interfaces to four algorithms for post-quantum cryptography: 'AIMer', a digital-signature algorithm based on symmetric primitives; 'HAETAE', a module-lattice-based digital-signature algorithm; and 'NTRU+' and 'SMAUG-T', lattice-based key-encapsulation algorithms. These algorithms were selected by the Korean Post-Quantum Cryptography competition. Native reference implementations are compiled into the package and use operating-system entropy for key generation, signing, and encapsulation.
License: MIT + file LICENSE
URL: https://github.com/KpqC/kpqc-r
BugReports: https://github.com/KpqC/kpqc-r/issues
Depends: R (>= 3.6.0)
Encoding: UTF-8
SystemRequirements: C11
NeedsCompilation: yes
Packaged: 2026-10-22 13:43:27 UTC; osuolfou
Author: Owen Suolfou [aut, cre]
Maintainer: Owen Suolfou <osuolfou@gmail.com>
Repository: CRAN
Date/Publication: 2026-11-04 21:10:02 UTC

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New package ezrsurvey with initial version 0.7.1
Package: ezrsurvey
Title: Single-Line Helpers for Consumer Survey Analysis
Version: 0.7.1
Description: Simplifies the day-to-day work of research and insights professionals who analyse consumer and customer survey data but have limited coding experience. Wraps common 'tidyverse' patterns into single-line functions for the tasks these teams repeat constantly: loading and combining survey exports, turning questions into percentages and summaries, recoding rating and Net Promoter scales, deriving demographics such as age cohorts and regions, modelling the drivers of satisfaction, checking sampling precision, selecting illustrative open-text comments, and producing presentation-ready charts and reports. A simulated consumer-survey dataset is included for learning and examples. Weighting rakes to target margins as in Deming and Stephan (1940) <doi:10.1214/aoms/1177731829> and reports the design effect of Kish (1965, ISBN:978-0-471-10949-5); driver models use the relative weights of Johnson (2000) <doi:10.1207/S15327906MBR3501_1> or the random forests of Breiman (2001) <doi:10. [...truncated...]
License: MIT + file LICENSE
URL: https://mashud37.github.io/ezr-research/ezr-survey/, https://github.com/mashud37/ezr-research
BugReports: https://github.com/mashud37/ezr-research/issues
Encoding: UTF-8
Language: en-GB
LazyData: true
Depends: R (>= 4.1.0), dplyr (>= 1.1.0), ggplot2, tidyr (>= 1.2.0), tibble, readr, stringr, purrr
Imports: rlang (>= 1.0.0), withr
Suggests: rwa, randomForest, treemapify, ggrepel, scales, officer (>= 0.6.0), flextable, openxlsx2, xml2, systemfonts, quarto, knitr, rmarkdown, svglite, writexl, yaml, stopwords, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-10-22 14:42:37 UTC; andreas
Author: Andreas Schellewald [aut, cre]
Maintainer: Andreas Schellewald <aschellewald@acm.org>
Repository: CRAN
Date/Publication: 2026-11-04 21:40:02 UTC

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New package mdiharmonize with initial version 0.1.0
Package: mdiharmonize
Title: Harmonize Confidential Firm-Level Microdata into a Common Format
Version: 0.1.0
License: GPL-3
URL: https://github.com/Secretariat-CompNet/mdiharmonize
BugReports: https://github.com/Secretariat-CompNet/mdiharmonize/issues
Description: Harmonizes confidential firm-level microdata held at national statistical institutes into one common structure, so that the same analysis code runs unchanged in every country. Metadata tables describe each institute's raw files and map their variables to the common ones; the functions read the raw files, apply the mapping (revaluing, recoding, reclassifying, redefining and remapping), make industry, product and regional classifications consistent over time, switch between enterprise, firm and plant identifiers, and add capital stocks computed with the perpetual inventory method. Quality checks on the harmonized data report duplicate keys, type conversion losses, breaks in yearly statistics and jumps in missing values, and outputs pass statistical disclosure control before they leave the institute. Builds on the analysis tools in 'mditools'. Capital stocks via the perpetual inventory method follow OECD (2009) <doi:10.1787/9789264068476-en>; disclosure control applies the minimum-f [...truncated...]
Encoding: UTF-8
Imports: data.table, dplyr, grDevices, haven, igraph, mditools (>= 0.1.1), openxlsx, stats, stringr, tools, utils
Suggests: askpass, bit64, ggplot2, gridExtra, readr, RODBC, testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-10-22 13:13:01 UTC; johanna
Author: Daniele Aglio [aut], Eric Bartelsman [aut], Julian Diaz-Acosta [aut], Mirja Haelbig [aut], Marco Miorandi [aut], Johanna Weiss [aut, cre], Jose Alberto Ferreira [ctb], Elena Sponga [ctb], Reetuparna Vishwanath [ctb], Chengzi Yi [ctb], Alessandro Zona [...truncated...]
Maintainer: Johanna Weiss <johanna.weiss@iwhesl.onmicrosoft.com>
Repository: CRAN
Date/Publication: 2026-11-04 20:30:02 UTC

More information about mdiharmonize at CRAN
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New package IMW with initial version 1.1
Package: IMW
Title: Incremental Moment Windows
Version: 1.1
Date: 2026-10-08
Description: Computes rolling statistics, including the mean, variance, skewness, and kurtosis, over moving windows. The package uses incremental algorithms to efficiently update statistics as new observations arrive, supporting both online computation and batch processing for time-series analysis and streaming data applications. Implemented in C++, the package provides a high-performance, header-only implementation that facilitates direct integration into other packages.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: Rcpp (>= 1.0.4.6)
LinkingTo: Rcpp
NeedsCompilation: yes
Packaged: 2026-10-22 12:25:55 UTC; svilsen
Author: Soeren B. Vilsen [aut, cre]
Maintainer: Soeren B. Vilsen <svilsen@mp.aau.dk>
Repository: CRAN
Date/Publication: 2026-11-04 20:10:02 UTC

More information about IMW at CRAN
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New package DDAWASS with initial version 1.0.0
Package: DDAWASS
Title: Discrete Distribution Data Analysis with Wasserstein Distance
Version: 1.0.0
Date: 2026-10-21
Description: S4 classes and methods for the analysis of data described by discrete distributions with finite support (e.g. frequency distributions of ratings, scores or counts observed on groups of individuals), using the L2 Wasserstein metric between quantile functions. It is the discrete counterpart of 'HistDAWass' and provides exact Wasserstein distances (in C++), barycenters, Wasserstein variance, covariance and correlation, k-means and hierarchical clustering, quantile-based principal component and multiple factor analysis, two-component linear regression and reliability (Cronbach's alpha) indices. See Crocetta, Irpino, Antonucci and Marin (2025) <doi:10.1007/s11135-024-01956-0>.
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
Depends: R (>= 4.0.0), methods
Imports: Rcpp (>= 1.0.0), HistDAWass, FactoMineR, ggplot2, rlang, tibble, stats, utils, grDevices
LinkingTo: Rcpp
Suggests: testthat (>= 3.0.0), knitr, rmarkdown, CUB
VignetteBuilder: knitr
URL: https://github.com/Airpino/DDAWASS
BugReports: https://github.com/Airpino/DDAWASS/issues
NeedsCompilation: yes
Packaged: 2026-10-22 13:46:54 UTC; anton
Author: Antonio Irpino [aut, cre, cph]
Maintainer: Antonio Irpino <antonio.irpino@unicampania.it>
Repository: CRAN
Date/Publication: 2026-11-04 21:00:02 UTC

More information about DDAWASS at CRAN
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New package Compositionalridge with initial version 1.0
Package: Compositionalridge
Title: Ridge Regression for Compositional Data
Version: 1.0
Date: 2026-10-22
Maintainer: Michail Tsagris <mtsagris@uoc.gr>
Depends: R (>= 4.0)
Imports: Compositional, glmnet, minpack.lm, Rfast, stats, Rcpp
Suggests: Rfast2
Description: A few ridge regression models for compositional data with zero values present. These are the zero adjusted Dirichlet regression, the multivariate zero inflated logistic normal, the Kullback-Leibler divergence and the alpha-regression. Some relevant papers include Tsagris and Stewart (2018) <doi:10.1134/S1995080218030198>, Tsagris et al. (2026) <doi:10.48550/arXiv.2510.12663>, and Li et al. (2018) <doi:10.1007/s12561-018-9219-2>.
License: GPL (>= 2)
LinkingTo: Rcpp, RcppArmadillo
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2026-10-22 12:01:13 UTC; mtsag
Author: Michail Tsagris [aut, cre], Christos Adam [aut]
Repository: CRAN
Date/Publication: 2026-11-04 20:10:08 UTC

More information about Compositionalridge at CRAN
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New package CCNR with initial version 0.2.0
Package: CCNR
Title: Classifier Chain Network for Multi-Label Classification
Version: 0.2.0
Encoding: UTF-8
Description: Fits a Classifier Chain Network (CCN) for multi-label binary classification. The model jointly learns label dependencies through a chain structure and optimizes an Lq norm aggregated cross-entropy loss. Provides methods for prediction, model summary, and k-fold cross-validation with grid search over hyperparameters. The methodology is described in Touw and Van de Velden (2025) <doi:10.1016/j.eswa.2025.128048>.
License: GPL-3
Depends: R (>= 4.4.0)
URL: https://github.com/djwtouw/CCNR
BugReports: https://github.com/djwtouw/CCNR/issues
Imports: Rcpp (>= 1.0.9), MASS, stats, utils
Suggests: testthat (>= 3.0.0)
LazyData: true
LinkingTo: Rcpp, RcppEigen
NeedsCompilation: yes
Packaged: 2026-10-22 13:29:26 UTC; DanielTouw
Author: Daniel J.W. Touw [aut, cre] , Michel Van de Velden [ths]
Maintainer: Daniel J.W. Touw <touw@ese.eur.nl>
Repository: CRAN
Date/Publication: 2026-11-04 20:50:02 UTC

More information about CCNR at CRAN
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New package definecore with initial version 0.1.1
Package: definecore
Title: Generate CDISC Define-XML from Metacore Objects
Version: 0.1.1
Description: Generates CDISC Define-XML documents (versions 2.0 and 2.1) from metacore metadata objects. Maps dataset, variable, codelist, and derivation information into an ODM-based Define-XML structure suitable for further review and regulatory use. Integrates with the pharmaverse metacore ecosystem.
License: MIT + file LICENSE
URL: https://github.com/shekharchalwadigrepo-hub/definecore
BugReports: https://github.com/shekharchalwadigrepo-hub/definecore/issues
Depends: R (>= 4.1.0)
Imports: metacore, xml2, dplyr, rlang, cli, glue, magrittr
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
Encoding: UTF-8
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-10-22 06:21:35 UTC; skrch
Author: Shakhar Eranna Chalwadi [aut, cre]
Maintainer: Shakhar Eranna Chalwadi <skrchalwadicg@gmail.com>
Repository: CRAN
Date/Publication: 2026-11-04 20:00:02 UTC

More information about definecore at CRAN
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New package triplclust with initial version 2.0.1
Package: triplclust
Title: Algorithm for Curve Detection in 3D Point Clouds
Version: 2.0.1
Date: 2026-10-18
Maintainer: Christoph Dalitz <christoph.dalitz@hs-niederrhein.de>
Description: The TriplClust algorithm assigns each point in a 3D or 2D point cloud a cluster label representing curves or noise. It can be used to detect curves in point clouds. TriplClust is based on hierarchical clustering of point triplets and is explained in Dalitz et al. (2019) <doi:10.5201/ipol.2019.234>.
Depends: R (>= 3.5.0)
License: BSD_2_clause + file LICENSE
URL: https://github.com/cdalitz/triplclust/
LazyData: true
Imports: Rcpp (>= 1.0.0)
LinkingTo: Rcpp
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2026-10-22 09:59:28 UTC; dalitz
Author: Christoph Dalitz [aut, cre], Jens Wilberg [aut, cph], Lukas Aymans [aut, cph], Daniel Muellner [aut, cph], Vitali Krieger [aut]
Repository: CRAN
Date/Publication: 2026-11-04 10:10:02 UTC

More information about triplclust at CRAN
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New package shiny.element with initial version 0.3.1
Package: shiny.element
Title: 'Element Plus' Components for 'shiny'
Version: 0.3.1
Description: 'Element Plus' ('Vue' 3) components for 'shiny': forms, tables, trees, menus, dialog boxes and the rest, each reporting to the server and updated from it like any other 'shiny' input. 'Element Plus' and 'Vue' are bundled, so applications work offline.
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-GB
Depends: R (>= 4.1)
Imports: htmltools, shiny, jsonlite, uuid, stats, bslib, grDevices, utils, jquerylib
Suggests: testthat (>= 3.0.0), shinyjs, shinyvalidate, shinytest2, fontawesome, callr, chromote, httpuv, pkgload, promises, withr, knitr, rmarkdown, DT, later
VignetteBuilder: knitr
URL: https://kaipingyang.github.io/shiny.element/, https://github.com/kaipingyang/shiny.element
BugReports: https://github.com/kaipingyang/shiny.element/issues
NeedsCompilation: no
Packaged: 2026-10-22 03:43:15 UTC; kaiping.yang
Author: Kaiping Yang [aut, cre], Element Plus team [ctb, cph] , Evan You [ctb, cph]
Maintainer: Kaiping Yang <1260146556@qq.com>
Repository: CRAN
Date/Publication: 2026-11-04 09:20:02 UTC

More information about shiny.element at CRAN
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New package quartodown with initial version 0.1.0
Package: quartodown
Title: Package Websites Built Entirely with 'Quarto'
Version: 0.1.0
Description: Builds package websites with 'Quarto'. The whole site, help pages and vignettes included, is rendered by 'Quarto', so every 'Quarto' feature works, from callouts to code annotations. Functions mentioned in code link to their help pages, with hover tooltips.
License: MIT + file LICENSE
URL: https://bjarkehautop.github.io/quartodown/, https://github.com/bjarkehautop/quartodown
BugReports: https://github.com/bjarkehautop/quartodown/issues
SystemRequirements: Quarto command line tool (<https://github.com/quarto-dev/quarto-cli>).
Encoding: UTF-8
Imports: cli, desc, downlit, fansi, fs, quarto, tools, utils, xml2, yaml
Suggests: httr2, pkgload, servr, testthat (>= 3.0.0), withr
VignetteBuilder: quarto
NeedsCompilation: no
Packaged: 2026-10-22 06:07:40 UTC; bjarke
Author: Bjarke Hautop Kristensen [aut, cre, cph], Hadley Wickham [ctb] , Jay Hesselberth [ctb] , Maelle Salmon [ctb] , Olivier Roy [ctb] , Salim Brueggemann [ctb] , Posit Software, PBC [cph]
Maintainer: Bjarke Hautop Kristensen <bjarke.hautop@gmail.com>
Repository: CRAN
Date/Publication: 2026-11-04 10:00:08 UTC

More information about quartodown at CRAN
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New package ModalNet with initial version 0.3.0
Package: ModalNet
Title: Regularized Parametric Modal Regression: Lasso, Elastic Net and Ridge
Version: 0.3.0
Description: Variable selection and estimation for parametric modal regression with continuous positive responses (Gamma, Weibull and Lognormal families) under Lasso, elastic-net, ridge and adaptive-Lasso penalties. The conditional mode is linked to a linear predictor through a logarithmic link using the mode reparameterization of Galarza and Lachos (2026) <doi:10.48550/arXiv.2603.07099>. The penalized log-likelihood is maximized with a proximal Newton algorithm (iteratively reweighted penalized least squares): at each iteration the modal log-likelihood is replaced by a local quadratic surrogate in the linear predictor, which yields a pseudo-response and a working weight in closed form, and the resulting weighted penalized least-squares subproblem is solved by the coordinate-descent solver of 'glmnet' (Friedman, Hastie and Tibshirani, 2010, <doi:10.18637/jss.v033.i01>). The regularization parameter is chosen along a warm-started path by the extended Bayesian information criterion of Che [...truncated...]
License: GPL-3
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: glmnet, stats, graphics
Suggests: survival
LazyData: true
URL: https://github.com/chedgala/ModalNet
BugReports: https://github.com/chedgala/ModalNet/issues
NeedsCompilation: no
Packaged: 2026-10-22 04:36:04 UTC; chedgala
Author: Christian E. Galarza [aut, cre, cph] , Victor H. Lachos [aut] , Dashun Liu [aut]
Maintainer: Christian E. Galarza <chedgala@espol.edu.ec>
Repository: CRAN
Date/Publication: 2026-11-04 09:40:02 UTC

More information about ModalNet at CRAN
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New package glmheaders with initial version 1.0.1-2
Package: glmheaders
Title: 'OpenGL Mathematics' 'C++' Headers
Version: 1.0.1-2
Description: Provides the header-only 'OpenGL Mathematics' (GLM) 'C++' library for numerical computations in graphics and geometry <https://github.com/g-truc/glm>. Includes vector and matrix types, coordinate transformations, quaternions, and geometric functions following the conventions of the 'OpenGL Shading Language'.
License: MIT + file LICENSE
Copyright: file inst/COPYRIGHTS
URL: https://github.com/tylermorganwall/glmheaders
Suggests: Rcpp
Encoding: UTF-8
NeedsCompilation: no
BugReports: https://github.com/tylermorganwall/glmheaders/issues
Packaged: 2026-10-22 02:56:00 UTC; tyler
Author: Tyler Morgan-Wall [aut, cre] , G-Truc Creation [aut, cph]
Maintainer: Tyler Morgan-Wall <tylermw@gmail.com>
Repository: CRAN
Date/Publication: 2026-11-04 09:10:02 UTC

More information about glmheaders at CRAN
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New package FARM.eval with initial version 1.0.0
Package: FARM.eval
Title: FARM Algorithm Evaluation
Version: 1.0.0
Description: Providing data sets and functions used for evaluating the FARM (Forward Alignment Relevance Measure) algorithm. Datasets include energy consumption series from a university research cube in combination with two and four exogenous series consisting 768 and 62840 samples, respectively. To run particular functions from terminal: Rscript $(R -e 'cat(system.file("scripts","FARM.eval.R",package = "FARM.eval"))') --fexecute get.global.rel.meas --parworkers 1 --parobjsize 500.
License: GPL-3
Encoding: UTF-8
Imports: FARM, dplyr, purrr, lubridate, readr, stats, magrittr, dtw, DTWBI, reticulate, graphics, shape, utils, future.apply, nanoparquet, plotrix, tsmp, optparse, tidyr
Depends: R (>= 4.1.0)
NeedsCompilation: no
Packaged: 2026-10-21 20:00:22 UTC; prypjat
Author: Ramon Christen [aut, cre]
Maintainer: Ramon Christen <hiroshima@bluewin.ch>
Repository: CRAN
Date/Publication: 2026-11-04 09:30:02 UTC

More information about FARM.eval at CRAN
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Tue, 03 Nov 2026

New package WSSmod with initial version 0.1.0
Package: WSSmod
Title: Weighted Sum Scores for Protein Network Modules
Version: 0.1.0
Description: Computes Weighted Sum Score (WSS) module-level summaries from proteomic data. Protein-level values are sign-aligned to their association with core biomarkers and combined within 'STRING' network modules, weighted by network connectivity and association strength. Bundled reference modules and a fitted 'joinet' model also allow all module scores to be predicted from age, sex and a small panel of plasma biomarkers, without measuring the full proteomic panel. The method is described in Butler et al. (2026) <doi:10.64898/2026.08.14.26360394>.
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-US
Depends: R (>= 3.5.0)
Imports: data.table
Suggests: glmnet, joinet, knitr, rmarkdown, RNOmni, testthat (>= 3.0.0)
VignetteBuilder: knitr
LazyData: true
URL: https://github.com/Longo-Lab/WSSmod, https://Longo-Lab.github.io/WSSmod/
BugReports: https://github.com/Longo-Lab/WSSmod/issues
NeedsCompilation: no
Packaged: 2026-10-22 02:57:36 UTC; rrbutler
Author: Robert Butler [aut, cre] , WSSmod authors [cph]
Maintainer: Robert Butler <rrbutler@stanford.edu>
Repository: CRAN
Date/Publication: 2026-11-03 16:00:38 UTC

More information about WSSmod at CRAN
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New package shapleydecomp with initial version 1.0.0
Package: shapleydecomp
Title: Shapley Value Decomposition for Discrete-Time Simulation Models
Version: 1.0.0
Description: Attributes changes in the outcomes of a discrete-time simulation model to its input factors using Shapley values (Shapley 1953) <doi:10.1515/9781400881970-018>, which for binary factors coincide with the symmetric standardization of Das Gupta (1993) <https://www2.census.gov/library/publications/1993/demographics/p23-186.pdf>. Any calibrated model can be decomposed by implementing four S3 methods that run the model, summarize its output, and construct counterfactual inputs. Counterfactuals either remove a factor entirely or hold it at its value in a baseline year, and a sequential decomposition attributes each year's policy conditional on the past.
License: MIT + file LICENSE
URL: https://github.com/aucarter/shapleydecomp, https://aucarter.github.io/shapleydecomp/
BugReports: https://github.com/aucarter/shapleydecomp/issues
Encoding: UTF-8
Depends: R (>= 4.0.0)
Imports: data.table, parallel, utils
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-10-21 23:30:55 UTC; aucarter
Author: Austin Carter [aut, cre]
Maintainer: Austin Carter <aucarter@uw.edu>
Repository: CRAN
Date/Publication: 2026-11-03 16:00:02 UTC

More information about shapleydecomp at CRAN
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New package SexSeek with initial version 0.1.0
Package: SexSeek
Title: Estimate Genetic Sex from Expression Counts
Version: 0.1.0
Description: Infers the genetic sex of samples, donors or cells from bulk or single-cell RNA sequencing counts. Accepts dense or sparse matrices, delimited text files, 10x Genomics outputs, and 'Seurat', 'SingleCellExperiment' and 'SummarizedExperiment' objects.
License: MIT + file LICENSE
URL: https://sexseek.saketlab.org, https://github.com/saketlab/SexSeek
BugReports: https://github.com/saketlab/SexSeek/issues
Encoding: UTF-8
Language: en-GB
Depends: R (>= 4.1)
Imports: ggplot2, Matrix, methods, stats, utils
Suggests: genevintage (>= 0.1.3), hdf5r, knitr, rmarkdown, SeuratObject, SingleCellExperiment, SummarizedExperiment, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-10-21 06:14:54 UTC; mcclintock
Author: Saket Choudhary [aut, cre, cph]
Maintainer: Saket Choudhary <saketc@iitb.ac.in>
Repository: CRAN
Date/Publication: 2026-11-03 15:50:18 UTC

More information about SexSeek at CRAN
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New package sas2r with initial version 0.5.8
Package: sas2r
Title: Translate 'SAS' Programs to R with Dependency-Aware Migration
Version: 0.5.8
Description: Translates 'SAS' programs and projects into R code, orders connected programs by their dependencies, and executes generated code. Compares generated datasets with supplied reference outputs and reports unresolved translation and validation findings. Rule-based translation works offline without a 'SAS' installation. Optional language model translation, review, and repair use a user-configured provider through 'ellmer' and may require an account and API credentials.
License: Apache License (>= 2)
URL: https://github.com/songyue-chen/sas2r
BugReports: https://github.com/songyue-chen/sas2r/issues
Encoding: UTF-8
VignetteBuilder: knitr
Depends: R (>= 4.1)
Imports: callr, cli (>= 3.4), clue, filelock, haven, jsonlite, stats, tibble, utils, vctrs, yaml
Suggests: diffdf, dplyr (>= 1.1.0), ellmer (>= 0.4.2), ggplot2, knitr, pdftools, pkgload, ps, rmarkdown, S7, testthat (>= 3.1.7), withr
NeedsCompilation: no
Packaged: 2026-10-21 16:33:12 UTC; chuckchen
Author: Songyue Chen [aut, cre]
Maintainer: Songyue Chen <songyue.chen.dev@gmail.com>
Repository: CRAN
Date/Publication: 2026-11-03 15:50:02 UTC

More information about sas2r at CRAN
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New package RSYC with initial version 0.2.0
Package: RSYC
Title: Remote Sensing-Derived Yield Curves for Canada
Version: 0.2.0
Description: Provides published remote sensing-based yield curves for aboveground biomass and total volume across Canada, as described in Tompalski et al. (2024) <doi:10.1016/j.foreco.2024.121894> and Tompalski et al. (2025) <doi:10.1093/forestry/cpaf067>. Models are available for 150 km tiles and four levels of Canada's ecological land classification. Functions help users find curves by species and area, estimate yield at a given stand age, calibrate curves to local observations, and build spatial yield-curve datasets.
License: GPL (>= 3)
Encoding: UTF-8
Depends: R (>= 4.1.0)
LazyData: true
Imports: digest, glue, lifecycle, magrittr, tibble
Suggests: dplyr, purrr, sf, testthat (>= 3.0.0)
URL: https://ptompalski.github.io/RSYC/, https://github.com/ptompalski/RSYC
BugReports: https://github.com/ptompalski/RSYC/issues
NeedsCompilation: no
Packaged: 2026-10-21 22:58:11 UTC; ptompals
Author: Piotr Tompalski [aut, cre, cph], His Majesty the King in Right of Canada, as represented by the Minister of Natural Resources Canada [cph]
Maintainer: Piotr Tompalski <piotr.tompalski@NRCan-RNCan.gc.ca>
Repository: CRAN
Date/Publication: 2026-11-03 15:50:24 UTC

More information about RSYC at CRAN
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New package nestedscales with initial version 0.2.0
Package: nestedscales
Title: Nested Scales and Multi-Dimensional Indexes for Modeling
Version: 0.2.0
URL: https://optimal2050.github.io/nestedscales/r/, https://github.com/optimal2050/nestedscales
BugReports: https://github.com/optimal2050/nestedscales/issues
Description: Provides multi-level discrete representations of data dimensions for modeling, data processing and visualization. A nested scale records its finest units (atoms) and their membership in coarser levels (frames), including nested, cross-cutting and partially covered relationships. Recasts tabular data between levels using explicit, direction-aware rules for sums, means, standard deviations, copying and within-parent shares. Also supports labeling, subsetting, combining scales into multi-dimensional indexes, clustering units and storing data with its scale metadata. Members may carry attributes (a calorific value, an emission factor) and aliases, resolved along the hierarchy and applied row by row, and a scale is exchanged as a language-neutral definition file: a 'JSON' header with inline, 'Arrow' or 'CSV' tables ('YAML' accepted), with a catalogue of the definitions installed packages ship. Forms the dimension-agnostic core of 'timescales' <https://github.com/optimal2050/timescales> [...truncated...]
License: Apache License (>= 2)
Encoding: UTF-8
Depends: R (>= 4.2)
Imports: dplyr, jsonlite, rlang, S7, stats, utils
Suggests: arrow, cluster, data.table, dtplyr, ggplot2, knitr, pkgdown, rmarkdown, testthat (>= 3.0.0), tibble, withr, yaml
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-10-22 01:32:14 UTC; admin
Author: Oleg Lugovoy [aut, cre]
Maintainer: Oleg Lugovoy <olugovoy@optimalsolution.dev>
Repository: CRAN
Date/Publication: 2026-11-03 16:00:16 UTC

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New package naxp with initial version 0.1.0
Package: naxp
Title: Encoded ASCII Expressions
Version: 0.1.0
Description: Converts alphanumeric codes such as postcodes to whole numbers and back again, following the 'naxp' standard <https://naxp.org/spec/>. A naxp ('encoded ASCII expression') is a pattern, defined using a similar syntax to regular expressions, that maps each text it accepts to a number from 1 to a fixed maximum, and any other text to 0. The same pattern maps text to numbers identically across all 'naxp' libraries in all languages on all platforms (subject only to the availability of types able to store large enough integers). Standard naxps are defined for common code systems and are built into all 'naxp' libraries. Two naxps can be compared to determine, among other things, whether stored values keep their meaning when one replaces the other. Wraps the 'naxp' 'C++' library <https://naxp.org/api/#cpp>.
License: Apache License (== 2.0)
URL: https://naxp.org/, https://github.com/logmu-org/r-naxp, https://r-naxp.logmu.org/
BugReports: https://github.com/logmu-org/r-naxp/issues
Depends: R (>= 4.1.0)
Suggests: jsonlite, knitr, pillar, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
LinkingTo: cpp11
Encoding: UTF-8
Language: en-GB
SystemRequirements: C++17
NeedsCompilation: yes
Packaged: 2026-10-21 22:54:12 UTC; Tim Gordon
Author: Tim Gordon [aut, cre]
Maintainer: Tim Gordon <tim.gordon@btinternet.com>
Repository: CRAN
Date/Publication: 2026-11-03 16:00:26 UTC

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New package imedR with initial version 0.3.3
Package: imedR
Title: Guarded Evidence Synthesis for the Indian Microplastics Evidence Database
Version: 0.3.3
Description: A research-grade, guardrail-first interface to the Indian Microplastics Evidence Database (IMED). It provides release-data access, relational and scientific validation, comparability-aware filtering, descriptive and inferential statistics, evidence-synthesis eligibility, meta-analysis helpers, publication figures, mapping, provenance and citation retrieval, and manuscript-oriented outputs. Unsafe pooling across incompatible matrices, denominators, mass bases and comparability classes is blocked by default.
License: MIT + file LICENSE
URL: https://github.com/ChanikyaNaiduCN7/imedR
BugReports: https://github.com/ChanikyaNaiduCN7/imedR/issues
Encoding: UTF-8
Depends: R (>= 4.2.0)
Imports: dplyr, ggplot2, rlang, tibble, readr
Suggests: testthat (>= 3.0.0), sf, metafor, knitr, rmarkdown, scales
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-10-22 02:53:00 UTC; root
Author: Chanikya Naidu [aut, cre]
Maintainer: Chanikya Naidu <thefisherieschanikyaneeti@gmail.com>
Repository: CRAN
Date/Publication: 2026-11-03 16:00:32 UTC

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New package glmfsa with initial version 1.0.1
Package: glmfsa
Title: Feature Selection with Annealing for Sparse Generalized Linear Models
Version: 1.0.1
Date: 2026-10-21
Description: Fits sparse generalized linear models under an exact cardinality constraint using Feature Selection with Annealing (FSA), the method of Barbu, She, Ding and Gramajo (2017) <doi:10.1109/TPAMI.2016.2544315>. Rather than inducing sparsity through an L1 (lasso-type) penalty, FSA alternates a gradient step on the loss with a step that removes the lowest-magnitude coefficients according to an annealing schedule, so the user specifies the number of variables directly and the surviving coefficients carry no shrinkage bias. The working design matrix physically shrinks as iterations proceed, which makes the cost of a fit fall over time and the method well suited to problems with very many features. Gaussian, binomial, Poisson, multinomial, multi-response Gaussian and Cox proportional hazards families are supported, with robust Lorenz and smoothed support vector machine (SVM) losses available for classification with noisy labels. Dense and sparse design matrices are both handled, and the in [...truncated...]
License: GPL-3
Encoding: UTF-8
LazyData: true
LazyDataCompression: xz
Depends: R (>= 3.5.0)
Imports: Rcpp (>= 1.0.0), Matrix, methods, graphics, grDevices, stats, tools, utils
LinkingTo: Rcpp, RcppArmadillo
Suggests: testthat (>= 3.0.0), knitr, rmarkdown, glmnet, survival, foreach, doParallel, MASS
VignetteBuilder: knitr
URL: https://github.com/barbua/FSA
BugReports: https://github.com/barbua/FSA/issues
NeedsCompilation: yes
Packaged: 2026-10-21 19:42:32 UTC; abarbu
Author: Adrian Barbu [aut, cre, cph], Yiyuan She [aut], Liangjing Ding [ctb], Gary Gramajo [ctb]
Maintainer: Adrian Barbu <abarbu@fsu.edu>
Repository: CRAN
Date/Publication: 2026-11-03 15:40:02 UTC

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New package deepICMGP with initial version 0.1.1
Package: deepICMGP
Title: Deep Intrinsic Coregionalization Gaussian Processes for Multiple Outputs
Version: 0.1.1
Author: Chun-Yi Chang [aut, cre], Chih-Li Sung [aut], Annie S. Booth [ctb]
Maintainer: Chun-Yi Chang <chang103@msu.edu>
Description: Fits two-layer deep intrinsic coregionalization Gaussian process surrogate models for multiple outputs observed at shared input locations. Uses Markov chain Monte Carlo sampling for kernel parameters and latent coordinates, with plug-in coregionalization estimates. Provides burn-in removal and thinning, posterior predictive means and within-location output covariances, and sequential experimental design using an active learning criterion. The method is described by Chang and Sung (2026) <doi:10.1615/Int.J.UncertaintyQuantification.2026062570>. Adapts code from the 'deepgp' package, with underlying deep Gaussian process methodology described by Sauer, Gramacy, and Higdon (2023) <doi:10.1080/00401706.2021.2008505>.
License: LGPL
Encoding: UTF-8
Imports: lhs, parallel, stats
NeedsCompilation: yes
Packaged: 2026-10-21 18:59:35 UTC; chang103
Repository: CRAN
Date/Publication: 2026-11-03 15:30:02 UTC

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New package CompositionalLASSO with initial version 1.0
Package: CompositionalLASSO
Title: LASSO Compositional Data Regression
Version: 1.0
Date: 2026-10-22
Author: Michail Tsagris [aut, cre]
Maintainer: Michail Tsagris <mtsagris@uoc.gr>
Depends: R (>= 4.0)
Imports: Compositional, glmnet, Rfast, stats
Suggests: Rfast2
Description: LASSO (Least Absolute Shrinkage and Selection Operator) regression for compositional responses with and without zero values present and continuous predictors. The choice of the penalty parameter, lambda, takes place using K-fold cross-validation. Two relevant papers are Li Z. et al. (2018) <doi:10.1007/s12561-018-9219-2> and Alenazi A.A. (2022) <doi:10.18187/pjsor.v18i4.3969>.
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2026-10-21 20:55:04 UTC; mtsag
Repository: CRAN
Date/Publication: 2026-11-03 15:50:30 UTC

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New package wavecov with initial version 0.1.0
Package: wavecov
Title: Overlap-Aware Workforce Wave Comparisons
Version: 0.1.0
Description: Tools for comparing workforce metric distributions between panel waves using linked stayers, reliability assumptions, or Cauchy bounds. Its purpose is to provide a low-latency alternative to traditional hierarchical or latent-growth modeling that is better-able to scale in cloud based architectures. The mathematics is an extension of rotating panel formulae from the official statistics literature.
License: GPL-3
Encoding: UTF-8
Depends: R (>= 3.5.0)
Imports: stats
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-10-21 17:40:09 UTC; G561631
Author: Jack Kostal [aut, cre]
Maintainer: Jack Kostal <jack.kostal@genmills.com>
Repository: CRAN
Date/Publication: 2026-11-03 14:30:02 UTC

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New package theaitetos with initial version 0.1.0
Package: theaitetos
Title: Ancient Intelligence Geometric Superposition Field Calculations
Version: 0.1.0
Description: Establishes a deterministic geometric extension framework within the 'theaitetos' package, honoring the ancient mathematical foundations of Theaetetus of Athens (400 BC). Incorporates the stereometric proofs on the regular octahedron later recorded in Plato (ca. 369 BC) "Theaetetus" <urn:cts:greekLit:tlg0059.tlg006> and Euclid (ca. 300 BC) "Elements" <urn:cts:greekLit:tlg1799.tlg001>. References the standard Greek text tradition by Heiberg (1885) "Euclidis Elementa" and the analytical translations by Heath (1926) "The Thirteen Books of Euclid's Elements". To achieve operational utility, the architecture delivers a high-level computational core engine that abstracts complex 3D-to-2D vector projections and scalar wave superpositions, eliminating low-level reprogramming. It integrates a standardized visualization layer built upon 'ggplot2' to render high-resolution continuous scalar fields and provides a runtime-configurable selection interface across multiple physical and bio [...truncated...]
License: GPL-3
Encoding: UTF-8
Imports: ggplot2
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-10-21 18:41:44 UTC; katharinabrecht
Author: Katharina Brecht [aut, cre]
Maintainer: Katharina Brecht <katharina.quantumdata@proton.me>
Repository: CRAN
Date/Publication: 2026-11-03 14:40:02 UTC

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New package superstats with initial version 1.0
Package: superstats
Title: Super Statistics
Version: 1.0
Date: 2026-10-21
Author: Michail Tsagris [aut, cre], Manos Papadakis [aut], Alzeley Omar [aut, cph]
Maintainer: Michail Tsagris <mtsagris@uoc.gr>
Depends: R (>= 4.0)
Imports: graphics, grDevices, Rfast, Rfast2
Description: Superstatistics generally applies to analyzing complex systems where traditional statistical methods are insufficient. This approach is particularly valuable in areas like physics, finance, and environmental science. It steps in when there are underlying variables or parameters in a system that fluctuate significantly over space or time, which traditional statistics might overlook. For more information see: Alzeley O. (2020) <doi:10.1002/cmm4.1085>.
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2026-10-21 14:53:21 UTC; mtsag
Repository: CRAN
Date/Publication: 2026-11-03 14:20:02 UTC

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New package r2sbml with initial version 0.1.0
Package: r2sbml
Title: Read 'SBML' Models and Convert Them to Simulation Code
Version: 0.1.0
Description: Reads models in the Systems Biology Markup Language ('SBML') (Hucka et al. (2003) <doi:10.1093/bioinformatics/btg015>) through the bundled 'libSBML' library (Bornstein et al. (2008) <doi:10.1093/bioinformatics/btn051>). Lists a model's species, parameters, compartments, reactions, rules, events and function definitions, and converts the model into ready-to-run simulation code for 'deSolve', 'mrgsolve', 'rxode2', 'MATLAB', 'Julia' or 'ubiquity'. Models are read, not modified.
URL: https://sn248.github.io/r2sbml/, https://github.com/sn248/r2sbml
BugReports: https://github.com/sn248/r2sbml/issues
Encoding: UTF-8
Language: en-GB
License: GPL (>= 2)
Copyright: See file inst/COPYRIGHTS
Imports: Rcpp (>= 0.12.6)
Suggests: deSolve, knitr, mrgsolve, rmarkdown, rxode2, testthat (>= 3.0.0), ubiquity
VignetteBuilder: knitr
LinkingTo: Rcpp
Biarch: TRUE
SystemRequirements: cmake, libxml2, libbz2
NeedsCompilation: yes
Packaged: 2026-10-21 12:12:09 UTC; quantilogy
Author: Satyaprakash Nayak [aut, cre, cph], Sarah M. Keating [ctb] , Frank T. Bergmann [ctb] , Lucian P. Smith [ctb] , Brett G. Olivier [ctb] , Akiya Jouraku [ctb] , Michael Hucka [ctb] , Ben Bornstein [ctb] , Jeroen Ooms [ctb] , California Institute of Tech [...truncated...]
Maintainer: Satyaprakash Nayak <satyaprakash.nayak@gmail.com>
Repository: CRAN
Date/Publication: 2026-11-03 14:10:02 UTC

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New package nerfplus with initial version 1.0.0
Package: nerfplus
Title: Network-Assisted Random Forest+ (NeRF+)
Version: 1.0.0
Description: Network-assisted Random Forest+ (NeRF+) is a flexible and interpretable machine learning model for incorporating network data alongside node-level covariate information. Briefly, NeRF+ extends a generalization of random forests (RF) called RF+ to the network-assisted regression setting by incorporating both a network cohesion penalty and network embeddings as additional covariates. Using this approach, NeRF+ inherits both the flexibility and interpretability of RFs while allowing researchers to easily incorporate network information in their model to further improve predictive performance. This package provides tools to fit and interpret NeRF+ models, as detailed in Tang, Levina, and Zhu (2025) <doi:10.48550/arXiv.2509.15611>.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Suggests: DT, fresh, ggplot2, ggraph, htmltools, igraph, kableExtra, knitr, patchwork, plotly, shiny, shinycssloaders, shinydashboard, shinydashboardPlus, shinyjs, shinyWidgets, testthat (>= 3.0.0), tippy
Imports: abind, caret, dplyr, furrr, glmnet, irlba, Matrix, purrr, ranger, Rcpp, rlang, stringr, tibble, tidyr, tidyselect, yardstick
LinkingTo: Rcpp, RcppArmadillo
LazyData: true
URL: https://tiffanymtang.github.io/nerfplus/
NeedsCompilation: yes
Packaged: 2026-10-21 20:19:18 UTC; ttang4
Author: Tiffany Tang [aut, cre]
Maintainer: Tiffany Tang <ttang4@nd.edu>
Repository: CRAN
Date/Publication: 2026-11-03 14:40:08 UTC

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New package MMEFM with initial version 0.1.1
Package: MMEFM
Title: Multilevel Main Effects Matrix Factor Model Tools
Version: 0.1.1
Description: Provides estimation, rank selection, and simulation for grouped matrix-valued time series using the Multilevel Main Effects Matrix Factor Model. The model separates global and local grand means, row and column main effects, and bilinear interaction components, allowing nonstationary main effects under suitable conditions. A circular-shift bootstrap is used to detect a shared global common component and screen participating groups on a stationary segment. The underlying methodology is developed in Liu, Lam and Cen (2026) <doi:10.48550/arXiv.2610.18335>.
License: MIT + file LICENSE
URL: https://github.com/kx-liu/MMEFM
BugReports: https://github.com/kx-liu/MMEFM/issues
Depends: R (>= 4.1.0)
Imports: parallel, stats
Suggests: testthat (>= 3.2.0), knitr, rmarkdown
VignetteBuilder: knitr
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-10-21 15:57:49 UTC; liukaixin
Author: Kaixin Liu [aut, cre]
Maintainer: Kaixin Liu <k.liu31@lse.ac.uk>
Repository: CRAN
Date/Publication: 2026-11-03 14:10:08 UTC

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New package xlum with initial version 0.2.0
Package: xlum
Title: Read, Write, and Convert XLUM Data
Version: 0.2.0
Date: 2026-10-19
Maintainer: Sebastian Kreutzer <maintainer_luminescence@r-luminescence.org>
Description: Support for the XLUM file format (Kreutzer et al. (2023) <doi:10.5194/gchron-5-271-2023>) for exchange and long-term preservation of luminescence data. The package facilitates the import and export of XLUM files and the conversion from other ASCII and binary formats commonly used to store luminescence (dating) data.
License: GPL-3
URL: https://r-lum.github.io/xlum/
BugReports: https://github.com/R-Lum/xlum/issues
Depends: R (>= 4.5)
Imports: base64enc (>= 0.1), Luminescence (>= 1.3.1), utils, xml2 (>= 1.6.0)
Suggests: spelling (>= 2.3.2), testthat (>= 3.3.2)
Encoding: UTF-8
Language: en-GB
NeedsCompilation: no
Packaged: 2026-10-19 21:20:01 UTC; kreutzer
Author: Sebastian Kreutzer [aut, cre] , Marco Colombo [aut] , Christoph Burow [ctb]
Repository: CRAN
Date/Publication: 2026-11-03 12:30:02 UTC

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New package inlaops with initial version 0.1.2
Package: inlaops
Title: Deployment, Versioning and Scoring Tools for 'inlabru' Models
Version: 0.1.2
Description: Serves Bayesian spatial and latent Gaussian models fit with 'inlabru' as versioned Representational State Transfer (REST) application programming interfaces (APIs). Includes a 'vetiver' bridge (versioning, REST API serving with posterior uncertainty, 'Docker' packaging) for 'bru' objects, a 'parsnip' model constructor scoped to fixed-effects models, and predictive scoring helpers (continuous ranked probability, log, squared-error and Dawid-Sebastiani scores) computed from inlabru::generate() posterior samples via 'scoringRules'.
License: GPL (>= 3)
URL: https://github.com/novica/inlaops, https://novica.github.io/inlaops/
BugReports: https://github.com/novica/inlaops/issues
Additional_repositories: https://inla.r-inla-download.org/R/stable
Encoding: UTF-8
Imports: dplyr, inlabru (>= 2.15.0), rlang, tibble
Suggests: broom, callr, fmesher, ggplot2, hardhat, httpuv, httr2, INLA, jsonlite, knitr, parsnip, pins, plumber, purrr, recipes, rsample, scoringRules, sf, sn, testthat (>= 3.0.0), vetiver, yardstick, quarto
Enhances: sp
VignetteBuilder: quarto
NeedsCompilation: no
Packaged: 2026-10-21 06:00:07 UTC; novica
Author: Novica Nakov [aut, cre, cph]
Maintainer: Novica Nakov <nnovica@gmail.com>
Repository: CRAN
Date/Publication: 2026-11-03 13:10:02 UTC

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New package vayuayan with initial version 0.3.0

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New package uncertR with initial version 0.1.3
Package: uncertR
Title: Bootstrap Prediction Uncertainty and Its Biological Drivers in Gene-Expression Models
Version: 0.1.3
Description: Fits bootstrap ensembles of penalized regression models on bulk gene-expression data, derives per-sample uncertainty scores from out-of-bag predictions, and tests whether technical covariates explain that uncertainty. The bootstrap method is described by Efron and Tibshirani (1993, ISBN:9780412042317), and elastic-net regression follows Friedman, Hastie, and Tibshirani (2010) <doi:10.18637/jss.v033.i01>. The optional immunedeconv package, used for immune-cell deconvolution, is available from GitHub <https://github.com/omnideconv/immunedeconv>.
Encoding: UTF-8
Depends: R (>= 4.2.0)
License: MIT + file LICENSE
Imports: glmnet, future.apply, splines, stats, graphics
Suggests: testthat (>= 3.0.0), SummarizedExperiment, knitr, rmarkdown, immunedeconv
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-10-20 04:48:29 UTC; tanay
Author: Tanay Belapurkar [aut, cre]
Maintainer: Tanay Belapurkar <btanay041@gmail.com>
Repository: CRAN
Date/Publication: 2026-11-03 12:10:02 UTC

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New package lightson with initial version 0.2.0
Package: lightson
Title: Download and Analyse Nighttime Lights Satellite Data
Version: 0.2.0
Description: Downloads and processes nighttime lights satellite data from the 'NASA' 'VIIRS' Black Marble product suite (daily, monthly, and annual composites; Roman et al. (2018) <doi:10.1016/j.rse.2018.03.017>) served by the 'LAADS DAAC' archive <https://ladsweb.modaps.eosdis.nasa.gov>, and from the Indian Space Research Organisation's 'Bhuvan' nighttime lights portal. Provides zonal statistics over arbitrary polygons, returning tidy region-by-time panels, along with plotting helpers.
License: MIT + file LICENSE
Depends: R (>= 4.1.0)
Encoding: UTF-8
Imports: httr2 (>= 1.0.0), terra (>= 1.7.0), sf (>= 1.0.0), jsonlite, digest
Suggests: geodata, ggplot2, patchwork, scales, withr, testthat (>= 3.1.7), knitr, rmarkdown
VignetteBuilder: knitr
URL: https://lightson.saketlab.org, https://github.com/saketlab/lightson
BugReports: https://github.com/saketlab/lightson/issues
NeedsCompilation: no
Packaged: 2026-10-20 05:57:13 UTC; mcclintock
Author: Saket Choudhary [aut, cre]
Maintainer: Saket Choudhary <saketc@iitb.ac.in>
Repository: CRAN
Date/Publication: 2026-11-03 12:20:02 UTC

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New package stagelife with initial version 0.1.0
Package: stagelife
Title: Random Number Generation and Inferences for Two-Stage Life-Testing Data
Version: 0.1.0
Description: Provides random number generation, estimation, and hypothesis testing for two-stage life-testing experiments in which units begin on a baseline stress and, at a fixed or random change point, some or all surviving units move to an elevated stress ("stage life testing"), following the cumulative-exposure model of Laumen and Cramer (2019), "Stage life testing", <doi:10.1002/nav.21874>. Twelve baseline lifetime distributions are supplied (Weibull, Power Lindley, Exponentiated Lindley, Exponentiated Exponential, Marshall-Olkin Exponential, Lomax, Exponentiated Teissier, Log-Logistic, Chen, Log-normal, Gamma, and Power Muth/Power Teissier) together with three parameter-sharing cases (common, shape1, shape11). The package implements data simulation under both the fixed-proportion (typeP) and fixed-count (typeM) rules and the simple-step-stress special case, maximum likelihood estimation using a hybrid Nelder-Mead and BFGS optimisation routine, asymptotic (Wald) and non-parametric/parame [...truncated...]
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Depends: R (>= 4.1.0)
Imports: compiler, ggplot2, graphics, lamW, parallel, stats
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
URL: https://github.com/vksharma-bhu/stagelife
BugReports: https://github.com/vksharma-bhu/stagelife/issues
NeedsCompilation: no
Packaged: 2026-10-16 16:05:32 UTC; root
Author: Vikas Kumar Sharma [aut, cre]
Maintainer: Vikas Kumar Sharma <vksharma@bhu.ac.in>
Repository: CRAN
Date/Publication: 2026-11-03 12:00:02 UTC

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Mon, 02 Nov 2026

New package ruleatlas with initial version 0.0.1
Package: ruleatlas
Title: Syntactic Sport and Game Rules
Version: 0.0.1
Description: Provides native validation of sport and game states, permitted moves and observed events, deterministic rule consequences, and outcome calculation. Includes 212 profiles with explicit variant scopes and a bounded declarative interpreter for versioned user-defined rules. Does not simulate physical movement, generate strategies, or estimate winning probabilities.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: jsonlite, stats, utils
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
URL: https://github.com/rds0001/rulesatlas-r
BugReports: https://github.com/rds0001/rulesatlas-r/issues
Packaged: 2026-10-19 18:24:20 UTC; qwert123
Author: Dimitrios Geromichalos [cre], RiskDataScience GmbH [aut, cph]
Maintainer: Dimitrios Geromichalos <riskdatascience@web.de>
Repository: CRAN
Date/Publication: 2026-11-02 12:10:02 UTC

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Sat, 31 Oct 2026

New package vizintel with initial version 0.1.1
Package: vizintel
Title: Visualization Intelligence Toolkit
Version: 0.1.1
Description: Provides automated data profiling and visualization recommendation tools for exploratory data analysis (EDA). The package inspects a data frame, classifies each variable as numeric, categorical, or datetime, and computes distributional statistics including skewness, excess kurtosis, Shapiro-Wilk normality test p-values (Royston 1995) <doi:10.2307/2986146>, and cardinality. Based on these profiles, the package scores and ranks candidate chart types (histogram, density, boxplot, violin, bar, lollipop, scatter, hexbin, line, heatmap) using an internal taxonomy that accounts for variable types, analysis goal, skewness, cardinality, and data size. Additional functions audit existing ggplot objects for common visualization integrity problems such as truncated axes, lie factors, overplotting, and dual y-axes following principles described in Tufte (1983, ISBN:0961392142) and Wilke (2019) <https://clauswilke.com/dataviz/>. The package also checks visualizations for accessibility is [...truncated...]
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-US
Imports: dplyr, e1071, ggplot2, gridExtra, rlang
Suggests: colorspace, hexbin, patchwork, testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-10-20 16:43:15 UTC; pooja
Author: Pooja Thirumal [aut, cre], Ronesha Navaneethan [aut], Amrit Pal [ctb]
Maintainer: Pooja Thirumal <poojathirumal70@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-31 11:30:02 UTC

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New package traveltime with initial version 1.0.0
Package: traveltime
Title: Calculate Travel Times Over Space
Version: 1.0.0
Description: Calculate travel time across a landscape from a set of user-specified locations, over a friction surface describing the time taken to cross each cell. Implements the least-cost travel time approach of Weiss et al. (2018) <doi:10.1038/nature25181> and Weiss et al. (2020) <doi:10.1038/s41591-020-1059-1>, and provides convenient access to their global walking and motorised friction surfaces via the 'malariaAtlas' package. Travel times are computed with 'terra'. See Ryan et al. (2025) <doi:10.12688/gatesopenres.16356.1> for further details.
License: MIT + file LICENSE
Copyright: The 'stations' data contains information from the Land Transport Authority of Singapore, made available under the Singapore Open Data Licence version 1.0; see ?stations.
Imports: cli, malariaAtlas, terra
Encoding: UTF-8
Language: en-GB
Suggests: geodata, ggplot2, knitr, rmarkdown, testthat (>= 3.0.0), tidyterra
Depends: R (>= 4.1.0)
LazyData: true
URL: https://idem-lab.github.io/traveltime/, https://github.com/idem-lab/traveltime
BugReports: https://github.com/idem-lab/traveltime/issues
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-10-21 03:11:00 UTC; gryan
Author: Gerry Ryan [aut, cre] , Daniel Weiss [aut] , Nicholas Tierney [ctb]
Maintainer: Gerry Ryan <gerry.ryan@thekids.org.au>
Repository: CRAN
Date/Publication: 2026-10-31 11:50:02 UTC

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New package sysbreak with initial version 1.1.0
Package: sysbreak
Title: Structural Breaks in a System of Equations
Version: 1.1.0
Maintainer: Zhongjun Qu <qu@bu.edu>
Description: Methods for detecting, estimating, and conducting inference on multiple structural breaks in a linear system of equations, such as multivariate linear regressions, seemingly unrelated regressions, vector autoregressions, and network vector autoregressions. Breaks can occur in the regression coefficients, the covariance matrix of the errors, or both, and can be restricted to a subset of the coefficients. The main function, sysbreak(), returns the number of breaks detected and confidence intervals for the break dates and for the regression coefficients. A separate function ordbreak() estimates ordered breaks, in which a break in one subset of equations occurs before a break in another. Specialized functions for vector autoregressions varbreak() and network vector autoregressions netbreak() are also provided. Reference: Qu, Z., and Perron, P. (2007). 'Estimating and Testing Structural Changes in Multivariate Regressions.' Econometrica, 75(2), 459-502.
License: GPL (>= 3)
Depends: R (>= 4.3.0)
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
Encoding: UTF-8
NeedsCompilation: no
Imports: graphics, grDevices, MASS, stats, utils
LazyData: true
Packaged: 2026-10-20 19:49:01 UTC; qu
Author: Zhongjun Qu [aut, cre], Cheolju Kim [aut], Pierre Perron [aut]
Repository: CRAN
Date/Publication: 2026-10-31 11:40:02 UTC

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New package selSurv with initial version 0.1.1
Package: selSurv
Title: Inference after Cox-Lasso Variable Selection
Version: 0.1.1
Description: Methods for inference after Cox-Lasso variable selection in right-censored survival data. The package provides Cox-Lasso fitting, support-restricted Cox refitting, sample splitting, approximately debiased coefficient estimates, score-level bootstrap intervals, and model-based bootstrap intervals with fixed-support or repeated-selection procedures. The methods differ in their inferential targets and theoretical guarantees. Relevant methodological investigations are presented in Schemet and Friedrich-Welz (2026) <doi:10.1186/s12874-026-02887-0>, Schemet, Groll and Friedrich-Welz (2026) <doi:10.48550/arXiv.2608.18893>, and Schemet and Friedrich-Welz (2026) <doi:10.48550/arXiv.2608.24230>.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: stats, utils, survival, glmnet, MASS
Suggests: knitr, Matrix, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-10-20 11:23:57 UTC; schemele
Author: Lena Schemet [aut, cre], Sarah Friedrich-Welz [aut], Andreas Groll [aut]
Maintainer: Lena Schemet <lena.schemet@uni-a.de>
Repository: CRAN
Date/Publication: 2026-10-31 11:20:02 UTC

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New package misocialr with initial version 0.4.0
Package: misocialr
Title: Access the Brazilian 'MDS' Social Information Matrix ('MI Social') API from 'R'
Version: 0.4.0
Description: 'Tidyverse'-friendly interface to the 'MI Social' API of the Brazilian Ministry of Development and Social Assistance ('MDS', 'SAGI') <https://aplicacoes.mds.gov.br/sagi/servicos/misocial>. Retrieves monthly municipal series of the 'Cadastro Unico' (registered families and people by income bracket), the 'Bolsa Familia' programme (beneficiary families, benefits and transfers), the 'BPC' benefit, the social assistance network ('CRAS', 'CREAS' and other units), 'SUAS' funding, 'Bolsa Familia' conditionality monitoring and food security programmes as tidy long-format 'tibbles'.
License: MIT + file LICENSE
URL: https://strategicprojects.github.io/misocial/, https://github.com/StrategicProjects/misocial
BugReports: https://github.com/StrategicProjects/misocial/issues
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: httr2 (>= 1.0.4), cli (>= 3.6.1), tibble, purrr (>= 1.0.0), dplyr (>= 1.1.1), rlang, utils
Suggests: ggplot2, tidyr, scales, testthat (>= 3.2.1), httptest2, withr, jsonlite, webfakes, knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-10-20 15:39:21 UTC; leite
Author: Andre Leite [aut, cre] , Marcos Wasiliew [aut] , Hugo Vasconcelos [aut] , Carlos Amorim [aut] , Diogo Bezerra [aut]
Maintainer: Andre Leite <leite@castlab.org>
Repository: CRAN
Date/Publication: 2026-10-31 11:30:07 UTC

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New package brvmr with initial version 0.1.0
Package: brvmr
Title: Free Access to BRVM Stock Market Data
Version: 0.1.0
Language: fr
Description: Light client to read prices, indices and dividends of the Bourse Regionale des Valeurs Mobilieres (BRVM, West African stock exchange) from the public mirror 'harzat/brvm-data-public' of BRVMetrics. The package ships no data: it is downloaded at call time. Data remain the property of their sources (BRVM, SikaFinance, RicheBourse), with no guarantee of accuracy. This is not investment advice.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: jsonlite, utils
Suggests: testthat (>= 3.0.0), curl
URL: https://github.com/harzat/brvmr, https://brvmetrics.vercel.app
BugReports: https://github.com/harzat/brvmr/issues
NeedsCompilation: no
Packaged: 2026-10-20 22:58:47 UTC; HARZA
Author: Zabaly Noumoutche [aut, cre]
Maintainer: Zabaly Noumoutche <harzat1999@hotmail.com>
Repository: CRAN
Date/Publication: 2026-10-31 11:50:08 UTC

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New package acpbvar with initial version 0.2.0
Package: acpbvar
Title: Bayesian Structural VARs with Asymmetric Conjugate Priors
Version: 0.2.0
Description: Implements Bayesian estimation of structural Vector Autoregressions in the asymmetric A-form of Chan (2022) <doi:10.3982/QE1381>, with an asymmetric Minnesota prior whose own-lag and cross-lag hyperparameters are selected by empirical Bayes via the closed-form marginal likelihood. Exact equation-by-equation posterior simulation in the structural form (independent Normal-Inverse-Gamma draws) provides posterior draws of the reduced-form parameters; structural identification through sign restrictions follows the algorithm of Rubio-Ramirez, Waggoner and Zha (2010) <doi:10.1111/j.1467-937X.2009.00578.x>. Impulse responses, posterior bands, and acceptance diagnostics are computed from the accepted draws.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.0)
Imports: stats, utils, graphics, grDevices
Suggests: bsvarSIGNs, bsvars, knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
URL: https://github.com/ursillofederica/acpbvar
BugReports: https://github.com/ursillofederica/acpbvar/issues
NeedsCompilation: no
Packaged: 2026-10-20 13:43:47 UTC; federicaursillo
Author: Federica Ursillo [aut, cre]
Maintainer: Federica Ursillo <federica.ursillo@outlook.com>
Repository: CRAN
Date/Publication: 2026-10-31 11:20:08 UTC

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Fri, 30 Oct 2026

New package OECDdata with initial version 0.2.5
Package: OECDdata
Title: Fast and Friendly Access to OECD Data
Version: 0.2.5
Description: Discover, describe, compare and import statistical datasets from the Organisation for Economic Co-operation and Development ('OECD') via its public Statistical Data and Metadata eXchange ('SDMX') Representational State Transfer ('REST') API <https://sdmx.oecd.org/public/>. Adapts the discovery workflow of 'eurodata' to OECD-native names, catalogue-resolved short codes and dataset-scoped metadata. Uses SDMX REST version 2 by default, streamed downloads, native 'data.table' parsing, defensive metadata resolution, caching and bounded HTTP retries. Includes an explicit version 1 transport for interoperability.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: curl (>= 5.0.0), data.table (>= 1.14.8), digest (>= 0.6.31), magrittr (>= 2.0.3), utils, xml2 (>= 1.3.3)
Suggests: knitr, rmarkdown, testthat (>= 3.2.0), withr (>= 2.5.0)
VignetteBuilder: knitr
URL: https://github.com/alekrutkowski/OECDdata
NeedsCompilation: no
Packaged: 2026-10-20 08:32:20 UTC; CodexSandboxOffline
Author: Alek Rutkowski [aut, cre, cph]
Maintainer: Alek Rutkowski <alek.rutkowski@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-30 17:30:02 UTC

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New package cellsynth with initial version 0.1.0
Package: cellsynth
Title: Cell-Wise Synthetic Copies of De-Identified Tables
Version: 0.1.0
Description: Turns de-identified tables ('Excel' workbooks or delimited text files) into synthetic counterparts with the same layout, the same identifiers and the same data-entry quirks. Every non-identifier cell, missingness included, is censored once per sweep and redrawn by copying the raw value of a donor drawn from a classification and regression tree leaf fitted on the rest of the table, in the spirit of the sequential tree-based synthesis of Reiter (2005) "Using CART to generate partially synthetic public use microdata", Journal of Official Statistics 21(3):441-462, and Nowok, Raab and Dibben (2016) <doi:10.18637/jss.v074.i11>. Identifiers are kept so that tables stay joinable, and columns of other tables can condition the synthesis so cross-table associations survive a later join. Synthetic copies are intended for developing and testing analysis code; they are not an anonymisation method.
License: MIT + file LICENSE
URL: https://github.com/MartynK/cellsynth
BugReports: https://github.com/MartynK/cellsynth/issues
Encoding: UTF-8
Imports: openxlsx, readr, readxl, rpart, stats, tools, utils, withr
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-10-20 12:03:25 UTC; mrkma
Author: Marton Kiss [aut, cre]
Maintainer: Marton Kiss <mrkmarton@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-30 17:40:02 UTC

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New package ballast with initial version 0.6.1
Package: ballast
Title: Stress-Test a Pre-Specified Mixed Model for Repeated Measures
Version: 0.6.1
Description: Refits one pre-specified mixed model for repeated measures (MMRM) under families of data and analytic perturbations (covariance structure, degrees-of-freedom method and variance estimator, covariate set, analysis population, alternative analysis data sets, leave-one-out deletions, crossed specification grids, re-randomisation tests, delta-adjusted and reference-based multiple imputation, and alternative estimators) and judges every refit against the pre-specified estimate, confidence interval and p-value. Classifies the result as robust, sensitive or fragile, with a separate flag for marginal significance, and estimates by simulation the probability that a planned design gives a significant and robust result. Fitting uses 'mmrm' (Sabanes Bove et al., 2024, <https://openpharma.github.io/mmrm/>) with 'SAS' 'PROC MIXED' conventions for the least-squares-mean contrast, Kenward-Roger adjustment and the corrected Akaike criterion. Reference-based multiple imputation follows Carpenter, [...truncated...]
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-GB
Depends: R (>= 4.1.0)
Imports: mmrm (>= 0.3.0), stats, utils, parallel
Suggests: ggplot2, emmeans, nlme, MASS, flextable, officer, plotly, htmlwidgets, htmltools, jsonlite, testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
URL: https://github.com/Sullivanstatistics/ballast
BugReports: https://github.com/Sullivanstatistics/ballast/issues
NeedsCompilation: no
Packaged: 2026-10-19 17:37:26 UTC; asullivan
Author: Adam Sullivan [aut, cre, cph] , Nathan Hogan [ctb] , Capricor Therapeutics [fnd]
Maintainer: Adam Sullivan <asullivan@capricor.com>
Repository: CRAN
Date/Publication: 2026-10-30 12:30:02 UTC

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Thu, 29 Oct 2026

New package varunayan with initial version 0.4.0
Package: varunayan
Title: Download and Process 'ERA5', IMD, 'HadEX3' and 'CRU TS' Data
Version: 0.4.0
Description: Download climate data for a bounding box, polygon or point and return tidy tables. Sources are the 'ERA5' reanalysis (Hersbach et al. (2020) <doi:10.1002/qj.3803>) from the 'Copernicus' Climate Data Store <https://cds.climate.copernicus.eu/>, India Meteorological Department (IMD) gridded rainfall and temperature (Pai et al. (2014) <doi:10.54302/mausam.v65i1.851>), 'HadEX3' climate extremes (Dunn et al. (2020) <doi:10.1029/2019JD032263>) and 'CRU TS' (Harris et al. (2020) <doi:10.1038/s41597-020-0453-3>). Computes heat stress indices, including wet-bulb globe temperature (Liljegren et al. (2008) <doi:10.1080/15459620802310770>) and the Universal Thermal Climate Index (Bröde et al. (2012) <doi:10.1007/s00484-011-0454-1>), and heatwave indicators, including the Excess Heat Factor (Nairn and Fawcett (2015) <doi:10.3390/ijerph120100227>).
License: MIT + file LICENSE
URL: https://varunayan.saketlab.org/R/, https://github.com/saketlab/varunayan
BugReports: https://github.com/saketlab/varunayan/issues
Depends: R (>= 4.1.0)
Imports: data.table, digest, dplyr, ecmwfr (>= 2.0.0), httr, jsonlite, lubridate, magrittr, ncdf4, rlang, sf, stars, stats, terra, tools, utils, parallel
Suggests: ggplot2, ggpubr, gridExtra, knitr, maps, ncmeta, patchwork, R.utils, rmarkdown, scales, testthat (>= 3.1.7), tidyr, units, withr (>= 2.5.0)
VignetteBuilder: knitr
Copyright: See file inst/COPYRIGHTS
Encoding: UTF-8
Language: en-US
NeedsCompilation: no
Packaged: 2026-10-19 20:22:26 UTC; mcclintock
Author: Saket Choudhary [aut, cre, cph] , Darakhshan Nehal [aut], James C. Liljegren [ctb] , UChicago Argonne, LLC [cph]
Maintainer: Saket Choudhary <saketc@iitb.ac.in>
Repository: CRAN
Date/Publication: 2026-10-29 19:30:02 UTC

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New package relm with initial version 0.5.0
Package: relm
Title: Local Large Language Models as Base-R Objects
Version: 0.5.0
Description: Load and run local large language models (through a vendored, patched 'llama.cpp') from R and work with them as plain data frames and matrices in base-R idiom. Provides model loading and tokenization (llm(), llm_tokens()), text generation (llm_generate()), next-token distributions (llm_logits()), embeddings (llm_embed()), and mechanistic interpretability tools -- activation tracing (llm_trace()), activation steering (llm_steer()), neuron ablation (llm_ablate()), and grouped statistical probes (llm_probe()). Vision-language models loaded with their projector take image input in generation and embeddings. A checksum-verified downloader (llm_download()) fetches pinned models.
License: MIT + file LICENSE | Apache License (== 2.0)
Copyright: See inst/AUTHORS, inst/RUST-NOTICES and inst/THIRD-PARTY-NOTICES for bundled source authorship, copyrights and licenses.
URL: https://github.com/Vadale/R-ebirth, https://vadale.r-universe.dev/relm
BugReports: https://github.com/Vadale/R-ebirth/issues
Depends: R (>= 4.5.0)
Imports: methods, nanoarrow
Encoding: UTF-8
Suggests: testthat (>= 3.0.0), later (>= 1.4.8), promises (>= 1.5.0), glmnet, uwot, dbscan, quarto
VignetteBuilder: quarto
SystemRequirements: Cargo (Rust's package manager) >= 1.85.0, rustc >= 1.85.0, cmake (>= 3.28), xz
NeedsCompilation: yes
Packaged: 2026-10-19 17:50:24 UTC; runneradmin
Author: Alessandro Vadala [aut, cre, cph], ggml authors [ctb, cph] ), Authors of the bundled Rust and native dependencies [ctb, cph]
Maintainer: Alessandro Vadala <vadale93@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-29 19:20:02 UTC

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New package datagrade with initial version 0.2.0
Package: datagrade
Title: Data Quality Assessment on the ISO/IEC 25012 Model
Version: 0.2.0
Description: A single-call data quality assessment scoring a data set on the five inherent characteristics of the ISO/IEC 25012 data quality model (accuracy, completeness, consistency, credibility and currentness) through the fifteen quality properties beneath them, ISO/IEC (2008) <https://www.iso.org/standard/35736.html>. Each property is measured as a ratio of counted data items, the form ISO/IEC 25024 measurement functions take, ISO/IEC (2015) <https://www.iso.org/standard/35749.html>. Six properties are computable from a table alone; the rest compare the data against expectations declared through a specification object, and are reported as not applicable rather than approximated when none is supplied. Also reports missing-data patterns, duplicates, redundant columns, outliers, multicollinearity and distributional deviations, and returns a structured object with plots rather than console text alone. The statistics implement the methodology of the author's master's dissertation, Demir [...truncated...]
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: cli, ggplot2 (>= 3.4.0), stats, tools, utils
Suggests: knitr, randomForest, rmarkdown, readxl, testthat (>= 3.0.0)
URL: https://github.com/ohalukdemirhan/datagrade
BugReports: https://github.com/ohalukdemirhan/datagrade/issues
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-10-19 21:45:13 UTC; jupiter
Author: Omer Haluk Demirhan [aut, cre]
Maintainer: Omer Haluk Demirhan <hlk01dn@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-29 19:30:12 UTC

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New package cepip with initial version 0.1.0
Package: cepip
Title: Cell Explanatory Power with Inflection Point (CEP-IP) with CMRF
Version: 0.1.0
Description: Implements the cell explanatory power with inflection point (CEP-IP) framework for single-cell co-expression analysis. A generalized additive model (GAM) fitted by restricted maximum likelihood (REML) with a penalized residual sum of squares (PRSS) search over the basis dimension relates a gene of interest to the mean of its partner genes. Cells are ranked by their explanatory power, and the inflection point is the first negative-to-positive zero crossing of a residual GAM. Optional extensions are the Spearman-Kendall cell-level score (SKCS) and the copula monotone recovery filter (CMRF), which recovers cells near the module through a tolerance band and a repeated stratified k-fold cross-validation gate. Downstream helpers give per-donor module fractions, paired donor-level differential expression and donor-level association models. CEP-IP is described in Wong (2026) <doi:10.1016/j.cmpb.2026.109372>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Depends: R (>= 4.1.0)
Imports: mgcv, stats, utils, methods, grDevices, grid, parallel, Matrix, ggplot2 (>= 3.4.0), gridExtra, openxlsx
Suggests: Hmisc, energy, clinfun, pcaPP, testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
URL: https://github.com/kahkengwong/cepip
BugReports: https://github.com/kahkengwong/cepip/issues
NeedsCompilation: no
Packaged: 2026-10-19 23:24:38 UTC; root
Author: Kah Keng Wong [aut, cre]
Maintainer: Kah Keng Wong <kahkeng3@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-29 19:30:19 UTC

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New package caplime with initial version 0.1.0
Package: caplime
Title: Conic Adaptive Piecewise Local Explanations
Version: 0.1.0
Description: Provides educational, base-R implementations of a ridge-penalized piecewise hinge regression model and local surrogate explanations for numerical prediction functions. Includes simplified variants inspired by local interpretable model-agnostic explanations (LIME) and a simplified bandwidth selection variant (OPTILIME), plus exploratory stability diagnostics.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
NeedsCompilation: no
Packaged: 2026-10-18 00:19:59 UTC; vilda
Author: Nurguel Goekgoez Kuecueksakalli [aut, cre] , Vilda Purutcuoglu [aut]
Maintainer: Nurguel Goekgoez Kuecueksakalli <nurgul.gokgoz@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-29 19:20:14 UTC

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New package BiGaRx with initial version 0.5.1
Package: BiGaRx
Title: Unified Classical and Canonical Biplots
Version: 0.5.1
Description: Classical and canonical biplots computed from a single singular value decomposition (SVD) engine. Includes the two biplots of Gabriel (1971) <doi:10.1093/biomet/58.3.453>: the GH-biplot, named after its row markers G and column markers H, which preserves the column metric (covariances and correlations between variables), and the JK-biplot, named after its row markers J and column markers K, which preserves the row metric (distances between individuals). Also includes the HJ-biplot of Galindo (1986) <https://upcommons.upc.edu/entities/publication/e17797dd-e20b-4fe5-b34a-f4cde41695ed>, which combines the row markers J and the column markers H so that rows and columns are both represented with maximum quality. Options include configurable preprocessing, supplementary rows and columns, quality of representation, contributions, goodness of fit, bootstrap confidence intervals following Nieto, Galindo, Leiva and Vicente-Galindo (2014) <doi:10.15446/rce.v37n2spe.47944>, and i [...truncated...]
License: GPL (>= 3)
Encoding: UTF-8
Language: es
Depends: R (>= 3.6.0)
Imports: stats, graphics, grDevices, utils
Suggests: ggplot2, generics, MASS, testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-10-20 01:54:11 UTC; kleberin22
Author: Kleber Garzon [aut, cre] , Roxana Barrezueta [aut]
Maintainer: Kleber Garzon <garzon.kleber@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-29 19:30:25 UTC

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New package RWInfoLSTM with initial version 0.1.0
Package: RWInfoLSTM
Title: Random Walk-Informed LSTM for Time Series Forecasting
Version: 0.1.0
Maintainer: Ranjit Kumar Paul <ranjitstat@gmail.com>
Description: Implements a Random Walk (RW)-informed Long Short-Term Memory (LSTM) network for univariate time series forecasting. The LSTM is trained on the full series with a composite loss that blends the usual mean squared error (MSE) between predictions and observations with the MSE between predictions and the fitted Random Walk, weighted by a parameter lambda (0 gives a standard LSTM, 1 gives a fully RW-guided LSTM). The Random Walk, either simple or with drift, is selected automatically by its in-sample root mean squared error (RMSE), and the lambda value with the lowest training RMSE is retained. The LSTM hyperparameters can be supplied manually or tuned by grid search, and functions for out-of-sample forecasting, accuracy measures and plots are provided. The methodology is motivated by hybrid forecasting framework proposed by Yeasin and Paul (2024) <doi:10.1007/s11227-023-05542-3>.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: torch (>= 0.11.0), coro, ggplot2 (>= 3.4.0), cli (>= 3.6.0), stats, utils
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-10-19 16:24:45 UTC; borap
Author: Md Yeasin [aut], Ranjit Kumar Paul [aut, cre], Pushkar Bora [aut]
Repository: CRAN
Date/Publication: 2026-10-29 12:00:02 UTC

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New package powerup with initial version 0.3.1
Package: powerup
Title: Power Up Your PowerPoint Presentations
Version: 0.3.1
Description: Programmatically interact with new or existing 'Microsoft PowerPoint' documents, by adding new slides, updating existing slides, and inserting displays into specific locations in slides. Users can also add transition effects to slides, and add displays to specific locations in slides by pointing to specific placeholders or creating new ones. Preview the slides in a local viewer.
License: Apache License (>= 2)
URL: https://gsk-biostatistics.github.io/powerup/, https://github.com/GSK-Biostatistics/powerup/
BugReports: https://github.com/GSK-Biostatistics/powerup/issues/
Depends: R (>= 4.1.0), polish (>= 0.2.0)
Imports: rlang, dplyr, officer (>= 0.6.7), purrr, tibble, xml2, cli, glue, ggplot2, htmltools, base64enc, shiny
Suggests: testthat (>= 3.0.0), rmarkdown, webshot2, knitr, flextable, withr
Encoding: UTF-8
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-10-19 12:57:39 UTC; ehh82309
Author: Ellis Hughes [aut, cre] , Shannon Haughton [aut], Romain Francois [aut], GlaxoSmithKline Research & Development Limited [cph, fnd]
Maintainer: Ellis Hughes <ellis.h.hughes@gsk.com>
Repository: CRAN
Date/Publication: 2026-10-29 11:50:02 UTC

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New package MultinomFourier with initial version 1.0
Package: MultinomFourier
Title: p-Values of Multinomial Goodness-of-Fit Tests by Fourier Series Inversion
Version: 1.0
Author: Charles Thraves [aut], Pablo Rivas [aut, cre], Felipe Subiabre [aut]
Maintainer: Pablo Rivas <pablo.rivas.g@ug.uchile.cl>
Description: Computes p-values of multinomial goodness-of-fit tests based on an additive statistic: the log-likelihood ratio, Pearson's chi-squared, the Cressie-Read power divergence, and the exact multinomial test. The main function, pval_fourier(), writes the p-value as a Fourier series in the moment-generating function of the statistic and sums it until an adaptive stopping rule is met, which makes small p-values of large instances computationally feasible. The function pval_exact() computes the exact p-value by branch pruning with bounds from a dynamic program, and pval_flexible() chooses between the two according to the size of the instance.
License: GPL (>= 2)
Encoding: UTF-8
Imports: parallel
Suggests: knitr, rmarkdown, ggplot2
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2026-10-19 16:00:50 UTC; itspa
Repository: CRAN
Date/Publication: 2026-10-29 12:00:07 UTC

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New package MixedDiversityAnalysis with initial version 0.1.0
Package: MixedDiversityAnalysis
Title: Analysis and Visualization of Mixed-Trait Dissimilarity
Version: 0.1.0
Description: Provides methods for analysing datasets containing quantitative, qualitative, binary, and ordinal traits. Computes mixed-trait dissimilarities and performs hierarchical clustering using multiple linkage methods. Supports principal coordinates analysis (PCoA), cluster evaluation, trait contribution analysis, and graphical visualization. The package facilitates mixed-trait diversity assessment and characterization of crop germplasm. For more detail see Gower (1971) <doi:10.2307/2528823> and Jukanti et al. (2026) <doi:10.1007/s44187-025-00715-w>.
License: GPL (>= 3)
Encoding: UTF-8
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
Imports: cluster
NeedsCompilation: no
Packaged: 2026-10-19 09:00:18 UTC; Dr. Prabhat
Author: Santosha Rathod [aut], Prabhat Kumar [aut, cre], A. K. Jukanti [aut], Radha Upadhyay [aut], Prashantkumar S Hanjagi [aut], Basavaraj PS [aut], R. N. Singh [aut], Anil Kumar [aut]
Maintainer: Prabhat Kumar <prabhatkkv@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-29 11:10:07 UTC

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New package maxtwin with initial version 0.1.0
Package: maxtwin
Title: A Robust Deterministic Data Splitting Method
Version: 0.1.0
Description: Provides a deterministic method for splitting data into training and testing sets that maximizes the distance between training and testing points while preserving their distributions. See Joseph and Cho (in press) for details. This work is supported by U.S. National Science Foundation grant DMS-2310637.
License: GPL (>= 3)
Encoding: UTF-8
Depends: R (>= 3.5.0)
Imports: FNN, twinning (>= 1.1)
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-10-19 12:50:11 UTC; ycho397
Author: Youngseo Cho [aut, cre], V. Roshan Joseph [aut]
Maintainer: Youngseo Cho <ycho397@gatech.edu>
Repository: CRAN
Date/Publication: 2026-10-29 11:40:02 UTC

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New package IFARIMA with initial version 0.1.0
Package: IFARIMA
Title: Intuitionistic Fuzzy Autoregressive Integrated Moving Average Model
Version: 0.1.0
Description: The Intuitionistic Fuzzy Autoregressive Integrated Moving Average model offers advanced time series forecasting by integrating intuitionistic fuzzy sets with ARIMA. It enhances prediction accuracy by handling uncertainties and hesitations more effectively than traditional models, making it ideal for complex, real-world data applications. The package has been developed using the algorithm of Yolcu and Yolcu (2023) <doi:10.1016/j.eswa.2022.119336>.
License: GPL-3
Encoding: UTF-8
Imports: stats, forecast
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-10-19 14:26:45 UTC; borap
Author: Anita Sarkar [aut], Ankit Kumar Singh [aut], Md Yeasin [aut, cre], Ranjit Kumar Paul [aut], Amrit Kumar Paul [aut], Pushkar Bora [aut]
Maintainer: Md Yeasin <yeasin.iasri@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-29 11:50:09 UTC

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New package glt with initial version 1.0
Package: glt
Title: Bayesian Factor Modelling via Generalized Lower Triangular Priors
Version: 1.0
Description: Sparse Bayesian factor models for multivariate data, built around a flexible Generalized Lower Triangular (GLT) process prior on the loading matrix by Canale and Frühwirth-Schnatter (2026) <doi:10.48550/arXiv.2610.09762>. The number of active factors, their sparsity pattern, and the loadings themselves are learned jointly via a Markov chain Monte Carlo sampler implemented in C++ with 'Rcpp' and 'RcppArmadillo'.
License: GPL-2
Encoding: UTF-8
LinkingTo: Rcpp, RcppArmadillo
Imports: Rcpp, sparvaride
NeedsCompilation: yes
Packaged: 2026-10-19 11:18:16 UTC; antonio
Author: Antonio Canale [aut, cre]
Maintainer: Antonio Canale <antonio.canale@unipd.it>
Repository: CRAN
Date/Publication: 2026-10-29 11:10:01 UTC

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New package bmetapred with initial version 0.1.0
Package: bmetapred
Title: Bayesian Meta-Prediction in the Presence of Prediction Error
Version: 0.1.0
Description: Fits pseudo-Bayesian Model Averaging (pBMA) and Bayesian Stacking ensembles of linear meta-models while explicitly accounting for the prediction errors of the individual models, building on the Bayesian Stacking of predictive distributions framework of Yao et al. (2018) <doi:10.1214/17-BA1091>. When native uncertainty estimates are unavailable, it provides tools to estimate heteroscedastic errors via Local Polynomial Regression (LOESS). The meta-model space is explored using exhaustive search, a Markov Chain Monte Carlo Model Composition (MC3) algorithm following Madigan and Raftery (1994) <doi:10.1080/01621459.1994.10476894> when pBMA is selected, or a tabu-guided heuristic search with parallel tempering when bayesian stacking is selected, all powered by 'brms' (Bürkner, 2017 <doi:10.18637/jss.v080.i01>).
License: GPL (>= 3)
Encoding: UTF-8
Imports: brms, future, future.apply, loo, stats, utils
NeedsCompilation: no
Packaged: 2026-10-19 12:51:46 UTC; General
Author: Jorge Piqueras Marques [aut, cre] , Anabel Forte Deltell [aut] , Joaquin Martinez Minaya [ctb]
Maintainer: Jorge Piqueras Marques <jorge.piqueras.m@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-29 11:40:07 UTC

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New package aidatabroker with initial version 0.1.0
Package: aidatabroker
Title: Read Open Data on the AI Training Data Market
Version: 0.1.0
Description: Downloads the open datasets published by 'AIData.Broker' on the market for AI training data: public prices, licensing deals, buyers, vendors, lawsuits and related tables, each row with its source, from <https://aidata.broker/datasets>. The data are licensed CC BY 4.0.
License: MIT + file LICENSE
URL: https://aidata.broker/datasets
Encoding: UTF-8
Imports: utils
NeedsCompilation: no
Packaged: 2026-10-18 13:44:47 UTC; yuma2
Author: Yuma Heymans [aut, cre]
Maintainer: Yuma Heymans <hello@aidata.broker>
Repository: CRAN
Date/Publication: 2026-10-29 11:20:10 UTC

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New package SWORD with initial version 0.1.0
Package: SWORD
Title: Support Vector Machine Weighted Oblique Random Decision Forests
Version: 0.1.0
Description: Implements SWORD (Support vector machine Weighted Oblique Random Decision forests), a random forest method for regression based on TORS (Tree Oblique for Regression with weighted SVM) oblique regression trees. At each internal node a Weighted-SVM classifier with a linear kernel defines the oblique splitting hyperplane as a sparse linear combination of predictors. The C++ coordinate-descent solver provides fast training. Variable importance is computed via OIW-VI (Oblique Impurity-Weighted Variable Importance). Provides tree fitting (TORS), forest fitting (SWORD), prediction, and variable importance (VI_SWORD). Parallel tree fitting is supported via the 'future'/'furrr' framework. The SWORD method is described in Carta and Frigau (accepted, in press) 'Oblique Random Forests for Regression via Weighted Support Vector Machine', Advances in Data Analysis and Classification. The TORS algorithm is described in Carta and Frigau (2025) <doi:10.1007/s00180-025-01647-w>. The weighted SVM i [...truncated...]
License: GPL-3
URL: https://github.com/acarta88/sword-package
BugReports: https://github.com/acarta88/sword-package/issues
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: Rcpp (>= 1.0.0)
LinkingTo: Rcpp
Suggests: infotheo, furrr, progressr, future, visNetwork, microbenchmark, knitr, rmarkdown, ggplot2, MASS, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2026-10-19 09:02:03 UTC; acart
Author: Andrea Carta [aut, cre] , Luca Frigau [aut]
Maintainer: Andrea Carta <andrea.carta88@unica.it>
Repository: CRAN
Date/Publication: 2026-10-29 10:40:02 UTC

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Wed, 28 Oct 2026

New package gllvmTMB with initial version 0.7.1
Package: gllvmTMB
Title: Generalised Linear Latent Variable Models
Version: 0.7.1
Description: Fits multivariate generalised linear latent variable models using either long-format data or a wide data frame. Models support several response distributions and trait covariance structures, and can estimate correlations, shared latent axes, and trait-specific variances. Binary presence-absence data can be used for joint species distribution analyses. Optional animal, phylogenetic, spatial, and kernel covariance components are available. Estimation uses 'Template Model Builder'. Spatial effects can use sparse Gaussian Markov random field constructions. This 0.7.1 release remains experimental: evidence for estimates is model- and regime-specific. Broad interval coverage is not certified; a 0.94 coverage floor is documented only for one two-sided Gaussian total-variance profile setting.
License: GPL-3
Language: en-GB
Copyright: inst/COPYRIGHTS
URL: https://itchyshin.github.io/gllvmTMB/, https://github.com/itchyshin/gllvmTMB
BugReports: https://github.com/itchyshin/gllvmTMB/issues
Depends: R (>= 4.1.0)
Imports: assertthat, cli, fmesher, generics, graphics, lifecycle, Matrix, methods, rlang, stats, tidyselect, TMB (>= 1.8.0), utils
LinkingTo: BH, RcppEigen, TMB
Suggests: ape, DHARMa, detectseparation (>= 0.4.0), dplyr, future, future.apply, ggforce, ggplot2, galamm, glmmTMB, gllvm, JuliaCall, jsonlite, knitr, lme4, MASS, MCMCglmm, mgcv, mirt, mvtnorm, nadiv, rmarkdown, sf, testthat (>= 3.0.0), tibble, tidyr, tweedie, vegan, vdiffr, withr
VignetteBuilder: knitr
ByteCompile: true
Encoding: UTF-8
SystemRequirements: GNU make, C++17
NeedsCompilation: yes
Packaged: 2026-10-16 10:49:07 UTC; z3437171
Author: Shinichi Nakagawa [aut, cre, cph]
Maintainer: Shinichi Nakagawa <itchyshin@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-28 20:00:08 UTC

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New package lczexplore with initial version 0.1.1
Package: lczexplore
Title: Imports, Visualizes, Compares and Explores Maps of Local Climate Zones
Version: 0.1.1
Description: Easily import and visualize local climate zone maps with standard encoding. Compare two or more maps, and group some LCZ types according to user defined grouping vectors. Explore their differences through circular visualization and indicators. For more Details see Gousseff et al (2023) "lczexplore: an R package to explore Local Climate Zone classifications" <doi:10.21105/joss.05445>.
License: LGPL (>= 3)
Encoding: UTF-8
Imports: circlize, collapse, data.table, dplyr, forcats, ggnewscale, ggplot2, grDevices, ggspatial, ggsankeyfier, jsonlite, magrittr, methods, patchwork, randomcoloR, RColorBrewer, sf, shades, terra, tidyr, units
Suggests: knitr, markdown, rmarkdown, tinytest, png
VignetteBuilder: knitr
LazyData: true
Depends: R (>= 4.0.0)
NeedsCompilation: no
Packaged: 2026-10-19 08:44:34 UTC; gousseff
Author: Matthieu Gousseff [aut, cre, cph]
Maintainer: Matthieu Gousseff <matthieu.gousseff@cnrs.fr>
Repository: CRAN
Date/Publication: 2026-10-28 12:30:02 UTC

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New package dgtf with initial version 0.1.0
Package: dgtf
Title: Variational and Monte Carlo Inference for Bayesian State-Space Models of Count Data
Version: 0.1.0
Description: Bayesian inference for a general class of state-space models for count data, providing a unified interface to variational Bayes and Markov chain Monte Carlo. Models are assembled from modular components for the observation distribution, link function, gain function, lag distribution, system equation, and system error, and support Poisson and negative binomial observations together with seasonality terms. The model class and the hybrid variational approximation are described in Tang and Prado (2026) <doi:10.1016/j.csda.2026.108368>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
NeedsCompilation: yes
SystemRequirements: C++17
Depends: R (>= 4.1.0)
Imports: Rcpp (>= 1.0.10), stats, utils, graphics, grDevices, ggplot2 (>= 3.3.0)
LinkingTo: Rcpp, RcppArmadillo, BH, RcppProgress, pg
Suggests: testthat (>= 3.0.0), knitr, rmarkdown, EpiEstim
URL: https://github.com/minimeini/dgtf
BugReports: https://github.com/minimeini/dgtf/issues
VignetteBuilder: knitr
Packaged: 2026-10-19 08:37:18 UTC; meinitang
Author: Meini Tang [aut, cre] , Raquel Prado [aut]
Maintainer: Meini Tang <meini.tang@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-28 12:20:12 UTC

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New package cafast with initial version 0.1.0
Package: cafast
Title: Fast Companions to the 'CAs' Package for Covering Arrays
Version: 0.1.0
Description: Compiled implementations and generalizations of selected functions of the 'CAs' package by Ulrike Groemping for covering arrays. The package provides a C version of the search for the largest set of rows that can be made constant by permuting symbols, the power construction of Colbourn and Torres-Jimenez (2010) <doi:10.1090/conm/523/10309> for any strength, number of columns and number of levels, a counting kernel that tabulates value tuples for every set of t columns, and fast versions of the flexible-value tools and of the randomized post-optimization of Nayeri, Colbourn and Konjevod (2013) <doi:10.1016/j.ejc.2012.07.017>. Each function was tested against its 'CAs' counterpart, and the remaining differences are documented.
License: GPL (>= 3)
URL: https://github.com/chrispbsmolen/ca-tools
BugReports: https://github.com/chrispbsmolen/ca-tools/issues
Encoding: UTF-8
Language: en-US
Depends: R (>= 4.0)
Imports: CAs
Suggests: caverify, lhs
NeedsCompilation: yes
Packaged: 2026-10-18 02:52:21 UTC; axviam
Author: Christopher Smolen [aut, cre]
Maintainer: Christopher Smolen <chrispbsmolen@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-28 12:30:10 UTC

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New package saydo with initial version 0.1.0
Package: saydo
Title: Link What People Say to What They Do with LLM-Coded Themes
Version: 0.1.0
Description: Measures the say-do gap in mixed-methods data: whether themes in what people say go with differences in what they do. Codes free text against a codebook with large language models through 'ellmer', or any coder function, and validates the codes against a human-coded sample with Cohen's kappa, precision and recall. Links the codes to participants' behavioural or outcome data, aggregating segment-level transcripts to participants where needed, and tests each theme against each metric with Welch's t-test and multiple-comparison adjustment. Developed by Neudata Consulting Ltd.
License: MIT + file LICENSE
URL: https://neu-data.github.io/saydo/, https://github.com/neu-data/saydo
BugReports: https://github.com/neu-data/saydo/issues
Depends: R (>= 4.1)
Imports: cli, ellmer (>= 0.3.0), ggplot2 (>= 3.5.0), rlang, stats, tibble, withr
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-10-18 12:42:01 UTC; hp
Author: Bernard Isekah Osangir [aut, cre], Neudata Consulting Ltd [cph, fnd]
Maintainer: Bernard Isekah Osangir <b.osangir@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-28 12:00:02 UTC

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New package RDelta with initial version 0.1.0
Package: RDelta
Title: Parse and Query DELTA-Format Taxonomic Descriptions
Version: 0.1.0
Date: 2026-10-18 # Update to current date
Maintainer: Mauro Cavalcanti <maurobio@gmail.com>
Description: Provides an R interface to the 'tDelta' C++ library for parsing DELTA (DEscription Language for TAxonomy) format files <https://freedelta.sourceforge.net>. Supports loading character lists, item descriptions, and specifications, with efficient searching and matching of items based on character values. It also supports the generation of identification keys, diagnoses, natural-language descriptions, and clustering and ordination analyses by means of the DELTA programs 'CONFOR', 'KEY', and 'DIST'.
License: GPL (>= 3)
URL: https://github.com/maurobio/rdelta
BugReports: https://github.com/maurobio/rdelta/issues
Depends: R (>= 3.5.0)
Imports: Rcpp (>= 1.0.0), graphics, methods, stats, utils
LinkingTo: Rcpp
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
SystemRequirements: C++17
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2026-10-18 12:25:11 UTC; mauro
Author: Mauro Cavalcanti [aut, cre] , Edinaldo Nelson dos Santos Silva [ctb]
Repository: CRAN
Date/Publication: 2026-10-28 11:10:18 UTC

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New package RASbound with initial version 0.0.1
Package: RASbound
Title: Bounded RAS / Biproportional Matrix Balancing with Cell-Level Constraints
Version: 0.0.1
Description: Implements the RAS method for adjusting a matrix to match target row and column totals. In RAS, a matrix A is multiplied on the left by a diagonal matrix R and on the right by a diagonal matrix S, which gives the method its name. It is also known as biproportional matrix balancing, iterative proportional fitting (IPF) or raking. The package extends it with lower and upper bounds on individual cells. Provides several algorithmic variants for handling bound violations: hard cell-freezing with simultaneous, sequential, or hybrid fixation; two dependency-free clamp-and-compensate heuristics (proportional redistribution and iterative renormalization); and a naive unconstrained-recompute baseline; together with thin wrapper functions exposing equivalent bounded-calibration methods from the 'survey' package under a common interface. Intended for updating or regionalizing input-output tables, social accounting matrices (SAMs), and other applications where classic RAS/IPF is used but cell-level [...truncated...]
License: GPL-3
Encoding: UTF-8
Depends: R (>= 3.6)
Imports: stats, graphics, grDevices, utils
Suggests: survey, MASS, testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
URL: https://github.com/JMPavia/RASbound
BugReports: https://github.com/JMPavia/RASbound/issues
NeedsCompilation: no
Packaged: 2026-10-18 16:59:08 UTC; pavia
Author: Jose M. Pavia [aut, cre]
Maintainer: Jose M. Pavia <jose.m.pavia@uv.es>
Repository: CRAN
Date/Publication: 2026-10-28 11:30:10 UTC

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New package psdea with initial version 1.0.0
Package: psdea
Title: Data Envelopment Analysis with User-Defined and Learned Reference Sets
Version: 1.0.0
Author: Jiachao Peng [aut, cre]
Maintainer: Jiachao Peng <jiachao.peng@wit.edu.cn>
Description: Slacks-based data envelopment analysis for panel data in which the reference set is an explicit argument. A user-supplied weight matrix, or a matrix learned from the data by penalised non-negative reconstruction, selects the units that may enter each decision-making unit's frontier. The package reports the unrestricted and the restricted score, the ratio of the two and an exact decomposition of the shortfall into the part the restricted technology can remove and the part it cannot. Moran's I and local indicators of spatial association are provided as diagnostics. All linear programs are solved by a two-phase simplex with Bland's rule implemented in R, so the package needs no compiler.
License: GPL-3
Encoding: UTF-8
LazyData: true
Depends: R (>= 4.0)
Imports: utils
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-10-18 12:52:49 UTC; jiach
Repository: CRAN
Date/Publication: 2026-10-28 11:10:02 UTC

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New package PortinariColors with initial version 0.3.0
Package: PortinariColors
Title: Color Palettes Inspired by the Paintings of Candido Portinari
Version: 0.3.0
Description: Color palettes inspired by paintings of Candido Portinari held by the Sao Paulo Museum of Art (MASP) and by his Guerra (War) and Paz (Peace) panels at the United Nations Headquarters. Provides qualitative, diverging and sequential palettes for discrete and continuous data, ready-made 'ggplot2' color and fill scales, and a colorblind-safety check that simulates protanopia, deuteranopia and tritanopia following Machado, Oliveira and Fernandes (2009) <doi:10.1109/TVCG.2009.113>.
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-US
URL: https://rafalopespx.github.io/PortinariColors/, https://github.com/rafalopespx/PortinariColors
BugReports: https://github.com/rafalopespx/PortinariColors/issues
Imports: ggplot2 (>= 3.4.0), grDevices, graphics, stats, utils
Suggests: spelling, testthat (>= 3.1.5)
NeedsCompilation: no
Packaged: 2026-10-18 17:18:16 UTC; rl957
Author: Rafa Lopes [aut, cre]
Maintainer: Rafa Lopes <lopes1313@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-28 11:30:15 UTC

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New package multipathaic with initial version 0.1.3
Package: multipathaic
Title: Multi-Path Stepwise Selection with AIC
Version: 0.1.3
Description: Implements a multi-path forward selection algorithm using the Akaike Information Criterion (AIC) for both linear (Gaussian) and logistic (binomial) regression models. Unlike traditional stepwise methods that follow a single path, this approach explores multiple competitive model paths simultaneously by retaining near-optimal models at each step. The package includes stability estimation via bootstrap resampling and identifies plausible models based on AIC tolerance and variable stability thresholds. The information criterion is described by Akaike (1974) <doi:10.1109/TAC.1974.1100705>, and bootstrap resampling by Efron (1979) <doi:10.1214/aos/1176344552>.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 3.5.0)
Imports: stats, utils
Suggests: lars, knitr, rmarkdown, shiny, shinydashboard, plotly, DT, ggplot2, readxl, htmltools, kableExtra
VignetteBuilder: knitr
URL: https://github.com/mobuobi/multipathaic
BugReports: https://github.com/mobuobi/multipathaic/issues
NeedsCompilation: no
Packaged: 2026-10-18 15:04:53 UTC; michael
Author: Michael Obuobi [aut, cre]
Maintainer: Michael Obuobi <obuobimichael25@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-28 11:50:02 UTC

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New package lepidoptera with initial version 0.1.2
Package: lepidoptera
Title: Domain-Agnostic Causal Simulation Engine with Mixed Variable Types
Version: 0.1.2
Description: A domain-agnostic simulation engine for structural causal models with heterogeneous variable types. Users define systems of continuous, categorical, and ordinal features, declare a directed acyclic graph (DAG) over them, attach typed generative mechanisms to each node, and simulate synthetic populations. A pre-built mechanism library covers all nine parent-type/child-type combinations. Vine copula mechanisms estimate full joint dependence from observed data via pair-copula constructions (Bedford and Cooke, 2002) <doi:10.1214/aos/1031689014>. Individual-level counterfactual queries are supported through partial propagation, which freezes unaffected random draws and resamples only the downstream subgraph, enabling individual treatment effect (ITE) estimation alongside population-level average treatment effects (ATE). Any pre-fitted predictive model can serve as a generative mechanism through three wrapper functions. Systems serialise to JSON for cross-language portability with the [...truncated...]
License: MIT + file LICENSE
URL: https://github.com/danilosarti/lepidoptera
BugReports: https://github.com/danilosarti/lepidoptera/issues
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: stats
Suggests: testthat (>= 3.0.0), igraph, rvinecopulib (>= 0.6.0), jsonlite, yaml, knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-10-16 16:05:38 UTC; danilosarti
Author: Danilo Sarti [aut, cre]
Maintainer: Danilo Sarti <danilosarti@rcsi.ie>
Repository: CRAN
Date/Publication: 2026-10-28 11:40:02 UTC

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New package hairline with initial version 0.1.0
Package: hairline
Title: Clean, Predictable Figures for Medical and Data Science
Version: 0.1.0
Description: A design system for 'ggplot2' figures: one frame for titles, legends, panels and captions, a fixed spacing and type scale, colour-vision checked palettes, brand files in the 'brand.yml' format, and print-ready export. Produces output matching the 'hairline' Python package.
License: MIT + file LICENSE
URL: https://github.com/schradern/hairline
BugReports: https://github.com/schradern/hairline/issues
Copyright: The bundled 'Hairline Sans' font is a modified Public Sans, Copyright 2015 The Public Sans Project Authors, under the SIL Open Font License 1.1; see inst/COPYRIGHTS.
Encoding: UTF-8
Depends: R (>= 4.3)
Imports: S7, ggplot2 (>= 4.0.0), grid, grDevices, jsonlite, ragg, rlang, systemfonts, textshaping, tools, utils, yaml
Suggests: cowplot, metafor, patchwork, png, rsvg, survival, svglite, testthat (>= 3.0.0), withr
NeedsCompilation: no
Packaged: 2026-10-19 05:17:30 UTC; nschrader
Author: Nikolas Schrader [aut, cre, cph]
Maintainer: Nikolas Schrader <hi@nikolasschrader.com>
Repository: CRAN
Date/Publication: 2026-10-28 11:50:08 UTC

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New package evgmrf with initial version 0.1.0
Package: evgmrf
Title: Gaussian Markov Random Field Models for Extreme Values
Version: 0.1.0
Description: Fitting extreme value distributions with parameters that vary according to Gaussian Markov random fields (GMRFs). For details of distributions see Coles, S.G. (2001) <doi:10.1007/978-1-4471-3675-0>, GMRFs see Rue, H., & Held, L. (2005) <doi:10.1201/9780203492024>, and the fitting approach see Wood, S.N., Pya, N. & Safken, B. (2016) <doi:10.1080/01621459.2016.1180986>.
License: GPL-3
Encoding: UTF-8
Depends: R (>= 3.5.0)
Imports: Rcpp (>= 1.0.10), Matrix (>= 1.6-0), methods, lattice, gridExtra, sparseinv
LinkingTo: Rcpp, RcppArmadillo, RcppEigen, Matrix
NeedsCompilation: yes
Packaged: 2026-10-16 13:52:21 UTC; ben
Author: Ben Youngman [aut, cre] , Ayu Shabrina [aut, ctb]
Maintainer: Ben Youngman <b.youngman@exeter.ac.uk>
Repository: CRAN
Date/Publication: 2026-10-28 11:20:15 UTC

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New package creditratingsystem with initial version 0.1.0
Package: creditratingsystem
Title: Offline Credit Risk Modelling, Calibration and Validation
Version: 0.1.0
Description: Native credit risk calculations, statistical estimation, calibration, validation and cash flow simulation using local structured data. Methods cover consumer and business lending with explicit modelling assumptions, diagnostics and reproducible reference data.
License: AGPL-3
Encoding: UTF-8
Depends: R (>= 4.1.2)
Imports: stats, utils, jsonlite, digest, lpSolve, Matrix, survival, glmnet, MASS, e1071, brglm2, splines, xgboost, copula, mvtnorm, vars, urca, KFAS
Suggests: testthat, knitr, rmarkdown
NeedsCompilation: no
Packaged: 2026-10-16 14:09:40 UTC; qwert123
Author: RiskDataScience GmbH [aut, cph], Dimitrios Geromichalos [cre]
Maintainer: Dimitrios Geromichalos <riskdatascience@web.de>
Repository: CRAN
Date/Publication: 2026-10-28 11:20:21 UTC

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New package bartisan with initial version 0.1.0
Package: bartisan
Title: Generalized Bayesian Additive Regression Trees
Version: 0.1.0
Description: Fits Bayesian additive regression trees (BART) models for likelihoods outside the conditionally conjugate Gaussian case, using the Laplace-approximation reversible-jump sampler of Linero (2025) <doi:10.1080/01621459.2024.2337156>. Supported response families include Gaussian, binomial, Poisson, negative binomial, gamma, beta, ordered beta, ordinal (cumulative link), multinomial, zero-inflated counts, a Tweedie compound Poisson for a non-negative response with a point mass at zero, accelerated failure time and proportional hazards models for right-censored survival data, location-scale regression, and a Dirichlet process mixture for the error distribution. Decision rules may be hard, as in standard BART, or soft, as in the SoftBart model of Linero and Yang (2018) <doi:10.1111/rssb.12293>, which yields smoother fits. The interface follows that of glm(), so that a model is specified with a formula, a data frame, and a family.
License: GPL-2
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: arg (>= 0.2.1), cli (>= 3.6.4), rlang (>= 1.2.0), Matrix, Rcpp (>= 1.1.2), parallel, reformulas (>= 0.4.4), ggplot2 (>= 4.0.1), stats, utils
LinkingTo: Rcpp, RcppArmadillo
Suggests: bayesplot, cobalt, collapse, future, future.apply, insight, knitr, loo, MASS, marginaleffects, nlme, lme4, patrick (>= 0.3.0), performance, posterior, progressr, rmarkdown, rstanarm, rstantools, survival, testthat (>= 3.0.0), WeightIt
VignetteBuilder: knitr, rmarkdown
URL: https://github.com/ngreifer/bartisan, https://ngreifer.github.io/bartisan/
BugReports: https://github.com/ngreifer/bartisan/issues
LazyData: true
NeedsCompilation: yes
Packaged: 2026-10-18 18:33:17 UTC; NoahGreifer
Author: Noah Greifer [aut, cre, cph] , Antonio R. Linero [ctb, cph] , from which the MCMC engine is adapted)
Maintainer: Noah Greifer <noah.greifer@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-28 11:40:07 UTC

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New package awscrt with initial version 0.1.1
Package: awscrt
Title: Hardware-Accelerated 'CRC Checksums' from the AWS Common Runtime
Version: 0.1.1
Description: Computes 'CRC32', 'CRC32C' and 'CRC64NVME' 'checksums' using the 'aws-checksums' library from the 'AWS' Common Runtime, with runtime dispatch to hardware instructions ('SSE4.2', 'PCLMULQDQ', 'AVX-512', 'ARMv8' 'CRC' and 'PMULL') and a portable software fallback.
License: Apache License (>= 2)
URL: https://github.com/paws-r/aws-crt-r, https://paws-r.r-universe.dev/awscrt
BugReports: https://github.com/paws-r/aws-crt-r/issues
Encoding: UTF-8
Suggests: testthat (>= 3.0.0)
SystemRequirements: GNU make, C compiler
NeedsCompilation: yes
Packaged: 2026-10-18 17:30:32 UTC; Dyfan.Jones
Author: Dyfan Jones [aut, cre], Amazon.com, Inc. or its affiliates [cph]
Maintainer: Dyfan Jones <dyfan.r.jones@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-28 11:40:16 UTC

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New package AURMC with initial version 0.5.0
Package: AURMC
Title: Area Under the Repeated Measures Curve
Version: 0.5.0
Description: Estimates and compares areas under curves formed by repeatedly measured outcomes observed subject to censoring and a terminal event. Implements Kaplan-Meier adjustment for censoring, influence-function standard errors, Wald inference, and multiplier perturbation inference, with utilities for interpolation, simulation, tabulation, and plotting. For additional details, see: McCaw ZR, Armbruster S, Tian L, Claggett BL, Fitzmaurice G, Foà A, Pfeffer MA, Wei LJ (2026) <doi:10.1016/j.jchf.2026.103013>.
License: GPL-3
Encoding: UTF-8
Suggests: knitr, markdown, rmarkdown, testthat (>= 3.0.0), withr
LinkingTo: RcppArmadillo, Rcpp
Imports: cowplot, dplyr, ggplot2, methods, Rcpp, tibble
VignetteBuilder: knitr
URL: https://github.com/zrmacc/AURMC
BugReports: https://github.com/zrmacc/AURMC/issues
NeedsCompilation: yes
Packaged: 2026-10-16 17:07:16 UTC; zmccaw
Author: Zachary McCaw [aut, cre]
Maintainer: Zachary McCaw <zmccaw@alumni.harvard.edu>
Repository: CRAN
Date/Publication: 2026-10-28 11:40:28 UTC

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New package ASmiR with initial version 0.1.1
Package: ASmiR
Title: Prediction of Abiotic Stress-Specific miRNAs in Plants
Version: 0.1.1
Description: Provides functions for predicting plant microRNAs (miRNAs) associated with cold, drought, heat, and salt stress using the ASmiR machine learning framework. Implements PseKNC feature generation and stress-specific support vector machine models described by Pradhan et al. (2023), "ASmiR: a machine learning framework for prediction of abiotic stress-specific miRNAs in plants", Functional & Integrative Genomics, 23(2), article 92, <doi:10.1007/s10142-023-01014-2>.
License: GPL-3
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: Biostrings, e1071, stats
Suggests: testthat (>= 3.0.0)
SystemRequirements: Python (>= 3.7)
NeedsCompilation: no
Packaged: 2026-10-16 14:51:20 UTC; dell
Author: Upendra Kumar Pradhan [aut, cre] , Prabina Kumar Meher [aut]
Maintainer: Upendra Kumar Pradhan <upendra.iasri@icar.org.in>
Repository: CRAN
Date/Publication: 2026-10-28 11:20:32 UTC

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New package actuarialfitdist with initial version 0.2.3
Package: actuarialfitdist
Title: Actuarial Severity Fitting with Limits and Deductibles
Version: 0.2.3
Description: Fits actuarial claim severity distributions to ground-up loss data while accounting for deductible truncation, policy-limit censoring, observation weights, optional severity scaling variables, and fixed parameters. Supports single-family and spliced body-tail models, candidate-model comparison, limited expected values, loss elimination ratios, increased limits factors, deductible and limit rating factors, valuation or depreciation adjustments, simulation, diagnostics, and uncertainty estimation. The package is designed for property and casualty actuarial applications in which analysts fit ground-up severity and translate the fitted distribution into pricing factors for limits, deductibles, and valuation provisions. For background on statistical severity modeling, see Klugman, Panjer, and Willmot (2019, ISBN:9781119523789), "Loss Models: From Data to Decisions", 5th edition.
License: MIT + file LICENSE
URL: https://github.com/gs-actuary/actuarialfitdist
BugReports: https://github.com/gs-actuary/actuarialfitdist/issues
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: ggplot2, scales, stats, utils
Suggests: fitdistrplus, knitr, plotly, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-10-18 22:57:54 UTC; yagre
Author: Greg Sollenberger [aut, cre, cph]
Maintainer: Greg Sollenberger <yagreg7@yahoo.com>
Repository: CRAN
Date/Publication: 2026-10-28 11:50:16 UTC

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New package tppcm with initial version 0.1.0
Package: tppcm
Title: Step Discriminations for the Two-Parameter Partial Credit Model on Top of 'TAM'
Version: 0.1.0
Description: In the two-parameter partial credit model (TPPCM) of Yu (1991) <https://hdl.handle.net/2142/21459>, every step of a polytomous item has its own discrimination. Estimation is left to existing software: 'TAM' (tam.mml.3pl() with a step design matrix, tam.mml.2pl(), tam.mml()) and, for the bilinear product form and non-negativity constraints, 'sirt' (xxirt()). The package adds what these packages do not provide: standard errors of step discriminations based on the full observed information, step-level Wald tests, and score tests with modification indices and expected parameter changes for moving down the model ladder saturated TPPCM -> product form -> generalized partial credit model -> partial credit model, limited-information fit statistics (the M2 statistic, root mean square error of approximation, standardized root mean squared residual, comparative fit index and Tucker-Lewis index; Maydeu-Olivares and Joe (2006) <doi:10.1007/s11336-005-1295-9>) for any step desig [...truncated...]
License: GPL (>= 2)
URL: https://github.com/jiewenTsai/tppcm
BugReports: https://github.com/jiewenTsai/tppcm/issues
Encoding: UTF-8
Language: en-US
Depends: R (>= 4.1), TAM
Imports: CDM, graphics, MASS, sirt, stats
Suggests: knitr, mirt, numDeriv, partykit, psychotools, psychotree, rmarkdown, strucchange, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-10-16 13:44:45 UTC; jiewentsai
Author: Jie-Wen Tsai [aut, cre]
Maintainer: Jie-Wen Tsai <tsai.jiewen@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-28 11:00:02 UTC

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New package RidgeLRGLH with initial version 0.1.0
Package: RidgeLRGLH
Title: Ridge-Regularized Largest Root Tests for General Linear Hypotheses
Version: 0.1.0
Description: Tests general linear hypotheses in high-dimensional multivariate regression using a ridge-regularized largest root statistic. Estimates the population spectral distribution by linear programming and computes Tracy-Widom centering and scaling constants. Supports fixed, Bayesian, and minimax regularization choices. Implements the methods of Li (2025) <doi:10.48550/arXiv.2504.15510>.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: lpSolve, RMTstat, stats
NeedsCompilation: no
Packaged: 2026-10-18 02:07:20 UTC; haoranli
Author: Haoran Li [aut, cre]
Maintainer: Haoran Li <hzl0152@auburn.edu>
Repository: CRAN
Date/Publication: 2026-10-28 10:30:27 UTC

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New package rd2dnet with initial version 0.1.0
Package: rd2dnet
Title: Boundary Discontinuity Designs on Networks
Version: 0.1.0
Description: Estimation and inference for boundary discontinuity designs on street networks. Extends the location-based framework of 'rd2d' (Cattaneo, Titiunik and Yu, <doi:10.48550/arXiv.2505.07989>) from Euclidean coordinates to network-native coordinates (signed network distance to the boundary and offset along it) and user-defined network metrics (edge costs, travel time, road-class transition penalties, precomputed matrices). Provides side-specific local polynomial estimates of boundary average treatment effect curves with robust bias-corrected inference (Calonico, Cattaneo and Titiunik, 2014, <doi:10.3982/ECTA11757>), uniform confidence bands, weighted and largest aggregate effects, fuzzy designs, covariates, derivative targets, heteroskedasticity-robust, cluster and network Conley (1999, <doi:10.1016/S0304-4076(98)00084-0>) standard errors, a port of the 'rd2d' direct plug-in bandwidth selector, and a network-normalised version of the local polynomial density test of Cattan [...truncated...]
License: GPL-3
URL: https://github.com/zwinship/rd2dnet
BugReports: https://github.com/zwinship/rd2dnet/issues
Depends: R (>= 4.1.0)
Imports: graphics, grDevices, methods, Rcpp, stats, utils
LinkingTo: Rcpp
Suggests: dodgr, igraph, knitr, Matrix, osmdata, rmarkdown, sf, testthat (>= 3.0.0)
VignetteBuilder: knitr
Encoding: UTF-8
LazyData: true
NeedsCompilation: yes
Packaged: 2026-10-18 02:06:43 UTC; root
Author: Zach Winship [aut, cre, cph], Matias D. Cattaneo [ctb, cph] , Rocio Titiunik [ctb, cph] , Ruiqi Rae Yu [ctb, cph] , Michael Jansson [ctb, cph] , Xinwei Ma [ctb, cph]
Maintainer: Zach Winship <zachtwinship@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-28 10:30:08 UTC

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New package PrismR with initial version 1.0.0
Package: PrismR
Title: Pre-Modeling Statistical Audit Framework
Version: 1.0.0
Description: Introduces a statistical validation layer between data preprocessing and predictive modeling. Evaluates the statistical readiness of tabular datasets through data quality assessment, leakage detection, transformation analysis, and feature stability.
License: MIT + file LICENSE
URL: https://arshit-dv.github.io/PrismR/, https://github.com/Arshit-dv/PrismR
BugReports: https://github.com/Arshit-dv/PrismR/issues
Encoding: UTF-8
Imports: graphics, stats, utils, e1071, ggplot2, ggrepel
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-10-16 12:04:43 UTC; Arshit
Author: Arshit Choudhary [aut, cre, cph], Vanshika Sharma [aut, ctb], Amrit Pal [ths]
Maintainer: Arshit Choudhary <arshitchoudhary3010@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-28 10:50:17 UTC

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New package INLAcircular with initial version 1.0.0
Package: INLAcircular
Title: Bayesian Joint Circular Regression Using 'INLA'
Version: 1.0.0
Description: Provides a Bayesian regression framework for joint models with circular responses and covariates using integrated nested Laplace approximations, following Ye, Van Niekerk and Rue (2026) <doi:10.48550/arXiv.2602.08413>. The package supports link-adjusted von Mises likelihoods, shared latent predictors, structured latent effects, and optional LKJ-based multivariate covariance models. It also provides compiled circular densities and d/p/q/r penalized-complexity priors for von Mises, cardioid, and wrapped Cauchy concentration parameters as developed by Ye, Van Niekerk and Rue (2026) <doi:10.1177/1471082X261453677>.
License: GPL (>= 3)
URL: https://github.com/XiangYEstats/INLAcircular
BugReports: https://github.com/XiangYEstats/INLAcircular/issues
Depends: R (>= 4.1.0)
Encoding: UTF-8
LazyData: true
Imports: dplyr, stats, utils
Suggests: circular, graphpcor, INLA (>= 25.08.21), INLAtools, knitr, pkgload, rmarkdown
VignetteBuilder: knitr, rmarkdown
Additional_repositories: https://inla.r-inla-download.org/R/stable
NeedsCompilation: yes
Packaged: 2026-10-18 07:13:45 UTC; xiang
Author: Xiang Ye [aut, cre, cph], Janet Van Niekerk [aut], Haavard Rue [aut, cph], Gerard Jungman [ctb, cph] , Peter John Acklam [ctb]
Maintainer: Xiang Ye <xiang.ye@kaust.edu.sa>
Repository: CRAN
Date/Publication: 2026-10-28 10:40:08 UTC

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New package HMMscpg with initial version 1.0.0
Package: HMMscpg
Title: Hidden Markov Models and Shifted Compound Poisson-Gamma Renewal Process
Version: 1.0.0
Imports: Rdpack, methods, stats, utils, Bessel, Rcpp
LinkingTo: Rcpp, RcppArmadillo
Description: Provides functions to define, simulate and fit hidden Markov models, hidden semi-Markov models, and their time-varying versions, to incompletely observed point process records. Such data arise when some events of an underlying point process are not recorded or are otherwise missing. The models treat the number of missing events between each pair of consecutively observed events of a point process record as a hidden process. The number of missing events may be fixed or modelled as a random variable whose distribution can vary over time. When the number of missing events is fixed, the observed event times can be modelled as a compound gamma renewal process. When it is random, the observed process is represented by a shifted compound Poisson-gamma renewal process, which may also depend on time, leading to a time-dependent shifted compound Poisson-gamma renewal process. These modelling frameworks are described in detail in Shahzadi, Wang, Parry and Bebbington (2023) <doi:10.1007/s10463- [...truncated...]
License: GPL-3
Encoding: UTF-8
Suggests: knitr, rmarkdown, Rmpfr
NeedsCompilation: yes
Packaged: 2026-10-18 05:48:58 UTC; amina
Author: Amina Shahzadi [aut, cre], Ting Wang [aut]
Maintainer: Amina Shahzadi <aminashahzadi@gcu.edu.pk>
Repository: CRAN
Date/Publication: 2026-10-28 10:40:15 UTC

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New package BayesAiken with initial version 2.0.0
Package: BayesAiken
Title: Bayesian Content Validity Coefficients with Credibility Intervals
Version: 2.0.0
Date: 2026-09-24
Description: Bayesian inference for the six rating coefficients proposed by Aiken (1985) <doi:10.1177/0013164485451012> and Aiken (1989) <doi:10.1177/0013164489492003>: V (content validity), H (homogeneity), C (congruence), R (repeatability), A (rater agreement) and I (item coherence). All six are expressed as functionals of the population distribution of rating categories, so a single Dirichlet-Multinomial model yields their full posterior by push-forward. This treats each judge as one categorical observation and avoids the pseudo-replication of Beta-Binomial formulations. R is modelled on the c-by-c joint table because it is not a functional of the marginal distribution. Provides classical estimates with the correct parity correction, highest density and equal-tailed credibility intervals, posterior threshold probabilities, prior sensitivity analysis and a friendly step-by-step verbose report.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.0.0)
Imports: stats, graphics, grDevices, utils
Suggests: testthat (>= 3.0.0), shiny, readxl, writexl, openxlsx
URL: https://github.com/jventural/BayesAiken
BugReports: https://github.com/jventural/BayesAiken/issues
NeedsCompilation: no
Packaged: 2026-10-16 13:21:58 UTC; PC
Author: Jose Ventura-Leon [aut, cre]
Maintainer: Jose Ventura-Leon <jventuraleon@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-28 11:00:18 UTC

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New package aidR with initial version 0.2.4
Package: aidR
Title: Reading and Standardizing Automated Insulin Delivery Data
Version: 0.2.4
Description: Parses the native exports of several automated insulin delivery (AID) platforms into a common, platform-independent format for continuous glucose monitoring (CGM), basal, bolus, carbohydrate, and self-monitored blood glucose (SMBG) data. Additional functions check completeness, filter, produce visualizations, and convert the data to other formats.
License: GPL-3
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: readxl, tools, dplyr, lubridate, rjson, tidyr, stringr, utils, rlang, stats, graphics, iglu, hms
Suggests: knitr, rmarkdown, cgmquantify, ggplot2, testthat (>= 3.0.0), withr
VignetteBuilder: knitr
URL: https://github.com/madleina/aidR
BugReports: https://github.com/madleina/aidR/issues
NeedsCompilation: no
Packaged: 2026-10-16 12:43:03 UTC; madleina
Author: Madleina Caduff [aut, cre] , Aritz Lizoain [aut] , Diabetes Center Berne [cph, fnd]
Maintainer: Madleina Caduff <madleina.caduff@dcberne.com>
Repository: CRAN
Date/Publication: 2026-10-28 11:00:09 UTC

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Tue, 27 Oct 2026

New package truedist with initial version 0.1.0
Package: truedist
Title: Estimating the Distribution of True Effects from Noisy Estimates
Version: 0.1.0
Description: Estimates the distribution of true effects (or any latent parameter) from estimates that each have a known, possibly different, standard error. The main function, em_smooth(), implements the smoothed EM (EMS) algorithm of Silverman, Jones, Wilson and Nychka (1990) <doi:10.1111/j.2517-6161.1990.tb01788.x> for a nonparametric mixing distribution on a grid. The smoothing uses one constant standard deviation, set from the typical standard error and the sample size.
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-US
Depends: R (>= 3.5.0)
Imports: graphics, stats
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-10-17 12:54:42 UTC; ph3828
Author: Paul von Hippel [aut, cre]
Maintainer: Paul von Hippel <ph3828@eid.utexas.edu>
Repository: CRAN
Date/Publication: 2026-10-27 18:30:02 UTC

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New package transformerpalettes with initial version 0.4.0
Package: transformerpalettes
Title: Color Palettes Inspired by Transformers Toys, Cartoons and Comics
Version: 0.4.0
Description: Color palettes drawn from the Transformers franchise, centered on the 1984-1989 Generation 1 toys and extending to their Generation 2 re-releases, the cartoon animation models and the Marvel comics. Covers the leaders, every member and combined form of the combiner teams (Aerialbots, Protectobots, Technobots, Constructicons, Stunticons, Combaticons, Terrorcons, Predacons, Seacons, Pretender Monsters and Breastforce), the Dinobots, the Seeker jets, Soundwave and the cassettes, the Insecticons, the 1984 Autobot cars and Mini Vehicles and the 1986 movie cast, with separate palettes for the toy, the cartoon animation model, the Marvel comic coloring and the Generation 2 re-release where each exists. Includes 'ggplot2' color and fill scales for discrete and continuous data, team palettes that take one color from each member of a combiner team, metadata linking each palette to its character, faction, team and reference page, and helpers to shortlist palettes that suit categorical, color-blin [...truncated...]
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-US
Depends: R (>= 3.5)
Imports: ggplot2, grDevices, graphics, stats, utils
Suggests: testthat (>= 3.0.0)
URL: https://bmaitner.github.io/transformerpalettes/, https://github.com/bmaitner/transformerpalettes
BugReports: https://github.com/bmaitner/transformerpalettes/issues
NeedsCompilation: no
Packaged: 2026-10-17 15:28:48 UTC; bmaitner
Author: Brian Maitner [aut, cre]
Maintainer: Brian Maitner <bmaitner@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-27 18:30:07 UTC

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New package ReguGLH with initial version 0.1.0
Package: ReguGLH
Title: General Linear Hypothesis Tests via Spectral Shrinkage
Version: 0.1.0
Contact: Haoran Li <haoranli1990@gmail.com> (secondary email)
Description: Implements high-dimensional general linear hypothesis tests using ridge, reciprocal cubic polynomial, and user-defined analytic spectral regularizers. Provides prior-based shrinkage selection and Gaussian maximum calibration for composite tests. Implements the methods of Li, Aue and Paul (2020), "High-dimensional general linear hypothesis tests via non-linear spectral shrinkage", Bernoulli, 26(4), 2541-2571 <doi:10.3150/19-BEJ1186>.
License: GPL-3
Encoding: UTF-8
Imports: stats
NeedsCompilation: no
Packaged: 2026-10-17 22:07:23 UTC; haoranli
Author: Haoran Li [aut, cre]
Maintainer: Haoran Li <hzl0152@auburn.edu>
Repository: CRAN
Date/Publication: 2026-10-27 18:40:08 UTC

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New package radiatR with initial version 0.1.3
Package: radiatR
Title: Analyse and Visualise Headings and Trajectories on the Unit Disk
Version: 0.1.3
Description: A complete pipeline for analysing directional data -- headings and trajectories on the unit disk. Supply a table of angles directly, or reconstruct headings from movement trajectories imported from tracking tools ('EthoVision', 'DeepLabCut', 'SLEAP', 'TRex', 'ANY-maze', 'TrackMate', 'idtracker.ai', and others) via a unified dialect-based loader system, including multi-bodypart pose estimation with likelihood-weighted centroid. Derives per-trial heading directions using multiple rules (ring-crossing, distal point, pose body-axis, velocity-based, and more). Computes circular statistics including mean direction, resultant length, von Mises and wrapped Cauchy parametric fits, circular correlation (circular-linear and circular-circular), circular-linear regression (Fisher and Lee (1992) <doi:10.2307/2532334>), model selection among orientation models (Fitak and Johnsen (2017) <doi:10.1242/jeb.167056>), and uniformity and multi-sample hypothesis tests (Rayleigh, Watson-Williams, [...truncated...]
URL: https://johnkirwan.github.io/radiatR/, https://github.com/JohnKirwan/radiatR
BugReports: https://github.com/JohnKirwan/radiatR/issues
License: GPL (>= 3)
Copyright: file inst/COPYRIGHTS
Encoding: UTF-8
Language: en-GB
LazyData: true
LazyDataCompression: xz
Depends: R (>= 4.1.0)
Imports: rlang, ggplot2, tibble, vctrs, circular, methods, utils, stats
Suggests: bpDir, dplyr (>= 1.0.0), testthat (>= 3.2.0), knitr, rmarkdown, ggrepel, arrow, data.table (>= 1.14.0), jsonlite, readr, readxl, yaml, withr, writexl, shiny (>= 1.7.0), bslib (>= 0.5.0), pkgload, png, jpeg, svglite, shinytest2, chromote, CircMLE, vdiffr, sphunif
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-10-17 11:54:15 UTC; jdk
Author: John D. Kirwan [aut, cre, cph], A. & M.W. Mathis Labs [cph] , Talmo Pereira [cph] , The Trustees of Princeton University [cph]
Maintainer: John D. Kirwan <john@jkirwan.org>
Repository: CRAN
Date/Publication: 2026-10-27 18:20:02 UTC

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New package nesstarR with initial version 0.1.0
Package: nesstarR
Title: Read and Export 'Nesstar' Binary Files
Version: 0.1.0
Description: Reads '.Nesstar' binary files into data frames. '.Nesstar' is the file format of 'Nesstar Publisher', survey documentation software from the International Household Survey Network <https://www.ihsn.org/node/557>. Statistical agencies, for example the Ministry of Statistics and Programme Implementation ('MoSPI', India), publish survey microdata in this format.
License: MIT + file LICENSE
URL: https://nesstarr.saketlab.org, https://github.com/saketkc/nesstarR
BugReports: https://github.com/saketkc/nesstarR/issues
Encoding: UTF-8
Language: en-US
Depends: R (>= 4.1.0)
Imports: tools, utils
Suggests: haven, knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2026-10-17 16:26:34 UTC; mcclintock
Author: Saket Choudhary [aut, cre, cph]
Maintainer: Saket Choudhary <saketc@iitb.ac.in>
Repository: CRAN
Date/Publication: 2026-10-27 18:40:02 UTC

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New package glyospalettes with initial version 0.3.0
Package: glyospalettes
Title: Color Palettes Inspired by Glyos Colorways
Version: 0.3.0
Description: Color palettes based on the named colorways of the Glyos toy system: Onell Design's Glyos System Series and the Glyos-compatible lines from partner companies such as TheGodBeast, Spy Monkey Creations, Toyfinity and the Four Horsemen. Includes 'ggplot2' color and fill scales for discrete and continuous data, metadata linking each palette to its company and product line, helpers to shortlist palettes that suit categorical, color-blind-safe, sequential or diverging use, and tools to combine palettes (one color per colorway) or pick the most distinguishable colors from a pool for a light, dark or grayscale plot. Hex values are approximations curated from product photography. This is a fan project and is not affiliated with or endorsed by any of the companies.
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-US
Depends: R (>= 3.5)
Imports: ggplot2, grDevices, graphics, stats, utils
Suggests: testthat (>= 3.0.0)
URL: https://bmaitner.github.io/glyospalettes/, https://github.com/bmaitner/glyospalettes
BugReports: https://github.com/bmaitner/glyospalettes/issues
NeedsCompilation: no
Packaged: 2026-10-17 15:32:26 UTC; bmaitner
Author: Brian Maitner [aut, cre]
Maintainer: Brian Maitner <bmaitner@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-27 18:30:14 UTC

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New package zuxml with initial version 0.1.0
Package: zuxml
Title: Small XML Parser and Document Tree
Version: 0.1.0
Description: Reads, navigates, and writes XML documents using a bundled copy of the 'Expat' parser (<https://libexpat.github.io/>), so that no system XML library is required. Documents are parsed into a faithful immutable tree exposed through a small vectorized navigation interface. Parsing is strict by default: document type declarations are rejected, external entity resolution is not compiled in, and configurable limits bound nesting depth and memory use. A registered C interface allows other packages to parse XML without linking against the parser themselves, and to feed it incrementally so that a large document need not be held in memory all at once.
License: MIT + file LICENSE
Copyright: See inst/COPYRIGHTS.
URL: https://github.com/pedrobtz/zuxml, https://pedrobtz.github.io/zuxml/
BugReports: https://github.com/pedrobtz/zuxml/issues
Depends: R (>= 4.1)
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2026-10-17 08:36:28 UTC; pbtz
Author: Pedro Baltazar [aut, cre, cph], Clark Cooper [ctb] , Fred L. Drake, Jr. [ctb] , Greg Stein [ctb] , James Clark [ctb] , Karl Waclawek [ctb] , Rhodri James [ctb] , Sebastian Pipping [ctb] , Steven Solie [ctb] , William Ahern [ctb] ), Jean-Philippe Auma [...truncated...]
Maintainer: Pedro Baltazar <pedrobtz@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-27 18:00:02 UTC

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New package TTM with initial version 0.1.0
Package: TTM
Title: Terminal Trend Models on the Retrospective Time Scale
Version: 0.1.0
Description: Fits retrospective-time longitudinal models for terminal trend analysis using weighted generalized estimating equations and related joint modeling tools. The package provides functions to estimate spline-based baseline and treatment effect trajectories on the retrospective time scale, obtain pointwise confidence intervals, and visualize fitted trajectories.
License: GPL-2
URL: https://github.com/TChang-W/TTM
BugReports: https://github.com/TChang-W/TTM/issues
Depends: R (>= 4.4.0)
Imports: dplyr, geepack, geer, ggplot2 (>= 3.4.0), lme4, magrittr, splines, stats, survival, utils
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
LazyData: true
Encoding: UTF-8
Language: en-US
NeedsCompilation: no
Packaged: 2026-10-16 20:46:40 UTC; wtc_a
Author: Tingchang Wang [aut], Zhigang Li [aut, cre]
Maintainer: Zhigang Li <zhigang.li@ufl.edu>
Repository: CRAN
Date/Publication: 2026-10-27 17:10:09 UTC

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New package pyrt with initial version 0.1.0
Package: pyrt
Title: Runtime Support for Converted 'Python' Packages
Version: 0.1.0
Description: Provides the 'Python' runtime semantics required by 'R' packages generated with 'pyport', including reference-semantics containers, class and method-resolution-order dispatch, exception hierarchies, iteration and slicing helpers, arbitrary-precision integer arithmetic, and bit-exact random number generation.
License: MIT + file LICENSE
URL: https://github.com/lauyeehow1986-hub/r_python_converter
BugReports: https://github.com/lauyeehow1986-hub/r_python_converter/issues
Encoding: UTF-8
Depends: R (>= 4.3.0)
Imports: gmp (>= 0.7-1), R6 (>= 2.5.1), stats, utils
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2026-10-17 11:11:04 UTC; lauye
Author: Yee How Lau [aut, cre, cph]
Maintainer: Yee How Lau <lauyeehow1986@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-27 18:00:08 UTC

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New package mospiR with initial version 0.1.0
Package: mospiR
Title: Client for the 'MoSPI' Microdata Portal
Version: 0.1.0
Description: Download unit-level survey microdata from the Ministry of Statistics and Programme Implementation ('MoSPI', Government of India) Microdata Portal <https://microdata.gov.in>. Provides functions to list datasets, list files within a dataset, and download individual files or entire datasets through the portal's 'NADA' API.
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-US
Depends: R (>= 4.1.0)
Imports: httr2 (>= 1.0.0)
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
URL: https://mospir.saketlab.org, https://github.com/saketkc/mospiR
BugReports: https://github.com/saketkc/mospiR/issues
NeedsCompilation: no
Packaged: 2026-10-16 21:20:25 UTC; mcclintock
Author: Saket Choudhary [aut, cre]
Maintainer: Saket Choudhary <saketc@iitb.ac.in>
Repository: CRAN
Date/Publication: 2026-10-27 17:10:02 UTC

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New package cudacellr with initial version 0.4.0
Package: cudacellr
Title: GPU-Aware Single-Cell Analysis Workflows
Version: 0.4.0
Description: Provides single-cell analysis primitives for sparse count matrices, including library-size normalization, log-normalization, highly variable feature selection, principal component analysis, and nearest-neighbour construction. Integrates the 'cudaverse' numerical and sparse layers while preserving matrix identifiers and recording the computation backend for each stage. Optional adapters preserve native 'SingleCellExperiment' and 'SeuratObject' version 5 object structures.
License: MIT + file LICENSE
URL: https://cudaverse.github.io/cudacellr/, https://github.com/cudaverse/cudacellr
BugReports: https://github.com/cudaverse/cudacellr/issues
Encoding: UTF-8
Imports: cudaverse (>= 0.4.1), Matrix, methods
Suggests: DelayedArray, knitr, rmarkdown, S4Vectors, SeuratObject (>= 5.0.0), SingleCellExperiment, SummarizedExperiment, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-10-07 18:09:04 UTC; Li
Author: Yaoxiang Li [aut, cre]
Maintainer: Yaoxiang Li <liyaoxiang@outlook.com>
Repository: CRAN
Date/Publication: 2026-10-27 18:00:14 UTC

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New package rpspanel with initial version 0.1.0
Package: rpspanel
Title: US State Energy-Economy Panels with Renewable Portfolio Standards
Version: 0.1.0
Description: Builds a documented, reproducible state-by-year panel for the 50 US states and the District of Columbia that combines energy consumption, prices and production from the US Energy Information Administration (EIA) State Energy Data System, electricity generation and retail sales, state energy-related carbon dioxide emissions, and state GDP, income and population from the Bureau of Economic Analysis (BEA). Data are downloaded on demand through the official APIs and cached locally, with the source, vintage and transformation of every variable recorded in a codebook. Renewable Portfolio Standard (RPS) rules are turned into standardised annual stringency indices (adoption, nominal, coverage-adjusted and incremental requirements, following Yin and Powers (2010) <doi:10.1016/j.enpol.2009.10.067>, plus design-flexibility indicators). Output works directly with the 'plm', 'fixest' and 'csdm' packages.
License: MIT + file LICENSE
URL: https://github.com/adebayomoses/rpspanel
BugReports: https://github.com/adebayomoses/rpspanel/issues
Depends: R (>= 4.1.0)
Imports: cli, httr2 (>= 1.0.0), stats, tools, utils
Suggests: arrow, fixest, haven, knitr, plm, rmarkdown, testthat (>= 3.1.7), withr
VignetteBuilder: knitr
Encoding: UTF-8
Language: en-US
NeedsCompilation: no
Packaged: 2026-10-15 13:55:44 UTC; Mosdam
Author: Moses Adebayo [aut, cre, cph]
Maintainer: Moses Adebayo <adebayomoses2021@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-27 16:40:02 UTC

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New package ptLasso with initial version 1.0.2
Package: ptLasso
Title: Pretraining the Lasso
Description: Implements lasso pretraining for generalized linear models for data with grouped observations; data without grouped observations, but with multinomial responses; data with multiple Gaussian responses; and data with repeated measurements over time. The method fits a lasso model to an initial dataset and then uses its support and coefficient values to guide model fitting for a related task, which can improve performance by leveraging larger datasets and preserve interpretability by identifying features which are generally shared, and which are task specific. See Craig et al. (2026) <doi:10.1093/jrsssb/qkaf050> for details. Model fitting in this package is done with cv.glmnet() from the 'glmnet' package, and syntax closely follows that of 'glmnet' (Friedman, Hastie and Tibshirani (2010) <doi:10.18637/jss.v033.i01>).
Version: 1.0.2
Maintainer: Erin Craig <ercr@umich.edu>
License: GPL-2
Encoding: UTF-8
URL: https://erincr.github.io/ptLasso/, https://doi.org/10.1093/jrsssb/qkaf050
BugReports: https://github.com/erincr/ptLasso/issues
NeedsCompilation: yes
Depends: ggplot2, glmnet, gridExtra, Matrix
Suggests: knitr, rmarkdown, rpart, survival, xgboost, sparsepca, MASS, testthat
VignetteBuilder: knitr
Language: en
Packaged: 2026-10-16 20:48:46 UTC; ercr
Author: Erin Craig [aut, cre, cph] , Rob Tibshirani [aut, cph]
Repository: CRAN
Date/Publication: 2026-10-27 17:00:02 UTC

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New package mirrorslope with initial version 0.2.1
Package: mirrorslope
Title: Mirror Slope Plots for Two-Arm Clinical Trial Data
Version: 0.2.1
Description: Creates mirrored slope plots comparing two treatment arms over a single observation interval. Both arms share a common x-axis and converge at a central endpoint, making the between-arm gap the primary visual quantity. Returns standard 'ggplot2' objects for full extensibility. The display was designed by Kati Maharry and is described in Maharry and Sullivan (2026, manuscript in preparation); it was first used in the supplementary appendix of McDonald and colleagues (2026) <doi:10.1016/S0140-6736(26)01385-1>.
License: MIT + file LICENSE
URL: https://github.com/Sullivanstatistics/mirrorslope
BugReports: https://github.com/Sullivanstatistics/mirrorslope/issues
Encoding: UTF-8
Language: en-GB
Depends: R (>= 4.0.0)
Imports: ggplot2 (>= 3.4.0), rlang (>= 1.0.0), grDevices, stats, utils
Suggests: testthat (>= 3.0.0), knitr, rmarkdown, patchwork
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-10-16 19:47:47 UTC; asullivan
Author: Adam Sullivan [aut, cre], Capricor Therapeutics [fnd]
Maintainer: Adam Sullivan <asullivan@capricor.com>
Repository: CRAN
Date/Publication: 2026-10-27 16:50:02 UTC

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New package zigimports with initial version 0.1.0
Package: zigimports
Title: Call 'Zig' Code from R
Version: 0.1.0
Description: Loads shared libraries compiled from 'Zig' ('.so' files on Linux, '.dll' files on Windows) and binds their exported functions to R functions. Arguments are passed by value using the native calling convention, so functions with mixed integer, double, logical, string and vector arguments and with return values can be called. Also compiles and runs 'Zig' code directly from R. Compiling code requires the 'Zig' compiler.
URL: https://github.com/lokop5116/zigimports
BugReports: https://github.com/lokop5116/zigimports/issues
License: GPL-3
Encoding: UTF-8
Depends: R (>= 3.5.0)
SystemRequirements: 'Zig' compiler (>= 0.11), only needed for zig_call() and to build libraries
Suggests: testthat (>= 3.0.0)
NeedsCompilation: yes
Packaged: 2026-10-16 09:44:38 UTC; loko
Author: Lakshya Sharma [aut, cre], Amrit Pal [aut]
Maintainer: Lakshya Sharma <lakshya6115@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-27 15:20:02 UTC

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New package rapidxlsx with initial version 0.1.0
Package: rapidxlsx
Title: Fast Parallel Excel Spreadsheet Writer
Version: 0.1.0
Author: Amin Fathullah [aut, cre]
Maintainer: Amin Fathullah <amin_fathullah@yahoo.com>
Description: Serializes tabular data frames to Microsoft Excel 'OpenXML' ('xlsx') workbooks using a multi-threaded Rust core with parallel Deflate compression and zero-copy columnar memory mapping.
License: MIT + file LICENSE
Encoding: UTF-8
SystemRequirements: Cargo (Rust toolchain)
URL: https://github.com/aminfathullah/rapidxlsx
BugReports: https://github.com/aminfathullah/rapidxlsx/issues
NeedsCompilation: yes
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
Packaged: 2026-10-16 09:29:39 UTC; maja
Repository: CRAN
Date/Publication: 2026-10-27 15:10:02 UTC

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New package gcloglog with initial version 1.0
Package: gcloglog
Title: Methods for Fitting Binomial Models with the Generalized Complementary Log-Log Function
Version: 1.0
Date: 2026-10-16
Maintainer: Bert van der Veen <bert_van_der_veen@hotmail.com>
Description: Functionality for fitting a flexible link function in binomial regression based on a latent negative-binomial count. The original link function was proposed by Aranda-Ordaz (1981)<doi:10.1093/biomet/68.2.357>, and motivation via a negative-binomial latent count by van der Veen and Hui (in prep).
License: GPL (>= 2)
Imports: graphics, lme4, Matrix, methods, nloptr, numDeriv, stats, utils
Encoding: UTF-8
URL: https://github.com/BertvanderVeen/gcloglog
BugReports: https://github.com/BertvanderVeen/gcloglog/issues
NeedsCompilation: no
Packaged: 2026-10-16 11:36:32 UTC; bertv
Author: Bert van der Veen [aut, cre], Francis K.C. Hui [aut]
Repository: CRAN
Date/Publication: 2026-10-27 15:50:02 UTC

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New package enhancedTtest with initial version 0.1.0
Package: enhancedTtest
Title: Enhanced T-Test with Automatic Selection and APA Formatting
Version: 0.1.0
Description: Provides enhanced t-test functionality with automatic assumption checking, non-parametric fallbacks, effect size calculation, and APA-formatted tables that can be exported to Word documents. Supports one-sample, two-sample, and paired t-tests with intelligent test selection. Effect size interpretations follow Cohen (1988) <doi:10.4324/9780203771587> and APA formatting follows the Publication Manual of the American Psychological Association, 7th edition (2020) <doi:10.1037/0000165-000>.
License: GPL-3
Encoding: UTF-8
Depends: R (>= 3.5.0)
Imports: car (>= 3.0-0), dplyr (>= 1.0.0), flextable (>= 0.7.0), htmltools (>= 0.5.0), nortest (>= 1.0-4), officer (>= 0.4.0), rlang (>= 1.0.0), stats, utils
Suggests: ggplot2, knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-10-15 12:47:34 UTC; DELL
Author: Martin Nyamu [aut, cre]
Maintainer: Martin Nyamu <analystnyamu79@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-27 15:20:07 UTC

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New package DynMSR with initial version 0.1.1
Package: DynMSR
Title: Connect Systems Biology and Pharmacology Formats to Simulation Backends
Version: 0.1.1
Author: Evgeny Metelkin [aut, cre]
Maintainer: Evgeny Metelkin <evgeny.metelkin@gmail.com>
Description: Provides a convenient R interface for systems-biology and systems-pharmacology models in Heta, SBML (Systems Biology Markup Language), and DynMS (Dynamic Model Specification) formats. DynMS JSON files are loaded directly; Heta projects and SBML files are converted to DynMS by an optional compatible installation of 'heta-compiler'. Models can be validated, selected from a platform, and generated or built for simulation with 'mrgsolve' as a backend.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1)
Imports: jsonlite, jsonvalidate, whisker
Suggests: mrgsolve, testthat (>= 3.0.0), withr
URL: https://github.com/hetalang/DynMSR
BugReports: https://github.com/hetalang/DynMSR/issues
NeedsCompilation: no
Packaged: 2026-10-16 10:28:56 UTC; evgen
Repository: CRAN
Date/Publication: 2026-10-27 15:40:02 UTC

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New package windscape with initial version 2.0.0
Package: windscape
Title: Model Landscape Connectivity by Wind
Version: 2.0.0
Description: Model landscape connectivity by wind for ecological and evolutionary analyses. Summarize long time series of gridded wind data, downloaded from reanalyses or supplied by the user, into wind roses describing directional conductance between neighboring grid cells. Model dispersal through them with least-cost path and random walk algorithms, to map windsheds around sites and estimate pairwise connectivity among them, test hypotheses relating wind to ecological data, and visualize wind and connectivity with 'ggplot2'. The approach builds on Kling and Ackerly (2020) <doi:10.1038/s41558-020-0848-3> and Kling and Ackerly (2021) <doi:10.1073/pnas.2017317118>.
Encoding: UTF-8
LazyData: true
LazyDataCompression: xz
LinkingTo: Rcpp
Imports: gdistance, Rcpp, raster, geosphere, ggplot2, igraph, magrittr, Matrix, methods, stats, tools, utils
URL: https://matthewkling.github.io/windscape/, https://github.com/matthewkling/windscape
BugReports: https://github.com/matthewkling/windscape/issues
Suggests: knitr, maps, ncdf4, rmarkdown, scales, sf, testthat (>= 3.0.0), vegan, tidyverse, withr
VignetteBuilder: knitr
Depends: R (>= 4.0.0), terra (>= 1.8-42)
License: MIT + file LICENSE
NeedsCompilation: yes
Packaged: 2026-10-15 16:54:06 UTC; matthewkling
Author: Matthew Kling [aut, cre, cph]
Maintainer: Matthew Kling <mattkling@berkeley.edu>
Repository: CRAN
Date/Publication: 2026-10-27 15:00:02 UTC

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New package sppt with initial version 1.0.0
Package: sppt
Title: Spatial Point Pattern Test for Areal Data
Version: 1.0.0
Description: Implements the area-based nonparametric spatial point pattern test of Andresen (2009) <doi:10.1016/j.apgeog.2008.12.004> for comparing two spatial distributions of events aggregated to areal units, with the applications and extensions reviewed in Andresen (2016) <doi:10.1177/2059799116630659>. Unit-level inference uses bounded Monte Carlo bootstrap p-values, with marginal confidence interval overlap retained as an option. Global similarity is summarised by the robust S index, accompanied by a test of whether two patterns are more different than two realisations of a single process, and a test of the spatial arrangement of the differences. A longitudinal extension compares each period of a time series against a base period and classifies unit-level trajectories. Publication-ready maps can be redrawn with user-chosen layouts.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
LazyDataCompression: xz
Depends: R (>= 4.1.0)
Imports: classInt, ggplot2 (>= 3.5.0), ggspatial, graphics, grDevices, Matrix, rlang, scales, sf, spdep, stats, tools, utils
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-10-16 07:21:59 UTC; andre
Author: Martin A. Andresen [aut, cre, cph]
Maintainer: Martin A. Andresen <andresen@sfu.ca>
Repository: CRAN
Date/Publication: 2026-10-27 15:00:11 UTC

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New package FrailtyPackPlus with initial version 0.1.0
Package: FrailtyPackPlus
Title: Shared, Correlated, Additive, and Zero-Inflated Frailty Models
Version: 0.1.0
Description: Fits and compares shared, correlated, additive, zero-inflated promotion cure-rate, and k-out-of-M one-shot device frailty survival models under Bayesian Markov chain Monte Carlo (MCMC) and Maximum Likelihood Estimation (MLE) frameworks. Supports ten baseline hazard distributions (Weibull, Exponential, Generalized Exponential, Exponential Power, Linear Failure Rate, Generalized Log-Logistic, Generalized Weibull, Generalized Rayleigh, Weighted Exponential, Extended Weibull) and eight frailty distributions (Gamma, Inverse Gaussian, Positive Stable, Compound Poisson, Compound Negative Binomial, Generalized Lindley, Weighted Lindley, Mixture of Inverse Gaussians). Implements reversed hazard rate (RHR) models for bivariate left-censored survival data, additive shared frailty models under random right censoring, and one-shot device reliability analysis. Provides goodness-of-fit testing, information criteria (AIC, BIC, AICc, HQIC, DIC, EAIC, EBIC, LPML), convergence diagnostics (Geweke, Gelman [...truncated...]
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
ByteCompile: true
Depends: R (>= 4.0.0)
Imports: graphics, grDevices, MASS, methods, numDeriv, stats, survival, utils
Suggests: testthat (>= 3.0.0)
Language: en-US
NeedsCompilation: no
Packaged: 2026-10-15 22:59:12 UTC; shikhar tyagi
Author: Shikhar Tyagi [aut, cre]
Maintainer: Shikhar Tyagi <shikhar1093tyagi@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-27 14:30:02 UTC

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New package fastphylosig with initial version 0.3.1
Package: fastphylosig
Title: Fast Phylogenetic Signal Statistics
Version: 0.3.1
Description: Provides one-command and method-specific workflows for phylogenetic signal in continuous, binary, and categorical traits. Compiled tree-pruning algorithms implement Blomberg's K and Pagel's lambda without constructing a dense phylogenetic covariance matrix in production. Fritz and Purvis D retains separate random and Brownian null models, while categorical Delta combines discrete ancestral-state likelihoods with MCMC and permutation diagnostics. The package also provides reusable prepared trees, explicit tree/data matching, trait-wise missing-value handling, conservative tree diagnostics, bounded simulation memory, and structured timing and Monte Carlo uncertainty metadata. Methods follow Blomberg, Garland and Ives (2003) <doi:10.1111/j.0014-3820.2003.tb00285.x> for K, Pagel (1999) <doi:10.1038/44766> for lambda, Fritz and Purvis (2010) <doi:10.1111/j.1523-1739.2010.01455.x> for D, and Borges et al. (2019) <doi:10.1093/bioinformatics/bty800> for categorical Delt [...truncated...]
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: ape, parallel, Rcpp, stats
LinkingTo: Rcpp, RcppArmadillo
Suggests: caper, mvtnorm, phytools, testthat
URL: https://github.com/yinwen-ecology/fastphylosig, https://yinwen-ecology.github.io/fastphylosig/
BugReports: https://github.com/yinwen-ecology/fastphylosig/issues
SystemRequirements: C++17, OpenMP (optional)
NeedsCompilation: yes
Packaged: 2026-10-16 00:33:42 UTC; wenyi
Author: Yin Wen [aut, cre]
Maintainer: Yin Wen <wenyinsci@126.com>
Repository: CRAN
Date/Publication: 2026-10-27 14:40:02 UTC

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Sat, 24 Oct 2026

New package whence with initial version 0.1.0
Package: whence
Title: Explain Where a Number Came from in 'shiny' Apps
Version: 0.1.0
Description: Lets the viewer of a 'shiny' dashboard click a number, a row of a summary table or a bar of a 'ggplot2' plot, and see where it came from. The pipeline that makes the result is split into its steps. Each step is run in turn, and the number of rows after each step is recorded. The result is an attrition waterfall that shows how many rows each step removed, and what share of the rows that was, together with code that reproduces the result. The steps are found from the expression alone, so the pipeline does not need to be rewritten. The rows that contribute to a result, and the rows that a step removed, are found only when the viewer asks for them.
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-GB
Depends: R (>= 4.1.0)
Imports: htmltools, rlang, shiny (>= 1.7.0), utils
Suggests: dplyr, ggplot2, reactable, shinytest2, testthat (>= 3.0.0), tidyr, withr
URL: https://github.com/tenmeh/whence, https://tenmeh.github.io/whence/
BugReports: https://github.com/tenmeh/whence/issues
NeedsCompilation: no
Packaged: 2026-10-15 17:49:38 UTC; tchan
Author: Tanmay Chanda [aut, cre, cph]
Maintainer: Tanmay Chanda <tanmaychanda96@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-24 16:20:02 UTC

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New package SurveySolutionsAPIv2 with initial version 0.1.2
Package: SurveySolutionsAPIv2
Title: Comprehensive API Access to Your 'Survey Solutions' Server Using 'httr2'
Version: 0.1.2
Description: A comprehensive suite of functions for interfacing with the 'Survey Solutions' APIs (<https://demo.mysurvey.solutions/apidocs/index.html> and <https://docs.mysurvey.solutions/>). It supports all the current POST, GET, and PATCH requests of the 'REST' API and extends its capabilities by integrating selected 'GraphQL' API queries and mutations when 'REST' API equivalents are not available. Designed for ease of use, it includes several convenience functions to streamline operations. The package ensures that data retrieved from the API is automatically transformed into a single, easy-to-use data frame or data table, optimizing it for subsequent analysis and processing. Additionally, it is specifically designed to facilitate seamless integration into 'shiny' applications, enhancing the interactive web application development experience. Built on the robust 'httr2' package, this version supersedes the previous 'httr'-based implementation. Recognizing the needs of large-scale data [...truncated...]
License: MIT + file LICENSE
URL: https://michael-cw.github.io/SurveySolutionsAPIv2/, https://github.com/michael-cw/SurveySolutionsAPIv2
BugReports: https://github.com/michael-cw/SurveySolutionsAPIv2/issues
Depends: R (>= 4.1.0)
Imports: cli, curl, data.table, dplyr, foreach, graphics, httr2, jsonlite, lubridate, readr, rlang, shiny, stats, stringr, susographql (>= 0.1.1), tidyjson, tidyr, withr, zip
Encoding: UTF-8
Language: en
Suggests: doFuture, DT, future, future.apply, ggplot2, knitr, progressr, readxl, rmarkdown, sf, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-10-15 18:01:47 UTC; michaelwild
Author: Michael Wild [aut, cre, cph]
Maintainer: Michael Wild <michael.wild@me.com>
Repository: CRAN
Date/Publication: 2026-10-24 16:20:13 UTC

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New package soilwatR with initial version 0.1.1
Package: soilwatR
Title: Simulation of Soil Water Flow Based on Darcy's Law
Version: 0.1.1
Description: Provides a simple model to simulate soil water content and water flux changes at multiple soil depths. Calculations mainly follow Allen et al. (1998, ISBN:92-5-104219-5) and Teh (2017, ISBN:9789673447626).
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
Imports: dplyr, ggplot2, magrittr, rlang, stringr, tidyr
Suggests: ggpubr, testthat (>= 3.0.0)
Depends: R (>= 4.0)
NeedsCompilation: no
Packaged: 2026-10-15 16:23:27 UTC; liumg
Author: Minguo Liu [aut, cre]
Maintainer: Minguo Liu <liumg@nwafu.edu.cn>
Repository: CRAN
Date/Publication: 2026-10-24 16:10:02 UTC

More information about soilwatR at CRAN
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New package robotstxtr with initial version 0.3.1
Package: robotstxtr
Title: Engine-Aware 'robots.txt' Policy with Google's Matcher Algorithm
Version: 0.3.1
Language: en-US
Description: Evaluates whether URLs may be crawled according to 'robots.txt' rules. A versioned engine-aware facade keeps neutral fetch evidence, per-engine status policy, robots product tokens, and matcher capabilities separate, returning explicit non-decisions when policy is undocumented or a matcher is unavailable. The available matcher is a bundled, upstream-test-validated snapshot of Google's open-source C++ 'robots.txt' matcher, preserving 'Googlebot' behavior. Fetches use a deterministic, conservative policy built on 'httr2', with fetch origins constructed by 'rurl'. All network access in tests, examples, and vignettes is mocked or served locally, so no internet connection is required to install, test, or check the package. This matcher derives from Google's 'robotstxt' project <https://github.com/google/robotstxt>, distributed under the Apache License 2.0; see the package NOTICE.
License: MIT + file LICENSE
Copyright: file inst/COPYRIGHTS
URL: https://bart-turczynski.gitlab.io/robotstxtr/, https://gitlab.com/bart-turczynski/robotstxtr, https://bart-turczynski.r-universe.dev/robotstxtr
BugReports: https://gitlab.com/bart-turczynski/robotstxtr/-/issues
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: httr2 (>= 1.2.0), rurl (>= 3.0.1)
LinkingTo: cpp11
SystemRequirements: C++17
Suggests: callr, httpuv, jsonlite, knitr, oysteR, rmarkdown, rosv, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2026-10-15 14:04:24 UTC; bartturczynski
Author: Bart Turczynski [aut, cre, cph] , Google LLC [cph]
Maintainer: Bart Turczynski <bartek@turczynski.pl>
Repository: CRAN
Date/Publication: 2026-10-24 16:10:08 UTC

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New package p3d with initial version 0.1.0
Package: p3d
Title: Interactive 3D Visualization of p-Value Surfaces
Version: 0.1.0
Description: Provides interactive three-dimensional visualization of p-value surfaces for single-sample t-tests. Enables simultaneous exploration of effect size, sample size, and significance level, making the continuous nature of p-values and the moderating effect of sample size visually apparent. Includes both interactive ('rgl', 'plotly') and static (persp()) rendering options. The p-value surface is based on the approach of Infanger and Schmidt-Trucksäss (2019) <doi:10.1002/sim.8293>.
License: GPL (>= 3)
Encoding: UTF-8
URL: https://github.com/ahmetkutuk1/p3d, https://ahmetkutuk1.github.io/p3d/
BugReports: https://github.com/ahmetkutuk1/p3d/issues
Suggests: knitr, plotly, rgl, rmarkdown, testthat (>= 3.0.0)
Depends: R (>= 4.1.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-10-15 18:17:59 UTC; Ahmet
Author: Ahmet Kutuk [aut, cre]
Maintainer: Ahmet Kutuk <ahmetkutuk@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-24 16:30:02 UTC

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New package OptimalFactor with initial version 1.5.0
Package: OptimalFactor
Title: Item Selection in Factor Analysis by Boosting and Specification Search
Version: 1.5.0
Date: 2026-10-05
Description: Provides an iterative optimization algorithm for exploratory and confirmatory factor analysis that follows a boosting approach inspired by machine learning. It uses a composite fit index whose weights adapt to the degrees of freedom and the sample size, following Kenny and McCoach (2003) <doi:10.1207/S15328007SEM1003_1> and Shi, Lee and Maydeu-Olivares (2019) <doi:10.1177/0013164418783530>. It detects and removes problematic items (Heywood cases, cross-loadings, low loadings) with greedy or global search strategies, checks interfactor correlations, and supports ordinal data with WLSMV estimation and several rotation methods. A heuristic specification search for confirmatory models (MacCallum, 1986 <doi:10.1037/0033-2909.100.1.107>) explores move, drop and covariance operations across seed configurations. It also evaluates the resampling stability of the item selection, the recovery of a known or theoretical structure, and offers an optional conceptual analysis of remo [...truncated...]
License: GPL (>= 3)
URL: https://github.com/jventural/OptimalFactor, https://jventural.github.io/OptimalFactor/
BugReports: https://github.com/jventural/OptimalFactor/issues
Encoding: UTF-8
LazyData: true
Depends: R (>= 4.0.0)
Imports: lavaan, psych, dplyr, tidyr, ggplot2, stringr, parallel, stats, utils
Suggests: testthat (>= 3.0.0), httr, jsonlite, R.utils, knitr, rmarkdown, semTools
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-10-15 17:35:48 UTC; PC
Author: Jose Ventura-Leon [aut, cre]
Maintainer: Jose Ventura-Leon <jventuraleon@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-24 16:30:08 UTC

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New package MAC.address with initial version 0.1.0
Package: MAC.address
Title: Find, Validate and Identify Device MAC Addresses
Version: 0.1.0
Description: Tools to work with MAC (Media Access Control) addresses: list the MAC addresses of the local network interfaces and of the neighbors in the ARP cache on Linux, macOS and Windows, extract MAC addresses from free text, validate and normalize their notation, check the multicast and locally administered bits, generate random addresses, derive IPv6 interface identifiers (modified EUI-64), and identify the manufacturer using the public IEEE (Institute of Electrical and Electronics Engineers) MA-L, MA-M and MA-S registries <https://regauth.standards.ieee.org/standards-ra-web/pub/view.html#registries>.
URL: https://github.com/EnriquePH/mac-address, https://enriqueph.github.io/mac-address/
BugReports: https://github.com/EnriquePH/mac-address/issues
Depends: R (>= 4.0.0)
Imports: stats, tools, utils
Suggests: curl, testthat (>= 3.0.0), withr
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-US
NeedsCompilation: no
Packaged: 2026-10-14 19:39:39 UTC; eph
Author: Enrique Perez Herrero [aut, cre]
Maintainer: Enrique Perez Herrero <eph.project1500@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-24 16:30:15 UTC

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New package ltvlms with initial version 0.1.0
Package: ltvlms
Title: Linear Time-Variant Logistic Models with a Shape Parameter
Version: 0.1.0
Description: Evaluates and fits the Linear Time-Variant Logistic Model with Shape Parameter (LTVLMS) for dynamic growth processes. The model combines a linearly time-varying growth rate with a shape parameter for asymmetric trajectories and includes numerically stable prediction utilities. Methodological details are provided by Betrouni and Kernane (2026) "Linear Time-Varying Logistic Model With Shape Parameter for Dynamic Epidemic Modeling" <doi:10.1155/jama/4928447>.
Depends: R (>= 4.0.0)
License: MIT + file LICENSE
Copyright: Package code and documentation are copyright the listed authors. The included UNAIDS-derived datasets remain subject to the UNAIDS terms identified in inst/COPYRIGHTS.
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-10-15 18:03:31 UTC; bander
Author: Redouane Betrouni [aut] , Tewfik Kernane [aut] , Bander Hussein [aut, cre]
Maintainer: Bander Hussein <bshussein@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-24 16:20:08 UTC

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New package cdiscdata with initial version 0.2.0
Package: cdiscdata
Title: Versioned CDISC Standards Reference Data
Version: 0.2.0
Description: Provides versioned reference data for the standards of the Clinical Data Interchange Standards Consortium (CDISC) <https://www.cdisc.org/standards>: the CDISC Controlled Terminology (CT) for the Study Data Tabulation Model (SDTM) and the Analysis Data Model (ADaM); variable metadata for the SDTM model and for the families of the SDTM Implementation Guide (SDTMIG), the Standard for Exchange of Nonclinical Data Implementation Guide (SENDIG), and the ADaM Implementation Guide (ADaMIG); the Clinical Data Acquisition Standards Harmonization (CDASH) model and implementation guide; the Questionnaires, Ratings, and Scales (QRS) supplements; and the Define-XML schemas, written in the Extensible Markup Language (XML) Schema Definition (XSD) language, with Extensible Stylesheet Language Transformations (XSLT) stylesheets for them. A validity-date design stores every historical CT version compactly, without duplicating rows. Intended as a shared data dependency for pharmaverse-aligned packag [...truncated...]
License: MIT + file LICENSE
Depends: R (>= 4.1.0)
Suggests: testthat (>= 3.0.0), xml2, withr, covr, pkgdown, knitr, rmarkdown, callr
LazyData: true
LazyDataCompression: xz
Encoding: UTF-8
Language: en-US
URL: https://github.com/humanpred/cdiscdata, https://humanpred.github.io/cdiscdata/
BugReports: https://github.com/humanpred/cdiscdata/issues
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-10-15 21:46:07 UTC; bill
Author: Bill Denney [aut, cre] , Clinical Data Interchange Standards Consortium [cph] ), Lex Jansen [cph] ), National Cancer Institute Enterprise Vocabulary Services [dtc] )
Maintainer: Bill Denney <wdenney@humanpredictions.com>
Repository: CRAN
Date/Publication: 2026-10-24 16:40:09 UTC

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New package boltzrosen with initial version 0.1.0
Package: boltzrosen
Title: Boltzmann-Rosenbrock Distribution and Associated Copula
Version: 0.1.0
Description: Provides the probability density function, cumulative distribution function, quantile function, and random sample generation for the Boltzmann-Rosenbrock distribution. The package also includes functions for the marginal distributions of X and Y, the mutual information between the two components, and the copula associated with the distribution, including its density, distribution function, and sampling routines. The use of Boltzmann distribution in objective functions, such as the Rosenbrock function, is described in Segovia-Domínguez, I., Valdez, S.I. and Hernández-Aguirre, A. (2014) <doi:10.5220/0005079902510258>.
License: GPL-3
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-10-15 14:48:35 UTC; rogel
Author: Rogelio Salinas Gutierrez [aut, cre, cph] , Jhon Daniel Aguilar Payares [aut, cph] , Alejandro Fausto Cortes Salinas [aut, cph] , Sofia Isabel Soledad Limon [aut, cph] , Rogelio Emiliano Salinas Gutierrez [aut, cph] , Juan Pablo Salinas Munoz [aut, c [...truncated...]
Maintainer: Rogelio Salinas Gutierrez <rogelio.salinas@edu.uaa.mx>
Repository: CRAN
Date/Publication: 2026-10-24 16:10:14 UTC

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New package paretoinfer with initial version 0.1.0
Package: paretoinfer
Title: Sequential Identification of Approximately Pareto-Optimal Alternatives under Noise
Version: 0.1.0
Description: Sequential identification of epsilon-Pareto-optimal alternatives among a finite set with noisy, possibly correlated objectives. Simultaneous anytime-valid confidence sequences for every objective of every alternative (Waudby-Smith and Ramdas, 2024, <doi:10.1093/jrsssb/qkad009>) certify, at any time, which alternatives are epsilon-dominated and which are not, report the estimated frontier, the plausible Pareto set and the certified-dominated set, propose the next alternative to evaluate, and record an auditable result contract.
License: GPL (>= 3)
URL: https://castlaboratory.github.io/paretoinfer/, https://github.com/castlaboratory/paretoinfer
BugReports: https://github.com/castlaboratory/paretoinfer/issues
Encoding: UTF-8
Language: en-GB
Depends: R (>= 4.1)
Imports: cli (>= 3.6.0), generics, ggplot2 (>= 3.5.0), rlang (>= 1.1.0), seqbench (>= 0.1.0), stats, tibble (>= 3.2.0), utils
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-10-15 10:47:31 UTC; leite
Author: Andre Leite [aut, cre] , Raydonal Ospina [aut] , Cristiano Ferraz [aut]
Maintainer: Andre Leite <leite@castlab.org>
Repository: CRAN
Date/Publication: 2026-10-24 15:50:01 UTC

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New package DistLagHet with initial version 0.1.0
Package: DistLagHet
Title: Treatment Effect Estimation in Complex Designs
Version: 0.1.0
Description: Implements estimation methods for treatment effects in complex designs under parallel-trends assumptions. Based on the methodology of de Chaisemartin and D'Haultfoeuille (2025) <doi:10.48550/arXiv.2508.07808>. Provides three model specifications: base model with K lags, full dynamics model using all available periods, and interactions model with lag interaction terms. Includes C++ optimizations for faster bootstrap estimation.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 3.5.0)
Imports: MASS, Rcpp (>= 1.0.0)
LinkingTo: Rcpp, RcppEigen
Suggests: testthat (>= 3.0.0)
NeedsCompilation: yes
Packaged: 2026-10-15 09:34:12 UTC; henrifabre
Author: Clement de Chaisemartin [aut], Xavier D'Haultfoeuille [aut], Henri Fabre [cre, ctb]
Maintainer: Henri Fabre <henri.fabre@ensae.fr>
Repository: CRAN
Date/Publication: 2026-10-24 11:50:07 UTC

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New package agriTradeRisk with initial version 0.1.0
Package: agriTradeRisk
Title: Agricultural Export Competitiveness and Risk Analysis
Version: 0.1.0
Description: An integrated and reproducible workflow for analysing the competitiveness and risk of agricultural and horticultural exports. It measures destination and product concentration (Herfindahl-Hirschman, entropy and equivalent-number indices), revealed comparative advantage (Balassa, 1965) <doi:10.1111/j.1467-9957.1965.tb00050.x> and its symmetric form, relative unit values, and constant market share decomposition of export growth. It tests vertical price transmission between export and domestic prices with Engle-Granger cointegration (Engle and Granger, 1987) <doi:10.2307/1913236> using MacKinnon (2010) critical values and symmetric or asymmetric error correction models. It quantifies exchange-rate exposure of a multi-currency export portfolio (volatility, diversification ratio, risk contributions and value at risk), screens destination markets with composite entry-risk scores, and identifies risk-efficient destination mixes by mean-variance portfolio optimisation (Markowitz, 1 [...truncated...]
License: GPL (>= 3)
Encoding: UTF-8
Language: en-GB
LazyData: true
Depends: R (>= 3.5.0)
Imports: graphics, stats
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-10-15 09:10:53 UTC; root
Author: Anbukkani Perumal [aut, cre, cph]
Maintainer: Anbukkani Perumal <anbueconomic@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-24 11:50:02 UTC

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New package agriEquity with initial version 0.1.0
Package: agriEquity
Title: Equity and Sustainability Assessment of Agricultural Subsidies
Version: 0.1.0
Description: An integrated framework for evaluating whether agricultural support measures reach smallholders, women farmers and resource-poor regions, and at what productivity and environmental cost. It provides survey-weighted benefit incidence analysis by landholding class, gender, region or income quantile; concentration, Kakwani and Reynolds-Smolensky progressivity measures (Kakwani, 1977) <doi:10.2307/2230485> with bootstrap confidence intervals; multi-dimensional equity scorecards with parity ratios and Theil decomposition of benefit inequality; effects of subsidies on income inequality and Foster-Greer-Thorbecke poverty (Foster, Greer and Thorbecke, 1984) <doi:10.2307/1913475>; budget-neutral reallocation of a subsidy budget under alternative allocation rules, including a welfare-optimal allocation that combines diminishing productivity returns, Atkinson (1970) <doi:10.1016/0022-0531(70)90039-6> inequality aversion and environmental damage costs; and productivity-equity-sus [...truncated...]
License: GPL (>= 3)
Encoding: UTF-8
Language: en-GB
LazyData: true
Depends: R (>= 3.5.0)
Imports: graphics, stats
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-10-15 10:08:23 UTC; root
Author: Anbukkani Perumal [aut, cre, cph]
Maintainer: Anbukkani Perumal <anbueconomic@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-24 12:00:02 UTC

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New package fpoValue with initial version 0.1.0
Package: fpoValue
Title: Farmer Producer Organisation Economics and Member Benefit Accounting
Version: 0.1.0
Description: Tools to determine when collective marketing, aggregation, grading and bulk input procurement through farmer producer organisations (FPOs) and agricultural cooperatives improve member-farmer returns. The package provides channel-level transaction cost accounting (transport, commissions, market fees, time, rejection and payment-delay costs), estimation of scale economies from consolidated transport, tiered bulk input discounts and grading premiums, break-even throughput and procurement-price analysis, and comparison of individual and collective marketing scenarios. Its core is a member-level distributional accounting framework that separates the total surplus generated by an FPO from the benefits actually received by farmers through prices, transaction cost savings, input savings and dividends, and summarises their distribution across members with Gini and concentration indices and farm-size group shares.
License: GPL (>= 3)
Encoding: UTF-8
Language: en-GB
Depends: R (>= 3.5.0)
Imports: graphics
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-10-15 04:40:01 UTC; root
Author: Anbukkani Perumal [aut, cre, cph]
Maintainer: Anbukkani Perumal <anbueconomic@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-24 11:00:15 UTC

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New package controlledburn with initial version 0.3.1
Package: controlledburn
Title: Sparse Geometry Rasterization with Exact Coverage Fractions
Version: 0.3.1
Description: Rasterize polygon, line, and point geometry without materializing any pixel values. For polygons it computes exact coverage fractions for polygon-grid intersections, returning sparse tables: run-length encoded interior cells and individually weighted boundary cells. The scanline algorithm is O(perimeter) in both time and memory, using the scan line fill attributed to Wylie et al. (1967) <doi:10.1145/1465611.1465619>. Exact coverage fractions use the 'exactextract' algorithm by Daniel Baston, vendored from the 'exactextractr' package <doi:10.32614/CRAN.package.exactextractr>. Derived from the 'fasterize' package by Noam Ross.
License: Apache License (== 2.0)
Copyright: See file COPYRIGHTS
Encoding: UTF-8
LinkingTo: cpp11
Imports: wk
Suggests: geos, testthat (>= 3.0.0), knitr, rmarkdown, fasterize, terra, raster, ggplot2
URL: https://github.com/hypertidy/controlledburn
BugReports: https://github.com/hypertidy/controlledburn/issues
VignetteBuilder: knitr
Depends: R (>= 3.5)
NeedsCompilation: yes
Packaged: 2026-10-15 04:19:00 UTC; mdsumner
Author: Michael Sumner [aut, cre] , Noam Ross [aut] , EcoHealth Alliance [cph] , Jim Hester [ctb] , Daniel Baston [cph] ), ISciences, LLC [cph] )
Maintainer: Michael Sumner <mdsumner@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-24 11:00:21 UTC

More information about controlledburn at CRAN
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New package smak with initial version 0.1.0
Package: smak
Maintainer: Steven E. Pav <shabbychef@gmail.com>
Version: 0.1.0
Date: 2026-10-13
License: LGPL-3
Title: Scalable Model Averageing Kit
BugReports: https://github.com/shabbychef/smak/issues
Description: Supports frequentist model averaging on linear regression problems via the scalable method of Zhu et. al. (2022) <doi:10.1080/07350015.2022.2116442>. The scalable model averaging technique projects to singular vectors, performs one linear regression per singular vector, then combines the estimates to optimize either Mallows' criterion, or the jackknife estimate of error.
Depends: R (>= 4.0)
Imports: generics, methods, quadprog
Suggests: broom, testthat, knitr
URL: https://github.com/shabbychef/smak
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-10-14 21:54:30 UTC; spav
Author: Steven E. Pav [aut, cre]
Repository: CRAN
Date/Publication: 2026-10-24 09:20:02 UTC

More information about smak at CRAN
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New package LMDT with initial version 0.1.0
Package: LMDT
Title: Local Manifold Dispersion Test for Heteroskedasticity
Version: 0.1.0
Description: Implements the Local Manifold Dispersion Test (LMDT) for detecting complex, non-linear, and high-dimensional heteroskedasticity in linear regression models. LMDT measures the spectral smoothness (Dirichlet energy) of robust log-dispersion residuals over a self-tuning k-nearest neighbors graph Laplacian, as formulated in Jabbar (2026). The test statistic is asymptotically distribution-free with respect to error kurtosis and accommodates high-dimensional covariates (p > 50) via Gavish-Donoho optimal hard thresholding and supervised metric learning.
License: GPL (>= 3)
URL: https://amjed-droid.github.io/LMDT/, https://github.com/amjed-droid/LMDT
BugReports: https://github.com/amjed-droid/LMDT/issues
Depends: R (>= 4.0.0)
Imports: stats
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-10-14 23:29:15 UTC; intel
Author: Ahmed Sattar Jabbar [aut, cre]
Maintainer: Ahmed Sattar Jabbar <ahmed.state.me@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-24 09:30:02 UTC

More information about LMDT at CRAN
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New package LAGOtrials with initial version 1.1.0
Package: LAGOtrials
Title: Learn-as-You-Go Adaptive Trial Optimization
Version: 1.1.0
Description: Optimizes interventions for adaptive "Learn-As-you-GO" (LAGO) trials, in which the intervention package is updated between stages using accumulating data. Given data from completed stages, lago_optimization() fits the outcome model (via 'stats' generalized linear models or, for clustered designs, cluster-robust variance) and computes the cost-optimal recommended intervention for the next stage that is expected to reach a target mean outcome and/or a desired statistical power. get_confidence_set() constructs confidence sets for the optimal intervention, and visualize_cost() and lago_report() summarize the cost surface and results. Methods are described in Nevo, Lok and Spiegelman (2021) <doi:10.1214/20-aos1978> and Bing, Spiegelman, Nevo and Lok (2025) <doi:10.1093/biomtc/ujaf061>.
License: GPL-3
Copyright: This package bundles the D3 v7 library (inst/js/d3.v7.min.js), which is ISC-licensed and Copyright 2010-2023 Mike Bostock. See inst/COPYRIGHTS and inst/js/d3-LICENSE. All other code is Copyright the LAGO authors under GPL-3.
URL: https://correspondmerchant.github.io/LAGO-R-Package/, https://github.com/correspondMerchant/LAGO-R-Package
BugReports: https://github.com/correspondMerchant/LAGO-R-Package/issues
Encoding: UTF-8
LazyData: true
Imports: rje, NlcOptim, cli, bslib, shiny, ggplot2, shinyjs, Rcpp
LinkingTo: Rcpp
Suggests: testthat (>= 3.0.0), tibble, knitr, rmarkdown, jsonlite, spelling
VignetteBuilder: knitr
Depends: R (>= 2.10)
Language: en-US
NeedsCompilation: yes
Packaged: 2026-10-14 21:28:13 UTC; antebing
Author: Ante Bing [aut, cre], Minh Bui [aut], Jingyu Cui [aut], Mike Bostock [cph]
Maintainer: Ante Bing <abing@bu.edu>
Repository: CRAN
Date/Publication: 2026-10-24 09:10:02 UTC

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New package DoExp with initial version 0.1.0
Package: DoExp
Title: Design of Experiments with Hasse Diagrams and Anatomy Tables
Version: 0.1.0
Depends: R (>= 4.1.0)
Description: Constructs Hasse diagrams and anatomy tables from structural formulas and experimental data sets. Hasse diagrams may display sources of variation and their degrees of freedom for general experimental structures. For orthogonal designs, the package can also compute core matrices associated with quadratic forms for sums of squares and contributions to the expected mean squares. Anatomy tables display the degrees of freedom and A-efficiencies associated with the sources of variation.
License: GPL (>= 3)
Encoding: UTF-8
Imports: dplyr, ggplot2, knitr, psych, purrr, rlang, stringr, tibble, utils
Suggests: dae, patchwork, rmarkdown
NeedsCompilation: no
Packaged: 2026-10-14 22:32:07 UTC; Leo Peressim
Author: Leonardo Peressim [aut, cre] , Renata Sermarini [aut]
Maintainer: Leonardo Peressim <leonardoperessim@usp.br>
Repository: CRAN
Date/Publication: 2026-10-24 09:30:08 UTC

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New package tidyfault with initial version 0.1.0
Package: tidyfault
Title: Tidy Fault Tree Analysis
Version: 0.1.0
Description: Fault tree analysis with tidy data. Represent a fault tree as two tables, one of nodes (the top event, gates and basic events) and one of edges, so the whole workflow stays in ordinary data frames. Derive the Boolean equation of the top event, enumerate the truth table, and find minimal cut sets with the Method of Obtaining Cut Sets (MOCUS) algorithm of Fussell and Vesely (1972), implemented in 'R' and, by default, in C++ through 'Rcpp'. Evaluate thousands of binary or probabilistic scenarios in one vectorized call, put uncertainty intervals around the top-event probability, follow it over time, and rank which component fix lowers it most. Lay out and draw the tree with 'tidygraph', 'igraph' and 'ggplot2'. Methods follow the "Fault Tree Handbook" of Vesely, Goldberg, Roberts and Haasl (1981) <https://www.nrc.gov/docs/ML1007/ML100780465.pdf>. A 'Python' port with the same functions ships in the same repository.
URL: https://tidyfault.netlify.app, https://github.com/timothyfraser/tidyfault
BugReports: https://github.com/timothyfraser/tidyfault/issues
License: GPL-3
Encoding: UTF-8
Language: en-US
Depends: R (>= 4.1)
Imports: dplyr, ggplot2, graphics, igraph, methods, purrr, Rcpp, rlang, scales, stats, stringr, tibble, tidyr, tidygraph
LinkingTo: Rcpp
Suggests: ggraph, knitr, rmarkdown, spelling, testthat (>= 3.0.0)
VignetteBuilder: knitr
LazyData: true
NeedsCompilation: yes
Packaged: 2026-10-14 20:12:31 UTC; tmf77
Author: Timothy Fraser [aut, cre, cph] , Jingyao Tong [aut, cph] , Cornell University [cph]
Maintainer: Timothy Fraser <tmf77@cornell.edu>
Repository: CRAN
Date/Publication: 2026-10-24 09:00:02 UTC

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New package RQK with initial version 1.0.0
Package: RQK
Title: Rational Quadratic Kriging
Version: 1.0.0
Description: Fits the rational quadratic kriging models of Song and Joseph (2026) <doi:10.48550/arXiv.2610.18077> for deterministic and noisy responses using a rational quadratic kernel with anisotropic factor weights. Provides leave-one-out tuning, fast 'C++' prediction routines, and conformal prediction intervals. This work is supported by a U.S. NSF grant DMS-2310637.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.3.0)
Imports: Rcpp (>= 1.0.14), nloptr
LinkingTo: Rcpp, RcppArmadillo, nloptr
Suggests: testthat (>= 3.0.0)
NeedsCompilation: yes
Packaged: 2026-10-14 19:59:39 UTC; Difan
Author: Difan Song [aut, cre], V. Roshan Joseph [aut]
Maintainer: Difan Song <dfsong96@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-24 08:50:11 UTC

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New package RCPA4 with initial version 1.0.0
Package: RCPA4
Title: Data and Functions for "An R Companion to Political Analysis, Fourth Edition"
Version: 1.0.0
Description: Provides teaching-oriented functions and datasets for "An R Companion to Political Analysis, Fourth Edition" (forthcoming 2026). Functions produce readable tables and graphics for descriptive statistics, data transformation, confidence intervals, hypothesis testing, comparisons, cross-tabulation, and linear and logistic regression. Sampling weights are supported where appropriate, and analysis functions return reusable results for further examination. The package also includes curated political datasets designed for classroom instruction and independent practice. See Edwards and Pollock (forthcoming 2026) <https://www.poliscidata.com/textbooks/r_companion_4e.php>.
License: CC0
URL: https://www.poliscidata.com/textbooks/r_companion_4e.php
LazyData: TRUE
Encoding: UTF-8
Depends: R (>= 4.0)
Imports: beepr, car, graphics, grDevices, haven, Hmisc, knitr, lmtest, methods, stats, survey, utils
Suggests: hexbin, rgl, scatterplot3d, gdata, testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-10-09 13:32:27 UTC; Barry Edwards
Author: Barry C. Edwards [aut, cre] , Philip H. Pollock III [ctb]
Maintainer: Barry C. Edwards <bce@uga.edu>
Repository: CRAN
Date/Publication: 2026-10-24 08:20:02 UTC

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New package PheValuator with initial version 2.2.18
Package: PheValuator
Title: Rapid Phenotype Evaluation
Version: 2.2.18
Date: 2026-10-7
Description: Evaluates phenotype algorithms by developing a diagnostic prediction model using a set of noisy positives and noisy negatives. It can then apply the model to a large cohort to create a set of subjects each with a predicted probability for the health outcome of interest. This cohort can then be used to evaluate phenotype algorithms through the calculation of the necessary performance characteristics - sensitivity, specificity, and positive and negative predictive value. Based on work by Swerdel (2022) <doi:10.1016/j.jbi.2022.104177> and Swerdel (2019) <doi:10.1016/j.jbi.2019.103258>.
License: Apache License 2.0
VignetteBuilder: knitr
Depends: R (>= 4.1.1)
Imports: DatabaseConnector, PatientLevelPrediction (>= 6.0.4), FeatureExtraction (>= 2.1.5), SqlRender (>= 1.5.2), dplyr (>= 0.7.8), methods, ParallelLogger, tibble
Suggests: knitr, rmarkdown, shiny, shinydashboard, DT, htmltools, qpdf, testthat, Eunomia, withr, CohortGenerator
URL: https://ohdsi.github.io/PheValuator/, https://github.com/OHDSI/PheValuator
BugReports: https://github.com/OHDSI/PheValuator/issues
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-10-12 17:16:15 UTC; Admin_WObrien8
Author: William J. O'Brien [aut, cre], Joel Swerdel [aut], Martijn Schuemie [aut]
Maintainer: William J. O'Brien <wobrien8@its.jnj.com>
Repository: CRAN
Date/Publication: 2026-10-24 08:40:02 UTC

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New package flexsdm with initial version 1.4.2
Package: flexsdm
Title: Flexible Species Distribution Modeling Workflow
Version: 1.4.2
Maintainer: Santiago J.E. Velazco <sjevelazco@gmail.com>
URL: https://sjevelazco.github.io/flexsdm/, https://github.com/sjevelazco/flexsdm
BugReports: https://github.com/sjevelazco/flexsdm/issues
Depends: R (>= 3.5.0)
Imports: doParallel, dplyr, foreach, gbm, grDevices, kernlab, maxnet, mgcv, nnet, randomForest, spThin, terra (>= 1.5-21), methods, utils, ggplot2, patchwork, Rcpp
Description: Provides a flexible and comprehensive workflow for species distribution modeling, from data preparation (occurrence filtering, calibration areas, pseudo-absence and background sampling, data partitioning, and collinearity reduction) to model fitting, tuning, evaluation, prediction, ensemble modeling, and post-processing. The package is described in Velazco et al. (2022) <doi:10.1111/2041-210X.13874>. Implemented methods include the Shape metric to measure model extrapolation of Velazco et al. (2023) <doi:10.1111/ecog.06992>, ensembles of small models of Breiner et al. (2015) <doi:10.1111/2041-210X.12403> and Breiner et al. (2018) <doi:10.1111/2041-210X.12957>, Gaussian process models of Golding and Purse (2016) <doi:10.1111/2041-210X.12523>, and occurrence-based constraints for post-processing predictions of Mendes et al. (2020) <doi:10.1016/j.ecolmodel.2020.109180>.
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
Suggests: covr, fs, knitr, rmarkdown, testthat (>= 3.0.0), tibble, tidyr
VignetteBuilder: knitr
LinkingTo: Rcpp
NeedsCompilation: yes
Packaged: 2026-10-14 19:07:17 UTC; sjevelazco
Author: Santiago J.E. Velazco [aut, cre] , Brooke Rose [aut] , Andre F.A. Andrade [aut] , Ignacio Minoli [aut] , Janet Franklin [aut]
Repository: CRAN
Date/Publication: 2026-10-24 08:50:02 UTC

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New package esgcalc with initial version 0.2.0
Package: esgcalc
Title: Offline Environmental, Social and Governance Calculations
Version: 0.2.0
Description: Native, deterministic calculations for selected environmental, social and governance metrics. Provides granular taxonomy criteria, non-financial taxonomy indicators, principal adverse impact components, portfolio calculations and configurable performance ratings. Versioned local resources, explicit assumptions and structured results support reproducible offline use. Does not determine legal applicability or provide a complete regulatory reporting system. Selected methods reference EU Regulations 2020/852, 2022/1288 and 2023/2772; exact editions and provision locators are supplied in the bundled source contracts. For background on the taxonomy framework, see the European Commission <https://finance.ec.europa.eu/sustainable-finance/tools-and-standards/eu-taxonomy-sustainable-activities_en>.
License: GPL (>= 3)
Copyright: RiskDataScience GmbH
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: jsonlite, digest
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-10-09 10:34:42 UTC; qwert123
Author: Dimitrios Geromichalos [aut, cre], RiskDataScience GmbH [cph]
Maintainer: Dimitrios Geromichalos <riskdatascience@web.de>
Repository: CRAN
Date/Publication: 2026-10-24 08:10:02 UTC

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New package coiR with initial version 0.1.0
Package: coiR
Title: Analysis of Canopy Openness Index from Fisheye Images
Version: 0.1.0
Description: Tools to estimate the Canopy Openness Index (COI) from hemispherical (fisheye) canopy photographs. The package imports canopy images, crops them to the circular area delimited by the fisheye lens, binarizes them to separate sky from vegetation pixels, and computes the index as the proportion of sky pixels in the cropped image. Canopy openness is a measure related to canopy closure, canopy cover and understorey illumination, as discussed in Jennings, Brown and Sheil (1999) "Assessing forest canopies and understorey illumination: canopy closure, canopy cover and other measures" <doi:10.1093/forestry/72.1.59>. Example canopy images are included so users can test the workflow.
URL: https://github.com/Edbbioeco/coiR
BugReports: https://github.com/Edbbioeco/coiR/issues
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1)
Imports: ggplot2, dplyr, terra, tidyterra, rlang
Suggests: testthat (>= 3.0.0), purrr
NeedsCompilation: no
Packaged: 2026-10-14 21:17:24 UTC; LENOVO
Author: Edson Nilton de Moura Silva-Junior [aut, cre]
Maintainer: Edson Nilton de Moura Silva-Junior <edsonbbiologia@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-24 09:00:10 UTC

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New package AdaptiveGlasso with initial version 1.0.0
Package: AdaptiveGlasso
Title: Adaptive Graphical Lasso for Sparse Network Estimation
Version: 1.0.0
Description: Implements an adaptive graphical lasso method for sparse precision matrix and network estimation. The method combines ridge stabilization, cross-validated regularization, an initial graphical lasso estimate, and adaptive edge-specific penalties to estimate sparse conditional dependence structures. The method supports settings where the sample size is smaller than, equal to, or larger than the number of variables.
URL: https://github.com/elizabethamona/AdaptiveGlasso
BugReports: https://github.com/elizabethamona/AdaptiveGlasso/issues
License: MIT + file LICENSE
Encoding: UTF-8
Imports: CVglasso, glasso
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-10-13 04:39:31 UTC; amona
Author: Elizabeth B. Amona [aut, cre, cph]
Maintainer: Elizabeth B. Amona <amonaelizabeth1@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-24 08:40:09 UTC

More information about AdaptiveGlasso at CRAN
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Fri, 23 Oct 2026

New package zucrypt with initial version 0.1.0
Package: zucrypt
Title: Cryptography Without System Dependencies
Version: 0.1.0
Description: Cryptographic functions over raw vectors, including message digests of in-memory data, files and connections, keyed-hash message authentication codes (HMAC), Advanced Encryption Standard (AES) encryption, constant-time comparison and hexadecimal encoding, backed by a bundled and pinned copy of the 'Mbed TLS' project's cryptography library, 'TF-PSA-Crypto' (<https://github.com/Mbed-TLS/TF-PSA-Crypto>). No system cryptographic library, 'Java' or 'Python' is required at install or run time. Algorithm names are matched exactly, and failures are reported as structured conditions. The same primitives, and secure erasure of native buffers, are published to other packages as a static archive and as a registered C interface, so that a package can call them from C without going through R.
License: MIT + file LICENSE
Copyright: See inst/COPYRIGHTS and tools/vendor/manifest.tsv.
URL: https://github.com/pedrobtz/zucrypt, https://pedrobtz.github.io/zucrypt/
BugReports: https://github.com/pedrobtz/zucrypt/issues
Depends: R (>= 4.1)
Imports: utils
Suggests: openssl, testthat (>= 3.0.0)
SystemRequirements: A C99 compiler. No system cryptographic library is used, no CMake, Python or Perl is required, and nothing is downloaded or generated during installation: the backend is built from vendored sources, with an explicit object list in portable make.
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2026-10-13 21:33:01 UTC; pbtz
Author: Pedro Baltazar [aut, cre, cph], The Mbed TLS Contributors [cph] , Adriaan de Jong [ctb, cph] , Daniel King [ctb, cph] , Simon Tatham [ctb, cph]
Maintainer: Pedro Baltazar <pedrobtz@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-23 15:20:02 UTC

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Thu, 22 Oct 2026

New package umg with initial version 0.6.1
Package: umg
Title: Unified Model Graphs for Statistical Models in Psychology
Version: 0.6.1
Description: Constructs, validates, lays out, and renders Unified Model Graphs (UMG), a formal graphical grammar for statistical models in psychology. Vertices are typed by observability, support, and inferential role; edges distinguish stochastic, symmetric, deterministic, and mixing dependence; plates encode replication and hierarchy. Diagrams can be themed and rendered with base 'grid' graphics, with 'ggplot2', as 'TikZ' code, or as 'Graphviz' DOT, and can be constructed either from one-line motif builders for many model families or automatically from 'lavaan', 'lme4', 'mirt', 'blavaan', 'brms', 'OpenMx', and 'qgraph' model objects. A diagram can be inspected as a data frame, summarised, and exported back to 'lavaan' model syntax, making the model-diagram correspondence operational in both directions. Each diagram also exposes identification diagnostics (scaling checks, a graphical counting rule, and a d-separation reader) and generates the exploratory display scaffolds implied by the model-data [...truncated...]
License: MIT + file LICENSE
URL: https://hsiutingyu.github.io/umg/, https://github.com/hsiutingyu/umg
BugReports: https://github.com/hsiutingyu/umg/issues
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: grid, grDevices, stats, tools, utils
Suggests: lavaan, lme4, mirt, blavaan, brms, OpenMx, qgraph, ggplot2, DiagrammeR, knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
Language: en-US
NeedsCompilation: no
Packaged: 2026-10-14 10:07:50 UTC; Hsiu-TingYu
Author: Hsiu-Ting Yu [aut, cre]
Maintainer: Hsiu-Ting Yu <hsiutingyu@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-22 16:10:02 UTC

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New package twoPhaseSens with initial version 0.1.0
Package: twoPhaseSens
Title: Sensitivity Analysis for Covariates Observed in Two-Phase Samples
Version: 0.1.0
Description: Provides a structured method-comparison sensitivity-analysis workflow for linear regression when important continuous adjustment covariates are observed only in a Phase-2 subsample. Implements naive analysis, complete-case analysis, fully conditional specification multiple imputation, joint-model multiple imputation, inverse probability weighting, and augmented inverse probability weighting, with standardized tables, diagnostics, and publication-style forest plots. Methodological background is provided by Little and Rubin (2019) <doi:10.1002/9781119482260> for general missing-data methods, White and Carlin (2010) <doi:10.1002/sim.3944> for complete-case analysis with missing covariates, White, Royston and Wood (2011) <doi:10.1002/sim.4067> and van Buuren and Groothuis-Oudshoorn (2011) <doi:10.18637/jss.v045.i03> for chained-equations multiple imputation, Quartagno, Grund and Carpenter (2019) <doi:10.32614/RJ-2019-028> for joint-model multiple imputation, R [...truncated...]
License: MIT + file LICENSE
URL: https://rophenceojiambo.github.io/twoPhaseSens/, https://github.com/rophenceojiambo/twoPhaseSens
BugReports: https://github.com/rophenceojiambo/twoPhaseSens/issues
Encoding: UTF-8
Imports: ggplot2, gtsummary (>= 2.0.0), jomo, mice, rlang, tidyselect
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-10-14 14:26:41 UTC; runner
Author: Rophence Ojiambo [aut, cre] , Jemar Bather [aut]
Maintainer: Rophence Ojiambo <rophence.ojiambo@nyu.edu>
Repository: CRAN
Date/Publication: 2026-10-22 16:50:02 UTC

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New package SNPAssayR with initial version 1.0.1
Package: SNPAssayR
Title: SNP Genotyping Assay Design and Visualization
Version: 1.0.1
Description: Designs cleaved amplified polymorphic sequence (CAPS), derived CAPS (dCAPS), conventional amplification refractory mutation system (ARMS) and tetra-primer ARMS assays for single-locus, biallelic single nucleotide polymorphisms. Evaluates sequence-compatible primer binding, reconstructs ideal polymerase chain reaction products and computes theoretical complete restriction digestion and conditional genotype profiles. Transparent preference ranking, scientific visualizations and reproducible exports retain assumptions, missing specificity evidence and bounded search limitations. An optional offline 'shiny' interface uses the independently available analysis functions. Predictions do not establish experimental amplification, digestion efficiency or genome-wide specificity. Implements perfect-match nearest-neighbor thermodynamics from SantaLucia (1998) <doi:10.1073/pnas.95.4.1460>, single-substitution site-creation dCAPS based on Neff et al. (1998) <doi:10.1046/j.1365-313X.1998.001 [...truncated...]
License: GPL-3
Copyright: ICAR-Indian Institute of Rapeseed-Mustard Research (ICAR-IIRMR)
Encoding: UTF-8
Depends: R (>= 4.1.0)
Suggests: testthat (>= 3.2.1), shiny (>= 1.8.0), bslib (>= 0.6.1)
NeedsCompilation: no
Packaged: 2026-10-13 15:06:31 UTC; root
Author: Prashant Yadav [aut, cre] , Vinod Kumar [aut] , Vijay Veer Singh [aut] , ICAR-Indian Institute of Rapeseed-Mustard Research [cph]
Maintainer: Prashant Yadav <prashantnduat@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-22 16:20:02 UTC

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New package RDML7 with initial version 1.0.2
Package: RDML7
Title: Read, Write, Validate, and Analyze Real-Time PCR Data in the 'RDML' Format
Version: 1.0.2
Date: 2026-10-14
Encoding: UTF-8
Description: Reads, writes, validates, converts, and manipulates quantitative polymerase chain reaction (qPCR) data through the Real-Time PCR Data Markup Language ('RDML') application programming interface (API), using 'S7' objects. Includes an extensible file-format registry, vendor and tabular-data importers, 'RDES' import and export, fluorescence-table helpers, semantic validation, and compatibility wrappers for the historical 'RDML' API.
License: MIT + file LICENSE
URL: https://github.com/kablag/RDML7
BugReports: https://github.com/kablag/RDML7/issues
Depends: R (>= 4.1.0)
Imports: S7, checkmate (>= 1.6.2), data.table, readxl, stringr, tools, xml2 (>= 1.0), lubridate (>= 1.6.0)
Suggests: knitr, chipPCR, reshape2, qpcR, ggplot2, htmltools, DT, MBmca, PCRedux, shiny, shinythemes, testthat, rmarkdown, plotly
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-10-14 11:24:10 UTC; Blagodatskikh.KA
Author: Konstantin A. Blagodatskikh [cre, aut], Stefan Roediger [ctb], Michal Burdukiewicz [ctb], Andrej-Nikolai Spiess [ctb]
Maintainer: Konstantin A. Blagodatskikh <k.blag@yandex.ru>
Repository: CRAN
Date/Publication: 2026-10-22 16:40:26 UTC

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New package prime with initial version 0.5.5
Package: prime
Title: Proportional Inclusive Marginal Effects
Version: 0.5.5
Description: Implements a model-free variable importance measure based on proportional marginal effects estimated from noisy input-output data. See Cho and Joseph (2026) <doi:10.48550/arXiv.2610.17053> for details.
License: MIT + file LICENSE
Encoding: UTF-8
URL: https://github.com/ChoYoungSeo/prime-importance-r
BugReports: https://github.com/ChoYoungSeo/prime-importance-r/issues
Depends: R (>= 4.2.0)
Imports: FNN, MASS, parallel, Rcpp
LinkingTo: Rcpp, RcppArmadillo
Suggests: testthat (>= 3.0.0), twinning
NeedsCompilation: yes
Packaged: 2026-10-14 18:51:14 UTC; ycho397
Author: Youngseo Cho [aut, cre, cph], V. Roshan Joseph [aut, cph]
Maintainer: Youngseo Cho <josun@gatech.edu>
Repository: CRAN
Date/Publication: 2026-10-22 17:00:02 UTC

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New package NormGen with initial version 0.0.6
Package: NormGen
Title: An Efficient and Precise Quantile Mapping for Normal Pseudo-Random Number Generation
Version: 0.0.6
Description: High-performance pseudo-normal random generator using an optimized quantile mapping algorithm. It provides fast generation of normal pseudo-random numbers based on precise mathematical approximations. The package features Rnorm() for efficient single-threaded generation and parallel_Rnorm(), a high-performance, multithreaded variant powered by 'RcppParallel' and Intel 'TBB'. Package compilation flags are optimized to support multi-core parallel processing.
Depends: R (>= 3.5.0)
Imports: Rcpp (>= 1.0.0), RcppParallel
LinkingTo: Rcpp, RcppParallel
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
License: GPL-3
Language: en-US
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2026-10-14 10:41:41 UTC; piotr
Author: Piotr Sulewski [aut, cre]
Maintainer: Piotr Sulewski <piotr.sulewski@upsl.edu.pl>
Repository: CRAN
Date/Publication: 2026-10-22 16:20:08 UTC

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New package MultipleSystemsEstimation with initial version 1.3.2
Package: MultipleSystemsEstimation
Title: Methods for Multiple Systems Estimation
Version: 1.3.2
Description: Methods for multiple systems estimation using Poisson log-linear models, with particular attention to sparse capture data, model selection and its associated uncertainty, and Bayesian thresholding of interaction effects. The package implements and extends methodology from Silverman (2020) <doi:10.1111/rssa.12505>, Chan, Silverman and Vincent (2021) <doi:10.1080/01621459.2019.1708748>, and Silverman, Chan and Vincent (2024) <doi:10.1007/s11222-023-10346-9>.
URL: https://bernardsilverman.github.io/MultipleSystemsEstimation/, https://bernardsilverman.co.uk/contact
Depends: R (>= 4.2.0)
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
Imports: lpSolve, MCMCpack
VignetteBuilder: knitr
NeedsCompilation: no
Maintainer: Bernard W. Silverman <bernard.silverman@stats.ox.ac.uk>
Packaged: 2026-10-13 21:30:22 UTC; berna
Author: Bernard W. Silverman [aut, cre], Lax Chan [ctb], Kyle Vincent [ctb]
Repository: CRAN
Date/Publication: 2026-10-22 16:10:09 UTC

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New package hybridclock with initial version 0.1.1
Package: hybridclock
Title: How Long Have Hybrids Been Forming? Hybrid Population Histories from Diagnostic Markers
Version: 0.1.1
Description: Estimates the history of hybrid populations from diagnostic markers, with or without a genetic map: the average age of the hybrids, how long ago the rarer species' ancestry entered, the number of backcrosses, and whether pure animals of the rarer species are still arriving. Population samples of hybrid index and interspecies heterozygosity, as defined by Fitzpatrick (2012) <doi:10.1186/1471-2148-12-131>, are compared with forward simulations that include drift, small breeding groups, sibling mating and separate breeding pools, so that inbreeding is not mistaken for age. Estimates come from 'Cubist' models with split-conformal intervals. Recent hybrids are also classified individually, and the number of markers needed to detect backcrossed hybrids follows Boecklen and Howard (1997) <doi:10.1890/0012-9658(1997)078[2611:GAOHZN]2.0.CO;2>.
License: MIT + file LICENSE
URL: https://github.com/paulmaier/hybridclock, https://paulmaier.github.io/hybridclock/
BugReports: https://github.com/paulmaier/hybridclock/issues
Depends: R (>= 4.1)
Imports: Cubist, graphics, grDevices, parallel, ranger, stats
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2026-10-14 13:59:47 UTC; paulm
Author: Paul A. Maier [aut, cre, cph]
Maintainer: Paul A. Maier <maierpa@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-22 16:40:02 UTC

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New package fereg with initial version 0.4.0
Package: fereg
Title: Fast Fixed-Effects Estimation with the 'fixest' Interface
Version: 0.4.0
Description: Ordinary least squares, two-stage least squares, Poisson and logit regressions with any number of high-dimensional fixed effects, interactions of fixed effects, varying slopes, weights and iid, heteroskedasticity-robust (HC1, HC2, HC3), multiway-clustered, CRV3, Newey-West, Driscoll-Kraay or Conley standard errors. The formula syntax, arguments, results and methods follow the 'fixest' package and reproduce its estimates. The computations run in a parallel 'Rust' library that eliminates the largest fixed effect exactly and solves for the others by preconditioned conjugate gradient.
License: MIT + file LICENSE
URL: https://github.com/leoliu0/fereg
BugReports: https://github.com/leoliu0/fereg/issues
Depends: R (>= 4.2)
Imports: stats
Suggests: fixest, testthat (>= 3.0.0), data.table, generics, Matrix
SystemRequirements: Cargo (Rust's package manager), rustc (>= 1.85)
Encoding: UTF-8
LazyData: true
NeedsCompilation: yes
Packaged: 2026-10-14 12:13:57 UTC; leo
Author: Leo Liu [aut, cre, cph], Authors of the bundled Rust crates [ctb, cph]
Maintainer: Leo Liu <auleo.liu@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-22 16:30:02 UTC

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New package EnvRtype with initial version 0.1.3
Package: EnvRtype
Title: Envirotyping for Quantitative Genetics and Plant Breeding
Version: 0.1.3
Description: An enviromics toolkit for genotype-by-environment analysis and envirotype-informed genomic prediction. Collects worldwide daily and hourly weather from 'NASA POWER', soil profiles from 'SoilGrids', elevation and bioclimatic layers from 'WorldClim', agro-ecological zones from 'FAO GAEZ', and downscaled 'CMIP6' climate scenarios, with checkpointed retrieval that can resume after an interrupted run. Derives agro-meteorological parameters (solar radiation, evapotranspiration, thermal time, atmospheric demand), runs a FAO-56 single crop coefficient soil water balance, and maps daily weather onto crop developmental stages. Builds environmental covariable matrices, envirotype typologies and frequency matrices, mega-environment clusters, historical risk profiles and target population of environments weights. Reduces interval-resolved envirotypes by principal component analysis, delineates soil zones with Gaussian mixture models, and constructs linear, Gaussian and arc-cosine environmental rela [...truncated...]
License: GPL-3
URL: https://github.com/gcostaneto/EnvRtype, https://gcostaneto.github.io/EnvRtype/
BugReports: https://github.com/gcostaneto/EnvRtype/issues
Encoding: UTF-8
LazyData: true
Imports: ggplot2, grDevices, graphics, reshape2, stats, tools, utils
Suggests: cluster, curl, geobr, ggrepel, httr, jsonlite, knitr, mclust, nasapower, parallel, randomForest, rmarkdown, sf, terra, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-10-14 18:51:47 UTC; qvt192
Author: Germano Costa-Neto [aut, cre], Fernanda Pontes [aut]
Maintainer: Germano Costa-Neto <germano.cneto@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-22 16:50:13 UTC

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New package CoxRMSTSimpson with initial version 0.1.0
Package: CoxRMSTSimpson
Title: Restricted Mean Survival Time from Cox Models
Version: 0.1.0
Description: Calculates restricted mean survival time from predicted Cox proportional hazards survival curves using composite Simpson's rule and provides plots with shaded areas under the survival curves. Includes simulated survival data for reproducible examples.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: survival, graphics, grDevices, stats
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-10-14 08:45:43 UTC; fordeia
Author: Ian Forde [aut, cre]
Maintainer: Ian Forde <fordeia@appstate.edu>
Repository: CRAN
Date/Publication: 2026-10-22 16:20:14 UTC

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New package corridoR with initial version 0.2.0
Package: corridoR
Title: Migration Corridors and Genetic Range Shifts from Landscape Genetic Data
Version: 0.2.0
Description: Models genetic connectivity along migration corridors and forecasts how it shifts under climate change, following Maier et al. (2022) <doi:10.1038/s41437-022-00561-x>. Least cost corridors are built from accumulated cost surfaces and used as weights to summarize raw environmental layers between sites; each group of environmental features can choose its own corridor bandwidth; and pairwise predictions of differentiation and directional migration are mapped back onto the landscape as magnitude and net-direction surfaces. Includes readers for common genotype formats (STRUCTURE, GENEPOP, VCF, GenAlEx, FSTAT and PLINK files, and 'adegenet' objects), pairwise fixation indices, and the directional differentiation of Sundqvist et al. (2016) <doi:10.1002/ece3.2096>.
License: MIT + file LICENSE
URL: https://github.com/paulmaier/corridoR, https://paulmaier.github.io/corridoR/
BugReports: https://github.com/paulmaier/corridoR/issues
Depends: R (>= 4.1)
Imports: gdistance, graphics, grDevices, raster, sf, stats, terra, utils
Suggests: adegenet, caret, Cubist, exactextractr, ggplot2, knitr, lme4, ranger, rmarkdown, testthat (>= 3.0.0), vcfR
VignetteBuilder: knitr
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-10-14 13:33:26 UTC; paulm
Author: Paul A. Maier [aut, cre, cph]
Maintainer: Paul A. Maier <maierpa@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-22 16:40:19 UTC

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New package camplet with initial version 1.0.0
Package: camplet
Title: Seasonal Adjustment via the CAMPLET Method
Version: 1.0.0
Description: Seasonal adjustment with CAMPLET (Abeln and Jacobs (2023) <doi:10.1007/978-3-031-22845-2>), a transparent, adaptive method that corrects for seasonality and outliers via arithmetic-progression updates, without model identification or optimisation, and without revising earlier adjusted values when new observations arrive. A pure R port of the original 'Excel' 'VBA' implementation, validated against its output.
URL: https://gitrepo.service.rug.nl/team-data-science/camplet-r
License: GPL-3
Encoding: UTF-8
Depends: R (>= 3.5)
Suggests: testthat (>= 3.0.0), readxl
NeedsCompilation: no
Packaged: 2026-10-07 13:31:55 UTC; herbert
Author: Barend Abeln [aut] , Herbert Kruitbosch [aut, cre]
Maintainer: Herbert Kruitbosch <datascience@rug.nl>
Repository: CRAN
Date/Publication: 2026-10-22 16:30:08 UTC

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New package AccumulatR with initial version 1.0.0
Package: AccumulatR
Title: Simulation and Likelihood Tools for Evidence-Accumulation Models
Version: 1.0.0
Description: Toolbox for designing, simulating and fitting custom racing evidence-accumulation models to behavioral data. Users define a model in terms of accumulators, pooled channels, logical response rules, and timing dependencies. This allows more direct embedding of psychological hypotheses into the model. With that model you can simulate decision-making data and evaluate the likelihood of observed responses under alternative parameter values. The user-facing interface stays in R, while the simulation and likelihood calculations are handled in C++ for speed.
License: GPL-3
URL: https://github.com/niekstevenson/AccumulatR, https://niekstevenson.github.io/AccumulatR/
BugReports: https://github.com/niekstevenson/AccumulatR/issues
Encoding: UTF-8
Depends: R (>= 4.1)
Imports: Rcpp (>= 1.1.2), stats, utils
Suggests: knitr, rmarkdown, testthat (>= 3.0.0), DiagrammeR
VignetteBuilder: knitr
LinkingTo: Rcpp (>= 1.1.2), BH
SystemRequirements: C++17
NeedsCompilation: yes
Packaged: 2026-10-14 12:52:40 UTC; runner
Author: Niek Stevenson [aut, cre]
Maintainer: Niek Stevenson <niek.stevenson@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-22 16:30:14 UTC

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New package ccva with initial version 0.1.0
Package: ccva
Title: Climate Change Vulnerability Assessment with Constrained Latent Models
Version: 0.1.0
Description: A general framework for climate change vulnerability assessment (CCVA) of any species and any dataset. Variables are tagged as exposure, sensitivity or adaptive capacity; each component is computed from its own predictors by a chosen method; and the three components are combined into vulnerability. Methods range from the conventional weighted index of Ofori et al. (2017) <doi:10.1038/s41598-017-13245-y> to shape-constrained additive models ('scam'), latent-variable structural equation models ('lavaan') in which vulnerability is inferred from observable proxies, and penalised regression ('glmnet') for high-dimensional predictors. Ecological knowledge enters as explicit constraints on predictors, on each component's role and on the links between components. Diagnostics, validation against observed outcomes, bootstrap and weight-based uncertainty, calibrated risk predictions and plots for every step are included.
License: GPL (>= 3)
URL: https://github.com/DoostiH/ccva
BugReports: https://github.com/DoostiH/ccva/issues
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: ggplot2 (>= 3.4.0), lavaan (>= 0.6-12), stats, utils
Suggests: scam, glmnet, knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
LazyData: true
NeedsCompilation: no
Packaged: 2026-10-14 06:45:01 UTC; MQ20173444
Author: Hassan Doosti [aut, cre, cph]
Maintainer: Hassan Doosti <hassan.doosti@mq.edu.au>
Repository: CRAN
Date/Publication: 2026-10-22 16:00:02 UTC

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New package zufft with initial version 0.1.0
Package: zufft
Title: Fast Fourier, Cosine and Sine Transforms
Version: 0.1.0
Description: Computes discrete Fourier transforms (complex, real-to-complex and complex-to-real) and discrete cosine and sine transforms of types one to four over any axes of an array, with the fast Fourier transform (FFT) code of 'ducc0' (<https://github.com/mreineck/ducc>) bundled in the BSD-licensed subset that 'SciPy' uses. Transforms of any length run in O(n log n) time, real input uses true real transforms, and several threads can share one transform.
License: MIT + file LICENSE
URL: https://github.com/pedrobtz/zufft, https://pedrobtz.github.io/zufft/
BugReports: https://github.com/pedrobtz/zufft/issues
Depends: R (>= 4.1)
Suggests: fftwtools, knitr, parallel, rmarkdown, testthat (>= 3.0.0), withr
VignetteBuilder: knitr
Copyright: See inst/COPYRIGHTS.
Encoding: UTF-8
Language: en-GB
SystemRequirements: C++17
NeedsCompilation: yes
Packaged: 2026-10-13 21:42:17 UTC; pbtz
Author: Pedro Baltazar [aut, cre, cph], Martin Reinecke [ctb] , Peter Bell [ctb, cph] , Max-Planck-Society [cph] , Matteo Frigo [cph] , Massachusetts Institute of Technology [cph] , The TensorFlow Authors [cph] , SciPy Developers [cph]
Maintainer: Pedro Baltazar <pedrobtz@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-22 11:10:02 UTC

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New package zuexact with initial version 0.1.0
Package: zuexact
Title: Exactly Rounded Sums, Means and Dot Products
Version: 0.1.0
Description: Sums of double-precision numbers computed exactly and rounded once, so the result is the correctly rounded true sum and does not depend on the order of the elements, the platform, or whether R was built with long doubles. Built on the small and large superaccumulators of Neal (2015) <doi:10.48550/arXiv.1505.05571>. Provides exactly rounded sums, means, cumulative sums, dot products and norms, row, column and grouped sums, accumulators that can be built in pieces and merged across processes, and a registered 'C' interface for other packages.
License: MIT + file LICENSE
URL: https://pedrobtz.github.io/zuexact/, https://github.com/pedrobtz/zuexact
BugReports: https://github.com/pedrobtz/zuexact/issues
Depends: R (>= 4.1)
Suggests: gmp, knitr, parallel, PreciseSums, rmarkdown, testthat (>= 3.0.0), withr
VignetteBuilder: knitr
Encoding: UTF-8
Language: en-GB
SystemRequirements: C99
NeedsCompilation: yes
Packaged: 2026-10-13 22:05:27 UTC; pbtz
Author: Pedro Baltazar [aut, cre, cph], Radford M. Neal [cph]
Maintainer: Pedro Baltazar <pedrobtz@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-22 11:20:02 UTC

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New package geoecu with initial version 0.3.0
Package: geoecu
Title: Maps of the Provinces, Cantons and Parishes of Ecuador (Mapas de Provincias, Cantones y Parroquias del Ecuador)
Version: 0.3.0
Description: Provides the boundaries of the provinces, cantons and parishes of Ecuador as 'sf' objects, identified by the codes of the national political-administrative division (DPA, "División Político-Administrativa"), ready to be mapped and joined with health, epidemiological surveillance or other data. The three levels nest exactly and are offered in two resolutions: a light one for maps and dashboards and a detailed one for spatial analysis. The layers are derived from the free-access cartography of the Geographic Military Institute of Ecuador (IGM) <https://www.geoportaligm.gob.ec/portal/>, are downloaded on first use as 'GeoPackage' files and cached locally. Includes a catalogue of DPA codes, helpers to clean codes and place names, and tools to relocate the Galapagos Islands in national maps. Documentation is in Spanish.
License: MIT + file LICENSE
URL: https://github.com/f-slg/geoecu
BugReports: https://github.com/f-slg/geoecu/issues
Depends: R (>= 4.1.0)
Imports: sf, stats, tools, utils
Suggests: ggplot2, testthat (>= 3.0.0)
Encoding: UTF-8
Language: es
LazyData: true
NeedsCompilation: no
Packaged: 2026-10-14 00:07:35 UTC; fabriciosalas
Author: Ronald Fabricio Salas Guerrero [aut, cre, cph]
Maintainer: Ronald Fabricio Salas Guerrero <fabriciosalasguerrero@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-22 11:30:02 UTC

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New package Applr with initial version 1.0.0
Package: Applr
Title: Visualize and Explain Linear Models
Version: 1.0.0
Description: Tools for visualizing and explaining linear models fit with lm(). Draws 2D slices of higher-dimensional models in base graphics and as a 'ggplot2' layer, offers an interactive 'plotly' 3D scatter with a fitted surface for two-predictor models, and renders model equations as plain text or 'LaTeX'.
License: MIT + file LICENSE
URL: https://saundersg.github.io/Applr/, https://github.com/saundersg/Applr
BugReports: https://github.com/saundersg/Applr/issues
Encoding: UTF-8
Language: en-US
Depends: R (>= 4.1.0)
Imports: ggplot2 (>= 3.5.0), plotly, rlang, graphics, grDevices, grid, stats
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-10-13 23:16:30 UTC; DELL
Author: Cameron McClellan [aut], James Beeson [aut, cre], Garrett Saunders [ths]
Maintainer: James Beeson <jamesbeeson01@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-22 11:20:09 UTC

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New package spifa with initial version 0.1.0
Package: spifa
Title: Bayesian Spatial Item Factor Analysis
Version: 0.1.0
Encoding: UTF-8
Description: Fits spatial item factor analysis models for binary responses, following Chacón-Montalván, E. A., Parry, L., Giorgi, E., Torres, P., Orellana, J. D. Y., Moraga, P., and Taylor, B. M. (2025) <doi:10.1214/25-AOAS2072>, using full Bayesian inference via adaptive Metropolis-Hastings within Gibbs sampling and auxiliary variables with a probit link function. The latent factors are modelled as the sum of a predictor effect, a multivariate Gaussian process capturing spatial dependence, and a multivariate non-spatial term, allowing users to fit and predict spatially-referenced constructs such as food insecurity or socioeconomic indices. Standard exploratory and confirmatory item factor analysis are supported as particular cases, simply by dropping the spatial structure.
License: GPL-3
URL: https://github.com/ErickChacon/spifa, https://ErickChacon.github.io/spifa/
Depends: R (>= 4.1.0)
BugReports: https://github.com/ErickChacon/spifa/issues
Imports: Rcpp (>= 0.12.13), RcppTN, tibble, dplyr, tidyr, sf, ggplot2, posterior, ggridges, patchwork
LinkingTo: Rcpp, RcppArmadillo, RcppTN
Suggests: knitr, rmarkdown, testthat (>= 3.0.0), mirt, gstat
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2026-10-13 14:41:24 UTC; rstudio
Author: Erick A. Chacon-Montalvan [aut, cre] , Emanuele Giorgi [ctb], Benjamin M. Taylor [ctb]
Maintainer: Erick A. Chacon-Montalvan <erick.chaconmontalvan@wur.nl>
Repository: CRAN
Date/Publication: 2026-10-22 10:30:02 UTC

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New package progme with initial version 0.1.0
Package: progme
Title: Extended Progression Models for Repeated Measures
Version: 0.1.0
Description: Extended progression models for repeated measures in progressive disease clinical trials. Provides nonlinear mixed-effects progression models (linear, plateau, Emax, exponential decay), delayed treatment onset estimation by profile likelihood, joint longitudinal-survival models for informative dropout, competing-risks extensions, biomarker-informed adaptive dosing rules, and simulation-based power and sample-size calculation. The progression-model view of treatment effects, in which effects are characterised on the underlying disease trajectory rather than as additive shifts on the outcome scale, follows Raket (2022) <doi:10.1002/sim.9581>. The nonlinear mixed-effects machinery is built on the 'nlme' implementation described by Pinheiro and Bates (2000, ISBN 978-0-387-98957-0), and the joint modelling of longitudinal and time-to-event data follows Rizopoulos (2012, ISBN 978-1-4398-7286-4).
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
Depends: R (>= 4.1.0)
Imports: nlme, survival, ggplot2, stats, graphics, utils
Suggests: rstan, testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
URL: https://github.com/MukulBijalwan/progme
BugReports: https://github.com/MukulBijalwan/progme/issues
NeedsCompilation: no
Packaged: 2026-10-13 13:47:08 UTC; Admin
Author: Mukul Bijalwan [aut, cre] , Gunjan Aggrwal [aut], Mukul Jain [aut]
Maintainer: Mukul Bijalwan <mukulbijalwan555@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-22 10:30:09 UTC

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New package nrMCmix with initial version 0.3
Package: nrMCmix
Title: Non-Reversible Markov Chains for Bayesian Mixture Models
Version: 0.3
Date: 2026-10-13
Description: Provides Bayesian inference for finite and infinite mixture models using Markov chain Monte Carlo (MCMC) methods. Supports Gaussian, multivariate Gaussian, Poisson, Binomial, and multivariate Bernoulli mixture kernels with different covariance structures and flexible prior specifications. Provides tools for data generation, posterior density evaluation, clustering and similarity analysis, and advanced MCMC sampling strategies, including reversible and non-reversible samplers: Ascolani et al. (2026) <doi:10.48550/arXiv.2510.03226>, informed proposals: Zanella (2020) <doi:10.1080/01621459.2019.1585255>, collapsed Gibbs sampling: Diebolt and Robert (1994) <doi:10.1111/j.2517-6161.1994.tb01985.x>, and split-and-merge samplers: Dahl and Newcomb (2021) <doi:10.1080/00949655.2021.1998502>.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: base, coda, graphics, grDevices, fields, ggplot2, salso, Rcpp (>= 1.0.12), Rdpack, stats
LinkingTo: Rcpp, RcppArmadillo
Suggests: knitr, rmarkdown, bmixture, datasets
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2026-10-13 16:00:28 UTC; paolomanildo
Author: Filippo Ascolani [aut] , Paolo Manildo [aut, cre] , Giacomo Zanella [aut]
Maintainer: Paolo Manildo <paolo.manildo@studenti.unipd.it>
Repository: CRAN
Date/Publication: 2026-10-22 10:40:02 UTC

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New package fkr with initial version 0.1.0
Package: fkr
Title: Realistic Fake Data Generator for the Philippines
Version: 0.1.0
Description: Generates realistic, locale-aware synthetic data for the Philippines, covering both personal data (names, ages, birthdays, contact details, addresses, government-ID-style numbers) and business data (company names, industries, job titles, products, prices, and permit numbers). Every value, including anything formatted to resemble a government identifier, is drawn uniformly at random for software testing, prototyping, and teaching, and does not correspond to any real person, business, or record.
License: MIT + file LICENSE
URL: https://github.com/yng-me/fkr
BugReports: https://github.com/yng-me/fkr/issues
Encoding: UTF-8
Depends: R (>= 3.5.0)
Imports: stats, phscs, psgc
Suggests: curl, knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-10-13 16:21:36 UTC; bhasabdulsamad
Author: Bhas Abdulsamad [aut, cre, cph]
Maintainer: Bhas Abdulsamad <aeabdulsamad@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-22 10:40:07 UTC

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New package rjd3bridge with initial version 0.1.0
Package: rjd3bridge
Title: Bridge Between 'RJDemetra' (V2) and 'rjd3' (V3)
Version: 0.1.0
Description: Provides bidirectional tools to convert seasonal adjustment models and specifications between 'RJDemetra' ('JDemetra+' v2) and the 'rjd3' ecosystem ('JDemetra+' v3, packages 'rjd3x13' and 'rjd3tramoseats'). Facilitates workflow migration and backward compatibility analysis.
Depends: R (>= 4.1.0)
Imports: rJava, RJDemetra (>= 0.2.7), rjd3toolkit(>= 3.3.0), rjd3x13 (>= 3.3.0), rjd3tramoseats (>= 3.3.0), rjd3jars (>= 0.0.5)
URL: https://github.com/AQLT/rjd3bridge, https://aqlt.github.io/rjd3bridge/
BugReports: https://github.com/AQLT/rjd3bridge/issues
SystemRequirements: Java (>= 17)
License: EUPL
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-10-13 10:02:24 UTC; aquartier-la-tente01
Author: Alain Quartier-la-Tente [aut, cre, cph]
Maintainer: Alain Quartier-la-Tente <alain.quartier@yahoo.fr>
Repository: CRAN
Date/Publication: 2026-10-22 10:00:02 UTC

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Wed, 21 Oct 2026

New package fieldopt with initial version 0.1.0
Package: fieldopt
Title: Area-Frame and Dual-Frame Survey Design under Real Field Cost
Version: 0.1.0
Description: Design of agricultural and other area-frame and dual-frame (area plus list) sample surveys that go to the field, with the real cost of field work (travel between sampling units plus interviews) next to the variance of the design-based estimator. Travel matrices from coordinates or a road network; GRASP routing of the field work for one or several teams; stratified spatially balanced (local pivotal) or spatially ordered systematic selection of segments with interpenetrating replicates; points inside segments with multiplicity (expected-hits) estimation; closed, open and weighted segment estimators; Horvitz-Thompson estimation with local-mean or replicate variances; cost-aware allocation across strata, Hartley's dual-frame allocation with an overlap, and two-stage allocation with a cost function; and the cost-variance frontier of a design by simulation. The computational engine is the Rust crate 'fieldopt-core'.
License: GPL (>= 3)
URL: https://castlaboratory.github.io/fieldopt/, https://github.com/castlaboratory/fieldopt
BugReports: https://github.com/castlaboratory/fieldopt/issues
Depends: R (>= 4.2)
Imports: cli, generics, ggplot2, rlang, stats, tibble
Suggests: arrow, BalancedSampling, dplyr, highs, knitr, osrm, purrr, Matrix, rmarkdown, sf, survey, testthat (>= 3.0.0), tidyr, vrpr
VignetteBuilder: knitr
Encoding: UTF-8
Language: en-GB
SystemRequirements: Cargo (Rust's package manager), rustc >= 1.70.0, xz
NeedsCompilation: yes
Packaged: 2026-10-10 21:46:00 UTC; leite
Author: Andre Leite [aut, cre] , Raydonal Ospina [aut] , Cristiano Ferraz [aut] , The authors of the dependency Rust crates [ctb]
Maintainer: Andre Leite <leite@castlab.org>
Repository: CRAN
Date/Publication: 2026-10-21 18:50:02 UTC

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New package tsexplorer with initial version 0.1.0
Package: tsexplorer
Title: Exploratory and Diagnostic Tools for Time Series and Forecasts
Version: 0.1.0
Description: Exploratory, descriptive and diagnostic tools for univariate and multivariate time series and tools to evaluate and compare forecasts: summary statistics and gaussianity tests; sample autocorrelation functions with the Ljung and Box (1978) <doi:10.1093/biomet/65.2.297> and Monti (1994) <doi:10.2307/2337080> tests; information criteria and Granger (1969) <doi:10.2307/1912791> causality; unit root tests of Dickey and Fuller (1979) <doi:10.1080/01621459.1979.10482531> and Phillips and Perron (1988) <doi:10.1093/biomet/75.2.335>; the cointegration test of Johansen (1988) <doi:10.1016/0165-1889(88)90041-3>; heteroskedasticity tests; non-linearity tests of McLeod and Li (1983) <doi:10.1111/j.1467-9892.1983.tb00373.x>, Tsay (1986) <doi:10.1093/biomet/73.2.461> and Brock, Dechert, Scheinkman and LeBaron (1996) <doi:10.1080/07474939608800353>; spectral analysis; and forecast accuracy measures with the Diebold and Mariano (1995) <doi:10.10 [...truncated...]
License: GPL-3
URL: https://github.com/djpedregal/tsexplorer
BugReports: https://github.com/djpedregal/tsexplorer/issues
Encoding: UTF-8
LazyData: true
Depends: R (>= 4.1.0)
Imports: graphics, grDevices, stats, utils
Suggests: shiny, tcltk, testthat (>= 3.0.0), jsonlite, tseries, urca, xts, zoo
NeedsCompilation: no
Packaged: 2026-10-13 08:10:03 UTC; diego.pedregal
Author: Diego J. Pedregal [aut, cre, cph], Ludwig Kanzler [ctb]
Maintainer: Diego J. Pedregal <diego.pedregal@uclm.es>
Repository: CRAN
Date/Publication: 2026-10-21 17:50:02 UTC

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New package survHC with initial version 0.1.0
Package: survHC
Title: Higher Criticism Tests for Non-Proportional Hazard Deviations
Version: 0.1.0
Description: Implements omnibus tests for comparing two right-censored survival samples that are powerful against sparse departures from equal hazards, where the hazard difference is concentrated in a small and a priori unknown subset of the follow-up. Exact hypergeometric p-values are computed for each time interval and aggregated with the Higher Criticism statistic of Donoho and Jin (2004) <doi:10.1214/009053604000000265>, or alternatively with the Berk-Jones, Fisher or minimum-p statistics. Global p-values are obtained by permuting group labels, and the intervals driving a detection can be recovered for diagnostic plotting. Tests accept either two samples as vectors or the usual survival formula. The method is described in Kipnis, Galili and Yakhini (2026) <doi:10.1093/biomet/asaf075>, and the companion application note is Kipnis, Galili and Yakhini (2026) <doi:10.48550/arXiv.2610.07268>.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 3.5.0)
Imports: stats, graphics
Suggests: survival
URL: https://github.com/alonkipnis/lifelines-hc/tree/main/R-package/survHC
BugReports: https://github.com/alonkipnis/lifelines-hc/issues
NeedsCompilation: no
Packaged: 2026-10-12 19:43:22 UTC; kipnisal
Author: Alon Kipnis [aut, cre], Ben Galili [aut], Zohar Yakhini [aut]
Maintainer: Alon Kipnis <alonkipnis@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-21 17:20:02 UTC

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New package publishTC with initial version 0.2.3
Package: publishTC
Title: Tools to Help to Publish the Trend-Cycle Component
Version: 0.2.3
Description: Tools to facilitate the computation of the trend-cycle component of time series. In particular, the computation can be performed using: the Cascade Linear Filter ('CLF', Dagum and Luati, 2008), classical Henderson symmetric filters with surrogate Musgrave asymmetric filters, local parameterizations of Musgrave filters (Quartier-la-Tente, 2024), and robust extensions taking into account additive outliers and level shifts (Quartier-la-Tente, 2025). Computes confidence intervals and provides specialized plotting functions for publication.
LazyData: true
Depends: R (>= 4.1.0)
Imports: rJava, rjd3filters (>= 2.4.0), rjd3x13 (>= 3.3.0), ggplot2, zoo, rjd3jars (>= 0.0.5)
URL: https://github.com/AQLT/publishTC, https://aqlt.github.io/publishTC/
BugReports: https://github.com/AQLT/publishTC/issues
SystemRequirements: Java (>= 17)
License: EUPL
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-10-12 20:08:27 UTC; alainquartierlatente
Author: Alain Quartier-la-Tente [aut, cre, cph]
Maintainer: Alain Quartier-la-Tente <alain.quartier@yahoo.fr>
Repository: CRAN
Date/Publication: 2026-10-21 17:30:02 UTC

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New package powerutilities with initial version 0.7.1
Package: powerutilities
Title: Power Analysis for Linear and Generalized Linear Mixed Models
Description: Prospective power analysis and design planning using the "plug-in" approach described by Piepho et al. (2022) <doi:10.1017/S0021859622000466> and Stroup, Ptukhina and Garai (2024) <doi:10.1201/9780429092060-24>. Expected treatment means and the proposed experimental design are encoded in an artificial data set, and a model is "fit" to it with random effect variances, correlations and residual dispersion fixed at user-specified values rather than being estimated. The resulting standard errors are used to compute the power of F-tests and user-defined contrasts, as well as Type S (sign) and Type M (magnitude) error rates (Gelman and Carlin, 2014 <doi:10.1177/1745691614551642>). Models are fit with 'glmmTMB', so the approach accommodates non-normal responses, heteroscedasticity, nested and crossed random effects, correlated random slopes, and structured covariances such as AR(1) and spatial correlation. Helper functions convert standard deviations and correlations into th [...truncated...]
Version: 0.7.1
Depends: R (>= 4.1.0)
Imports: dplyr, emmeans, glmmTMB (>= 1.1.14), pbkrtest, reformulas,retrodesign, rlang
Suggests: agridat, knitr, rmarkdown, testthat (>= 3.0.0), tidyr
License: BSD_3_clause + file LICENSE
URL: https://github.com/SimonShamusRiley/powerutilities/tree/main
BugReports: https://github.com/SimonShamusRiley/powerutilities/issues
Encoding: UTF-8
VignetteBuilder: knitr
LazyData: true
NeedsCompilation: no
Packaged: 2026-10-13 07:40:02 UTC; Simon
Author: Simon Riley [aut, cre]
Maintainer: Simon Riley <ssriley@protonmail.com>
Repository: CRAN
Date/Publication: 2026-10-21 17:50:09 UTC

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New package DetectOutlier with initial version 0.1.1
Package: DetectOutlier
Title: Detect Outliers in Data Frames and Export Results
Version: 0.1.1
Maintainer: Prakash Kumar <prakash289111@gmail.com>
Description: Identifies potential outliers in numeric columns of a data frame using the interquartile range (IQR), defined as the difference between the third and first quartiles. Values below the first quartile minus 1.5 times the IQR or above the third quartile plus 1.5 times the IQR are flagged as potential outliers. The package can export rows containing outliers to comma-separated values (CSV) files and create 'Excel' workbooks with outlier values highlighted and a summary of outlier counts.
Depends: R (>= 4.0)
Imports: openxlsx
License: GPL-3
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-10-13 04:36:59 UTC; iasri
Author: Prakash Kumar [aut, cre], Himadri Sekhar Roy [aut], Ranjit Kumar Paul [aut], Md. Yeasin [aut], Paritosh Kumar ICAR-NIASM [aut], Amrit Kumar Paul [aut]
Repository: CRAN
Date/Publication: 2026-10-21 17:30:09 UTC

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New package convertxlsform with initial version 0.3.0
Package: convertxlsform
Title: Convert an 'XLSForm' to a 'Word' or PDF Document
Version: 0.3.0
Description: Converts 'XLSForm' questionnaires, as used by 'Open Data Kit' ('ODK') and 'KoboToolbox', into formatted paper versions for interviewing and review. See <https://xlsform.org> for the 'XLSForm' standard. Output is a 'Word' document ('.docx') or, optionally, a PDF produced from that 'Word' document with 'LibreOffice'. Supports multilingual forms, nested question numbering, skip logic display, and question and choice media.
License: MIT + file LICENSE
URL: https://github.com/masud90/convertxlsform
BugReports: https://github.com/masud90/convertxlsform/issues
Encoding: UTF-8
Language: en-US
Depends: R (>= 4.1)
Imports: cli, flextable (>= 0.9.5), magrittr, officer (>= 0.6.9), readxl, rlang, stats, tools, utils, zip
Suggests: doconv, knitr, rmarkdown, testthat (>= 3.0.0), withr, writexl
SystemRequirements: 'LibreOffice' (optional, for PDF output)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-10-13 07:24:37 UTC; masud
Author: Masud Rahman [aut, cre, cph]
Maintainer: Masud Rahman <write2masud+convertxlsform@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-21 17:40:18 UTC

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New package zinbcdpmm with initial version 0.1.0
Package: zinbcdpmm
Title: Bayesian ZINB-Ordinal Joint Model with CDPMM Random Effects
Version: 0.1.0
Description: Fits a Bayesian joint model for longitudinal zero-inflated negative binomial (ZINB) and ordinal outcomes with shared random effects under a centered Dirichlet process mixture model (CDPMM) prior. Provides a blocked Gibbs sampler with Polya-Gamma (PG) and Chinese restaurant table data augmentation, plus helpers for simulation and posterior summaries based on the deviance information criterion (DIC), the widely applicable information criterion (WAIC) and the leave-one-out information criterion (LOOIC). The PG augmentation follows Polson, Scott and Windle (2013) <doi:10.1080/01621459.2013.829001>, the zero-inflated negative binomial construction follows Neelon (2019) <doi:10.1214/18-BA1132>, and the centered Dirichlet process mixture prior follows Tang, Tang and Pan (2014) <doi:10.1016/j.csda.2014.02.015>.
License: MIT + file LICENSE
URL: https://github.com/Liang-ShuQing/zinb-ordinal-cdpmm-code
BugReports: https://github.com/Liang-ShuQing/zinb-ordinal-cdpmm-code/issues
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: BayesLogit, mvtnorm, MCMCpack, truncnorm, loo, stats
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-10-12 08:00:56 UTC; lenovo
Author: Shuqing Liang [aut, cre], Jiang Du [aut]
Maintainer: Shuqing Liang <lsq19853500795@163.com>
Repository: CRAN
Date/Publication: 2026-10-21 16:40:02 UTC

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New package rjd3highfreq with initial version 3.0.1
Package: rjd3highfreq
Title: Seasonal Adjustment of High Frequency Data with 'JDemetra+ 3.x'
Version: 3.0.1
Description: R interface to 'JDemetra+ 3.x' (<https://github.com/jdemetra>), the time series analysis software. It provides functions for seasonal adjustment of higher-frequency data, including those with multiple or non-integer periodicities. It includes pre-adjustment via the extended airline model and several seasonal decomposition methods: extended airline model based decomposition, extended X-11, and augmented STL.
Depends: R (>= 4.1.0)
Imports: rJava (>= 1.0-6), rjd3toolkit (>= 3.7.1), rjd3xjars (>= 0.1.0)
SystemRequirements: Java (>= 21)
License: EUPL-1.2
URL: https://github.com/rjdverse/rjd3highfreq/, https://rjdverse.github.io/rjd3highfreq/
Suggests: knitr, rmarkdown, testthat
BugReports: https://github.com/rjdverse/rjd3highfreq/issues
VignetteBuilder: knitr
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-10-12 05:07:16 UTC; s3504do
Author: Jean Palate [aut], Daniel Ollech [cre, ctb], Christiane Hofer [ctb], Witthohn Thomas [ctb], Lea Hengen [ctb], Martin Stefan [ctb], Alessandro Piovani [ctb], Tanguy Barthelemy [ctb, art], Karsten Webel [ctb]
Maintainer: Daniel Ollech <daniel.ollech@bundesbank.de>
Repository: CRAN
Date/Publication: 2026-10-21 16:10:02 UTC

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New package openstudyval with initial version 0.1.1
Package: openstudyval
Title: Open Validator for FDA Study-Data Submissions
Version: 0.1.1
Description: Validates clinical and nonclinical study-data packages against publicly described FDA technical-rejection criteria, SAS XPORT constraints from the Study Data Technical Conformance Guide, and an extensible catalog of SDTM, SEND, and ADaM structural conformance checks. Reads a study folder of CSV, RDS, or (when the suggested package haven is installed) SAS v5/v8 transport files, optionally checks define.xml, and writes a submission-style HTML and CSV validation report. This package is an independent open-source implementation. It is not affiliated with, endorsed by, or a copy of Pinnacle 21, Certara, or the FDA.
License: MIT + file LICENSE
URL: https://github.com/shekharchalwadigrepo-hub/openstudyval
BugReports: https://github.com/shekharchalwadigrepo-hub/openstudyval/issues
Encoding: UTF-8
Language: en-US
Depends: R (>= 4.1.0)
Imports: stats, tools, utils
Suggests: haven, xml2, knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-10-12 10:04:38 UTC; skrch
Author: Shekhar Eranna Chalwadi [aut, cre]
Maintainer: Shekhar Eranna Chalwadi <skrchalwadicg@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-21 16:30:02 UTC

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New package geopt with initial version 0.1.0
Package: geopt
Title: Tools to Access and Map Spatial Datasets of Portugal
Version: 0.1.0
Description: Tools to download, process, and visualize official spatial datasets for Portugal. Get administrative boundaries at all levels and other geographic data ready for mapping. Data from Statistics Portugal (INE), for example retrieved with the 'ineptr2' package, can be joined to the boundaries by place name or code, including names from earlier boundary reforms.
License: MIT + file LICENSE
URL: https://c-matos.github.io/geopt/, https://github.com/c-matos/geopt
BugReports: https://github.com/c-matos/geopt/issues
Encoding: UTF-8
LazyData: true
Depends: R (>= 4.1.0)
Imports: R6, sf, httr2 (>= 1.0.0), geojsonsf, digest
Suggests: rmapshaper, stringdist, ggplot2, tmap, echarts4r, htmlwidgets, dplyr, plotly, knitr, rmarkdown, testthat (>= 3.0.0), withr
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-10-12 12:18:49 UTC; CM
Author: Carlos Matos [aut, cre, cph]
Maintainer: Carlos Matos <carlosmdmatos@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-21 16:50:18 UTC

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New package exactcond with initial version 0.2.0
Package: exactcond
Title: Exact Conditional Reference Distributions for Tables and Selected Linear Models
Version: 0.2.0
Description: Reference distributions that are exact at every sample size, obtained by conditioning on a statistic sufficient for the nuisance parameter rather than by appealing to an asymptotic approximation. Two forms of conditioning are supplied. For a two-way table the row and column totals are sufficient for the marginal parameters, so conditioning on both margins leaves the Fisher-Yates law, sampled here exactly by random permutation of the column labels; statistics include Goodman's linear-by-linear association and, for nominal rows against an ordinal column, the dispersion of the row mean scores, whose components are the group contrasts themselves. A two-table form conditions further on the total score to cancel a common association parameter, giving a nuisance-free test that two tables share it. For a linear model under a null in which the tested structure is absent, a statistic invariant to the coefficients and the error scale depends on the data only through the residual direction, which [...truncated...]
URL: https://github.com/mtloots/exactcond
BugReports: https://github.com/mtloots/exactcond/issues
License: GPL-3
Encoding: UTF-8
Imports: stats
NeedsCompilation: yes
Suggests: testthat (>= 3.0.0)
Packaged: 2026-10-12 08:11:04 UTC; home
Author: M. Theodor Loots [aut, cre]
Maintainer: M. Theodor Loots <theo.loots@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-21 16:30:14 UTC

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New package anotherSAS7bdat with initial version 0.0.7
Package: anotherSAS7bdat
Title: Read 'SAS' Data in Chunks and Convert to 'Parquet'
Version: 0.0.7
Description: Reads 'SAS' 'sas7bdat' files through a persistent native reader. Processes configurable chunks without reopening the input or restarting the parser between chunks. Supports uncompressed, run-length encoded, and Ross Data Compression data through the bundled 'ReadStat' library. Also streams native decoded batches directly to 'Parquet' through the 'Arrow' C Data Interface and the optional 'arrow' package, without constructing R data frames.
License: MIT + file LICENSE
URL: https://github.com/Fred-Wu/anotherSAS7bdat
BugReports: https://github.com/Fred-Wu/anotherSAS7bdat/issues
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: Rcpp, hms, utils
LinkingTo: Rcpp
Suggests: testthat (>= 3.1.7), haven, arrow (>= 14.0.0)
SystemRequirements: C++17, POSIX threads, iconv
NeedsCompilation: yes
Packaged: 2026-10-12 13:21:47 UTC; 60168126
Author: Jianyun Wu [aut, cre], Evan Miller [aut, cph]
Maintainer: Jianyun Wu <jianyun.fred.wu@hotmail.com>
Repository: CRAN
Date/Publication: 2026-10-21 16:50:30 UTC

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New package taruwind with initial version 0.1.1
Package: taruwind
Title: Reduced-Mode Terrain and Surface Wind Downscaling
Version: 0.1.1
Description: Constructs reusable local wind responses using a neutral terrain-following reduced-vertical-mode adjustment and exact raster-ray integration of finite-fetch surface memory. Explicit metric-grid inputs separate terrain, target aerodynamic roughness and the effective source profile. Prepared responses can be applied to wind-component time series without target-site wind calibration. This diagnostic approximation does not resolve turbulence or guarantee conservation of the final field.
License: MIT + file LICENSE
Copyright: See inst/COPYRIGHTS for bundled third-party components.
Encoding: UTF-8
Depends: R (>= 4.2.0)
Imports: Rcpp, tibble, curl, jsonlite, parallel
LinkingTo: Rcpp
Suggests: testthat (>= 3.0.0), terra, Rarr, lutz, ncdf4
SystemRequirements: C++17
NeedsCompilation: yes
Packaged: 2026-10-11 07:54:33 UTC; cemozen
Author: Cem Oezen [aut, cre], Martin Reinecke [ctb] , Peter Bell [ctb, cph] , Matteo Frigo [ctb, cph] , Tan Ping Liang [ctb, cph] , Cris Luengo [ctb, cph] , Max-Planck-Society [cph] , Massachusetts Institute of Technology [cph]
Maintainer: Cem Oezen <ozenc@itu.edu.tr>
Repository: CRAN
Date/Publication: 2026-10-21 15:10:02 UTC

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New package ssurvdr with initial version 0.1.0
Package: ssurvdr
Title: Sparse Survival Dimension Reduction for High-Dimensional Censored Data
Version: 0.1.0
Description: Implements sparse survival sufficient dimension reduction methods for high-dimensional censored data, including covariance-stabilised SAVE, Maximum Entropy Covariance estimation, information-complexity-guided variable weighting, dual-space high-dimensional SAVE computation, row-wise post-estimation sparsification paths, and Cox proportional hazards model selection.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: stats, MASS, survival
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
URL: https://github.com/ilovemaths/ssurvdr
BugReports: https://github.com/ilovemaths/ssurvdr/issues
NeedsCompilation: no
Packaged: 2026-10-11 19:06:28 UTC; DR OLOREDE
Author: Kabir Opeyemi Olorede [aut, cre]
Maintainer: Kabir Opeyemi Olorede <kabir.olorede@kwasu.edu.ng>
Repository: CRAN
Date/Publication: 2026-10-21 15:50:01 UTC

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New package metrictrails with initial version 1.0.0
Package: metrictrails
Title: Processing of GNSS Streams from Sports Watches
Version: 1.0.0
Description: Tools to read, clean and standardise GNSS (Global Navigation Satellite System) streams recorded by sports watches and similar devices, with a focus on trail and mountain running. The pipeline reads GPX files, applies a naming convention, sanitises coordinates (Kalman, LOESS, Gaussian kernel or Savitzky-Golay smoothing, and red flags for implausible readings), resamples the trajectory to a uniform spatial resolution derived from the Nyquist criterion, and replaces elevation with values from a Digital Elevation Model. Derived measures include speed, slope, elevation gain and kilometre-effort, Tobler hiking function parameters fitted by quantile regression, comparison between streams, detection of passes along a route and map matching to a known reference trail by dynamic programming. Methods follow Sanchez and Villena (2020) <doi:10.1177/1754337120918975>, Sanchez et al. (2024) <doi:10.1109/ICECET61485.2024.10698606>, Sanchez et al. (2025) <doi:10.1177/17543371251341660> [...truncated...]
URL: https://github.com/raimun2/metrictrails
BugReports: https://github.com/raimun2/metrictrails/issues
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Depends: R (>= 4.1)
Imports: magrittr, sf, stats, terra, tibble, utils
Suggests: curl, knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-10-11 10:28:13 UTC; raimu
Author: Raimundo Sanchez [aut, cre]
Maintainer: Raimundo Sanchez <raimundosanchezu@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-21 15:20:02 UTC

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