CRANberries

Thu, 11 Jun 2026

New package tabular with initial version 0.1.0
Package: tabular
Title: Render Tables and Listings for Clinical Submissions
Version: 0.1.0
Description: Render clinical submission tables and listings to 'RTF', 'LaTeX', 'HTML', 'PDF', and 'DOCX' from pre-summarised data frames, with no external 'Java' or 'SAS' dependency. Features include decimal alignment via font metrics, multi-level column headers with passthrough leaves, predicate-targeted cell styling, footnotes, and group-aware pagination. Built for Clinical Data Interchange Standards Consortium (CDISC) Analysis Data Model (ADaM) workflows and regulatory submissions to agencies such as the Food and Drug Administration (FDA), European Medicines Agency (EMA), and Pharmaceuticals and Medical Devices Agency (PMDA).
License: MIT + file LICENSE
URL: https://vthanik.github.io/tabular/, https://github.com/vthanik/tabular
BugReports: https://github.com/vthanik/tabular/issues
Encoding: UTF-8
Depends: R (>= 4.3.0)
Imports: S7, cli, commonmark, rlang, xml2
Suggests: testthat (>= 3.0.0), withr, digest, ggplot2, htmltools, knitr, quarto, pkgdown, rstudioapi, systemfonts, tibble, tinytex, webshot2, yaml
VignetteBuilder: quarto
SystemRequirements: Quarto command line tool (<https://github.com/quarto-dev/quarto-cli>), needed only to build the package vignettes.
LazyData: true
NeedsCompilation: no
Packaged: 2026-06-05 20:23:01 UTC; vignesh
Author: Vignesh Thanikachalam [aut, cre, cph]
Maintainer: Vignesh Thanikachalam <about.vignesh@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-11 12:30:02 UTC

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New package ShinyBlock with initial version 0.1.3
Package: ShinyBlock
Title: Multi-Protocol Blockchain Simulator and Enterprise Ledger Framework
Version: 0.1.3
Maintainer: Isaac Osei <ikemillar65@gmail.com>
Description: An interactive framework for simulating blockchain protocols using a hybrid 'R-Shiny' and 'Python' architecture. The package provides tools to visualize peer-to-peer network maps, manage supply chain logistics on-chain, and execute cross-border settlements via smart contract logic. It leverages the 'reticulate' package to perform standardized cryptographic operations, including 'SHA-256' hashing, 'Merkle' Tree construction, and 'ECDSA' (Elliptic Curve Digital Signature Algorithm) key generation. This tool is designed for pedagogical demonstration and rapid prototyping of distributed ledger requirements.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: shiny, reticulate, reactable, networkD3, bslib, jsonlite
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
SystemRequirements: Python (>= 3.7), ecdsa (Python package)
VignetteBuilder: knitr
URL: https://github.com/ikemillar/ShinyBlock
BugReports: https://github.com/ikemillar/ShinyBlock/issues
NeedsCompilation: no
Packaged: 2026-06-05 17:54:07 UTC; isaacosei
Author: Isaac Osei [aut, cre], Yamini Alakunta [aut]
Repository: CRAN
Date/Publication: 2026-06-11 12:10:18 UTC

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New package punycoder with initial version 1.0.0
Package: punycoder
Title: Unicode and Punycode Domain Name Processing
Version: 1.0.0
Description: High-performance Unicode and Punycode encoding/decoding for internationalized domain names. Provides RFC 3492 compliant conversion functions with a focus on URL processing and data analysis workflows. Addresses limitations in existing R packages for handling international domain names in web scraping and URL parsing applications.
Depends: R (>= 3.5.0)
Imports: Rcpp (>= 1.0.0)
LinkingTo: Rcpp
SystemRequirements: GNU libidn2 (optional, for native punycode backend)
License: MIT + file LICENSE
URL: https://github.com/bart-turczynski/punycoder
BugReports: https://github.com/bart-turczynski/punycoder/issues
Encoding: UTF-8
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2026-06-05 18:13:57 UTC; bartturczynski
Author: Bart Turczynski [aut, cre]
Maintainer: Bart Turczynski <bartek+punycoder@turczynski.pl>
Repository: CRAN
Date/Publication: 2026-06-11 12:20:02 UTC

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New package impower133 with initial version 1.0.0
Package: impower133
Title: Reproduce IMpower133 Clinical Trial Results
Version: 1.0.0
Description: Provides functions to simulate baseline characteristics, reconstruct overall survival data from published Kaplan-Meier curves, and generate publication-ready tables and forest plots reproducing the IMpower133 clinical trial results (Horn et al., 2018, <doi:10.1056/NEJMoa1809064>). The IPD reconstruction method is based on Liu et al.(2021, <doi:10.1186/s12874-021-01308-8>).
License: MIT + file LICENSE
Encoding: UTF-8
Imports: dplyr, survival, survminer, gt, forestplot, IPDfromKM, ggplot2, stats, utils, grid
SystemRequirements: GNU make
Suggests: testthat (>= 3.0.0)
URL: https://github.com/fanfande131/impower133
BugReports: https://github.com/fanfande131/impower133/issues
NeedsCompilation: no
Packaged: 2026-06-05 18:10:45 UTC; 总行是只煤球
Author: Lu Huang [aut, cre], Wenkai Nie [aut], Qingyang Jiang [aut], Qinxin Chen [aut]
Maintainer: Lu Huang <2998785392@qq.com>
Repository: CRAN
Date/Publication: 2026-06-11 12:20:07 UTC

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New package tutorizeR with initial version 0.4.5
Package: tutorizeR
Title: Convert R Markdown or Quarto Content into Interactive Tutorials
Version: 0.4.5
Author: Aurelien Nicosia [aut, cre]
Maintainer: Aurelien Nicosia <aurelien.nicosia@mat.ulaval.ca>
Description: Helps teachers convert existing '.Rmd' and '.qmd' teaching material into interactive tutorials for 'learnr' or 'quarto-live'. Conversion preserves narrative text, setup chunks, and major chunk options, supports teacher tags, and provides explicit validation and conversion reports. Output conventions follow 'learnr' as described by Aden-Buie et al. (2025) <doi:10.32614/CRAN.package.learnr>, 'quarto-live' as described by Stagg (2024) <https://tidyverse.org/blog/2024/10/quarto-live-0-1-1/>, and R Markdown as described by Xie, Allaire and Grolemund (2018, ISBN:9781138359338).
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.0)
Imports: cli, jsonlite, lifecycle, rlang, rmarkdown, rstudioapi, yaml
Suggests: commonmark, covr, dplyr, ggplot2, knitr, learnr, lintr, miniUI, readr, shiny, testthat (>= 3.0.0)
VignetteBuilder: knitr
URL: https://github.com/AurelienNicosiaULaval/tutorizeR
BugReports: https://github.com/AurelienNicosiaULaval/tutorizeR/issues
NeedsCompilation: no
Packaged: 2026-06-05 15:26:09 UTC; aureliennicosia
Repository: CRAN
Date/Publication: 2026-06-11 11:40:02 UTC

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New package sysreqr with initial version 0.1.0
Package: sysreqr
Title: Preflight Checks for 'R' Package System Requirements
Version: 0.1.0
Description: Helps users on 'Linux' (and, where applicable, 'macOS') find the system packages they need before installing 'R' packages from source. Queries maintained system requirement sources, reports missing system packages, and generates installation commands, 'Dockerfile' snippets, 'GitHub Actions' steps, administrator request templates, and diagnostic reports from failed installation logs.
License: GPL-3
URL: https://github.com/choxos/sysreqR
BugReports: https://github.com/choxos/sysreqR/issues
Depends: R (>= 4.1)
Suggests: knitr, rmarkdown, testthat (>= 3.0.0), withr
VignetteBuilder: knitr
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-06-05 16:08:45 UTC; choxos
Author: Ahmad Sofi-Mahmudi [aut, cre]
Maintainer: Ahmad Sofi-Mahmudi <a.sofimahmudi@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-11 11:50:02 UTC

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New package rtrees with initial version 2.0.2
Package: rtrees
Title: Deriving Phylogenies from Synthesis Trees
Version: 2.0.2
Description: Provides tools to derive species-level phylogenies from large synthesis mega-trees for a wide range of taxonomic groups, including plants, birds, mammals, amphibians, reptiles, fish, bees, butterflies, and sharks. When a queried species is absent from the mega-tree, it is grafted onto the tree using one of two placement strategies: attachment at the basal node of the most closely related genus or family ('at_basal_node'), or random attachment below that basal node with probability proportional to branch length ('random_below_basal'). See Li (2023) <doi:10.1111/ecog.06643> for details. Multiple species from a genus not represented in the mega-tree are placed as a polytomy to preserve clade coherence. The package interfaces with the 'megatrees' data package, which bundles or downloads on demand curated mega-trees. Users can also provide their own mega-trees.
License: GPL-3
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.5.0)
Imports: ape, tidytree, dplyr, tibble, utils, castor, furrr, future, megatrees (>= 0.1.3), fastmatch, data.table, Rcpp
LinkingTo: Rcpp
Suggests: knitr, rmarkdown, testthat, piggyback, R.rsp, ggplot2
URL: https://daijiang.github.io/rtrees/
VignetteBuilder: knitr, R.rsp
NeedsCompilation: yes
Packaged: 2026-06-05 15:40:11 UTC; dli
Author: Daijiang Li [aut, cre]
Maintainer: Daijiang Li <daijianglee@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-11 11:40:07 UTC

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New package pvarife with initial version 0.1.1
Package: pvarife
Version: 0.1.1
Title: Panel VAR Models with Interactive Fixed Effects
Description: Implements the estimator of Tugan (2021) <doi:10.1093/ectj/utaa021> for panel vector autoregression (VAR) models with interactive fixed effects. Provides joint estimation of VAR coefficients, latent common factors, and factor loadings via an iterative algorithm that alternates between principal component estimation of the factors and least squares estimation of the VAR coefficients, following the approach of Bai (2009). Supports impulse response functions under recursive (Cholesky) identification, parametric confidence bands from the joint asymptotic distribution of the estimator (Theorem 2.3), and a classical residual bootstrap for robustness checks.
License: GPL-3
Encoding: UTF-8
LazyData: true
Depends: R (>= 4.1.0)
Imports: stats, mvtnorm, ggplot2, rlang
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
URL: https://github.com/Rickchen0910/pvarife
BugReports: https://github.com/Rickchen0910/pvarife/issues
NeedsCompilation: no
Packaged: 2026-06-05 17:01:21 UTC; apple
Author: Binzhi Chen [aut, cre]
Maintainer: Binzhi Chen <Binzhi.Chen9@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-11 12:00:02 UTC

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New package myIO with initial version 1.2.0
Package: myIO
Title: Interactive Data Visualizations Using 'd3.js'
Version: 1.2.0
Description: Create interactive 'd3.js' visualizations from R with built-in statistical transforms. Computes confidence intervals, regression fits, LOESS smoothing, moving averages, error bars, and uncertainty visualizations (quantile dot plots and fan charts) in R and renders them as composable chart layers via 'htmlwidgets'. Supports 36 chart types including boxplots, violin plots, Q-Q diagnostic plots, calendar heatmaps, survival curves, and group comparisons with pairwise significance testing. Also provides a machine-readable chart specification schema with validators so that large language model agents can author and verify charts. Works in 'RStudio', 'Shiny', and 'R Markdown'.
License: MIT + file LICENSE
URL: https://mortonanalytics.github.io/myIO/, https://github.com/mortonanalytics/myIO
BugReports: https://github.com/mortonanalytics/myIO/issues
Depends: R (>= 4.1.0)
Encoding: UTF-8
Language: en-US
Suggests: testthat (>= 3.0.0), knitr, rmarkdown, pkgdown, shiny, crosstalk (>= 1.2.0), dplyr, DT, reactable, htmltools, arrow, base64enc, cli, curl, DBI, duckdb, openssl, later, mockery, withr
VignetteBuilder: knitr
Imports: htmlwidgets, jsonlite, stats
NeedsCompilation: no
Packaged: 2026-06-05 16:01:05 UTC; ryanemorton
Author: Ryan Morton [aut, cre, cph], Mike Bostock [cph] , James Hall [cph] , yWorks GmbH [cph]
Maintainer: Ryan Morton <morton@myma.us>
Repository: CRAN
Date/Publication: 2026-06-11 11:50:08 UTC

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Wed, 10 Jun 2026

New package mums2 with initial version 0.1.0
Package: mums2
Title: Microbial Ecology by Tandem Mass Spectrometry
Version: 0.1.0
Description: Tools that researchers can use to analyze untargeted metabolomics data generated using tandem mass spectroscopy from microbial communities. The overall approach taken to analyze metabolomics data parallels that used to analyze microbial communities using 16S rRNA gene sequencing data. Thus, we have a number of methods a user is able to use to generate data. Firstly, users can import Mass Spectrometry 1(MS1) data and filter it. Users are then able to match Mass Spectrometry 2(MS2) data to the filtered (or unfiltered) MS1 data. With the matched data users are able to cluster it, annotate it, predict de novo chemical formulas and calculate alpha and beta diversity. For chemical formula predictions, this was the method used; "Towards de novo identification of metabolites by analyzing tandem mass spectra" (Sebastian Böcker, Florian Rasche (2008) <doi:10.1093/bioinformatics/btn270>). The similarity/dissimilarity calculations we used to cluster our data together was: "Spectral entropy o [...truncated...]
License: GPL (>= 3)
Encoding: UTF-8
URL: https://github.com/mums2/mums2, https://www.mums2.org/mums2/
BugReports: https://github.com/mums2/mums2/issues
LinkingTo: sitmo, Rcpp, RcppThread, testthat, RcppProgress
Imports: clustur, Rcpp, data.table, mpactr, utils, stats, parallel, xml2,
Suggests: knitr, rmarkdown, testthat (>= 3.0.0), tidyverse, networkD3, mzR
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2026-06-04 21:26:57 UTC; grejoh
Author: Allison Mason [aut] , Gregory Johnson [aut] , Patrick Schloss [aut, cre] , Anton Pervukhin [ctb, cph], Florian Rasche [ctb, cph], Henner Sudek [ctb, cph], Marcel Martin [ctb, cph], Yuanyue Li [ctb, cph]
Maintainer: Patrick Schloss <pschloss@umich.edu>
Depends: R (>= 4.1.0)
Repository: CRAN
Date/Publication: 2026-06-10 08:10:02 UTC

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New package fluffy with initial version 1.0.0
Package: fluffy
Title: Schema-Based Validation of 'R' Objects with User-Defined Rules
Version: 1.0.0
Description: A schema-based validation framework for 'R' objects using user-defined rules. Provides three 'S7' classes 'Registry', 'Schema', and 'Validator' to manage rules, define list-based schemas, and validate data in a flexible and extensible manner.
License: MIT + file LICENSE
Encoding: UTF-8
Suggests: jsonlite, kableExtra, knitr, lobstr, readr, rmarkdown, stats, testthat (>= 3.0.0), yaml
Imports: methods, S7, utils
URL: https://lj-jenkins.github.io/fluffy/, https://github.com/LJ-Jenkins/fluffy
VignetteBuilder: knitr
BugReports: https://github.com/LJ-Jenkins/fluffy/issues
NeedsCompilation: no
Packaged: 2026-06-05 14:49:04 UTC; lukej
Author: Luke Jenkins [aut, cre, cph]
Maintainer: Luke Jenkins <luke-jenkins-dev@outlook.com>
Repository: CRAN
Date/Publication: 2026-06-10 08:10:09 UTC

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New package exeval with initial version 0.0.1
Package: exeval
Language: en-US
Title: External Evaluation of Population Pharmacokinetic-Pharmacodynamic (popPKPD) Models
Version: 0.0.1
Description: Provides tools to automate external pharmacokinetic model evaluation workflows, including Bayesian forecasting, predictive performance metrics, diagnostic plotting, and automated reporting.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Depends: R (>= 4.1)
Imports: mapbayr, dplyr, ggplot2, ggpubr, mrgsolve (>= 1.0.8), scales, stats, methods, rlang
Suggests: knitr, rmarkdown,
URL: https://github.com/Martin-Umpierrez/exeval
BugReports: https://github.com/Martin-Umpierrez/exeval/issues
NeedsCompilation: no
Packaged: 2026-06-05 15:03:33 UTC; ialvarez
Author: Manuel Ibarra [aut], Martin Umpierrez [aut, cre], Ignacio Alvarez Castro [aut] , Nicolas Schmidt [aut]
Maintainer: Martin Umpierrez <mumpierrez@fq.edu.uy>
Repository: CRAN
Date/Publication: 2026-06-10 08:10:14 UTC

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New package deepImp with initial version 1.1.0
Package: deepImp
Title: Imputation with Deep Learning Methods
Version: 1.1.0
Description: Imputation of mixed-type and compositional data with neural networks. The architecture (number and size of hidden layers, dropout, activation, optimiser) is user-configurable. See Templ (2021) <doi:10.1007/978-3-030-71175-7>.
License: GPL-2
Encoding: UTF-8
LazyData: TRUE
ByteCompile: TRUE
Depends: R (>= 4.1)
Imports: torch, luz, VIM, robCompositions, stats, utils, graphics
Suggests: keras3, knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-06-05 12:07:20 UTC; matthias
Author: Matthias Templ [aut, cre]
Maintainer: Matthias Templ <matthias.templ@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-10 08:10:20 UTC

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New package CircularRegression with initial version 0.5.1
Package: CircularRegression
Title: Circular Regression Models
Version: 0.5.1
Description: Implements regression models for circular response data, including homogeneous angular regression, consensus angular regression, a two-step workflow, selected special-case model wrappers, and a random-intercept extension for clustered circular outcomes. The main methodology follows Rivest et al. (2016) "A General Angular Regression Model for the Analysis of Data on Animal Movement in Ecology" <doi:10.1111/rssc.12124>.
License: GPL-3
Encoding: UTF-8
Language: en-US
LazyData: true
Imports: circular, graphics, stats, utils
Depends: R (>= 3.5.0)
Suggests: ggplot2, gridExtra, knitr, pkgdown, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
URL: https://github.com/AurelienNicosiaULaval/CircularRegression
BugReports: https://github.com/AurelienNicosiaULaval/CircularRegression/issues
NeedsCompilation: no
Packaged: 2026-06-05 15:27:48 UTC; aureliennicosia
Author: Aurelien Nicosia [aut, cre]
Maintainer: Aurelien Nicosia <aurelien.nicosia@mat.ulaval.ca>
Repository: CRAN
Date/Publication: 2026-06-10 08:20:02 UTC

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New package pkgmatch with initial version 0.5.4
Package: pkgmatch
Title: Find R Packages Matching Either Descriptions or Other R Packages
Version: 0.5.4
Description: Find R packages from CRAN, 'rOpenSci', or Bioconductor corpora. Packages can be matched to general text descriptions, to names of installed packages, or to local paths to entire source repositories. The package is used to list the most similar packages for each new submission to the 'rOpenSci' software peer-review program ('rOpenSci' authors, 2026; <doi:10.5281/zenodo.18885936>).
License: MIT + file LICENSE
URL: https://docs.ropensci.org/pkgmatch/, https://github.com/ropensci-review-tools/pkgmatch
BugReports: https://github.com/ropensci-review-tools/pkgmatch/issues
Depends: R (>= 4.1.0)
Imports: brio, checkmate, cli, curl (>= 6.0.0), dplyr, fs, httr2, memoise, piggyback, Rcpp, rvest, tibble, tidyr, tokenizers, treesitter, treesitter.r, vctrs
Suggests: gert, hms, httptest2, jsonlite, pkgbuild, rappdirs, roxygen2, testthat (>= 3.0.0), withr, knitr, rmarkdown
LinkingTo: Rcpp
NeedsCompilation: yes
Encoding: UTF-8
Language: en-GB
VignetteBuilder: knitr
Packaged: 2026-06-05 11:46:25 UTC; smexus
Author: Mark Padgham [aut, cre] , Davis Vaughan [ctb]
Maintainer: Mark Padgham <mark.padgham@email.com>
Repository: CRAN
Date/Publication: 2026-06-10 07:40:02 UTC

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New package hcinfer with initial version 0.1.0
Package: hcinfer
Title: Heteroskedasticity-Consistent Inference for Linear Models
Version: 0.1.0
Description: Computes heteroskedasticity-consistent covariance matrix estimators for ordinary least squares regression models. The published HC0 through HC5m estimators implemented in the package follow White (1980) <doi:10.2307/1912934>, Hinkley (1977) <doi:10.1080/00401706.1977.10489550>, Horn et al. (1975) <doi:10.1080/01621459.1975.10479877>, MacKinnon and White (1985) <doi:10.1016/0304-4076(85)90158-7>, Cribari-Neto (2004) <doi:10.1016/S0167-9473(02)00366-3>, Cribari-Neto and da Silva (2011) <doi:10.1007/s10182-010-0141-2>, Cribari-Neto et al. (2007) <doi:10.1080/03610920601126589>, and Li et al. (2016) <doi:10.1080/00949655.2016.1198906>. The package also includes HCbeta, a new estimator proposed by the package authors. It provides normal Wald tests, confidence intervals, diagnostics, and S3 output for applied inference.
URL: https://prdm0.github.io/hcinfer/, https://github.com/prdm0/hcinfer
BugReports: https://github.com/prdm0/hcinfer/issues
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: cli, ggplot2, purrr, rlang, tibble
Suggests: dplyr, knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
LazyData: true
NeedsCompilation: no
Packaged: 2026-06-05 12:46:39 UTC; prdm0
Author: Pedro Rafael D. Marinho [aut, cre] , Francisco Cribari-Neto [aut] , Marina Oliveira Cunha [aut]
Maintainer: Pedro Rafael D. Marinho <pedro.rafael.marinho@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-10 08:00:02 UTC

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New package dcorBSS with initial version 1.0-0
Package: dcorBSS
Title: Distance-Correlation Based Methods for Blind Source Separation and Dependence Analysis
Version: 1.0-0
Description: Independent component analysis based on distance correlation, including a robust variant using the bowl transformation. The package provides user-facing implementations of distance covariance and distance correlation, including memory-efficient blockwise computations for large data sets. It includes a sequential ICA estimator based on minimizing distance correlation, as well as tools for analyzing serial dependence via distance autocorrelation, dependograms, and permutation-based tests. In addition, it provides functions for testing serial dependence based on distance correlation and the Hilbert–Schmidt independence criterion. The methodology is related to Matteson and Tsay (2017) <doi:10.1080/01621459.2016.1150851> and to the robust framework of Leyder et al. (2026) <doi:10.1007/s11634-026-00674-9>.
License: GPL (>= 3)
Encoding: UTF-8
LinkingTo: Rcpp
Depends: R (>= 4.1.0)
Imports: dccpp, dHSIC, minqa, nloptr, stats, utils, Rcpp
Suggests: energy, JADE, robustbase, knitr, rmarkdown
NeedsCompilation: yes
Author: Sarah Leyder [aut] , Klaus Nordhausen [aut, cre]
Maintainer: Klaus Nordhausen <klausnordhausenR@gmail.com>
VignetteBuilder: knitr
Packaged: 2026-06-04 18:45:44 UTC; nordklau
Repository: CRAN
Date/Publication: 2026-06-10 07:30:09 UTC

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New package clusterindices with initial version 1.0
Package: clusterindices
Title: Cluster Validity Indices
Version: 1.0
Date: 2026-06-05
Author: Michail Tsagris [aut, cre], Nikolaos Kontemeniotis [aut]
Maintainer: Michail Tsagris <mtsagris@uoc.gr>
Depends: R (>= 4.0)
Imports: factoextra, graphics, lowmemtkmeans, Rfast, Rfast2, stats
Description: Numerous indices to choose the optimal number of clusters when performing k-means. Relevant papers include: Tsagris M. and Kontemeniotis N. (2025). Lobachevskii Journal of Mathematics <doi:10.1134/S1995080225613700>. Garcia-Escudero Luis A., Gordaliza Alfonso, Matran Carlos, Mayo-Iscar Agustin. (2008) <doi:10.1214/07-AOS515>.
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2026-06-05 09:13:20 UTC; mtsag
Repository: CRAN
Date/Publication: 2026-06-10 07:40:08 UTC

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Tue, 09 Jun 2026

New package tinydng with initial version 0.1.0-0
Package: tinydng
Title: 'TinyDNG' C++ Header Files
Version: 0.1.0-0
Description: Provides C++ header files for 'TinyDNG', a small header-only library for reading and writing 'DNG' and 'TIFF' files.
License: MIT + file LICENSE
URL: https://github.com/tylermorganwall/tinydng
BugReports: https://github.com/tylermorganwall/tinydng/issues
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-06-05 02:29:35 UTC; tyler
Author: Tyler Morgan-Wall [aut, cre, cph] , Syoyo Fujita [aut, cph]
Maintainer: Tyler Morgan-Wall <tylermw@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-09 16:10:02 UTC

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New package stbimageheaders with initial version 0.1.0
Package: stbimageheaders
Title: 'stb' Image C/C++ Header Files
Version: 0.1.0
Description: Provides image-related C/C++ header files from the 'stb' single-file libraries for image loading, writing, and resizing.
License: MIT + file LICENSE
URL: https://github.com/tylermorganwall/stbimageheaders
BugReports: https://github.com/tylermorganwall/stbimageheaders/issues
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-06-05 02:24:39 UTC; tyler
Author: Tyler Morgan-Wall [aut, cre, cph] , Sean Barrett [aut, cph], Jeff Roberts [aut], Jorge L. Rodriguez [aut]
Maintainer: Tyler Morgan-Wall <tylermw@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-09 16:10:07 UTC

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New package normality with initial version 0.0.1
Package: normality
Title: Tests for Departure from Normality
Version: 0.0.1
Description: A toolkit for assessing data normality using a comprehensive collection of statistical methods. It includes descriptive measures and formal hypothesis tests, such as skewness and kurtosis tests, the Anderson–Darling test, the Shapiro–Wilk test, and the D'Agostino–Pearson K2 omnibus test.
License: MIT + file LICENSE
URL: https://github.com/P10911004-NPUST/normality
BugReports: https://github.com/P10911004-NPUST/normality/issues
Encoding: UTF-8
Depends: R (>= 3.5)
LazyData: true
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-06-05 07:11:20 UTC; ABRC
Author: Joon-Keat Lai [aut, cre, cph]
Maintainer: Joon-Keat Lai <p10911004@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-09 16:10:13 UTC

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New package wbCorr with initial version 0.3.1
Package: wbCorr
Title: Bivariate Within- and Between-Cluster Correlations
Version: 0.3.1
Date: 2026-05-23
Description: Separates supplied variables into within- and between-cluster components and calculates bivariate correlations for each level separately. The centered-score decomposition corresponds to commonly used between- and within-cluster correlations discussed by Tu et al. (2025) <doi:10.1002/sim.10326>. The package is also motivated by the distinction between within- and between-person variation described by Curran and Bauer (2011) <doi:10.1146/annurev.psych.093008.100356> and by Hamaker (2024) <doi:10.1080/00273171.2022.2155930>. The package is intended for longitudinal or otherwise clustered data where researchers need transparent correlation matrices before fitting more complex multilevel models.
License: MIT + file LICENSE
Encoding: UTF-8
Suggests: httr, spelling, testthat (>= 3.0.0)
Imports: methods, writexl
Language: en-US
URL: https://github.com/Pascal-Kueng/wbCorr
BugReports: https://github.com/Pascal-Kueng/wbCorr/issues
NeedsCompilation: no
Packaged: 2026-06-04 22:03:17 UTC; pascalkueng
Author: Pascal Kueng [aut, cre, cph]
Maintainer: Pascal Kueng <pascal.kueng@psychologie.uzh.ch>
Depends: R (>= 3.5.0)
Repository: CRAN
Date/Publication: 2026-06-09 16:00:02 UTC

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New package quak with initial version 0.1.0
Package: quak
Title: Query 'Azure Data Lake Storage Gen2' with 'DuckDB'
Version: 0.1.0
Description: Provides convenience utilities for using 'DuckDB' directly over datasets stored in 'Azure Data Lake Storage Gen2' (ADLS Gen2, 'abfss://'). Opens connections configured for Azure-backed 'Delta Lake' and 'Parquet' data, registers Azure credentials as 'DuckDB' secrets, and supports optional repository mirrors for restricted networks. Integrates well with 'DBI' for SQL workflows and with 'dplyr' and 'dbplyr' for lazy table queries.
URL: https://github.com/pedrobtz/quak
BugReports: https://github.com/pedrobtz/quak/issues
License: MIT + file LICENSE
Encoding: UTF-8
Imports: cli, curl, DBI, duckdb, fs, glue, rlang, tools, utils
Suggests: azr (>= 0.3.4), dbplyr, dplyr, testthat (>= 3.0.0), tibble, withr
NeedsCompilation: no
Packaged: 2026-06-04 20:51:19 UTC; pbtz
Author: Pedro Baltazar [aut, cre, cph]
Maintainer: Pedro Baltazar <pedrobtz@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-09 15:50:02 UTC

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New package qtbi with initial version 0.1.2
Package: qtbi
Title: Quantum Toxic Burden Index
Version: 0.1.2
Description: Compute the Quantum Toxic Burden Index from multi-exposure panels using a fixed quantum-inspired entanglement encoder; method reference (2026) <doi:10.5281/zenodo.20476574>. Provides percentile encoding, optional potency-weighted readout, and synergy diagnostics for environmental mixture burden scores.
License: MIT + file LICENSE
URL: https://github.com/january-msemakweli/qtbi, https://doi.org/10.5281/zenodo.20476574
BugReports: https://github.com/january-msemakweli/qtbi/issues
Encoding: UTF-8
Language: en-US
Depends: R (>= 4.1.0)
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-06-04 16:40:18 UTC; msema
Author: January G. Msemakweli [aut, cre]
Maintainer: January G. Msemakweli <jmsemak1@jh.edu>
Repository: CRAN
Date/Publication: 2026-06-09 15:40:02 UTC

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New package plantmix with initial version 1.0.2
Package: plantmix
Title: Genetic Study of Plant Mixtures
Version: 1.0.2
Maintainer: Timothee Flutre <timothee.flutre@inrae.fr>
Description: Fit linear mixed models dedicated to the genetic study of plant mixtures, such as those based on general and specific mixing abilities (GMA-SMA) as well as direct and social breeding values (DBV-SBV), also known as direct and indirect genetic effects (DGE-IGE). More details in Forst et al (2019, <doi:10.1016/j.fcr.2019.107571>) for GMA-SMA models, and Salomon et al (2026, <doi:10.64898/2026.03.27.714849>) for DBV-SBV models. The package also provides functions to optimize experimental designs, simulate data sets and compute interaction indices.
Depends: R (>= 4.0.0), ggplot2, lme4
Imports: graphics, igraph, MASS, Matrix, methods, Rcpp (>= 1.0.13), stats, TMB (>= 1.9.17), utils
License: AGPL-3
Copyright: INRAE
Encoding: UTF-8
Suggests: breedR, INLA, emmeans, knitr, MM4LMM, rmarkdown, testthat
Additional_repositories: https://famuvie.github.io/breedR, https://inla.r-inla-download.org/R/stable
VignetteBuilder: knitr
LinkingTo: TMB, Rcpp, RcppEigen
NeedsCompilation: yes
Packaged: 2026-06-04 19:04:01 UTC; tflutre
Author: Timothee Flutre [aut, ctb, cre] , INRAE [cph, fnd], Jerome Enjalbert [ctb] , Emma Forst [ctb] , Maxence Remerand [ctb] , Jemay Salomon [ctb]
Repository: CRAN
Date/Publication: 2026-06-09 15:50:07 UTC

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New package ofhsyn with initial version 0.1.1
Package: ofhsyn
Title: Synthetic Our Future Health Data Generator
Version: 0.1.1
Author: Hannah Nicholls [aut, cre]
Maintainer: Hannah Nicholls <h.l.nicholls@qmul.ac.uk>
Description: Generates synthetic Our Future Health cohort datasets for method development, including participant, questionnaire, clinic measurements, outpatient, inpatient, emergency, mortality, primary care medication, and geography outputs. Supports reproducible generation with configurable cohort size and user-defined International Classification of Diseases, Tenth Revision (ICD-10), Office of Population Censuses and Surveys Classification of Interventions and Procedures, version 4 (OPCS-4), and British National Formulary (BNF) code pools.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.2.0)
Imports: methods, utils, stats
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-06-04 15:10:53 UTC; btx925
Repository: CRAN
Date/Publication: 2026-06-09 15:40:08 UTC

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New package harness with initial version 0.1.0
Package: harness
Title: Curated Agentic Harnesses for R Professional Roles
Version: 0.1.0
Description: A bootstrapper that launches a command-line coding agent of the user's choice in a terminal tab pre-configured for a professional R role. Each role is described by a curated harness: a subset of community skills, a system prompt, a folder layout, and quality gates. The package does not run an agent loop and does not call a language model; it discovers the chosen coder binary, generates its configuration, links the curated skills, and opens the terminal. Code written by the agent is run manually by the user, by design, so that every generated script passes through a human audit gate before execution.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.2)
Imports: jsonlite, yaml
Suggests: rstudioapi, testthat (>= 3.0.0), withr
URL: https://github.com/pcbrom/harness
BugReports: https://github.com/pcbrom/harness/issues
NeedsCompilation: no
Packaged: 2026-06-04 16:59:39 UTC; pcbrom
Author: Pedro Carvalho Brom [aut, cre, cph]
Maintainer: Pedro Carvalho Brom <pcbrom@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-09 15:40:13 UTC

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New package evoFE with initial version 0.1.0
Package: evoFE
Title: Evolutionary Feature Engineering
Version: 0.1.0
Description: Automates feature engineering using evolutionary algorithms inspired by genetic programming. Starting from raw input features, the package evolves candidate transformation recipes through selection, crossover, and mutation, evaluating fitness via cross-validation or train/validation splits with gradient-boosted tree models ('LightGBM' or 'XGBoost'). Built-in transformers include arithmetic, logarithmic, and power operations, interaction terms, target encoding, quantile and log-based binning, principal component analysis, truncated singular value decomposition, Uniform Manifold Approximation and Projection (UMAP) dimensionality reduction, and minimum spanning tree (MST) graph-based clustering. The evolutionary search yields an optimised feature recipe that can be applied to new data for prediction. Methods are described in McInnes et al. (2018) <doi:10.21105/joss.00861>, Ke et al. (2017) <https://papers.nips.cc/paper/6907-lightgbm-a-highly-efficient-gradient-boosting-decision-f [...truncated...]
License: MIT + file LICENSE
Encoding: UTF-8
Imports: data.table, lightgbm, xgboost, stats, digest, uwot, quitefastmst, genieclust
Suggests: RhpcBLASctl, testthat, knitr, rmarkdown, lumbermark, deadwood
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-06-04 20:51:19 UTC; vero
Author: Gustavo Pereira [aut, cre]
Maintainer: Gustavo Pereira <tanopereira@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-09 15:50:14 UTC

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New package cox.rvph with initial version 0.1.1
Package: cox.rvph
Title: Remedy the Violation of the Proportional Hazards Assumption of Cox Regression
Version: 0.1.1
Description: Remedying proportional hazards assumption violations of a Cox proportional hazards model using stepwise changepoint and time-varying coefficient methods based on Cox (1972) <doi:10.1111/j.2517-6161.1972.tb00899.x> and Grambsch and Therneau (1994) <doi:10.1093/biomet/81.3.515>.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: survival
Suggests: KMsurv
NeedsCompilation: no
Packaged: 2026-06-05 00:23:45 UTC; user
Author: Hamin Kim [aut, cre]
Maintainer: Hamin Kim <siru9170@naver.com>
Repository: CRAN
Date/Publication: 2026-06-09 16:00:08 UTC

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New package spDBL with initial version 1.0.2
Package: spDBL
Title: Dynamic Bayesian Learning for Spatiotemporal Mechanistic Models
Version: 1.0.2
Description: Provides tools for Bayesian learning of spatiotemporal dynamical mechanistic models. Includes methods for parameter estimation, simulation, and inference using hierarchical and state-space modeling approaches, following Banerjee, Chen, Frankenburg and Zhou (2025) <https://jmlr.org/papers/v26/22-0896.html>.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.0)
LinkingTo: Rcpp, RcppEigen
Imports: Rcpp, matrixsampling, invgamma, deSolve, ReacTran, LaplacesDemon, matrixcalc, mniw, utils, stats, ggpubr, ggplot2, readr, magrittr, rlang, scales
Suggests: testthat (>= 3.0.0), here, knitr, rmarkdown
VignetteBuilder: knitr
LazyData: true
NeedsCompilation: yes
Packaged: 2026-06-04 01:55:41 UTC; xiangchen
Author: Xiang Chen [aut, cre], Sudipto Banerjee [aut]
Maintainer: Xiang Chen <xiangchen@ucla.edu>
Repository: CRAN
Date/Publication: 2026-06-09 07:20:02 UTC

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New package NeutroCODsAnalysis with initial version 0.0.1
Package: NeutroCODsAnalysis
Title: Neutrosophic Analysis Crossover Designs
Version: 0.0.1
Maintainer: Vinaykumar L.N. <vinaymandya123@gmail.com>
Description: Provides methods for Neutrosophic Analysis of Variance (NANOVA) for crossover designs and multi-session designs with direct and residual effects using interval-valued observations. The package computes neutrosophic sums of squares, mean squares, interval-valued F-statistics, significance tests, and multiple comparisons using Least Significant Difference (LSD) procedures. For crisp data, users may enter identical lower and upper response values to obtain classical Analysis of Variance (ANOVA) results. The basic idea of neutrosophic statistics is obtained from Smarandache (2014) <https://fs.unm.edu/NeutrosophicStatistics.pdf>, while the analysis procedures implemented in this package are newly developed.
License: GPL (>= 2)
Encoding: UTF-8
Imports: MASS
NeedsCompilation: no
Packaged: 2026-06-04 04:38:07 UTC; admin
Author: Neethu R.S [aut, ctb], Boyina Devi Priyanka [aut, ctb], Cini Varghese [aut, ctb], Mohd Harun [aut, ctb], Anindita Datta [aut, ctb], Vinaykumar L.N. [aut, cre]
Repository: CRAN
Date/Publication: 2026-06-09 07:20:16 UTC

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New package mimar with initial version 0.8.0
Package: mimar
Title: Compact Multiple Imputation, Assessment, and Reporting
Version: 0.8.0
Author: Imad EL BADISY [aut, cre]
Maintainer: Imad EL BADISY <elbadisyimad@gmail.com>
Description: Provides compact tools for missing-data analysis, including artificial amputation, chained single and multiple imputation, statistical and machine-learning-based imputation methods, diagnostic evaluation, and post-imputation pooling.
License: MIT + file LICENSE
URL: https://github.com/ielbadisy/mimar
BugReports: https://github.com/ielbadisy/mimar/issues
Encoding: UTF-8
Imports: BART, e1071, functionals, gbm, ggplot2, glmnet, missMDA, naivebayes, ranger, rpart, stats, tibble, xgboost
Suggests: testthat (>= 3.0.0), knitr, rmarkdown, pkgload
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-06-03 22:58:35 UTC; imad-el-badisy
Repository: CRAN
Date/Publication: 2026-06-09 07:10:02 UTC

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New package consolidatePacks with initial version 1.0.0
Package: consolidatePacks
Title: Eliminate '@import' by Incorporating Dependencies Directly into the Package
Version: 1.0.0
Date: 2026-06-03
Maintainer: Barry Zeeberg <barryz2013@gmail.com>
Depends: R (>= 4.2.0)
Imports: vprint, stringr, utils, devtools
Description: The purpose of this package is to remove the '@import' dependence of an external package by consolidating the functions into your package. This may be necessary when the '@import' package is decommissioned by CRAN, and you do not want your dependent package to also be decommissioned. The functions in this package recursively retrieve dependencies in the external package. It also performs the other needed bookkeeping, such as retrieving .Rd files in the man subdirectory.
License: GPL (>= 2)
Encoding: UTF-8
VignetteBuilder: knitr
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-06-03 23:13:53 UTC; barryzeeberg
Author: Barry Zeeberg [aut, cre]
Repository: CRAN
Date/Publication: 2026-06-09 07:10:07 UTC

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New package cash with initial version 1.0.2
Package: cash
Version: 1.0.2
Title: Discrete Choice and Competitive Reactions: End-to-End Simulation
Author: Jan H. R. Dressler [aut, cre, cph], Peter Kurz [ths], Winfried J. Steiner [ths]
Maintainer: Jan H. R. Dressler <jhrd13@tu-clausthal.de>
License: GPL (>= 3)
Imports: reshape2, ggplot2, idefix (>= 1.1.0), DoE.base, evd, bayesm, coda, ggridges, foreach, doParallel, parallel, doRNG, Rcpp, arrangements, grDevices, stats, utils
LinkingTo: Rcpp
Encoding: UTF-8
Repository: CRAN
Description: Although discrete choice (choice-based conjoint) analysis has become a widely used technique for the elicitation of consumer preferences and hence a foundation for product design, to the best of our knowledge, there exists neither free and open-source nor commercial software that covers the game-theoretic simulation of competitive reactions among firms based on discrete choice models to improve decision making beyond traditional product (line) optimization. The package does not only provide functions to fill this gap but comprises an entire simulation pipeline including the upstream processes of discrete choice analysis itself. It ranges from preference generation, choice design, design assessment, error and response simulation, through hierarchical Bayesian estimation of mixed logit models as well as convergence and model assessment, to Nash equilibrium computation. Doing so, it partly draws from established packages concerned with discrete choice analysis. While its structure general [...truncated...]
NeedsCompilation: yes
Packaged: 2026-06-04 01:49:13 UTC; jan_d
Date/Publication: 2026-06-09 07:20:11 UTC

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New package NetSurvProx with initial version 1.0.0
Package: NetSurvProx
Title: 'NetSurvProx': Network-Based Survival Analysis via Proximal Methods
Version: 1.0.0
Maintainer: Maura Mecchi <maura.mecchi@unibas.it>
Description: Introduces a novel network-constrained survival analysis framework for variable selection and parameter estimation in penalized survival models with convex penalties. The package extends two classical survival models, the Cox Proportional Hazards (PH) model and the Accelerated Failure Time (AFT) model, by incorporating prior biological knowledge from curated interaction networks (e.g., KEGG) into a double-penalty framework. The first penalty enforces variable selection through a LASSO penalty, while the second preserves gene-gene correlations by incorporating Laplacian-based constraints, ensuring that biologically relevant network structures are maintained. Using censored survival data, the method enables the identification of predictive biomarkers and pathways with potential relevance for target therapies. Model estimation is performed via proximal optimization algorithms combined with cross-validation for reliable tuning. To enhance interpretability, dedicated utility functions are i [...truncated...]
Depends: R (>= 4.3)
Imports: AnnotationDbi, curl, cvTools, dplyr, flexsurv, foreach, ggplot2, ggpubr, glmnet, grDevices, Hmisc, httr, igraph, magic, openxlsx, RColorBrewer, rmarkdown, survAUC, survival, survminer,
Suggests: knitr, org.Hs.eg.db, plotly, scales, sessioninfo, stringr, visNetwork
VignetteBuilder: knitr
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
LazyDataCompression: bzip2
NeedsCompilation: no
Packaged: 2026-06-03 12:02:58 UTC; maura
Author: Maura Mecchi [aut, cre], Antonella Iuliano [aut]
Repository: CRAN
Date/Publication: 2026-06-09 06:50:02 UTC

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Mon, 08 Jun 2026

New package vizClust with initial version 0.1.0
Package: vizClust
Title: Visualization and Exploration of Cluster Transitions
Version: 0.1.0
Description: Provides tools to explore and visualize transitions between clusters in multivariate data. The package generates pseudo-samples by interpolating between cluster medoids, enabling the study of gradual changes in feature space. It also computes k-nearest neighbors (KNN)-based statistics to relate pseudo-samples to real data and summarize variable behavior using mean, median, or standard deviation. Finally, the package offers interactive visualizations of variable trajectories along cluster transitions, including both direct trajectory plots and bootstrap-based interactive plots with confidence intervals to assess variability and uncertainty across the transition path.
License: GPL-3
Encoding: UTF-8
Imports: ggplot2, ggiraph, reshape2, FNN, dplyr, tibble
Suggests: webshot, cluster, webshot2, phenomap
NeedsCompilation: no
Packaged: 2026-06-03 09:31:09 UTC; elsaa
Author: Elsa Arribas [aut, cre], YingHong Chen [ctb], Ferran Reverter [ctb]
Maintainer: Elsa Arribas <elsaarribasg@gmail.com>
Depends: R (>= 4.1.0)
Repository: CRAN
Date/Publication: 2026-06-08 19:40:02 UTC

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New package Uno with initial version 2.7.3
Package: Uno
Title: R Interface to the 'Uno' Nonlinear Optimization Solver
Version: 2.7.3
Description: Bindings to 'Uno' (Unifying Nonlinear Optimization), a C++ solver for smooth nonlinearly constrained optimization. 'Uno' unifies Lagrange-Newton methods, including sequential quadratic programming and interior-point methods, by decomposing them into interacting building blocks (constraint-relaxation, inequality-handling, Hessian, and globalization strategies) that can be freely combined, either through options or through presets that reproduce established solvers such as 'filterSQP' and 'IPOPT'. The framework is described in Vanaret and Leyffer (2024) <doi:10.48550/arXiv.2406.13454>.
License: MIT + file LICENSE
Copyright: file inst/COPYRIGHTS
URL: https://bnaras.github.io/Uno/, https://github.com/bnaras/Uno
BugReports: https://github.com/bnaras/Uno/issues
SystemRequirements: CMake (>= 3.16), C++17, GNU make
Imports: rmumps (>= 5.2.1-41)
LinkingTo: cpp11, rmumps
Suggests: cpp11, tinytest, knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: yes
Encoding: UTF-8
Packaged: 2026-06-03 04:37:30 UTC; naras
Author: Balasubramanian Narasimhan [aut, cre], Charlie Vanaret [aut, cph] , Sven Leyffer [aut, cph] , HiGHS development team [cph] ; see inst/COPYRIGHTS)
Maintainer: Balasubramanian Narasimhan <naras@stanford.edu>
Repository: CRAN
Date/Publication: 2026-06-08 19:20:02 UTC

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New package twinsvm with initial version 0.0.1
Package: twinsvm
Title: Twin Support Vector Machines
Version: 0.0.1
Author: Shamika Tissera [aut, cre]
Maintainer: Shamika Tissera <nimeshshamika@gmail.com>
Description: Provides twin support vector machine classifiers and visualization tools for small to moderate classification problems. Includes one-vs-one multi-class classification and a standard support vector machine baseline for comparison.
License: GPL-3
Encoding: UTF-8
Depends: R (>= 3.5.0)
LinkingTo: Rcpp, RcppArmadillo
Imports: ggplot2, Rcpp, rlang
Suggests: e1071, gganimate, knitr, plotly, rmarkdown, shiny, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2026-06-03 07:12:12 UTC; Shamika
Repository: CRAN
Date/Publication: 2026-06-08 19:30:02 UTC

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New package sparsediff with initial version 0.4.0
Package: sparsediff
Title: R Interface to the 'SparseDiffEngine' Sparse Differentiation Backend
Version: 0.4.0
Description: Bindings for the 'SparseDiffEngine' C library, the sparse Jacobian and Hessian differentiation backend used by 'CVXPY' for its Disciplined Nonlinear Programming (DNLP) extension. Provides low-level routines for building nonlinear expression graphs and evaluating sparse derivatives, intended as a backend for higher-level modeling layers such as 'CVXR'. This is the R analog of the 'sparsediffpy' Python package and wraps the same C library.
License: Apache License (== 2.0)
Copyright: file inst/COPYRIGHTS
URL: https://bnaras.github.io/sparsediff/, https://github.com/bnaras/sparsediff
BugReports: https://github.com/bnaras/sparsediff/issues
Encoding: UTF-8
SystemRequirements: GNU make
LinkingTo: cpp11
Suggests: cpp11, knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2026-06-03 04:46:07 UTC; naras
Author: Balasubramanian Narasimhan [aut, cre], Daniel Cederberg [aut, cph] , William Zijie Zhang [aut, cph]
Maintainer: Balasubramanian Narasimhan <naras@stanford.edu>
Repository: CRAN
Date/Publication: 2026-06-08 19:30:08 UTC

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New package rrstools with initial version 1.1.0
Package: rrstools
Title: Analyzing RoboCupRescue Simulation Data
Version: 1.1.0
Description: Tools for analyzing data from RoboCupRescue Simulation (RRS) <https://rescuesim.robocup.org>, a disaster rescue simulation platform. Supports reading virtual city map and disaster scenario files into analyzable data structures and provides functions for their visualization.
License: MIT + file LICENSE
URL: https://nononoexe.github.io/rrstools/
Depends: R (>= 3.5)
Imports: graphics, jsonlite, sf, stats, utils, xml2
Suggests: spelling, testthat (>= 3.3.0), withr
LinkingTo: cpp11
Encoding: UTF-8
Language: en-US
NeedsCompilation: yes
Packaged: 2026-06-03 05:18:54 UTC; ando
Author: Keisuke Ando [aut, cre]
Maintainer: Keisuke Ando <nononoexe@ymail.ne.jp>
Repository: CRAN
Date/Publication: 2026-06-08 19:30:14 UTC

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New package onnxr with initial version 0.1.2
Package: onnxr
Title: Bindings to 'ONNX' Runtime
Version: 0.1.2
Description: Provides native access to the 'Open Neural Network Exchange' (ONNX) Runtime <https://onnxruntime.ai/>, which is a performant engine for running machine learning models that are saved to a standardized format. Rather than interfacing with 'ONNX' via 'Python', as in the official 'onnx' package, 'onnxr' directly interfaces with the runtime's 'C++' API via 'cpp11'. Models saved to '.onnx' files can be loaded and run on various backends, including CPUs and Apple's 'CoreML' library.
License: MIT + file LICENSE
LinkingTo: cpp11
Suggests: jpeg, knitr, rmarkdown, testthat (>= 3.0.0)
URL: https://corymccartan.com/onnxr/, https://github.com/CoryMcCartan/onnxr
BugReports: https://github.com/CoryMcCartan/onnxr/issues
Language: en-US
Encoding: UTF-8
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2026-06-03 17:23:23 UTC; cmccartan
Author: Cory McCartan [aut, cre, cph], Caleb Carr [cph] , Microsoft Corporation [cph]
Maintainer: Cory McCartan <mccartan@psu.edu>
Repository: CRAN
Date/Publication: 2026-06-08 20:00:10 UTC

More information about onnxr at CRAN
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New package DrivePlotR with initial version 0.1.0
Package: DrivePlotR
Title: Linked Plot Maps for Multivariate High-Resolution Spatio-Temporal Data
Version: 0.1.0
Description: Create interactive, linked plot maps for multivariate high-resolution spatio-temporal data, such as vehicle trajectories. You can explore the spatial, temporal, and multivariate aspects of the data simultaneously.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: leaflet, plotly (>= 4.10.4), crosstalk, dplyr, ggplot2 (>= 3.5.2), htmltools, rlang (>= 1.1.6), viridisLite
Depends: R (>= 4.1)
LazyData: true
URL: https://hardtme.github.io/DrivePlotR/, https://github.com/hardtme/DrivePlotR
Suggests: testthat (>= 3.0.0), sf
BugReports: https://github.com/hardtme/DrivePlotR/issues
NeedsCompilation: no
Packaged: 2026-06-03 14:43:59 UTC; MarieHardt
Author: Marie Hardt [aut, cre, cph] , Heike Hofmann [ctb] , Guillermo Basulto-Elias [ctb]
Maintainer: Marie Hardt <hardtme@iastate.edu>
Repository: CRAN
Date/Publication: 2026-06-08 19:50:10 UTC

More information about DrivePlotR at CRAN
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New package data.checker with initial version 2.0.0
Package: data.checker
Title: Data Checker for Validating Data Frames Against Defined Schema
Version: 2.0.0
Description: Validates data frames against a defined schema. Produces a report of the checks performed and any issues found, with index and entry value where appropriate. Backend checks are performed using pointblank Richard Iannone et al (2025) <doi:10.32614/CRAN.package.pointblank>.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: dplyr, glue, jsonlite, knitr, lubridate, magrittr, tools, yaml, tomledit, utils, cli, rlang, pointblank, tidyselect, tidyr, stringr, hms
Suggests: rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
URL: https://onsdigital.github.io/data.checker/
NeedsCompilation: no
Packaged: 2026-06-03 13:24:41 UTC; dayj1
Author: Crown Copyright [cph], Analysis Standards and Pipelines Team [cre, aut]
Maintainer: Analysis Standards and Pipelines Team (ONS) <ASAP@ons.gov.uk>
Repository: CRAN
Date/Publication: 2026-06-08 19:40:07 UTC

More information about data.checker at CRAN
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New package bvars with initial version 1.0
Package: bvars
Title: Bayesian Forecasting with Large Vector Autoregressions
Version: 1.0
Date: 2026-06-03
Maintainer: Tomasz Wozniak <wozniak.tom@pm.me>
Description: Provides fast and efficient procedures for Bayesian estimation and forecasting using state-of-the-art Vector Autoregressions. This package includes the model proposed by Chan (2020) <doi:10.1080/07350015.2018.1451336>, that is, a Bayesian Vector Autoregression with Minnesota priors and a flexible structure of the error term specification. The latter includes: conditional multivariate normal or Student’s t distributions, as well as homoskedastic or heteroskedastic specifications with a common volatility modelled by centred or non-centred Stochastic Volatility. Additionally, the package facilitates predictive analyses using density forecasting and forecast-error variance decompositions. All this is complemented by simple workflows, useful plots and summary functions, and comprehensive documentation. The 'bvars' package aligns with R packages 'bsvars' by Woźniak (2024) <doi:10.32614/CRAN.package.bsvars>, 'bsvarSIGNs' by Wang & Woźniak (2025) <doi:10.32614/CRAN.package.b [...truncated...]
License: GPL (>= 3)
Depends: R (>= 4.1.0), RcppArmadillo, bsvars
Imports: generics, Rcpp (>= 1.0.14), RcppProgress, RcppTN, R6
LinkingTo: Rcpp, RcppArmadillo, RcppProgress, RcppTN, bsvars
URL: https://bsvars.org/bvars/
BugReports: https://github.com/bsvars/bvars/issues
Encoding: UTF-8
LazyData: true
NeedsCompilation: yes
Packaged: 2026-06-03 08:54:49 UTC; twozniak
Author: Rui Liu [aut] , Andres Ramirez Hassan [aut] , Tomasz Wozniak [aut, cre, cph]
Repository: CRAN
Date/Publication: 2026-06-08 19:40:12 UTC

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New package AdmixPoly with initial version 1.0.0
Package: AdmixPoly
Title: Global and Local Admixture Inference in Polyploids
Version: 1.0.0
Description: Provides functions to perform global (genome-wide) and local admixture inference from bi- and multi-allelic marker dosages (discrete or continuous) in polyploid species.
License: GPL (>= 3)
Encoding: UTF-8
NeedsCompilation: yes
Imports: Rcpp, purrr, utils, dplyr (>= 1.1.0), tidyr, tibble, ggplot2, magrittr, Matrix, data.table
LinkingTo: Rcpp, RcppArmadillo
Depends: R (>= 3.6.0)
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
Language: en-US
SystemRequirements: A system with a C++ compiler supporting OpenMP
Packaged: 2026-06-03 07:00:29 UTC; rio
Author: Simon Rio [aut, cre] , Tristan Mary-Huard [aut] , Franck Gauthier [aut]
Maintainer: Simon Rio <simon.rio@cirad.fr>
Repository: CRAN
Date/Publication: 2026-06-08 19:30:20 UTC

More information about AdmixPoly at CRAN
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New package saferDev with initial version 1.0.0
Package: saferDev
Title: Function and Pipeline Development
Version: 1.0.0
Date: 2026-06-02
Encoding: UTF-8
Maintainer: Gael Millot <gael.millot@pasteur.fr>
Description: Set of functions that perform checks according to the safer-r project recommendations for R function development (see <https://github.com/safer-r>). This includes checking argument values, ensuring correct specification of all mandatory arguments for embedded functions, as well as their explicit package namespace qualification, among other things.
URL: <https://github.com/safer-r/saferDev>, <https://safer-r.github.io/saferDev/>
License: GPL-3
Imports: ggplot2
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-06-02 16:14:25 UTC; gmillot
Author: Haiding Wang [ctb], Yushi Han [ctb], Mia Legras [ctb], Gael Millot [cre, aut, ctb]
Repository: CRAN
Date/Publication: 2026-06-08 18:10:03 UTC

More information about saferDev at CRAN
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New package rsgl with initial version 0.1.0
Package: rsgl
Title: An Implementation of the 'SGL' Graphics Language
Version: 0.1.0
Description: Generates plots from a database connection and a 'SGL' statement. 'SGL' is a graphics language designed to look and feel like 'SQL'. It is especially useful for those familiar with 'SQL' who want to specify plots in a similar manner. The 'SGL' language is described in Chapman (2025) <doi:10.48550/arXiv.2505.14690>.
License: MIT + file LICENSE
URL: https://github.com/sgl-projects/rsgl, https://sgl-projects.github.io/rsgl/, https://arxiv.org/abs/2505.14690
BugReports: https://github.com/sgl-projects/rsgl/issues
Encoding: UTF-8
Suggests: testthat (>= 3.0.0), vdiffr, lubridate, knitr, rmarkdown, patrick, tibble, withr
Imports: DBI, dplyr, duckdb, ggplot2, purrr, Rcpp, rlang
LinkingTo: Rcpp
VignetteBuilder: knitr, rmarkdown
Depends: R (>= 4.1)
LazyData: true
NeedsCompilation: yes
Packaged: 2026-06-02 16:46:56 UTC; jochapjo
Author: Jon Chapman [aut, cre, cph], Free Software Foundation, Inc. [cph]
Maintainer: Jon Chapman <jochapjo@icloud.com>
Repository: CRAN
Date/Publication: 2026-06-08 18:20:02 UTC

More information about rsgl at CRAN
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New package PMLE4SCR with initial version 0.1.0
Package: PMLE4SCR
Title: Pseudo Maximum Likelihood Estimation for Semi-Competing Risks Data
Version: 0.1.0
Description: Implements two-stage pseudo maximum likelihood estimation (PMLE) for copula-based regression models with semi-competing risks data. The marginal distributions are modeled by semiparametric transformation regression models, and the dependence between bivariate event times is specified by a parametric copula function. See Arachchige, Chen and Zhou (2025) <doi:10.1007/s10985-024-09640-z> for details.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: trust, dplyr, rlang, VineCopula
Suggests: knitr, rmarkdown, kableExtra, SemiCompRisks
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-06-02 18:03:10 UTC; KHAN GADGET
Author: Qian M. Zhou [aut], Md. Ismail Hossain [aut, cre]
Maintainer: Md. Ismail Hossain <mr2618@msstate.edu>
Repository: CRAN
Date/Publication: 2026-06-08 18:20:19 UTC

More information about PMLE4SCR at CRAN
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New package irtbem2pl with initial version 1.0.0
Package: irtbem2pl
Title: Marginalized Bayesian Item Parameter Estimation, 2pl Model IRT
Version: 1.0.0
Maintainer: Juan Luis Legorreta Torres <jlegorreta2002@yahoo.com.mx>
Description: Estimates item parameters of the two-parameter logistic (2PL) model in Item Response Theory (IRT) using the marginal Bayesian modal estimation via the Expectation-Maximization (EM) algorithm. The package calibrates item discrimination and difficulty parameters, yielding results comparable to software like 'BILOG-MG'.
License: GPL (>= 2)
URL: https://github.com/juanluislegorretatorres/irtbem2pl
Depends: R (>= 3.5.0)
Imports: IRTBEMM
NeedsCompilation: no
Encoding: UTF-8
Language: en-US
Packaged: 2026-06-02 16:11:16 UTC; juan.legorreta
Author: Juan Luis Legorreta Torres [aut, cre]
Repository: CRAN
Date/Publication: 2026-06-08 18:10:10 UTC

More information about irtbem2pl at CRAN
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New package genefindr with initial version 1.0.0
Package: genefindr
Title: Rapid Gene Characterization Using Public Genomic Databases
Version: 1.0.0
Description: A user-friendly interface for characterizing gene function by disease type and tissue site, integrating curated data from publicly available genomic and proteomic databases to support candidate gene prioritization in experimental workflows.
Depends: R (>= 4.1.0)
License: GPL-3
Encoding: UTF-8
Imports: httr2, gtexr
URL: https://github.com/martincyd/genefindr
BugReports: https://github.com/martincyd/genefindr/issues
Suggests: knitr, rmarkdown, spelling
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-06-02 21:07:59 UTC; cyd
Author: Cydnie Martin [aut, cre]
Maintainer: Cydnie Martin <martincydenise@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-08 18:30:02 UTC

More information about genefindr at CRAN
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New package binest with initial version 0.2-1
Package: binest
Title: Estimation of Group Means and SDs from Binned Count Data
Version: 0.2-1
Date: 2026-05-27
Depends: R (>= 3.5.0), splines, stats
Suggests: knitr, rmarkdown, R2jags
Description: Estimates group-level means and standard deviations from binned (coarsened) count data, where the within-bin scores are unobserved. The package implements three methods that share a common output structure: bin_means() (a fast estimator that assumes within-district normality and uses pooled bin proportions to derive bin-conditional truncated-normal expectations), mle_hetop() (maximum likelihood for the heteroskedastic ordered probit model of Reardon, Shear, Castellano and Ho 2017 <doi:10.3102/1076998616666279>), and fh_hetop() (the Bayesian Fay-Herriot variant of Lockwood, Castellano and Shear 2018 <doi:10.3102/1076998618795124>). The mle_hetop() and fh_hetop() functions are forked from the 'HETOP' package by J. R. Lockwood ('CRAN', last released 2019). mle_hetop() has been modified to speed up the runtime via a vectorized inner loop and to remove two user-facing arguments (fixedcuts and svals) that some users found confusing; cutpoints and starting values are now derive [...truncated...]
License: GPL (>= 2)
VignetteBuilder: knitr
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-06-02 16:51:41 UTC; ph3828
Author: Paul T. von Hippel [aut, cre], David J. Hunter [aut], J.R. Lockwood [aut]
Maintainer: Paul T. von Hippel <ph3828@eid.utexas.edu>
Repository: CRAN
Date/Publication: 2026-06-08 18:20:08 UTC

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New package tlgarima with initial version 0.1.0
Package: tlgarima
Title: The Topp–Leone Garima Distribution
Version: 0.1.0
Description: Density, distribution function, quantile function, and random generating function of the Topp–Leone Garima distribution based on Boonmeekham, A., Supapakorn, T., & Bodhisuwan, W. (2025)<doi:10.1134/S1995080225608471>. In addition, maximum likelihood estimation for the Topp–Leone Garima distribution is provided.
License: GPL-3
Language: en-US
Encoding: UTF-8
Imports: stats, lamW
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-06-02 13:33:54 UTC; User
Author: Arin Boonmeekham [aut], Thidaporn Supapakorn [aut], Winai Bodhisuwan [aut], Atchanut Rattanalertnusorn [cre, ctb]
Maintainer: Atchanut Rattanalertnusorn <atchanut_r@rmutt.ac.th>
Repository: CRAN
Date/Publication: 2026-06-08 17:50:02 UTC

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New package spboost with initial version 0.7.0
Package: spboost
Title: Gradient Boosting for Nonlinear Spatial Autoregressive Models
Version: 0.7.0
Description: Flexible nonlinear extension of spatial autoregressive (SAR), spatial error (SEM), and spatial autoregressive with autoregressive disturbances (SARAR) models with multiple regression engines (generalized additive models ('mgcv'), gradient boosting ('mboost'), multivariate adaptive regression splines ('earth'), and 'xgboost') and two families of spatial-parameter estimators: maximum likelihood and the determinant-free Closed-Form Estimator of Smirnov (2020) <doi:10.1111/gean.12268>. See Geniaux G. (2026). "Flexible nonlinear spatial autoregressive models: a gradient boosting approach with closed-form estimation." Presented at Spatial Econometrics World Congress (SEA/SEW 2026, Paris), unpublished.
License: GPL (>= 2)
Depends: Matrix, mboost, mgcv, methods, mgwrsar
Imports: Rcpp, sf, MASS, data.table, xgboost, caret, doParallel, foreach, nabor, earth
Suggests: blockCV, knitr, rmarkdown, RSpectra, spatialreg, spdep, testthat (>= 3.0.0)
VignetteBuilder: knitr
LinkingTo: RcppEigen, Rcpp
NeedsCompilation: yes
Encoding: UTF-8
Packaged: 2026-06-02 13:54:02 UTC; geniaux
Author: Ghislain Geniaux [aut, cre]
Maintainer: Ghislain Geniaux <ghislain.geniaux@inrae.fr>
Repository: CRAN
Date/Publication: 2026-06-08 18:00:02 UTC

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New package NeutroRCDsAnalysis with initial version 0.1.0
Package: NeutroRCDsAnalysis
Title: Neutrosophic Analysis of Row Column Designs
Version: 0.1.0
Maintainer: Vinaykumar L.N. <vinaymandya123@gmail.com>
Description: Description: Provides methods for Neutrosophic Analysis of Variance (NANOVA) and Neutrosophic Analysis of Covariance (NANCOVA) for row-column designs, including Latin square designs and Youden square designs, using interval-valued observations. The package computes neutrosophic sums of squares, mean squares, interval-valued F-statistics, significance tests, and multiple comparisons using Least Significant Difference (LSD) procedures. For crisp data, users may enter identical lower and upper values of responses to obtain classical Analysis of Variance (ANOVA) results. Similarly, users may enter identical lower and upper values for both responses and covariates to obtain classical Analysis of Covariance (ANCOVA) results.
License: GPL-3
Encoding: UTF-8
Depends: R (>= 4.0.0)
Imports: MASS
NeedsCompilation: no
Packaged: 2026-06-02 09:37:17 UTC; admin
Author: Neethu R.S. [aut, ctb], Cini Varghese [aut, ctb], Mohd Harun [aut, ctb], Anindita Datta [aut, ctb], Vinaykumar L.N. [aut, cre]
Repository: CRAN
Date/Publication: 2026-06-08 17:50:26 UTC

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New package iDIFr with initial version 1.0.1
Package: iDIFr
Title: Intersectional Differential Item Functioning Analysis
Version: 1.0.1
Description: A toolkit for detecting Differential Item Functioning (DIF) using Logistic Regression (LR) as described in Swaminathan and Rogers (1990) <doi:10.1111/j.1745-3984.1990.tb00754.x>, the IRT Likelihood Ratio Test (LRT) following Thissen, Steinberg & Wainer (1993, ISBN:0-8058-0972-4), and model-based recursive partitioning (MOB) as implemented in 'strucchange' following Strobl, Kopf and Zeileis (2015) <doi:10.1007/s11336-013-9388-3>. Designed for both standard two-group and intersectional multi-group designs, 'iDIFr' prioritises effect size reporting alongside statistical significance, clear guidance on group construction, and interpretable output suitable for applied testing contexts. Built-in Intersectional Contrast Analysis (ICA) classifies items as amplified, pure-intersection, obscured, or none by comparing single-variable and intersectional analyses.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: Rcpp (>= 1.0.0), generics, parallel, stats, cli, dplyr, ggplot2, rlang, strucchange
LinkingTo: Rcpp
Suggests: testthat (>= 3.0.0), knitr, rmarkdown, openxlsx
VignetteBuilder: knitr
URL: https://github.com/thmsrgrs/iDIFr
BugReports: https://github.com/thmsrgrs/iDIFr/issues
NeedsCompilation: yes
Packaged: 2026-06-02 10:59:57 UTC; TMRog
Author: Thomas Rogers [aut, cre]
Maintainer: Thomas Rogers <thomas.rogers@britishcouncil.org>
Repository: CRAN
Date/Publication: 2026-06-08 17:50:06 UTC

More information about iDIFr at CRAN
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New package FastSegmentation with initial version 0.0.1
Package: FastSegmentation
Title: Unsupervised Cell Segmentation by Fast Gaussian Processes
Version: 0.0.1
Author: Blythe King [aut, cre], Haoran Yan [aut], Laura Baracaldo [aut], Mengyang Gu [aut]
Maintainer: Blythe King <blyking@gmail.com>
Description: Performs fast Gaussian process-based segmentation of microscopy images using spatial smoothing and data-driven thresholding. Code based on Baracaldo, L., King, B., Yan, H., Lin, Y., Miolane, N., & Gu, M. (2025). "Unsupervised cell segmentation by fast Gaussian processes." arXiv preprint <doi:10.48550/arXiv.2505.18902>.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: EBImage, stats, magick, pracma, RobustGaSP
Suggests: plot3D
NeedsCompilation: no
Packaged: 2026-06-02 05:23:12 UTC; blyki
Repository: CRAN
Date/Publication: 2026-06-08 17:40:07 UTC

More information about FastSegmentation at CRAN
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New package easyRasch2 with initial version 0.8.0
Package: easyRasch2
Title: Psychometric Analysis with Rasch Measurement Theory
Version: 0.8.0
Description: Streamlines reproducible Rasch measurement theory analyses for ordinal item-response data, combining estimation routines from 'eRm', 'psychotools', 'mirt', 'iarm', and 'lavaan' with consistent diagnostic, plotting, and reporting layers. Covers the four basic psychometric criteria summarised by Christensen et al. (2021) <doi:10.1111/sms.13908> -- unidimensionality, local independence, ordered response category thresholds, and invariance across subgroups -- together with item fit, targeting, reliability, category functioning, and descriptive item-response plots. A distinguishing feature is the use of simulation-based critical values to replace rule-of-thumb cutoffs for conditional infit mean-square, Yen's Q3 local-dependence statistic, the largest residual-PCA eigenvalue, and ordinal CFA fit indices. Outputs are knitr::kable() tables and 'ggplot2' figures suitable for direct inclusion in 'Quarto' and 'R Markdown' reports.
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
URL: https://github.com/pgmj/easyRasch2, https://pgmj.github.io/easyRasch2/
BugReports: https://github.com/pgmj/easyRasch2/issues
Depends: R (>= 4.1.0)
Imports: eRm, knitr, mirt, psychotools (>= 0.7-3), stats, utils, rlang
Suggests: difR, dplyr, geomtextpath, ggdist, ggtext, iarm, mirai, ggplot2 (>= 3.4.0), partykit, psychotree, stablelearner, testthat (>= 3.0.0), rmarkdown, patchwork, scales, mice, ggrepel, lavaan
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-06-02 12:03:20 UTC; magnus.johansson.3
Author: Magnus Johansson [aut, cre] , Nicklas Korsell [ctb] , Mirka Henninger [ctb] , Jan Radek [ctb]
Maintainer: Magnus Johansson <pgmj@pm.me>
Repository: CRAN
Date/Publication: 2026-06-08 17:50:12 UTC

More information about easyRasch2 at CRAN
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New package CIMEHR with initial version 0.1.0
Package: CIMEHR
Title: Gaussian Clinically Informative Visiting and Observation Processes in Electronic Health Record (EHR) Data
Version: 0.1.0
Description: Fits semiparametric joint models for longitudinal electronic health record (EHR) data that addresses two-stage hierarchical missingness mechanism. The first stage is the visiting process, and the second stage is the observation process. The core CIMEHR method (Clinical Informative Missingness for Electronic Health Records) uses a three-stage procedure: partial likelihood with log-normal frailty for visit intensity, probit regression with shared latent factor-linked random effects for observation, and weighted least squares with risk-set centering for the outcome. These three stages are connected through a shared latent factor that induces dependence across all three processes. A data simulator and implementations of common benchmark methods (linear mixed models, multiple imputation, and others) are included for comparative studies. Detailed methods are described in Yang, Shi, and Mukherjee (2026) <doi:10.48550/arXiv.2602.15374>.
License: MIT + file LICENSE
Encoding: UTF-8
Suggests: tibble, dplyr, tidyr, knitr, rmarkdown
Imports: MASS, Rcpp, nleqslv, pbivnorm, numDeriv, stats, utils, data.table, mice, nlme, slim
LinkingTo: Rcpp
URL: https://github.com/ysph-dsde/CIMEHR
BugReports: https://github.com/ysph-dsde/CIMEHR/issues
VignetteBuilder: knitr
Depends: R (>= 3.5)
LazyData: true
NeedsCompilation: yes
Packaged: 2026-06-02 13:29:18 UTC; yh785
Author: Cheng-Han Yang [aut, cre] , Yiren Hou [aut]
Maintainer: Cheng-Han Yang <chenghanyang728@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-08 18:00:25 UTC

More information about CIMEHR at CRAN
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New package chmsflow with initial version 0.1.0
Package: chmsflow
Title: Transforming and Harmonizing CHMS Variables
Version: 0.1.0
Description: Harmonizes variables from the Canadian Health Measures Survey (CHMS) across cycles 1-6 (2007-2019), producing consistent, analysis-ready variables for use with CHMS data. Recoding is data-driven through metadata tables and applied with recodeflow::rec_with_table() from the 'recodeflow' package. The recoding approach builds on sjmisc::rec() from the 'sjmisc' package (Ludecke 2018) <doi:10.21105/joss.00754>.
Depends: R (>= 4.1.0)
Imports: dplyr, haven, purrr, recodeflow
License: MIT + file LICENSE
URL: https://github.com/Big-Life-Lab/chmsflow, https://big-life-lab.github.io/chmsflow/
BugReports: https://github.com/Big-Life-Lab/chmsflow/issues
Encoding: UTF-8
Suggests: DT, kableExtra, knitr, quarto, readr, testthat (>= 3.0.0)
VignetteBuilder: quarto
LazyData: true
NeedsCompilation: no
Packaged: 2026-06-02 14:36:36 UTC; rafidulislam
Author: Rafidul Islam [aut, cre, cph] , Douglas Manuel [aut, cph] , Therese Chan [ctb] , The Ottawa Hospital Research Institute [cph]
Maintainer: Rafidul Islam <raislam@ohri.ca>
Repository: CRAN
Date/Publication: 2026-06-08 18:00:08 UTC

More information about chmsflow at CRAN
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New package BayesForge with initial version 0.0.1
Package: BayesForge
Title: Bayesian Inference using 'numpyro' and 'XLA'
Version: 0.0.1
Description: A high-performance probabilistic programming library that aims to unify the modeling experience by providing an intuitive model-building syntax together with the flexibility of low-level abstraction coding. It also includes pre-built functions for high-level abstraction and supports hardware-accelerated computation for improved scalability, including parallelization, vectorization, and execution on CPU (Central Processing Unit), GPU (Graphics Processing Unit), or TPU (Tensor Processing Unit) using 'JAX' (Just-In-Time compiled Accelerated linear algebra) as the computational backend: Sosa (2026) <doi:10.64898/2026.01.19.700318>.
URL: https://s-sosa.com/BF/
Encoding: UTF-8
Imports: reticulate, abind, methods
SystemRequirements: Python (>= 3.6), 'bayesforge' python library.
Depends: R (>= 3.5.0)
Suggests: testthat (>= 3.0.0), brms, rstan
License: GPL (>= 3)
NeedsCompilation: no
Packaged: 2026-06-02 07:55:20 UTC; sebastian_sosa
Author: Sebastian Sosa [aut, cre]
Maintainer: Sebastian Sosa <bf@s-sosa.com>
Repository: CRAN
Date/Publication: 2026-06-08 17:50:31 UTC

More information about BayesForge at CRAN
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New package autocodebook with initial version 0.1.0
Package: autocodebook
Title: Automatic Codebook and Tracking for 'Spark' and 'dplyr' Pipelines
Version: 0.1.0
Description: Wraps 'dplyr' verbs (mutate, summarise, filter) to automatically capture variable metadata (type, source columns, categories, and source code), producing a codebook and eligibility tracking table with zero manual documentation. Works with both 'sparklyr' (tbl_spark) and local data frames. Adds big-data optimizations (caching, assume-unique counting, checkpointing) and a standardized report module with an eligibility flowchart, editable codebook export (HTML, DOCX, XLSX), and cross-sectional or longitudinal variable inspection. The eligibility flowchart follows the CONSORT statement (Schulz, Altman and Moher (2010) <doi:10.1136/bmj.c332>) and the reporting of observational cohort studies follows the STROBE recommendations (von Elm and others (2007) <doi:10.1371/journal.pmed.0040296>).
License: MIT + file LICENSE
URL: https://github.com/patriciafortesm/autocodebook
BugReports: https://github.com/patriciafortesm/autocodebook/issues
Encoding: UTF-8
Imports: dplyr (>= 1.1.0), rlang (>= 1.0.0), tibble, gt, grid
Suggests: sparklyr, dbplyr, testthat (>= 3.0.0), tidyplots, ggplot2, patchwork, rmarkdown, knitr, officer, flextable, openxlsx, scales, rvg, devEMF, svglite
NeedsCompilation: no
Packaged: 2026-06-02 14:13:06 UTC; maced
Author: Patricia Fortes C. de Macedo [aut, cre]
Maintainer: Patricia Fortes C. de Macedo <macedopatriciafortes@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-08 18:00:19 UTC

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New package aisdk.providers with initial version 0.1.0
Package: aisdk.providers
Title: Additional Model Provider Adapters for the 'aisdk' Toolkit
Version: 0.1.0
Description: Additional AI model provider adapters for the 'aisdk' toolkit, covering OpenAI-compatible and Anthropic-compatible services such as 'DeepSeek', 'Moonshot'/'Kimi', 'Stepfun', 'Volcengine', 'AiHubMix', 'xAI', 'OpenRouter', 'Bailian', and 'NVIDIA'. Providers register themselves with the core 'aisdk' provider registry on load.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: aisdk (>= 1.4.12), R6, rlang, base64enc, jsonlite, curl, utils
Suggests: withr, testthat (>= 3.0.0)
URL: https://github.com/YuLab-SMU/aisdk.providers
BugReports: https://github.com/YuLab-SMU/aisdk.providers/issues
Depends: R (>= 4.1.0)
NeedsCompilation: no
Packaged: 2026-06-02 10:47:44 UTC; xiayh
Author: Yonghe Xia [aut, cre]
Maintainer: Yonghe Xia <xiayh17@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-08 17:50:20 UTC

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New package seine with initial version 0.1.2
Package: seine
Title: Semiparametric Ecological Inference
Version: 0.1.2
Description: Efficient and user-friendly routines for modern ecological inference. Implements the methods described in McCartan & Kuriwaki (2025+) <doi:10.48550/arXiv.2509.20194>, which generalize ecological regression as introduced by Goodman (1953) <doi:10.2307/2088121>. Includes routines for preprocessing, synthetic data generation, double/debiased machine learning (DML) estimation, partial identification bounds, and sensitivity analysis.
Depends: R (>= 3.5.0)
Imports: rlang, cli, tidyselect, tibble, hardhat, quadprog, graphics, utils, stats
Suggests: bases, knitr, rmarkdown, testthat (>= 3.0.0), xml2
LinkingTo: cpp11, cpp11armadillo, testthat
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
URL: https://corymccartan.com/seine/, https://github.com/CoryMcCartan/seine
BugReports: https://github.com/CoryMcCartan/seine/issues
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2026-06-02 04:06:58 UTC; cmccartan
Author: Cory McCartan [aut, cre, cph] , Shiro Kuriwaki [aut, cph]
Maintainer: Cory McCartan <mccartan@psu.edu>
Repository: CRAN
Date/Publication: 2026-06-08 15:10:02 UTC

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New package autoLibLoad with initial version 1.0
Package: autoLibLoad
Version: 1.0
Date: 2026-05-25
Title: Automate Retrieving, Building, Installing and Loading Specified Packages
Maintainer: Barry Zeeberg <barryz2013@gmail.com>
Author: Barry Zeeberg [aut, cre]
Depends: R (>= 4.2.0)
Imports: utils, stringr, devtools, tools, vprint
Description: Packages required for the search path may be located in the CRAN repository, the system library, or a local directory. We automate determining the disposition of each required package, retrieving it, and loading it as needed.
License: GPL (>= 2)
Encoding: UTF-8
VignetteBuilder: knitr
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-06-01 20:42:49 UTC; barryzeeberg
Repository: CRAN
Date/Publication: 2026-06-08 15:10:09 UTC

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New package wqrr with initial version 1.0.0
Package: wqrr
Title: Wavelet Quantile Regression Toolbox
Version: 1.0.0
Description: A comprehensive toolbox for wavelet-domain quantile analyses of bivariate and multivariate time series. Provides Wavelet Quantile Regression and Multivariate Wavelet Quantile Regression after Adebayo and Ozkan (2024) <doi:10.1016/j.jclepro.2024.140832>, Wavelet Quantile-on-Quantile regression with bootstrap p-values extending Sim and Zhou (2015) <doi:10.1016/j.jbankfin.2015.01.013>, the nonparametric Causality-in-Quantiles test of Balcilar, Gupta and Pierdzioch (2016) <doi:10.1016/j.resourpol.2016.04.004> together with its wavelet variant, Wavelet Quantile Mediation and Moderation, Wavelet Quantile Correlation, and a wavelet-based nonparametric Quantile Density estimator. The Maximal Overlap Discrete Wavelet Transform (MODWT) decomposition is performed via 'waveslim' and Short / Medium / Long band aggregation is supported throughout. For plain Quantile-on-Quantile regression see the companion CRAN package 'QuantileOnQuantile'. All interactive 3D surfaces, heatmaps and [...truncated...]
License: GPL-3
Encoding: UTF-8
Depends: R (>= 3.5.0)
Imports: quantreg (>= 5.0), waveslim (>= 1.8), plotly (>= 4.0.0), stats, utils, grDevices
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
URL: https://github.com/merwanroudane/wqrr
BugReports: https://github.com/merwanroudane/wqrr/issues
NeedsCompilation: no
Packaged: 2026-06-01 19:02:19 UTC; HP
Author: Merwan Roudane [aut, cre, cph], Nicholas Sim [ctb] , Hongtao Zhou [ctb] , Tomiwa Sunday Adebayo [ctb] , Mehmet Balcilar [ctb]
Maintainer: Merwan Roudane <merwanroudane920@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-08 15:00:02 UTC

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New package rsdv with initial version 0.1.0
Package: rsdv
Title: Synthetic Tabular Data Generation with Gaussian Copulas
Version: 0.1.0
Description: Generates synthetic tabular data from real datasets using Gaussian copula models, with parametric marginal selection for numerical columns and a cumulative-frequency embedding that brings categorical and boolean columns into the same joint copula. Includes a metadata system with column types and primary keys, declarative constraints enforced via rejection sampling, conditional sampling, and quality, validity and privacy reports modeled on those of the 'SDMetrics' library. Inspired by the Python 'SDV' (Synthetic Data Vault) library by 'DataCebo'; see Patki, Wedge and Veeramachaneni (2016) "The Synthetic Data Vault" <doi:10.1109/DSAA.2016.49>.
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-US
URL: https://kvenkita.github.io/rsdv/, https://github.com/kvenkita/rsdv
BugReports: https://github.com/kvenkita/rsdv/issues
Depends: R (>= 4.3.0)
Imports: copula (>= 1.1-0), generics (>= 0.1.3), jsonlite (>= 1.8.0), ggplot2 (>= 3.4.0), tibble (>= 3.2.0), FNN (>= 1.1.3), rpart (>= 4.1.0), scales (>= 1.2.0), stats, utils
Suggests: testthat (>= 3.0.0), withr, knitr (>= 1.40), rmarkdown (>= 2.20)
VignetteBuilder: knitr
LazyData: true
NeedsCompilation: no
Packaged: 2026-06-01 19:36:42 UTC; kyle
Author: Kailas Venkitasubramanian [aut, cre]
Maintainer: Kailas Venkitasubramanian <kailasv@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-08 15:00:07 UTC

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New package OlinkAnalyzeVignettes with initial version 1.0.1
Package: OlinkAnalyzeVignettes
Title: Vignettes for Analyzing Data using 'OlinkAnalyze'
Version: 1.0.1
Description: Exemplifying analysis of large-scale protein data from the 'Olink platform', primarily relative protein expression data that has been exported from 'Olink NPX Software', as well as QUANT data from 'Olink'. QUANT data is log-transformed. Materials focus on reading data, demonstrating data wrangling and quality control analysis, performing statistical analysis and generating figures to visualize the results of the statistical analysis. The goal of this package is to guide users extract biological insights from large-scale protein data run on the 'Olink platform'. More information on 'Olink' data can be found at <https://olink.com/>.
Contact: biostattools@olink.com
URL: https://olink.com/ https://github.com/Olink-Proteomics/OlinkRPackage
License: AGPL (>= 3)
Encoding: UTF-8
Depends: R (>= 4.1.0)
Suggests: dplyr (>= 1.2.0), ggplot2, ggpubr, ggrepel, kableExtra, knitr, OlinkAnalyze, stringr, tidyr
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-06-01 18:27:06 UTC; kathy.nevola
Author: Kathleen Nevola [aut, cre] , Marianne Sandin [aut] , Jamey Guess [aut] , Simon Forsberg [aut] , Christoffer Cambronero [aut] , Pascal Pucholt [aut] , Boxi Zhang [aut] , Masoumeh Sheikhi [aut] , Klev Diamanti [aut] , Amrita Kar [aut] , Lei Conze [aut] [...truncated...]
Maintainer: Kathleen Nevola <biostattools@olink.com>
Repository: CRAN
Date/Publication: 2026-06-08 14:50:26 UTC

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New package DonutMap with initial version 0.1.0
Package: DonutMap
Title: Donut Maps with 'sf', 'ggplot2', and 'leaflet'
Version: 0.1.0
Description: Create donut charts positioned on maps from tidy data. The package provides helpers to compute donut polygon geometries, optional origin-destination flow lines, ready-to-use 'ggplot2' map layers, and interactive 'leaflet' widgets.
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-US
Depends: R (>= 4.1.0)
Imports: dplyr, ggplot2, htmltools, leaflet, rlang, scales, sf, tibble
Suggests: ragg, knitr, rmarkdown, rnaturalearth, rnaturalearthdata, testthat (>= 3.0.0)
VignetteBuilder: knitr
URL: https://aureliennicosiaulaval.github.io/DonutMap/, https://github.com/AurelienNicosiaULaval/DonutMap
BugReports: https://github.com/AurelienNicosiaULaval/DonutMap/issues
NeedsCompilation: no
Packaged: 2026-06-01 18:11:05 UTC; aureliennicosia
Author: Aurelien Nicosia [aut, cre]
Maintainer: Aurelien Nicosia <aurelien.nicosia@mat.ulaval.ca>
Repository: CRAN
Date/Publication: 2026-06-08 14:40:02 UTC

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New package HAMMER with initial version 1.0
Package: HAMMER
Title: High-Dimensional Factor-Analytic Representation Modeling and Metrics
Version: 1.0
Maintainer: Carel F.W. Peeters <carel.peeters@wur.nl>
Description: The goal of 'HAMMER' is to provide factor analytic representation learningand associated determinacy metrics for very-high-dimensional data. It projects high-dimensional data onto low-dimensional generative latent sources and assesses the uncertainty in the projection. The projection is distribution-free, scale-equivariant, and efficient.
Depends: R (>= 3.5.0)
Imports: stats, RSpectra
LazyData: true
License: GPL (>= 2)
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-06-01 14:54:33 UTC; peete064
Author: Carel F.W. Peeters [aut, cre, cph]
Repository: CRAN
Date/Publication: 2026-06-08 11:40:02 UTC

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Sun, 07 Jun 2026

New package yaap with initial version 1.0.0
Package: yaap
Title: A Toolkit for Archetypal Analysis Methods
Version: 1.0.0
Description: Fits archetypal analysis models, including Euclidean, probabilistic, kernel, and directional variants. Methods include classical archetypal analysis from Cutler and Breiman (1994) <doi:10.1080/00401706.1994.10485840>, PCHA and kernel variants from Mørup and Hansen (2012) <doi:10.1016/j.neucom.2011.06.033>, probabilistic archetypal analysis from Seth and Eugster (2016) <doi:10.1007/s10994-015-5498-8>, directional archetypal analysis from Olsen et al. (2022) <doi:10.3389/fnins.2022.911034>, AA++ initialization from Mair and Sjölund (2023) <doi:10.48550/arXiv.2301.13748>, coreset-style initialization from Mair and Brefeld (2019) <https://proceedings.neurips.cc/paper_files/paper/2019/file/7f278ad602c7f47aa76d1bfc90f20263-Paper.pdf>, and adapted AIC from Suleman (2017) <doi:10.1109/FUZZ-IEEE.2017.8015385>. Provides initialization helpers, model selection paths, plotting methods, 'broom' methods, and a 'tidymodels' recipe step.
License: GPL (>= 3)
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: generics (>= 0.1.3), graphics, methods, Matrix, matrixStats, nnls, rlang (>= 1.0.0), stats, tibble (>= 3.0.0), utils, vctrs
Suggests: archetypes, bench, compositions, fda, geometry, ggplot2, ggtern, irlba, knitr, MASS, quadprog, recipes (>= 1.0.0), rmarkdown, RSpectra, testthat (>= 3.0.0), tune (>= 1.0.0), withr (>= 2.5.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-06-01 09:51:56 UTC; teo
Author: Teo Sakel [aut, cre, cph] , MCIU/AEI [fnd]
Maintainer: Teo Sakel <teo@intelligentbiodata.com>
Repository: CRAN
Date/Publication: 2026-06-07 18:40:02 UTC

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New package ValidationExplorer with initial version 0.1.1
Package: ValidationExplorer
Title: Simulation-Based Tools for Bioacoustic Study Design
Version: 0.1.1
Description: Many bioacoustic data workflows rely on manual review (i.e., validation) of a subset of call files to provide information to statistical models that account for misclassification by automated algorithms. Because manual review can be prohibitively expensive, simulation can be a valuable tool to aid the design of studies that use validation. This package provides user-friendly functions to reduce the programming burden of simulation studies that compare validation sampling designs. Simulations assume the count-detection model, which is a realistic model for bioacoustic data, especially for bats. For more information, see Oram et al. (2025) <doi:10.1214/25-AOAS2096>.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: nimble, R (>= 4.1.0)
Imports: coda, dplyr, ggplot2, magrittr, purrr, rlang, rstan, stringr, tibble, tidyr, viridis
LazyData: true
Suggests: testthat (>= 3.0.0), withr
URL: https://j-oram.github.io/ValidationExplorer/
BugReports: https://github.com/j-oram/ValidationExplorer/issues
NeedsCompilation: no
Packaged: 2026-06-01 14:12:58 UTC; jacoboram
Author: Jacob Oram [aut, cre, cph] , Katharine Banner [aut] , Christian Stratton [aut] , Kathryn Irvine [aut]
Maintainer: Jacob Oram <jacoboram@montana.edu>
Repository: CRAN
Date/Publication: 2026-06-07 18:50:02 UTC

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New package SKBD with initial version 0.1.1
Package: SKBD
Title: Shared Keyboard Designs for Phase I Dose-Finding Trials
Version: 0.1.1
Maintainer: Jiangyan Zhao <zhaojy2017@126.com>
Description: Implements the shared keyboard design (SKBD) for model-assisted phase I dose-finding, including decision-boundary construction, operating-characteristic simulation, and extensions for dose insertion and time-to-event settings. The package also provides an interactive Shiny interface for trial-planning workflows. For more details, see Zhao, Shi, and Xu (2026) <doi:10.48550/arXiv.2605.25043>.
License: GPL (>= 3)
URL: https://github.com/Jiangyan-Zhao/SKBD
BugReports: https://github.com/Jiangyan-Zhao/SKBD/issues
Encoding: UTF-8
NeedsCompilation: no
Depends: R (>= 3.5.0)
Imports: shiny
Suggests: DT, testthat (>= 3.0.0)
Packaged: 2026-06-01 12:04:51 UTC; JYZHAO
Author: Jiangyan Zhao [cre, aut], Xian Shi [aut], Jin Xu [aut]
Repository: CRAN
Date/Publication: 2026-06-07 18:50:09 UTC

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New package shinyphaser with initial version 0.1.0
Package: shinyphaser
Title: An Interface to the 'Phaser.js' Game Framework
Version: 0.1.0
Description: An API to build and control 2D games using the 'Phaser' 'JavaScript' engine. It enables integration with 'shiny' applications, allowing to create interactive games and simulations.
License: MIT + file LICENSE
Encoding: UTF-8
URL: https://github.com/maciekbanas/shinyphaser
BugReports: https://github.com/maciekbanas/shinyphaser/issues
Imports: htmltools, R6, rlang, shiny
Suggests: knitr, rmarkdown, shinyalert, testthat (>= 3.0.0), shinytest2 (>= 0.5.1)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-06-01 14:40:01 UTC; banas
Author: Maciej Banas [aut, cre]
Maintainer: Maciej Banas <banasmaciek@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-07 19:00:02 UTC

More information about shinyphaser at CRAN
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New package PsiUEngineRL with initial version 0.1.3
Package: PsiUEngineRL
Title: Homotopy Type Theory Engine for Reinforcement Learning
Version: 0.1.3
Description: Core architecture for interpreting continuous data streams as homotopy types. It evaluates identity paths against the Gnomonic Ratio ('Lombardi', 2026) <doi:10.5281/zenodo.20385840> and processes them via a dynamic 'Tableau Refutation Tree'. The engine categorizes data into necessity (BOX), possibility (DIAMOND), or noise based on deviation thresholds from the invariant value. Includes adaptive auto-tuning and native high-contrast Cartesian graphics for structural entropy isolation.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 3.5)
NeedsCompilation: no
Packaged: 2026-06-01 14:08:35 UTC; Roberto
Author: Roberto Lombardi [aut, cre]
Maintainer: Roberto Lombardi <lombardisedr@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-07 18:50:14 UTC

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New package NRMstatsML with initial version 0.1.4
Package: NRMstatsML
Title: Statistical and Machine Learning Engine for Long-Term Natural Resource Management Data
Version: 0.1.4
Description: A comprehensive toolkit for statistical and machine learning-based analysis of long-term Natural Resource Management (NRM) datasets. Integrates formula-driven approaches, statistical inference, and machine learning (ML) models for advanced analytics. Modules cover trend and structural analysis (Mann-Kendall test, slope estimation, Chow test, structural break detection), multivariate system modelling (Partial Least Squares (PLS), Structural Equation Modelling (SEM)), response curve optimisation, time-series forecasting (Autoregressive Integrated Moving Average (ARIMA), hybrid models), panel data and treatment effects (Difference-in-Differences (DiD), causal machine learning), uncertainty and sensitivity analysis (bootstrap, Monte Carlo, Bayesian), and automated model selection and performance comparison. Designed for long-term datasets covering soil, water, crop, and climate domains. Key references: Mann and Kendall (1945) <doi:10.2307/1907187>; Sen (1968) <doi:10.1080/01621459 [...truncated...]
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
Language: en-US
Depends: R (>= 4.1.0)
Imports: Kendall (>= 2.2), trend (>= 1.1.4), strucchange (>= 1.5.3), plm (>= 2.6.0), forecast (>= 8.20), lavaan (>= 0.6.12), pls (>= 2.8.0), caret (>= 6.0.93), boot (>= 1.3.28), ggplot2 (>= 3.4.0), rlang (>= 1.1.0), stats, utils
Suggests: testthat (>= 3.0.0), knitr, rmarkdown, keras, tensorflow, BayesianTools, sensitivity, mboost, mlr3, covr
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-06-01 09:22:01 UTC; acer
Author: Sadikul Islam [aut, cre, cph]
Maintainer: Sadikul Islam <sadikul.islamiasri@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-07 18:30:08 UTC

More information about NRMstatsML at CRAN
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New package AutoMLR with initial version 1.0.0
Package: AutoMLR
Title: Automated Multi-Outcome Machine Learning Combination Models
Version: 1.0.0
Description: Provides automated machine learning workflows for survival analysis, binary classification, continuous outcomes, and ordinal outcomes. The package trains and combines model variants across user-supplied multi-cohort data, evaluates survival models by leave-one-out cross-validation using Harrell's concordance index, binary models by leave-one-out cross-validation using receiver operating characteristic area under the curve, continuous models by out-of-fold root mean squared error and R-squared, and ordinal models by out-of-fold quadratic weighted kappa. It renders reproducible reports in Hypertext Markup Language (HTML) with figures and diagnostics. The survival workflow supports penalized and tree-based Cox proportional hazards models, stepwise Cox models, partial least squares regression for Cox models, supervised principal components, gradient boosting machine Cox models, survival support vector machines (survival-SVM), random survival forests, and optional 'CoxBoost'. The binary wor [...truncated...]
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1)
Imports: survival, graphics, grDevices, parallel, stats, utils
Suggests: CoxBoost, digest, future, future.apply, glmnet, gbm, log4r, plsRcox, quadprog, randomForestSRC, superpc, survivalsvm, testthat (>= 3.0.0), timeROC
NeedsCompilation: no
Packaged: 2026-05-19 16:21:46 UTC; abc
Author: Peng Luo [aut, cre]
Maintainer: Peng Luo <luopeng@smu.edu.cn>
Repository: CRAN
Date/Publication: 2026-06-07 18:50:19 UTC

More information about AutoMLR at CRAN
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Fri, 05 Jun 2026

New package rsocsim with initial version 1.9.18
Package: rsocsim
Title: SOCSIM
Version: 1.9.18
Date: 2026-06-01
Maintainer: Tom Theile <theile@demogr.mpg.de>
Description: Tools for preparing inputs, running SOCSIM (SOCial SIMulator) demographic kinship microsimulations, and reading simulation outputs from R. The package includes helpers for creating simulation folders, downloading demographic rate schedules, starting simulations, and loading population and marriage result files.
License: GPL-3
Imports: Rcpp (>= 1.0.5), magrittr, dplyr, tidyr, utils
LinkingTo: Rcpp
Suggests: future, parallel, testthat (>= 3.0.0)
URL: https://github.com/MPIDR/rsocsim, https://mpidr.github.io/rsocsim/
BugReports: https://github.com/MPIDR/rsocsim/issues
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2026-06-01 06:20:57 UTC; Theile
Author: Tom Theile [aut, cre, cph] , Diego Alburez-Gutierrez [aut] , Mallika Snyder [aut], Liliana P. Calderon-Bernal [aut]
Repository: CRAN
Date/Publication: 2026-06-05 15:00:02 UTC

More information about rsocsim at CRAN
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New package RiskyCNV with initial version 0.1.0
Package: RiskyCNV
Title: Risk Analysis of Genomic Copy Number Variation
Version: 0.1.0
Description: Provides a complete seven-step workflow for copy number variation (CNV) analysis applicable to any disease or condition where samples with genomic copy number data is available. Supports built-in grading and risk stratification presets for seven major cancers (viz. prostate, breast, colorectal, lung, cervical, lymphoma, melanoma) based on clinically validated systems including ISUP Grade Groups, Nottingham Grading System, Dukes staging, IASLC TNM, FIGO, Ann Arbor/Lugano classification, and Breslow depth. Generalizable to other disease types. An automatic mode derives a normalised Risk Score from the data using min-max normalisation and adaptive binning. Custom user-defined thresholds are supported for any other disease type. Downstream functions for CNV aberration detection, recurrence analysis, gene annotation, CNV matrix generation, and CNV-RNA expression correlation are disease-type agnostic.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: dplyr, GenomicRanges, rlang, S4Vectors, stats, tidyr, tools, utils
Suggests: BiocManager, knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-05-14 08:37:47 UTC; ida_titus
Author: Ashok Palaniappan [aut, cre] , Priyanka Ramesh [aut], Ida Titus [aut], Sangeetha Muthamilselvan [aut]
Maintainer: Ashok Palaniappan <apalania@scbt.sastra.edu>
Repository: CRAN
Date/Publication: 2026-06-05 15:00:17 UTC

More information about RiskyCNV at CRAN
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New package nlmixr2targets with initial version 0.1.0
Package: nlmixr2targets
Title: Targets for 'nlmixr2' Pipelines
Version: 0.1.0
Description: 'nlmixr2' often has long runtimes. A pipeline toolkit tailored to 'nlmixr2' workflows leverages 'targets' and 'nlmixr2' to ease reproducible workflows. 'nlmixr2targets' ensures minimal rework in model development with 'nlmixr2' and 'targets' by simplifying and standardizing models and datasets.
License: GPL (>= 2)
URL: https://nlmixr2.github.io/nlmixr2targets/
BugReports: https://github.com/nlmixr2/nlmixr2targets/issues
Depends: R (>= 4.1)
Imports: checkmate, digest, nlmixr2est, rxode2 (>= 2.0.14), targets
Suggests: covr, knitr, nlmixr2data, rmarkdown, spelling, tarchetypes, testthat (>= 3.0.0), withr
VignetteBuilder: knitr
Encoding: UTF-8
Language: en-US
NeedsCompilation: no
Packaged: 2026-05-31 20:45:01 UTC; bill
Author: Bill Denney [aut, cre]
Maintainer: Bill Denney <wdenney@humanpredictions.com>
Repository: CRAN
Date/Publication: 2026-06-05 14:40:11 UTC

More information about nlmixr2targets at CRAN
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New package NeutroIBDAnalysis with initial version 0.1.1
Package: NeutroIBDAnalysis
Title: Neutrosophic Analysis of Incomplete Block Designs
Version: 0.1.1
Maintainer: Vinaykumar L.N. <vinaymandya123@gmail.com>
Description: Provides methods for neutrosophic analysis of variance (NANOVA) and neutrosophic analysis of covariance (NANCOVA) for interval-valued data arising from incomplete block design experiments. The package supports balanced incomplete block designs (BIBDs), partially balanced incomplete block designs (PBIBDs), and lattice designs. Functions are included for treatment comparisons, least significant difference (LSD) tests, and interval-based statistical inference under neutrosophic environments.
License: GPL (>= 2)
Encoding: UTF-8
Depends: R (>= 4.0.0)
Imports: MASS, stats
NeedsCompilation: no
Packaged: 2026-06-01 04:29:26 UTC; admin
Author: Neethu R.S. [aut, ctb], Cini Varghese [aut, ctb], Mohd Harun [aut, ctb], Anindita Datta [aut, ctb], Vinaykumar L.N. [aut, cre]
Repository: CRAN
Date/Publication: 2026-06-05 14:50:06 UTC

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New package GeoDensityR with initial version 0.1.2
Package: GeoDensityR
Title: Generate Density Rasters from Polygon and Census Data
Version: 0.1.2
Description: Creates density rasters from polygon vector data and tabular census or survey data. The package joins polygon boundaries with attribute data, calculates densities, rasterizes outputs, and exports ASCII Grid or GeoTiff rasters. Methods are based on spatial rasterization workflows implemented in the 'terra' package Hijmans (2025) <https://rspatial.github.io/terra/>.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: terra
Suggests: testthat, knitr, rmarkdown
URL: https://github.com/sahalpaladan/GeoDensityR
BugReports: https://github.com/sahalpaladan/GeoDensityR/issues
NeedsCompilation: no
Packaged: 2026-06-01 07:30:55 UTC; dell
Author: Sahal Paladan [aut, cre]
Maintainer: Sahal Paladan <sahalpaladan@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-05 15:00:22 UTC

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New package ensembleML with initial version 0.2.5
Package: ensembleML
Title: Unified Interface for Ensemble Machine Learning Methods
Version: 0.2.5
Date: 2026-05-20
Description: Provides a clean, unified interface for training, predicting, and evaluating ensemble machine learning models including Random Forest, Gradient Boosting ('XGBoost'), 'AdaBoost', and 'Bagging'. All algorithms share a consistent API: em_fit(), em_predict(), em_evaluate(), and em_tune(). Includes built-in cross-validation, feature importance, calibration diagnostics, partial dependence plots, and model comparison utilities. Methods: Breiman (2001) <doi:10.1023/A:1010933404324>; Chen and Guestrin (2016) <doi:10.1145/2939672.2939785>; Freund and Schapire (1997) <doi:10.1006/jcss.1997.1504>; Breiman (1996) <doi:10.1007/BF00058655>.
Language: en-US
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: randomForest (>= 4.7-1), xgboost (>= 1.7.0), adabag (>= 4.2), ggplot2 (>= 3.4.0), rlang (>= 1.1.0), stats, utils
Suggests: pROC (>= 1.18.0), gridExtra (>= 2.3), testthat (>= 3.0.0), knitr, rmarkdown, mlbench
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-06-01 07:29:28 UTC; acer
Author: Sadikul Islam [aut, cre]
Maintainer: Sadikul Islam <sadikul.islamiasri@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-05 15:00:07 UTC

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New package csbewma with initial version 1.0.1
Package: csbewma
Title: Cumulative Standardized Binomial EWMA for Multiple Stream Processes
Version: 1.0.1
Author: Faruk Muritala [aut, cre], Austin Brown [aut], Dhrubajyoti Ghosh [aut], Sherry Ni [aut]
Maintainer: Faruk Muritala <fmurital@students.kennesaw.edu>
Description: Implements the Cumulative Standardized Binomial Exponentially Weighted Moving Average (CSB-EWMA) control chart for monitoring multiple independent streams with binomial outcomes. Provides exact variance calculations, adaptive control limits, post-hoc identification with multiple testing corrections (Bonferroni, Holm, Benjamini-Hochberg), and visualization tools. The method is described in Muritala et al. (2026) <doi:10.48550/arXiv.2601.09968>.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 3.5)
Imports: ggplot2, stats, patchwork
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-06-01 03:15:42 UTC; fmurital
Repository: CRAN
Date/Publication: 2026-06-05 14:50:02 UTC

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New package betaStability with initial version 0.0.4
Package: betaStability
Title: Quantify the Compositional Stability of Each Community Based on a Single Sampling Event
Version: 0.0.4
Description: Quantify the stability of each community based on the beta diversity between communities gathered in a single sampling event rather than a series of continuous sampling activities.
URL: https://github.com/gaoyu19920914/betaStability/
BugReports: https://github.com/gaoyu19920914/betaStability/issues/
License: MIT + file LICENSE
Encoding: UTF-8
VignetteBuilder: knitr
Imports: BBmisc, gdm, ggplot2, glmnet, mgcv, randomForest, reshape2, stats, usedist, vegan, xgboost
Suggests: BiocManager, knitr, rioja, rmarkdown, testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-06-01 07:50:05 UTC; gaoyu
Author: Yu Gao [aut, cre, cph, fnd]
Maintainer: Yu Gao <gaoyu19920914@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-05 15:00:12 UTC

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Thu, 04 Jun 2026

New package shinyds with initial version 0.2.2
Package: shinyds
Title: 'Shiny' Bindings for Designsystemet Components
Version: 0.2.2
Description: Provides 'R' wrappers for the Designsystemet component library <https://designsystemet.no>, enabling use of Norwegian government design system components in Shiny applications. Includes web components and CSS-based HTML components with full Shiny input binding support.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: htmltools (>= 0.5.0), shiny (>= 1.7.0)
Suggests: testthat (>= 3.0.0), shinytest2, chromote, jsonlite, withr, bslib, quarto
VignetteBuilder: quarto
URL: https://github.com/novica/shinyds
BugReports: https://github.com/novica/shinyds/issues
NeedsCompilation: no
Packaged: 2026-05-31 18:16:12 UTC; novica
Author: Novica Nakov [aut, cre, cph]
Maintainer: Novica Nakov <nnovica@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-04 12:20:02 UTC

More information about shinyds at CRAN
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New package MSN with initial version 0.1.0
Package: MSN
Title: Multivariate Survival Data with Network Structures
Version: 0.1.0
Description: Implements a semi-parametric estimation framework combined with a boosting algorithm to marginally estimate the conditional cumulative distribution function of survival times given informative covariates. It then utilizes the graphical lasso method to reconstruct network structures among multivariate time-to-event variables, accommodating both multivariate outcomes measured within a single dataset and survival times integrated from heterogeneous (multi-source) datasets..
License: GPL-3
Encoding: UTF-8
Imports: MASS, glasso, survival, stats
NeedsCompilation: no
Packaged: 2026-05-31 15:38:31 UTC; Li-Pang Chen
Author: Li-Pang Chen [aut, cre]
Maintainer: Li-Pang Chen <lchen723@nccu.edu.tw>
Repository: CRAN
Date/Publication: 2026-06-04 12:10:09 UTC

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New package ggcircular with initial version 0.1.0
Package: ggcircular
Title: A 'ggplot2' Extension for Circular and Directional Data
Version: 0.1.0
Description: Provides a 'ggplot2' grammar for circular, axial and directional data, including rose diagrams, circular densities, mean directions, confidence arcs, theoretical circular distributions and movement data visualizations.
License: MIT + file LICENSE
URL: https://github.com/AurelienNicosiaULaval/ggcircular, https://aureliennicosiaulaval.github.io/ggcircular/
BugReports: https://github.com/AurelienNicosiaULaval/ggcircular/issues
Encoding: UTF-8
Language: en-US
Depends: R (>= 4.1.0)
Imports: dplyr, ggplot2, grid, rlang, scales, stats, tibble, utils, vctrs
Suggests: circular, knitr, momentuHMM, posterior, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
LazyData: true
NeedsCompilation: no
Packaged: 2026-05-31 15:45:12 UTC; aureliennicosia
Author: Aurelien Nicosia [aut, cre]
Maintainer: Aurelien Nicosia <aurelien.nicosia@mat.ulaval.ca>
Repository: CRAN
Date/Publication: 2026-06-04 12:10:03 UTC

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New package tamd with initial version 1.0.2
Package: tamd
Title: Transcendental Algorithm for Mixtures of Distributions
Version: 1.0.2
Date: 2026-05-31
Maintainer: Ernest Fokoue <epfeqa@rit.edu>
Description: Implements the Transcendental Algorithm for Mixtures of Distributions (TAMD), a penalized likelihood framework for fitting finite Gaussian mixture models. TAMD augments the Expectation-Maximization (EM) algorithm with analytic barrier terms built from the Hellinger affinity that diverge on the singular locus, actively preventing component coalescence and weight degeneracy. Provides the core TAMD fitting function, closed-form Hellinger affinity and gradient computations, the Transcendental Affinity Criterion (TAC) for geometry-aware model selection, the regularity index rho (a scalar diagnostic for mixture fit quality), and reproduction scripts for all simulation studies. Methods are described in Fokoue (2024) <doi:10.48550/arXiv.2602.03889>. See also Titterington, Smith and Makov (1985, ISBN:0-471-90510-4) and Watanabe (2009, ISBN:978-0-521-86408-7).
License: GPL-3
Encoding: UTF-8
Depends: R (>= 4.0.0)
Imports: stats, utils, MASS, mvtnorm
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-05-31 06:55:26 UTC; epfeqa
Author: Ernest Fokoue [aut, cre]
Repository: CRAN
Date/Publication: 2026-06-04 11:50:02 UTC

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New package pye with initial version 0.1.0
Package: pye
Title: Penalized Youden Index Estimator
Version: 0.1.0
Date: 2026-05-31
Description: Implements the Penalized Youden Index Estimator (PYE) and the Covariate-Adjusted Youden Index Estimator (covYI), providing a novel framework for feature and covariate selection and combination in high-dimensional binary classification problems. Methodologies are based on Salaroli and Pardo (2023) <doi:10.1016/j.chemolab.2023.104786> and an unpublished manuscript by Salaroli and Pardo (2026) under review.
License: GPL (>= 2)
Encoding: UTF-8
Depends: R (>= 4.0.0)
Suggests: knitr, rmarkdown, roxygen2, spelling, testthat (>= 3.0.0)
VignetteBuilder: knitr
Language: en-US
Imports: evmix, ggplot2, glmnet, MASS, Matrix, methods, ncvreg, OptimalCutpoints, pROC, penalizedSVM, plyr, ROCnReg, Rmpfr, sparseSVM, stats, survival
NeedsCompilation: yes
Packaged: 2026-05-31 14:24:37 UTC; claud
Author: Claudio J. Salaroli [aut, cre], Maria del Carmen Pardo [aut]
Maintainer: Claudio J. Salaroli <clasalar@ucm.es>
Repository: CRAN
Date/Publication: 2026-06-04 11:50:07 UTC

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New package phyloatlas with initial version 0.1.0
Package: phyloatlas
Title: Access to the 'Phylo-Species Atlas' of Empirical Phylogenies
Version: 0.1.0
Description: Provides convenience functions to fetch standardized phylogenetic trees and per-tree provenance metadata from the 'Phylo-Species Atlas' <https://github.com/franciscorichter/phylo-species-atlas> directly from R. The atlas is a curated collection of empirical species-level trees covering Bacteria, Archaea, and Eukaryota, organized into 62 partitions of life with tip labels normalized against a shared dictionary of standardized species identifiers. Functions load any of the standardized trees with species labels resolved from the dictionary, list available trees, and inspect per-tree provenance.
License: MIT + file LICENSE
Encoding: UTF-8
URL: https://github.com/franciscorichter/phylo-species-atlas, https://franciscorichter.github.io/phylo-species-atlas/
BugReports: https://github.com/franciscorichter/phylo-species-atlas/issues
Depends: R (>= 4.0)
Imports: ape, utils
Suggests: knitr, rmarkdown, testthat (>= 3.0.0), withr
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-05-31 14:49:51 UTC; pancho
Author: Francisco Richter [aut, cre]
Maintainer: Francisco Richter <richtf@usi.ch>
Repository: CRAN
Date/Publication: 2026-06-04 12:00:02 UTC

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New package LEAVcore with initial version 0.1.0
Package: LEAVcore
Title: Constitution of Core Collections using Length of Encoded Attribute Values
Version: 0.1.0
Description: Construct core collections using the information measure 'Length of Encoded Attribute Values' (LEAV) using qualitative and/or quantitative trait data as described by Balakrishnan and Suresh (2001a) <https://indianjournals.com/article/ijpgr-14-1-006> and (2001b) <https://indianjournals.com/article/ijpgr-14-3-005>.
License: GPL (>= 2)
Encoding: UTF-8
BuildManual: TRUE
Imports: mathjaxr, Rdpack, dplyr, stats, stratification
Suggests: EvaluateCore, knitr, rmarkdown, SampleCore, pander
Copyright: 2024-2026, ICAR-NBPGR
URL: https://github.com/aravind-j/LEAVcore https://aravind-j.github.io/LEAVcore/
BugReports: https://github.com/aravind-j/LEAVcore/issues
NeedsCompilation: no
Packaged: 2026-05-31 12:37:36 UTC; J. Aravind
Author: J. Aravind [aut, cre] , Suman Roy [aut] , Anju Mahendru Singh [aut] , ICAR-NBGPR [cph]
Maintainer: J. Aravind <j.aravind@icar.org.in>
Repository: CRAN
Date/Publication: 2026-06-04 12:00:13 UTC

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New package hoboR with initial version 1.1.0
Package: hoboR
Title: Weather Station Data Summarization and Manipulation for HOBO Data Loggers
Version: 1.1.0
Author: Ricardo I. Alcala Briseno [aut, cre], Adam Carson [ctb], Yung-Hsiang Lan [ctb], Ebba Peterson [ctb], Niklaus J. Grunwald [ctb], Jared M. LeBoldus [ctb]
Maintainer: Ricardo I. Alcala Briseno <ria5282@psu.edu>
Description: Processing of CSV files generated by HOBO weather stations and data loggers. The package automatically imports multiple HOBO data records, removes duplicate records, identifies impossible values, subsets user-defined time ranges, and summarizes environmental data.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.3.0)
Imports: dplyr, lubridate, reshape, reshape2, ggplot2, tidyr, scales
Suggests: testthat (>= 3.0.0)
URL: https://www.r-project.org, https://leboldus-lab.github.io/hoboR/
BugReports: https://github.com/LeBoldus-Lab/hoboR/issues
NeedsCompilation: no
Packaged: 2026-05-31 04:57:29 UTC; ricar
Repository: CRAN
Date/Publication: 2026-06-04 11:40:03 UTC

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New package dppca with initial version 0.1.0
Package: dppca
Title: Differentially Private Principal Component Analysis Visualization
Version: 0.1.0
Description: Provides tools for differentially private principal component analysis (PCA) visualization. It includes functions for estimating private principal component directions, constructing private scree and proportion of variance explained summaries, and visualizing two-dimensional PCA score summaries using additive and sparse histogram mechanisms. Group-wise score visualizations and an interactive 'shiny' app are also provided. Private principal component directions are based on Kim and Jung (2025) <doi:10.1002/sam.70053>. Private scree summaries use mechanisms motivated by Dwork and Roth (2014) <doi:10.1561/0400000042>, Ramsay and Spicker (2025) <doi:10.48550/arXiv.2501.14095>, and Yu, Ren and Zhou (2024) <doi:10.3150/23-BEJ1706>. Private score plot frames use smooth sensitivity quantiles from Nissim, Raskhodnikova and Smith (2007) <doi:10.1145/1250790.1250803>. Private score histograms use additive and sparse histogram ideas from Wasserman and Zhou (2010) < [...truncated...]
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.3.0)
Imports: dplyr, ggplot2, graphics, grDevices, patchwork, rARPACK, Rdpack, rlang, stats, VGAM
Suggests: knitr, rmarkdown, shiny
VignetteBuilder: knitr
LazyData: true
LazyDataCompression: xz
URL: https://github.com/yejinjo0220/dppca, https://yejinjo0220.github.io/dppca/
BugReports: https://github.com/yejinjo0220/dppca/issues
NeedsCompilation: no
Packaged: 2026-05-31 15:07:23 UTC; 82109
Author: Yejin Jo [aut, cre], Minwoo Kim [aut]
Maintainer: Yejin Jo <yejinjo0220@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-04 12:00:07 UTC

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Wed, 03 Jun 2026

New package sgmean with initial version 0.1.0
Package: sgmean
Title: Trimmed Mean Compatible with 'Statgraphics' Method
Version: 0.1.0
Description: Computes the trimmed mean using a proportional discount method on the extremes, replicating the behavior of 'Statgraphics' software. Unlike R's built-in mean() with trim, this method applies a weighted reduction to boundary values rather than removing them entirely.
License: MIT + file LICENSE
Encoding: UTF-8
URL: https://github.com/jcarlosgaviria/sgmean
BugReports: https://github.com/jcarlosgaviria/sgmean/issues
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-05-30 20:55:07 UTC; Personal
Author: Juan Carlos Gaviria Chaverra [aut, cre]
Maintainer: Juan Carlos Gaviria Chaverra <jcarlos.gaviria@udea.edu.co>
Repository: CRAN
Date/Publication: 2026-06-03 14:10:02 UTC

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New package robusttseq with initial version 0.1.0
Package: robusttseq
Title: Robust Statistical Methods with Huber Estimators
Version: 0.1.0
Author: Nair Gonzalez Sotomayor [aut, cre], Aquiles Enrique Darghan Contreras [aut]
Maintainer: Nair Gonzalez Sotomayor <njgonzalezs@unal.edu.co>
Description: Provides robust statistical methods for analyzing numeric data, including robust estimation of location and scale using Huber M-estimators and a robust two-sample t-test. Methods are based on Huber (1981, ISBN:0471418056) "Robust Statistics" and Smyth (2004) <doi:10.2202/1544-6115.1027>.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: limma, stats
NeedsCompilation: no
Packaged: 2026-05-30 17:09:41 UTC; root
Repository: CRAN
Date/Publication: 2026-06-03 14:10:07 UTC

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New package polish with initial version 0.3.1
Package: polish
Title: Polishing Content for 'Word' and 'PowerPoint'
Version: 0.3.1
Description: Set of functions to polish content for Microsoft 'Word' and 'PowerPoint' into 'OOXML'. Polishing is the conversion of the R object into an 'OOXML' representation of the object that can then be added to 'Word' or 'PowerPoint' files.
License: Apache License (>= 2)
Encoding: UTF-8
URL: https://gsk-biostatistics.github.io/polish/, https://github.com/GSK-Biostatistics/polish/
BugReports: https://github.com/GSK-Biostatistics/polish/issues/
Depends: R (>= 4.1.0)
Imports: cli, commonmark, dplyr, flextable, ggplot2, glue, gt, htmltools, magick, officer (>= 0.6.9), purrr, rlang, rmarkdown, sloop, tibble, webshot2, xml2
Suggests: testthat (>= 3.0.0), withr
NeedsCompilation: no
Packaged: 2026-05-30 17:40:34 UTC; ehh82309
Author: Romain Francois [aut], Ellis Hughes [aut, cre], Shannon Haughton [aut], GlaxoSmithKline Research & Development Limited [cph, fnd]
Maintainer: Ellis Hughes <ellis.h.hughes@gsk.com>
Repository: CRAN
Date/Publication: 2026-06-03 14:10:12 UTC

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New package twscrapeR with initial version 0.1.3
Package: twscrapeR
Title: Twitter/X Scraping via Python's 'twscrape' Library
Version: 0.1.3
Date: 2026-05-23
Description: A comprehensive R interface to Python's 'twscrape' library for scraping Twitter/X data. This package uses 'reticulate' to provide a seamless R interface to the fully functional Python 'twscrape' library. Supports searching tweets, user timelines, followers, and more, with built-in rate limiting and multi-account support. Built on top of 'twscrape' by vladkens <https://github.com/vladkens/twscrape> and inspired by 'snscrape' by JustAnotherArchivist <https://github.com/JustAnotherArchivist/snscrape>.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 3.6.0)
Imports: reticulate (>= 1.20), cli (>= 3.0.0), jsonlite
Suggests: dplyr, purrr, tibble, testthat (>= 3.0.0)
URL: https://github.com/agusnieto77/twscrapeR
BugReports: https://github.com/agusnieto77/twscrapeR/issues
NeedsCompilation: no
Packaged: 2026-05-30 02:35:27 UTC; agustin
Author: Agustin Nieto [aut, cre], Claude AI [ctb]
Maintainer: Agustin Nieto <agustin.nieto77@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-03 13:10:02 UTC

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New package regcorr with initial version 0.1.0
Package: regcorr
Title: Regression Models of Pearson Correlation Coefficient
Version: 0.1.0
Description: Provides statistical tools for evaluating how covariates influence the strength of Pearson correlation coefficients between two response variables. Supports bivariate normal and bivariate binary responses, with likelihood-based inference and bootstrap-based significance testing. The methodology is based on Dufera, Liu and Xu (2023) "Regression models of Pearson correlation coefficient" <doi:10.1080/24754269.2023.2164970>.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: stats
Suggests: testthat (>= 3.0.0)
URL: https://github.com/lonze-nb/regcorr
BugReports: https://github.com/lonze-nb/regcorr/issues
NeedsCompilation: no
Packaged: 2026-05-30 13:32:53 UTC; 34351
Author: Ze Lin [aut, cre], Bo Li [aut], Jinyao Shen [aut]
Maintainer: Ze Lin <zlin5858@163.com>
Repository: CRAN
Date/Publication: 2026-06-03 13:50:02 UTC

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New package picreg with initial version 0.1.2
Package: picreg
Title: Variable Selection using the Pivotal Information Criterion
Version: 0.1.2
Date: 2026-05-30
Description: Sparse regression and classification via the Pivotal Information Criterion (PIC), an alternative to the Bayesian Information Criterion (BIC), cross-validation, and Lasso-based tuning. The regularisation parameter is selected from a pivotal null-distribution statistic, eliminating the need for cross-validation and yielding sharper support recovery. Provides Fast Iterative Shrinkage-Thresholding Algorithm (FISTA) optimisation for the L1, Smoothly Clipped Absolute Deviation (SCAD), and Minimax Concave Penalty (MCP) penalties across six response distributions: Gaussian, binomial, Poisson, exponential, Gumbel, and Cox. Under standard sparsity assumptions, the selector achieves a phase transition for exact support recovery, analogous to results in compressed sensing. See Sardy, van Cutsem and van de Geer (2026) <doi:10.48550/arXiv.2603.04172>.
License: GPL-2
URL: https://github.com/VcMaxouuu/picreg
BugReports: https://github.com/VcMaxouuu/picreg/issues
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.6.0)
Imports: stats, graphics, grDevices, parallel, future, future.apply, Rcpp (>= 1.0.10)
LinkingTo: Rcpp, RcppArmadillo
Suggests: testthat (>= 3.0.0), knitr, rmarkdown, xfun, glmnet
VignetteBuilder: knitr
SystemRequirements: C++17
NeedsCompilation: yes
Packaged: 2026-05-30 10:45:46 UTC; maxvancutsem
Author: Maxime van Cutsem [aut, cre], Sylvain Sardy [aut]
Maintainer: Maxime van Cutsem <maxime.vancutsem@unige.ch>
Repository: CRAN
Date/Publication: 2026-06-03 13:40:02 UTC

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New package opencltools with initial version 0.8.1
Package: opencltools
Title: 'OpenCL' Tools for R Package Developers
Version: 0.8.1
Date: 2026-05-26
Description: Runtime 'OpenCL' support for R package developers: probe hardware and drivers, load and concatenate kernel sources, and manage dependency-annotated '.cl' libraries, so packages like 'nmathopencl' and other ported libraries can offer GPU acceleration without each re-implementing the same plumbing. Vignettes use the 'glmbayes' envelope-gradient example and likelihood subgradient methodology (Nygren and Nygren, 2006, <doi:10.1198/016214506000000357>).
License: GPL-2
URL: https://github.com/knygren/opencltools, https://knygren.r-universe.dev/opencltools
BugReports: https://github.com/knygren/opencltools/issues
Imports: stats, Rcpp (>= 1.1.1), RcppParallel, Rdpack (>= 0.11-0), jsonlite
LinkingTo: Rcpp, RcppArmadillo, RcppParallel
Depends: R (>= 3.5.0)
Suggests: glmbayes (>= 0.9.3), testthat (>= 3.0.0), spelling, knitr, rmarkdown
VignetteBuilder: knitr
SystemRequirements: Optional 'OpenCL' support. If available, GPU acceleration will be used; otherwise, computation runs on CPU.
Encoding: UTF-8
Language: en-US
NeedsCompilation: yes
Packaged: 2026-05-30 11:28:59 UTC; kjell
Author: Kjell Nygren [aut, cre], The R Core Team [ctb, cph] , The R Foundation [cph] , Ross Ihaka [ctb, cph] , Robert Gentleman [ctb, cph] , Simon Davies [ctb] , Morten Welinder [ctb, cph] , Martin Maechler [ctb]
Maintainer: Kjell Nygren <kjell.a.nygren@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-03 13:50:07 UTC

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New package lacunarity with initial version 0.1.0
Package: lacunarity
Title: Standard and Generalized Lacunarity for Binary Time Series
Version: 0.1.0
Depends: R (>= 3.0.1)
Description: Estimates lacunarity and generalized lacunarity for unidimensional binary time series. The lacunarity index summarizes the similarity of parts from different regions of a series at a given scale by averaging the behavior of variable size structures of zeros and ones. The generalized lacunarity concept provides an enhanced measure of the organization of the gaps over all measured scales and over the different arrangements of smaller and larger gaps in the series.
License: GPL (>= 2)
Encoding: UTF-8
Imports: zoo, plyr, stats
URL: https://github.com/Ikarobarreto/lacunarity
BugReports: https://github.com/Ikarobarreto/lacunarity/issues
Suggests: rmarkdown, knitr, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-05-30 15:06:56 UTC; ikaro.barreto
Author: Ikaro Barreto [aut, cre]
Maintainer: Ikaro Barreto <daniel.carvalho.ib@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-03 13:50:14 UTC

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New package JumpDiffSim with initial version 0.1.0
Package: JumpDiffSim
Title: Jump Diffusion Simulation and Calibration for Merton and Kou Models
Version: 0.1.0
Description: Implements the Merton (1976) <doi:10.1016/0304-405X(76)90022-2> and Kou (2002) <doi:10.1287/mnsc.48.8.1086.166> jump-diffusion models through a unified S4 object-oriented interface. Provides exact compound-Poisson asset price simulation, maximum likelihood parameter estimation with Hessian-based standard errors, Wald-type confidence intervals, European option pricing via the Merton analytic series expansion, and publication-quality diagnostic plots. All functionality operates entirely offline without market data dependencies.
License: GPL (>= 3)
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: methods, stats, ggplot2 (>= 4.0.2), numDeriv (>= 2016.8.1.1)
Suggests: knitr, pkgdown, rmarkdown, covr, testthat (>= 3.0.0)
VignetteBuilder: knitr
URL: https://kennedy2244.github.io/JumpDiffSim/, https://github.com/kennedy2244/JumpDiffSim
BugReports: https://github.com/kennedy2244/JumpDiffSim/issues
NeedsCompilation: no
Packaged: 2026-05-30 10:25:35 UTC; kenne
Author: Kennedy Titus Kayaki [aut, cre], Dohyun Oh [aut], Ju Seong Hyeon [aut], Lee Se Eun [aut], Choi Jiwoo [aut], Yuri Shin [aut]
Maintainer: Kennedy Titus Kayaki <kennedy_2244@yu.ac.kr>
Repository: CRAN
Date/Publication: 2026-06-03 13:40:08 UTC

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New package fssg with initial version 1.0.0
Package: fssg
Title: Parametric Survival Modeling in Bulk
Version: 1.0.0
Description: A simple tool for the bulk creation and testing of parametric survival models. Simply provide 'fssg' with a formula and some data, and let it identify the best distributions for you.
License: MIT + file LICENSE
URL: https://github.com/jmrothen/fssg
BugReports: https://github.com/jmrothen/fssg/issues
Encoding: UTF-8
LinkingTo: Rcpp
Imports: actuar, dplyr, extraDistr, flexsurv, magrittr, methods, Rcpp, rstudioapi, stats, survAUC, survival, SurvMetrics, tictoc, VGAM
Suggests: knitr, rmarkdown, testthat (>= 3.0.0), splines2
VignetteBuilder: knitr
Depends: R (>= 3.5)
LazyData: true
NeedsCompilation: yes
Packaged: 2026-05-30 00:17:00 UTC; jmrot
Author: John Rothen [aut, cre, cph]
Maintainer: John Rothen <jmrothen.business@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-03 13:10:08 UTC

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New package AIGRA with initial version 0.1.1
Package: AIGRA
Title: Agentic Item Generation, Review, and Analysis
Version: 0.1.1
Author: Moses O. Omopekunola [aut, cre]
Maintainer: Moses O. Omopekunola <omopekunola.m@hse.ru>
Description: Provides tools for validating, generating, reviewing, reporting, and visualising assessment item generation workflows. The package supports tabular item-bank templates, item-bank validation, 'Python'-backed agentic generation workflows, multimodal diagram generation, quality summaries, and 'HTML' reporting. External artificial intelligence services and related 'API' calls require user-supplied credentials and are not called during package checks. The workflow is informed by automatic item generation methods described by Gierl and Haladyna (2013, ISBN:9780415897518) and evidence-centered assessment design described by Mislevy et al. (2003) <doi:10.1002/j.2333-8504.2003.tb01908.x>.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: graphics, grid, reticulate, utils, grDevices,
Suggests: base64enc, png, readxl, rmarkdown, writexl
NeedsCompilation: no
Packaged: 2026-05-29 23:01:12 UTC; OMOPEKUNOLA
Repository: CRAN
Date/Publication: 2026-06-03 13:10:21 UTC

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New package pathdb with initial version 0.1.0
Package: pathdb
Title: Comprehensive Database for Pathway Enrichment Analysis
Version: 0.1.0
Description: Provides access to large-scale genomics data from the South Dakota State University's bioinformatics database, a unified platform for pathway analysis of over 13,000 organisms. It includes various gene mappings, gene characteristics, and pathway mapping data from KEGG, GOBP, GOCC, and many more pathway databases. Also provides various helper functions for processing RNA-Seq data for differential expression analysis and pathway enrichment analysis, occasionally sourced from code from Integrated Differential Expression & Pathway analysis (iDEP), developed by Ge, S.X., Son, E.W. & Yao, R. (2018) <doi:10.1186/s12859-018-2486-6>.
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
Language: en-US
Imports: DBI, dplyr, edgeR, R.utils, RSQLite, stats, utils, tools
Suggests: clusterProfiler, curl, knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
Depends: R (>= 4.1.0)
URL: https://github.com/aidanfred24/pathdb, https://aidanfred24.github.io/pathdb/
BugReports: https://github.com/aidanfred24/pathdb/issues
NeedsCompilation: no
Packaged: 2026-05-29 23:02:25 UTC; aidan
Author: Aidan Frederick [aut, cre], Xijin Ge [fnd]
Maintainer: Aidan Frederick <Aidan.Frederick@sdstate.edu>
Repository: CRAN
Date/Publication: 2026-06-03 13:00:02 UTC

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New package bayprior with initial version 0.2.12
Package: bayprior
Title: Bayesian Prior Elicitation and Diagnostics for Clinical Trials
Version: 0.2.12
Description: A toolkit for constructing, validating, and justifying Bayesian priors in clinical trial settings. Implements expert elicitation via quantile matching, the roulette method, and moment matching across six distribution families, linear and logarithmic expert pooling, prior-data conflict diagnostics including the Box p-value, surprise index, information divergence, and Mahalanobis distance, sensitivity analyses with tornado and influence heatmap plots, sceptical, robust, and power priors, and automated prior justification reports. Includes a fully modular 'Shiny' application for interactive use. Methods based on O'Hagan et al. (2006, ISBN:9780470029886), Box (1980) <doi:10.2307/2982063>, Oakley and O'Hagan (2010) <https://tonyohagan.co.uk/shelf/>, Schmidli et al. (2014) <doi:10.1111/biom.12242>, Ibrahim and Chen (2000) <doi:10.1214/ss/1009212673>, Spiegelhalter et al. (1994) <doi:10.2307/2983527>.
License: GPL-3
URL: https://github.com/ndohpenngit/bayprior
BugReports: https://github.com/ndohpenngit/bayprior/issues
Depends: R (>= 4.1.0)
Imports: cli (>= 3.6.0), config (>= 0.3.1), dplyr (>= 1.1.0), DT (>= 0.27), ggplot2 (>= 3.4.0), glue (>= 1.6.2), golem (>= 0.4.1), plotly (>= 4.10.1), purrr (>= 1.0.0), rlang (>= 1.2.0), shiny (>= 1.7.4), shinycssloaders (>= 1.0.0), shinydashboard (>= 0.7.2), shinyjs (>= 2.1.0), shinyWidgets (>= 0.7.6), stats
Suggests: htmlwidgets (>= 1.5.4), knitr (>= 1.40), patchwork (>= 1.1.0), quarto (>= 1.4), rmarkdown (>= 2.20), shinytest2 (>= 0.3.1), spelling (>= 2.2.0), testthat (>= 3.0.0), vdiffr (>= 1.0.0), withr (>= 2.5.0)
VignetteBuilder: knitr
Encoding: UTF-8
Language: en-GB
SystemRequirements: Quarto CLI (>= 1.5, https://quarto.org)
NeedsCompilation: no
Packaged: 2026-05-29 21:31:16 UTC; ndohpenn
Author: Ndoh Penn [aut, cre]
Maintainer: Ndoh Penn <ndohpenn9@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-03 13:00:08 UTC

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Tue, 02 Jun 2026

New package selectTWFE with initial version 0.2.1
Package: selectTWFE
Title: Model Selection Between TWFE and ETWFE
Version: 0.2.1
Description: Estimates both a vanilla two-way fixed effects (TWFE) model and an extended TWFE (ETWFE) model, then selects between them using Cochran's Q test for heterogeneity. When ETWFE wins, reports the heterogeneity fraction (I-squared) and cohort-time estimates with empirical Bayes shrinkage and Bonferroni multiplicity correction. Methods build on Wooldridge (2025) <doi:10.1007/s00181-025-02807-z> and Callaway and Sant'Anna (2021) <doi:10.1016/j.jeconom.2020.12.001>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: etwfe, fixest, ggplot2, scales, stats
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-05-29 15:10:18 UTC; ph3828
Author: Paul von Hippel [aut, cre]
Maintainer: Paul von Hippel <ph3828@eid.utexas.edu>
Depends: R (>= 3.5.0)
Repository: CRAN
Date/Publication: 2026-06-02 11:20:02 UTC

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New package rarefun with initial version 0.1.0
Package: rarefun
Title: Functions for Rare Events Analysis
Version: 0.1.0
Description: Functions for detecting and analyzing rare events in data. Implements isolation forest (Liu et al., 2008, <doi:10.1109/ICDM.2008.17>) and clustering for anomaly detection in time series residuals. Decomposes time series using LOESS (Locally Estimated Scatterplot Smoothing) or STL (Seasonal-Trend decomposition using LOESS). Detects marine heatwaves and cold spells following Hobday et al. (2016) <doi:10.1016/j.pocean.2015.12.014>. Provides goodness-of-fit tests for quantile regression (Haupt et al., 2011, <doi:10.1080/02664763.2011.573542>), partial dependence with quantile random forests, MCC (Matthews Correlation Coefficient) computation and testing, knee-point detection via the Kneedle algorithm (Satopaa et al., 2011, <doi:10.1109/ICDCSW.2011.20>), and spatial point matching.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: RANN, boot, dbscan, geosphere, isotree, Rdpack, parallel, pdp, stats
Suggests: testthat (>= 3.0.0), dplyr, ggplot2, heatwaveR, patchwork, quantmod, quantreg, ranger, viridis
URL: https://github.com/vlyubchich/rarefun
BugReports: https://github.com/vlyubchich/rarefun/issues
LazyData: true
NeedsCompilation: no
Packaged: 2026-05-29 16:09:36 UTC; vyach
Author: Vyacheslav Lyubchich [aut, cre] , Genevieve Nesslage [aut]
Maintainer: Vyacheslav Lyubchich <lyubchich@umces.edu>
Repository: CRAN
Date/Publication: 2026-06-02 11:10:02 UTC

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New package PFCI with initial version 0.1.0
Package: PFCI
Title: Penalized Fast Causal Inference for High-Dimensional Structure Learning
Version: 0.1.0
Date: 2026-05-28
Description: Implements Penalized Fast Causal Inference (PFCI), a two-stage causal structure learning procedure for high-dimensional settings with potential latent variables and selection bias. In the first stage, neighborhood selection via the Lasso constructs a sparse undirected skeleton. In the second stage, the Fast Causal Inference (FCI) algorithm orients edges on this reduced graph, producing a Partial Ancestral Graph (PAG) that accounts for latent confounders. The method is consistent under sparsity assumptions and substantially faster than standard FCI and RFCI in high dimensions. See Pal, Ghosh, and Yang (2025) <doi:10.48550/arXiv.2507.00173> for the underlying theory.
License: MIT + file LICENSE
Encoding: UTF-8
URL: https://github.com/djghosh1123/PFCI
BugReports: https://github.com/djghosh1123/PFCI/issues
Imports: stats, glasso, methods
Suggests: pcalg, graph, RBGL, Rgraphviz, testthat (>= 3.0.0), knitr, rmarkdown, spelling
VignetteBuilder: knitr
Language: en-US
NeedsCompilation: no
Packaged: 2026-05-29 19:16:19 UTC; dghosh3
Author: Samhita Pal [aut] , Dhrubajyoti Ghosh [aut, cre] , Shu Yang [aut]
Maintainer: Dhrubajyoti Ghosh <dghosh3@kennesaw.edu>
Repository: CRAN
Date/Publication: 2026-06-02 11:20:13 UTC

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New package mapnhanespa with initial version 0.1.0
Package: mapnhanespa
Title: Map Quantiles for Physical Activity from 'NHANES'
Version: 0.1.0
Description: Maps physical activity from the National Health and Nutrition Examination Survey ('NHANES') study into population-based quantiles.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 3.5)
LazyData: true
LazyDataCompression: xz
URL: https://github.com/jhuwit/mapnhanespa
BugReports: https://github.com/jhuwit/mapnhanespa/issues
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
Imports: dplyr, magrittr, purrr, survey
NeedsCompilation: no
Packaged: 2026-05-29 16:31:16 UTC; johnmuschelli
Author: John Muschelli [aut, cre]
Maintainer: John Muschelli <muschellij2@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-02 11:10:08 UTC

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New package childpen with initial version 0.2.3
Package: childpen
Title: Identification and Estimation of Child Penalties
Version: 0.2.3
Description: Tools to simulate child-penalty data and estimate DID, TD, and NTD identification frameworks from Leventer (2025), "Identification of Child Penalties" <doi:10.48550/arXiv.2602.07486>.
License: MIT + file LICENSE
URL: https://github.com/dorleventer/childpen, https://dorleventer.github.io/childpen/
BugReports: https://github.com/dorleventer/childpen/issues
Imports: data.table, stats
Suggests: knitr, rmarkdown, testthat (>= 3.0.0), purrr, scales, dplyr, tidyr, ggplot2
Encoding: UTF-8
VignetteBuilder: knitr
Depends: R (>= 3.5)
NeedsCompilation: no
Packaged: 2026-05-29 20:21:48 UTC; dorleventer
Author: Dor Leventer [aut, cre]
Maintainer: Dor Leventer <leventerdor@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-02 11:20:07 UTC

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New package serad with initial version 0.2.0
Package: serad
Title: Standardized Economic Reporting and Automated Dynamic Writing / Synthèse d'Écrits Avec des Règles Automatisées et Dynamiques
Version: 0.2.0
Description: Provides tools for generating dynamic and standardized economic narratives in R Markdown documents. The package is primarily designed for French-language statistical and economic publications. It includes functions to describe changes in levels, percentages, trends, accelerations and short-term economic developments using consistent linguistic rules. The package supports automated reporting workflows and reproducible economic writing. Fournit des outils permettant de générer des textes économiques dynamiques et standardisés dans des documents R Markdown. Le package est principalement conçu pour les publications statistiques et économiques en français. Il propose des fonctions permettant de décrire les évolutions de niveaux, de pourcentages, de tendances, d'accélérations et les évolutions conjoncturelles à l'aide de règles linguistiques homogènes. Le package facilite l'automatisation de la rédaction et la reproductibilité des publications économiques.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: utils, tibble
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-05-29 14:33:43 UTC; X6QOAN
Author: Alexandre Cazenave-Lacroutz [aut] , Jules Lejas [cre], Direction de l'animation de la recherche, des etudes et des statistiques [cph]
Maintainer: Jules Lejas <jules.lejas@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-02 11:00:02 UTC

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New package HOME with initial version 0.1.0
Package: HOME
Title: Harmonized Orphanhood Mortality Estimation
Version: 0.1.0
Description: Implements indirect demographic methods for estimating adult mortality from orphanhood data. The package includes the standard Brass and Hill (1973) method <https://scholar.google.com/scholar_lookup?&title=Estimating%20Adult%20Mortality%20from%20Orphanhood&pages=111-23&publication_year=1973&author=Brass%2CW.&author=Hill.%2CK.>, the regression-based approach developed by Timaeus (1992) <https://pubmed.ncbi.nlm.nih.gov/12317481/>, and the adjustments proposed by Luy (2012) <doi:10.1007/s13524-012-0101-4> for low-mortality populations. A relational model is used to harmonize estimates into comparable adult mortality indicators. The package also provides diagnostic tools to assess the sensitivity of results to assumptions about the mean age of childbearing and the choice of model life table family.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 3.5.0)
Imports: ggplot2, gridExtra
Suggests: shiny, testthat, DT, readxl, writexl, plotly, scales, bslib
URL: https://github.com/tamaravaz/HOME
BugReports: https://github.com/tamaravaz/HOME/issues
NeedsCompilation: no
Packaged: 2026-05-29 14:07:52 UTC; tvaz
Author: Tamara Vaz [aut, cre]
Maintainer: Tamara Vaz <tamaravaz.m@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-02 11:00:19 UTC

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New package ahocorasick with initial version 0.2.0
Package: ahocorasick
Title: Fast Multi-Pattern String Matching with the 'Aho-Corasick' Algorithm
Version: 0.2.0
Description: Provide fast multi-pattern string matching for 'R' using the 'Aho-Corasick' algorithm, powered by the 'Rust' 'aho-corasick' crate. It builds reusable automatons for detecting matches, counting matches, locating character, extracting matched text, and replacing matches in character vectors. For more details on the 'Aho-Corasick' algorithm, please see Aho and Corasick (1975) <doi:10.1145/360825.360855>.
License: MIT + file LICENSE
URL: https://yousa-mirage.github.io/r-ahocorasick/, https://github.com/Yousa-Mirage/r-ahocorasick
BugReports: https://github.com/Yousa-Mirage/r-ahocorasick/issues
Encoding: UTF-8
SystemRequirements: Cargo (Rust's package manager), rustc >= 1.65.0, xz
Depends: R (>= 4.2)
Imports: checkmate, cli, fs, rlang
Suggests: dplyr, knitr, pkgdown, rmarkdown, tibble, tidyr, testthat (>= 3.0.0)
VignetteBuilder: knitr
Language: en-US
NeedsCompilation: yes
Packaged: 2026-05-29 15:07:59 UTC; Yousa-Mirage
Author: Hao Cheng [aut, cre, cph]
Maintainer: Hao Cheng <Yousa-Mirage@foxmail.com>
Repository: CRAN
Date/Publication: 2026-06-02 11:00:07 UTC

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New package admixr2 with initial version 0.1.0
Package: admixr2
Title: Aggregate Data Modelling
Version: 0.1.0
Description: Fit pharmacokinetic/pharmacodynamic (PK/PD) models to aggregate-level data (mean vector and covariance matrix per study) rather than individual-level data. Integrates with the 'nlmixr2'/'rxode2' ecosystem via three estimation methods: a First-Order ('FO') analytical estimator, a Monte Carlo (MC) estimator, and an Iterative Reweighting Monte Carlo ('IRMC') estimator. Methods are based on Välitalo (2021) <doi:10.1007/s10928-021-09760-1>; software described in van de Beek et al. (2025) <doi:10.1007/s10928-025-10011-w>.
License: GPL (>= 3)
URL: https://leidenpharmacology.github.io/admixr2/, https://github.com/LeidenPharmacology/admixr2
BugReports: https://github.com/LeidenPharmacology/admixr2/issues
Encoding: UTF-8
LazyData: true
Depends: R (>= 4.1.0)
Imports: checkmate, digest, nlmixr2est, nloptr, qs2, randtoolbox, Rcpp, rxode2
LinkingTo: Rcpp, RcppEigen
Suggests: expm, furrr, future, ggplot2, knitr, mnormt, nlmixr2, patchwork, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2026-05-29 13:52:39 UTC; hidde
Author: H. van de Beek [aut, cre], P.A.J. Vaelitalo [aut], L.B. Zwep [aut], J.G.C. van Hasselt [aut]
Maintainer: H. van de Beek <h.van.de.beek@lacdr.leidenuniv.nl>
Repository: CRAN
Date/Publication: 2026-06-02 10:50:02 UTC

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New package TestNet with initial version 1.0
Package: TestNet
Title: A Method for Inferring Microbial Networks with FDR Control
Version: 1.0
Date: 2026-05-28
Description: A testing method for inferring microbial networks. It differs from existing microbial network analyses in that it provides calibrated results by controlling the false discovery rate. The method accounts for the complex features of taxa count data. It also accommodates both independent and clustered samples, offers separate linear and nonlinear tests for each pair of taxa, and includes an omnibus test that bypasses the need to specify the type of relationship for each pair of taxa.
License: GPL (>= 2)
Depends: R (>= 3.5.0)
Imports: permute, matrixStats, dcov, stats, utils
Suggests: R.rsp, testthat
URL: https://github.com/yijuanhu/TestNet
BugReports: https://github.com/yijuanhu/TestNet/issues
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2026-05-29 12:29:27 UTC; yhu30
Author: Yi-Juan Hu [aut, cre]
Maintainer: Yi-Juan Hu <yijuanhu@bicmr.pku.edu.cn>
Repository: CRAN
Date/Publication: 2026-06-02 09:40:02 UTC

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New package DENSaftertransform with initial version 0.1
Package: DENSaftertransform
Title: Estimating Density after Logarithmic or Power Transformation of Data
Version: 0.1
Description: Functions for computing: (1) the adaptive normal PI estimate for data after the logarithmic transformation; (2) single-bandwidth PI density estimate for data after the logarithmic transformation; (3) single bandwidth PI estimate for data after the power transformation. See the articles: (1) Savchuk, O. (2026, under review). Density estimation for log-transformed data; (2) Savchuk, O., Schick A. (2013). Density estimation for power transformations. Journal of Nonparametric Statistics, 25(3), 545-559 <doi:10.1080/10485252.2013.811788>.
License: GPL-2
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-05-29 12:41:48 UTC; olgay
Author: Olga Savchuk [aut, cre]
Maintainer: Olga Savchuk <olga.y.savchuk@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-02 09:40:07 UTC

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New package db2pq with initial version 0.0.4
Package: db2pq
Title: Export Database Tables to 'Parquet'
Version: 0.0.4
Description: Tools for exporting 'PostgreSQL' tables to 'Parquet' files, with support for chunked writes, column type overrides, and timezone-aware timestamp handling. Includes functions for maintaining a local 'Parquet' data library sourced from 'WRDS' (Wharton Research Data Services), with update-checking based on table metadata, and archive management utilities for versioning local data files. See Gow and Ding (2024) "Empirical Research in Accounting: Tools and Methods" <doi:10.1201/9781003456230>.
URL: https://github.com/iangow/db2pqr, https://iangow.github.io/db2pqr/
BugReports: https://github.com/iangow/db2pqr/issues
Author: Ian D. Gow [aut, cre]
Maintainer: Ian D. Gow <iandgow@gmail.com>
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: arrow, DBI, keyring, RPostgres, tibble, tools, wrds
Suggests: adbcpostgresql, adbcdrivermanager, adbi, duckdb, dplyr, dbplyr, ggplot2, knitr, nanoarrow, processx, quarto, rstudioapi, testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-05-29 13:34:03 UTC; igow
Repository: CRAN
Date/Publication: 2026-06-02 09:50:02 UTC

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New package RCtest with initial version 1.0
Package: RCtest
Title: Reality Check and Predictive Ability Tests for Forecast Evaluation
Description: Implements a comprehensive suite of statistical tests for evaluating the accuracy of forecasting models against a benchmark. The package is grounded in the reality check framework of White (2000) <doi:10.1111/1468-0262.00152>, extended by Hansen (2005) <doi:10.1198/073500105000000063> for Superior Predictive Ability (SPA), 'Giacomini' & White (2006) <doi:10.1111/j.1468-0262.2006.00718.x> for Conditional Predictive Ability (CPA), and 'Corradi' & Swanson (2006) <doi:10.1016/j.jeconom.2005.07.026> for predictive density evaluation via the 'Kullback'-'Leibler' Information Criterion ('KLIC') and 'ZP' Quantile Loss test, the Continuous Ranked Probability Score ('CRPS') ('Gneiting' & 'Raftery', 2007) <doi:10.1198/016214506000001437>, coverage tests ('Kupiec', 1995) <doi:10.3905/jod.1995.407942>, 'HAC' covariance estimation ('Newey' & West, 1987) <doi:10.2307/1913610>, and Moving Block Bootstrap resampling ('Kunsch', 1989) <doi:10.12 [...truncated...]
Imports: ggplot2, gridExtra, ggrepel, rlang, stats
Encoding: UTF-8
LazyData: true
Note: This research was funded in whole by National Science Centre, Poland, grant number 2022/45/B/HS4/00510.
Version: 1.0
Date: 2026-05-29
License: GPL-3
NeedsCompilation: no
Author: Joanna Jedrzejewska [aut, cre] , Krzysztof Drachal [ctb]
Maintainer: Joanna Jedrzejewska <j.jedrzejewska3@uw.edu.pl>
Depends: R (>= 3.5.0)
Packaged: 2026-05-29 11:34:48 UTC; joannajedrzejewska
Language: en-US
Repository: CRAN
Date/Publication: 2026-06-02 08:20:08 UTC

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New package leunbachR with initial version 0.1.0
Package: leunbachR
Title: Leunbach Test Equating
Version: 0.1.0
URL: https://github.com/pgmj/leunbachR, https://pgmj.github.io/leunbachR/
BugReports: https://github.com/pgmj/leunbachR/issues
Description: Implements the Leunbach test equating method, following the 'DIGRAM' software written by Svend Kreiner. Both direct and indirect equating are available, with parametric bootstrap standard errors and diagnostic statistics including the Goodman-Kruskal gamma test and orbit analysis for person fit. See Adroher et al. (2019) <doi:10.1186/s12874-019-0768-y> for details of the method.
License: GPL (>= 3)
Encoding: UTF-8
Depends: R (>= 3.5.0)
Suggests: knitr, rmarkdown, mirai, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-05-29 10:40:43 UTC; magnus.johansson.3
Author: Magnus Johansson [aut, cre]
Maintainer: Magnus Johansson <pgmj@pm.me>
Repository: CRAN
Date/Publication: 2026-06-02 08:20:02 UTC

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New package fussclust with initial version 0.1.0
Package: fussclust
Title: Fuzzy Unsupervised and Semi-Supervised Clustering
Version: 0.1.0
Description: Methods for distance-based fuzzy unsupervised and semi-supervised clustering, including fuzzy and possibilistic models based on alternating optimization (AO) algorithm. The package introduces a vectorized estimation framework for prototype-based fuzzy clustering algorithms, enabling modular algorithm design and extensibility. It also supports storage and retrieval of intermediate AO optimization results for downstream analysis and processing. For more details see Kmita et al. (2024) <doi:10.1109/TFUZZ.2024.3370768>.
License: MIT + file LICENSE
LazyData: true
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: rdist
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-05-29 11:52:20 UTC; user
Author: Kamil Kmita [aut, cre, cph]
Maintainer: Kamil Kmita <kamil.kmita17@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-02 08:30:02 UTC

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New package fjohansen with initial version 0.1.0
Package: fjohansen
Title: Johansen Cointegration Test with Fourier-Type Smooth Nonlinear Trends
Version: 0.1.0
Date: 2026-05-29
Maintainer: Merwan Roudane <merwanroudane920@gmail.com>
Description: Implements the Johansen cointegration test with Fourier-type smooth nonlinear deterministic trends restricted to cointegrating relations, as developed by Kurita and Shintani (2025) <doi:10.1080/07474938.2025.2530640>. Six model variants are supported: CNR (constant plus nonlinear, restricted in the cointegrating space), LNR (linear plus nonlinear, restricted), CNU (constant restricted, nonlinear unrestricted), LNU (linear restricted, nonlinear unrestricted), plus the standard constant- and linear-trend restricted Johansen models. The package also bundles the feasible generalised least squares (FGLS) Wald test of Perron, Shintani and Yabu (2017) <doi:10.1111/obes.12169> used as a frequency-selection pre-step, together with bundled critical-value tables, a vectorised simulator for the limiting distribution, publication-quality table exports (LaTeX and HTML) and 'ggplot2' figures matching those of the paper.
URL: https://github.com/merwanroudane/fjohansen
BugReports: https://github.com/merwanroudane/fjohansen/issues
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.0.0)
Imports: stats, utils, grDevices, graphics, ggplot2 (>= 3.4.0), scales
Suggests: testthat (>= 3.0.0), kableExtra, knitr, rmarkdown, patchwork
NeedsCompilation: no
Packaged: 2026-05-29 12:04:25 UTC; HP
Author: Merwan Roudane [aut, cre]
Repository: CRAN
Date/Publication: 2026-06-02 08:30:09 UTC

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New package catekappa with initial version 0.1.0
Package: catekappa
Title: Design and Analysis of Consistency Tests Based on Kappa Statistic
Version: 0.1.0
Description: Provides a 'Shiny' application and supporting functions for the design and analysis of consistency tests based on Kappa statistic with categorical responses. Wraps 'irr' and 'kappaSize' packages.
License: CC0
Encoding: UTF-8
Imports: bslib, irr, kappaSize, shiny, utils
NeedsCompilation: no
Packaged: 2026-05-29 12:12:46 UTC; z2118
Author: Gai Zheng [aut, cre], Xincheng Li [aut], Yingjie Jiangwang [aut], Panwei Zhao [aut]
Maintainer: Gai Zheng <z2118778229@163.com>
Repository: CRAN
Date/Publication: 2026-06-02 08:30:15 UTC

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New package actigraph.sleepr with initial version 0.3.1
Package: actigraph.sleepr
Title: Detect Periods of Sleep and Non-Wear in 'ActiGraph' Data
Version: 0.3.1
Description: Reads *.agd files exported from 'ActiGraph' devices; implements the Troiano (2008) <doi:10.1249/mss.0b013e31815a51b3> and Choi (2011) <doi:10.1249/MSS.0b013e3181ed61a3> algorithms for detecting periods on non-wear; implements the Sadeh (1994) <doi:10.1093/sleep/17.3.201> and Cole-Kripke (1992) <doi:10.1093/sleep/15.5.461> algorithms for detecting asleep/awake state and the Tudor-Locke (2014) <doi:10.1139/apnm-2013-0173> algorithm to detect sleep periods from asleep/awake states.
URL: https://github.com/dipetkov/actigraph.sleepr
BugReports: https://github.com/dipetkov/actigraph.sleepr/issues
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.2.4)
Imports: DBI, RcppRoll, RSQLite, dplyr (>= 1.0.1), tidyr (>= 1.1.1), assertthat, ggplot2, lubridate, purrr, rlang, zoo, magrittr, tibble, tidyselect
Suggests: covr, knitr, readr, rmarkdown, testthat, lintr
VignetteBuilder: knitr
LinkingTo: Rcpp
NeedsCompilation: yes
Packaged: 2026-05-29 12:09:55 UTC; desislp
Author: Desislava Petkova [aut, cre], John Muschelli [ctb]
Maintainer: Desislava Petkova <desislavka@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-02 08:30:20 UTC

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New package tpglp with initial version 0.1.0
Package: tpglp
Title: Three-Parameter Generalized Lindley-Poisson Distribution Functions
Version: 0.1.0
Description: Provides functions for random generation, density, cumulative distribution, quantile function, moments, and log-likelihood for a three-parameter generalized Lindley-Poisson mixture model.
License: GPL-3
Encoding: UTF-8
Imports: stats
NeedsCompilation: no
Packaged: 2026-05-29 01:51:18 UTC; nisan
Author: Nisansala Wijerathna [aut, cre], DiangLiang Deng [ths]
Maintainer: Nisansala Wijerathna <nisansaladulmini32@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-02 07:50:08 UTC

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New package telegramR with initial version 0.0.1
Package: telegramR
Title: Interact with the 'Telegram' 'MTProto' API
Version: 0.0.1
Description: Provides a full-featured client for the 'Telegram' 'MTProto' protocol (<https://core.telegram.org/api>), enabling programmatic access to 'Telegram' chats, channels, messages, media, and stories. Implements binary encoding and decoding of the 'Telegram' 'TL' (Type Language) schema, authentication (including two-factor), encrypted transport, and high-level helpers for downloading channel history and reactions at scale. Intended for social-science research and data collection tasks that require direct API access rather than the 'Bot API'.
License: MIT + file LICENSE
Encoding: UTF-8
ByteCompile: no
Depends: R (>= 3.5.0)
Imports: Rcpp (>= 1.0.0), digest (>= 0.6.37), openssl (>= 2.2.2), base64enc (>= 0.1-3), jsonlite (>= 1.8.9), R6, future, httr, logger, promises, later, bitops, gmp, xml2, mime, tibble, dplyr, callr
LinkingTo: Rcpp
Suggests: data.table, testthat (>= 3.0.0), withr, exiftoolr, fs, getPass, magick, knitr, rmarkdown, ggplot2, lubridate, tidyr, covr, devtools, readr, stringr, stopwords, RColorBrewer, scales, stringi
URL: https://romankyrychenko.github.io/telegramR/, https://github.com/RomanKyrychenko/telegramR
BugReports: https://github.com/RomanKyrychenko/telegramR/issues
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2026-05-29 05:44:10 UTC; romankyrychenko
Author: Roman Kyrychenko [aut, cre, cph]
Maintainer: Roman Kyrychenko <roman.kyrychenko@helsinki.fi>
Repository: CRAN
Date/Publication: 2026-06-02 08:00:02 UTC

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New package serodynamics with initial version 0.1.0
Package: serodynamics
Title: Modeling Longitudinal Antibody Responses to Infection
Version: 0.1.0
Description: Implements Bayesian hierarchical models for estimating antibody kinetic parameters from longitudinal serological data. Fits two-phase within-host models capturing antibody rise, peak, and decay following pathogen infection, using 'JAGS' for posterior inference. Designed as the upstream companion to the 'serocalculator' package for end-to-end seroepidemiological analysis. Methods are described in Teunis and colleagues (2016) <doi:10.1016/j.epidem.2016.04.001> and Teunis and van Eijkeren (2020) <doi:10.1002/sim.8578>.
License: MIT + file LICENSE
Encoding: UTF-8
URL: https://github.com/UCD-SERG/serodynamics, https://ucd-serg.github.io/serodynamics/
BugReports: https://github.com/UCD-SERG/serodynamics/issues
SystemRequirements: JAGS (>= 4.3.1)
Imports: cli, coda, dplyr, ggmcmc (>= 1.5.1.2), ggplot2, purrr, rlang, runjags, scales, serocalculator (>= 1.4.1), stats, tibble, tidyr, tidyselect, utils
Suggests: Hmisc, knitr, readr, rlist, sessioninfo, spelling, stringr, testthat (>= 3.0.0), tidyverse, withr, vdiffr, fs, here, rjags, rmarkdown, magrittr, rex, quarto
Language: en-US
Depends: R (>= 4.1.0)
LazyData: true
VignetteBuilder: knitr, quarto
NeedsCompilation: no
Packaged: 2026-05-28 21:59:23 UTC; samuelschildhauer
Author: Peter Teunis [aut, cph] , Samuel Schildhauer [aut, cre] , Kwan Ho Lee [aut] , Kristen Aiemjoy [aut] , Douglas Ezra Morrison [aut]
Maintainer: Samuel Schildhauer <sschildhauer@ucdavis.edu>
Repository: CRAN
Date/Publication: 2026-06-02 07:50:22 UTC

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New package RaCE.NMA with initial version 1.0.3
Package: RaCE.NMA
Title: Rank-Clustered Estimation for Network Meta-Analysis
Version: 1.0.3
Description: An implementation of the RaCE-NMA (Rank-Clustered Estimation for Network Meta-Analysis) model for post-hoc clustering of treatments or interventions by rank in network meta-analysis data. Functions for model estimation, assessment, and displaying results are provided. For more details, see Pearce and Zhou (2025) <doi:10.1017/rsm.2025.10049>.
License: GPL (>= 3)
Encoding: UTF-8
LazyData: TRUE
Imports: utils, magrittr, dplyr, invgamma, mvtnorm, coda, reshape2, ggplot2
Suggests: knitr, rmarkdown, devtools, cowplot, gridExtra
VignetteBuilder: knitr
URL: https://pearce790.github.io/RaCE.NMA/, https://github.com/pearce790/RaCE.NMA/
BugReports: https://github.com/pearce790/RaCE.NMA/issues
NeedsCompilation: no
Packaged: 2026-05-28 23:15:08 UTC; michaelpearce
Author: Michael Pearce [aut, cre, cph] , Shouhao Zhou [aut]
Maintainer: Michael Pearce <michaelpearce@reed.edu>
Depends: R (>= 3.5.0)
Repository: CRAN
Date/Publication: 2026-06-02 07:50:42 UTC

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New package blisa with initial version 0.2.0
Package: blisa
Title: Infer Cell-Cell Communication from Spatial Transcriptomics
Version: 0.2.0
Description: Identifies cell-cell communication hotspots in spatial transcriptomics data using bivariate Local Moran's I statistics on hexagonally binned cells. Provides functions for spatial weighting, ligand-receptor pair filtering, hotspot detection, and visualisation of sender-receiver cell-type interactions.
License: GPL (>= 3)
Encoding: UTF-8
Imports: sf, spdep, Matrix, SpatialExperiment, SummarizedExperiment, ComplexHeatmap, ggplot2, viridisLite, grid
VignetteBuilder: knitr
Suggests: knitr, rmarkdown
NeedsCompilation: no
Packaged: 2026-05-29 02:55:39 UTC; yuchen
Author: Yunshun Chen [aut, cre], Lei Qin [aut], Lizhong Chen [aut]
Maintainer: Yunshun Chen <yuchen@wehi.edu.au>
Repository: CRAN
Date/Publication: 2026-06-02 07:50:36 UTC

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Mon, 01 Jun 2026

New package tceper with initial version 0.1.4
Package: tceper
Title: Access the 'Open Data API' of Pernambuco Court of Accounts
Version: 0.1.4
Description: An R interface to the 'Open Data API' of the Tribunal de Contas do Estado de Pernambuco (TCE-PE), the Court of Accounts of the State of Pernambuco, Brazil. Provides tidy, ready-to-use functions to query public data on revenues, expenditures, commitments, procurement, contracts, agreements, public works, legal processes, personnel and reference tables for all state and municipal government entities in Pernambuco. All results are returned as tibbles with column names converted to 'snake_case' by default. Uses 'httr2' for HTTP requests and 'cli' for user-friendly messages. See <https://sistemas.tcepe.tc.br/DadosAbertos/> for the API documentation.
License: MIT + file LICENSE
URL: https://strategicprojects.github.io/tceper/, https://github.com/StrategicProjects/tceper
BugReports: https://github.com/StrategicProjects/tceper/issues
Encoding: UTF-8
Language: en
Depends: R (>= 4.1.0)
Imports: cli (>= 3.6.0), httr2 (>= 1.0.0), jsonlite, rlang (>= 1.1.0), tibble, purrr, janitor
Suggests: testthat (>= 3.0.0), knitr, rmarkdown, dplyr, stringr, ggplot2
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-05-28 20:33:08 UTC; leite
Author: Andre Leite [aut, cre], Marcos Wasilew [aut], Hugo Vasconcelos [aut], Carlos Amorin [aut], Diogo Bezerra [aut]
Maintainer: Andre Leite <leite@castlab.org>
Repository: CRAN
Date/Publication: 2026-06-01 14:20:02 UTC

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New package RsimdDispatch with initial version 0.1.1
Package: RsimdDispatch
Title: Runtime 'SIMD' Dispatch Templates for 'C' Code in 'R' Packages
Version: 0.1.1
Description: Provides templates and a working example for runtime Single Instruction Multiple Data ('SIMD') dispatch in 'C' code used by 'R' packages. Packages can stage scalar and architecture-specific kernel objects during configuration, then select a compiled and CPU-supported implementation at runtime through guarded function pointers. The package also vendors the header-only 'SIMDe' library for downstream packages through the 'LinkingTo' field.
License: GPL (>= 2)
Copyright: See inst/AUTHORS and inst/LICENCE.note for bundled SIMDe authorship and licensing details.
SystemRequirements: GNU make
Suggests: bench, knitr, rmarkdown, tinytest
VignetteBuilder: knitr
Encoding: UTF-8
URL: https://github.com/sounkou-bioinfo/RsimdDispatch, https://sounkou-bioinfo.github.io/RsimdDispatch/
BugReports: https://github.com/sounkou-bioinfo/RsimdDispatch/issues
NeedsCompilation: yes
Packaged: 2026-05-28 20:43:01 UTC; sounkoutoure
Author: Sounkou Mahamane Toure [aut, cre], Evan Nemerson [cph] , SIMDe contributors [ctb]
Maintainer: Sounkou Mahamane Toure <sounkoutoure@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-01 14:30:02 UTC

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New package rDeckgl with initial version 0.1.0
Package: rDeckgl
Title: R Bindings to 'Deck.gl'
Version: 0.1.0
Description: Provides R bindings for 'deck.gl', a 'WebGL' framework for rendering large interactive spatial and tabular visualizations. The package supplies 'htmlwidgets' and 'shiny' bindings, supports 'DuckDB'-backed data hydration, and bundles the JavaScript assets needed to render 'deck.gl' specifications from R.
License: MIT + file LICENSE
URL: https://github.com/TiRizvanov/rDeckgl
BugReports: https://github.com/TiRizvanov/rDeckgl/issues
Encoding: UTF-8
Language: en-US
Depends: R (>= 4.1.0)
Imports: htmlwidgets (>= 1.5.4), shiny (>= 1.7.0), jsonlite (>= 1.8.0), yaml (>= 2.3.0), DBI (>= 1.1.0), duckdb (>= 1.4.0), arrow (>= 12.0.0), base64enc (>= 0.1.3), stats
Suggests: adbcdrivermanager, nanoarrow, knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-05-28 17:02:22 UTC; timurrizvanov
Author: Timur Rizvanov [aut, cre], Edward C. Ruiz [aut], Ruben Dries [aut, rev], Dries Lab [fnd] , Boston University [fnd] )
Maintainer: Timur Rizvanov <timurr@bu.edu>
Repository: CRAN
Date/Publication: 2026-06-01 13:40:02 UTC

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New package miceDRF with initial version 0.1.0
Package: miceDRF
Title: Imputation with 'mice' and Distributional Random Forests
Version: 0.1.0
Description: Provides a custom imputation method for the 'mice' package based on distributional random forests. The package implements the 'mice.impute.DRF' method, which can be used within the standard 'mice' workflow. Missing values are imputed by estimating conditional distributions with distributional random forests and sampling observed responses using forest weights.
License: GPL-3
Encoding: UTF-8
URL: https://github.com/KrystynaGrzesiak/miceDRF, https://krystynagrzesiak.github.io/miceDRF/
BugReports: https://github.com/KrystynaGrzesiak/miceDRF/issues
Imports: drf
Suggests: mice, spelling, testthat (>= 3.0.0)
Language: en-US
NeedsCompilation: no
Packaged: 2026-05-28 17:24:23 UTC; Krysia
Author: Krystyna Grzesiak [aut, cre] , Jeffrey Naef [aut]
Maintainer: Krystyna Grzesiak <krygrz11@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-01 13:50:02 UTC

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New package corMLPE with initial version 0.1.0
Package: corMLPE
Title: Correlation Structures for Symmetric Relational Data
Version: 0.1.0
Description: Implements correlation structures for symmetric relational data (e.g. pairwise distances and dissimilarities) that interface with models using 'nlme'-style correlation structures. The maximum likelihood population effects method is described by Clarke et al. (2002) <doi:10.1198/108571102320>.
Imports: MASS, Matrix, methods, nlme, Rcpp
LinkingTo: Rcpp, RcppArmadillo
License: GPL-2
Encoding: UTF-8
Suggests: covr, testthat (>= 3.0.0)
NeedsCompilation: yes
Packaged: 2026-05-28 14:55:26 UTC; peterman.73
Author: Nathaniel Pope [aut], Bill Peterman [aut, cre]
Maintainer: Bill Peterman <peterman.73@osu.edu>
Repository: CRAN
Date/Publication: 2026-06-01 13:30:06 UTC

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New package mvBayes with initial version 1.2.1
Package: mvBayes
Title: Multivariate Bayesian Regression
Version: 1.2.1
Description: Fit, plot, and predict a multivariate response, using an arbitrary univariate Bayesian regression model to independently fit basis components (e.g., principal components) of the response (Francom et al., 2025 <DOI:10.1137/24M1644092>).
License: MIT + file LICENSE
Imports: MASS, methods, BASS, latex2exp, cli, splines
Suggests: fdasrvf, BayesPPR, knitr, rmarkdown
Encoding: UTF-8
URL: https://github.com/sandialabs/mvBayesR
BugReports: https://github.com/sandialabs/mvBayesR/issues
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-05-28 14:05:24 UTC; jdtuck
Author: Gavin Collins [aut, ctb], J. Derek Tucker [ctb, cre] , Sandia National Laboratories [cph, fnd]
Maintainer: J. Derek Tucker <jdtuck@sandia.gov>
Repository: CRAN
Date/Publication: 2026-06-01 09:10:02 UTC

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New package csemGT with initial version 1.0.0
Package: csemGT
Title: Conditional Standard Error of Measurement in Generalizability Theory
Version: 1.0.0
Description: Estimates the per-person conditional standard error of measurement (CSEM) under the persons-by-items single-facet crossed design of Generalizability Theory, following Brennan (1998) <doi:10.1177/014662169802200401>. Implements three estimators of the relative error variance (full, large_a, uncorrelated) and the closed-form absolute error variance, with both analytical and item-resampling bootstrap sampling variances, quadratic smoothing of CSEMs on observed score, D-study extrapolation, and base-graphics plotting.
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
Depends: R (>= 4.1.0)
Imports: stats, utils, graphics, grDevices
Suggests: boot, mgcv, ggplot2, knitr, rmarkdown, testthat (>= 3.0.0), vdiffr, covr, spelling, mirt, haven
VignetteBuilder: knitr
URL: https://github.com/rgempp/csemGT, https://gempp.cl/csemGT/
BugReports: https://github.com/rgempp/csemGT/issues
Language: en-GB
NeedsCompilation: no
Packaged: 2026-05-28 13:42:59 UTC; rene.gempp
Author: Rene Gempp [aut, cre, cph]
Maintainer: Rene Gempp <rene.gempp@udp.cl>
Repository: CRAN
Date/Publication: 2026-06-01 09:10:08 UTC

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New package cloudosR with initial version 0.2.0
Package: cloudosR
Title: 'Lifebit' Platform 'API' Client
Version: 0.2.0
Description: Interacts with the 'Lifebit' Platform Cohort Browser 'API' <https://cloudos.lifebit.ai>. Enables schema discovery, table exploration, and read-only 'SQL' query execution with policy-aware behavior and team-based access control for cohort data analysis. Requires bastion-enabled workspaces for 'API' access.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: httr2, jsonlite, utils
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-05-28 13:42:42 UTC; leilamansouri
Author: Leila Mansouri [aut, cre]
Maintainer: Leila Mansouri <leila.mansouri@lifebit.ai>
Repository: CRAN
Date/Publication: 2026-06-01 09:10:14 UTC

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New package XOMultinom with initial version 0.8.7
Package: XOMultinom
Title: Exact Distributions of Some Functions of the Ordered Multinomial Counts
Version: 0.8.7
Date: 2026-05-28
Maintainer: Sergio Venturini <sergio.venturini@unicatt.it>
Description: Implements exact algorithms for computing the distributions of the maximum, the minimum, the range, and the sum of the J largest order statistics of a multinomial random vector. Two complementary algorithm families are provided: the recursive tree-traversal method of Bonetti, Cirillo, and Ogay (2019) <doi:10.1098/rsos.190198>, which covers all four statistics under the equiprobable hypothesis; and the stochastic matrix method of Corrado (2011) <doi:10.1007/s11222-010-9174-3>, which handles the maximum, minimum, and range for arbitrary probability vectors. Functions for power evaluation and sample size determination for goodness-of-fit tests based on these order statistics are also provided. Computationally intensive routines are implemented in 'C++' for efficiency.
License: GPL-3
URL: https://github.com/sergioventurini/XOMultinom
BugReports: https://github.com/sergioventurini/XOMultinom/issues
Depends: R (>= 3.6.0), utils
Imports: ggplot2 (>= 3.5.1), graphics, methods, Rcpp, rlang, stats, tools
LinkingTo: Rcpp, RcppProgress
Encoding: UTF-8
LazyData: true
NeedsCompilation: yes
Packaged: 2026-05-28 09:26:17 UTC; Sergio
Author: Sergio Venturini [aut, cre], Marco Bonetti [ctb]
Repository: CRAN
Date/Publication: 2026-06-01 08:40:12 UTC

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New package tmap.sources with initial version 0.1
Package: tmap.sources
Title: Data Sources for 'tmap'
Version: 0.1
Description: Provides support for a variety of spatial data sources in 'tmap', including remote, tiled, and streaming formats. Enables the use of external vector and raster data without requiring full data import, facilitating efficient visualization workflows.
License: GPL-3
Encoding: UTF-8
Depends: R (>= 4.1)
Imports: tmap (>= 4.3), sf, httr2, jsonlite, freestiler, data.table, servr, cli
Suggests: tmap.mapgl (>= 0.2-1)
URL: https://github.com/r-tmap/tmap.sources
BugReports: https://github.com/r-tmap/tmap.sources/issues
NeedsCompilation: no
Packaged: 2026-05-28 08:29:14 UTC; mtes
Author: Martijn Tennekes [aut, cre]
Maintainer: Martijn Tennekes <mtennekes@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-01 08:40:02 UTC

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New package StochSimR with initial version 1.1.0
Package: StochSimR
Title: Stochastic Process Simulation Engine
Version: 1.1.0
Description: A modular simulation engine for a wide range of stochastic processes. Provides exact and approximate simulation methods for Poisson processes (homogeneous and inhomogeneous), Brownian motion (standard, drifted, and bridge), discrete- and continuous-time Markov chains, birth-death processes, the Yule pure-birth process, infinitesimal generator matrix utilities, Markovian queuing systems (M/M/1, M/M/c, M/M/c/K) with exact steady-state statistics, Levy processes (gamma, normal inverse Gaussian, variance-gamma, alpha-stable), Merton jump-diffusion models, Hawkes self-exciting processes, geometric Brownian motion, and Ornstein-Uhlenbeck mean-reverting diffusions. Includes variance reduction techniques (antithetic variates, control variates, importance sampling, stratified sampling), parallel simulation via the 'future' framework, rare-event simulation (cross-entropy and multilevel splitting), path visualisation, and summary statistics. Methods are based on Glasserman (2003) <doi:10.1007/ [...truncated...]
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 3.5.0)
Imports: ggplot2 (>= 3.4.0), rlang (>= 1.0.0), stats, parallel, future (>= 1.25.0), future.apply (>= 1.10.0)
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
URL: https://github.com/Ayush291202/StochSimR
BugReports: https://github.com/Ayush291202/StochSimR/issues
NeedsCompilation: no
Packaged: 2026-05-28 09:44:50 UTC; ayushkundu
Author: Ayush Kundu [aut, cre]
Maintainer: Ayush Kundu <ayushkundu25@iitk.ac.in>
Repository: CRAN
Date/Publication: 2026-06-01 08:50:13 UTC

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New package ssmooth with initial version 0.1.0
Package: ssmooth
Title: Smooth Raster Time Series
Version: 0.1.0
Description: Smooth a sequence of 'terra' rasters using various algorithms (currently moving average, weighted moving average, and exponential smoothing). Also includes wrappers to smooth a vector time-series using these same algorithms. All smoothers use 'Rcpp' implementations for performance.
Imports: terra, Rcpp
License: MIT + file LICENSE
Encoding: UTF-8
LinkingTo: Rcpp
Suggests: testthat (>= 3.0.0)
URL: https://github.com/Biodiversity-Futures-Lab/ssmooth
BugReports: https://github.com/Biodiversity-Futures-Lab/ssmooth/issues
NeedsCompilation: yes
Packaged: 2026-05-28 13:36:47 UTC; connd
Author: Connor Duffin [aut, cre], The Trustees of The Natural History Museum, London [cph]
Maintainer: Connor Duffin <c.duffin@protonmail.com>
Repository: CRAN
Date/Publication: 2026-06-01 09:00:02 UTC

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New package sphereclust with initial version 1.0
Package: sphereclust
Title: Model Based Clustering for Spherical Data Using Elliptically Symmetric Distributions
Version: 1.0
Date: 2026-05-28
Author: Michail Tsagris [aut, cre], Theodoros Perdikis [ctb]
Maintainer: Michail Tsagris <mtsagris@uoc.gr>
Depends: R (>= 4.0)
Imports: Directional, graphics, grDevices, mixture, parallel, rangen, rgl, Rfast, stats
Suggests: Rfast2
Description: Model based clustering with spherical data using mixtures of elliptically symmetric distributions, namely mixtures of spherical elliptically symmetric projected Cauchy (SESPC) or mixtures of elliptically symmetric angular Gaussian (ESAG) distributions. The relevant paper is: Perdikis T., Alharbi N. and Tsagris M. (2026). <doi:10.48550/arXiv.2605.27496>.
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2026-05-28 09:51:17 UTC; mtsag
Repository: CRAN
Date/Publication: 2026-06-01 08:50:02 UTC

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New package smqf with initial version 1.1-1
Package: smqf
Title: Statistical Methods in Quantitative Finance
Version: 1.1-1
Description: Provides data and functions used in the book "Statistical Methods in Quantitative Finance" by David Ardia (2026).
License: GPL-3
LazyData: true
Encoding: UTF-8
Depends: R (>= 4.1.0), xts
URL: https://github.com/ArdiaD/smqf-package
BugReports: https://github.com/ArdiaD/smqf-package/issues
Suggests: zoo, testthat (>= 3.0.0), PerformanceAnalytics, glmnet
Imports: graphics, stats, nloptr, pracma
NeedsCompilation: no
Packaged: 2026-05-28 13:02:31 UTC; ardiad
Author: David Ardia [aut, cre] , Marius Hofert [ctb, cph] , Kurt Hornik [ctb, cph] , Alexander J. McNeil [ctb, cph]
Maintainer: David Ardia <david.ardia.ch@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-01 09:00:07 UTC

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New package smoothbp with initial version 0.2.1
Package: smoothbp
Title: Hierarchical Piecewise Regression with Smoothed Change-Points
Version: 0.2.1
Description: Fits Bayesian hierarchical piecewise regression models with multiple logistic-smoothed change-points. Non-linear parameters (change-point locations and transition sharpness) and linear parameters can each be conditioned on covariates and factors via flexible design matrices. A random-intercept structure is supported for any parameter. Spike-and-slab regularization is supported for selecting the number of breakpoints. Posterior inference uses a Metropolis-within-Gibbs sampler implemented in 'Rust' for speed. Methods are based on the smooth transition piecewise regression model of Bacon and Watts (1971) <doi:10.2307/2334389> and variable selection spike-and-slab priors of Kuo and Mallick (1998) <https://www.jstor.org/stable/25053023>.
License: MIT + file LICENSE
Encoding: UTF-8
SystemRequirements: Cargo (Rust's package manager), rustc >= 1.65.0
Depends: R (>= 4.2)
Imports: posterior, ggplot2, stats, bridgesampling, loo, bayesplot
Suggests: testthat (>= 3.0.0), withr, knitr, rmarkdown, brms, mcp, dplyr, gt, tidyr, scales, rjags
VignetteBuilder: knitr
URL: https://github.com/ABindoff/smoothbp
BugReports: https://github.com/ABindoff/smoothbp/issues
NeedsCompilation: yes
Packaged: 2026-05-27 21:44:34 UTC; bindoffa
Author: Aidan D Bindoff [aut, cre]
Maintainer: Aidan D Bindoff <aidan.bindoff@utas.edu.au>
Repository: CRAN
Date/Publication: 2026-06-01 08:30:02 UTC

More information about smoothbp at CRAN
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New package qqkrls with initial version 1.0.0
Package: qqkrls
Title: Quantile-on-Quantile Kernel Regularized Least Squares
Version: 1.0.0
Description: Implements Quantile-on-Quantile Kernel-Based Regularized Least Squares (QQKRLS) as in Adebayo, Ozkan and Eweade (2024) <doi:10.1016/j.jclepro.2024.140832>. Combines Kernel-Based Regularized Least Squares (KRLS) of Hainmueller and Hazlett (2014) <doi:10.1093/pan/mpt019> with the Quantile-on-Quantile regression of Sim and Zhou (2015) <doi:10.1016/j.jbankfin.2015.01.013>: for each quantile theta of the independent variable the response is fit by KRLS on the corresponding sub-sample and the tau-quantile of the resulting pointwise marginal effects yields beta(theta, tau). Standard errors come from a paired bootstrap. Visualisations use the 'MATLAB' 'Parula' colour map by default.
License: GPL-3
Encoding: UTF-8
Depends: R (>= 3.5.0)
Imports: KRLS (>= 1.0-0), plotly (>= 4.0.0), stats, utils, grDevices
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
URL: https://github.com/merwanroudane/qqkrlsr
BugReports: https://github.com/merwanroudane/qqkrlsr/issues
NeedsCompilation: no
Packaged: 2026-05-28 12:45:49 UTC; HP
Author: Merwan Roudane [aut, cre, cph], Tomiwa Sunday Adebayo [ctb] , Jens Hainmueller [ctb] , Chad Hazlett [ctb]
Maintainer: Merwan Roudane <merwanroudane920@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-01 09:00:14 UTC

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New package PPCSexRx with initial version 0.1.0
Package: PPCSexRx
Title: Prescribe Sub-Symptom Exercise for Adolescent Concussion
Version: 0.1.0
Description: A clinical decision support system for sub-symptom threshold aerobic exercise (SSTAE) prescription in adolescents with persistent post-concussion symptoms (PPCS). Implements an evidence-based protocol derived from a systematic review of seven studies (Li, 2026; <doi:10.17605/osf.io/kvuf6>), encoding safety screening, Buffalo Concussion Treadmill Test (BCTT)-guided heart rate prescription, session-level progress tracking, and evidence disclosure using the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) framework into an open-source tool for athletic trainers and clinicians. Designed to support implementation in resource-limited settings where BCTT equipment may be unavailable. GRADE certainty of evidence: LOW. For clinician use only; not a substitute for clinical judgement.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: graphics, utils
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
URL: https://github.com/guangl10/PPCSexRx
BugReports: https://github.com/guangl10/PPCSexRx/issues
NeedsCompilation: no
Packaged: 2026-05-27 21:09:57 UTC; liguang
Author: Guang Li [aut, cre]
Maintainer: Guang Li <guangli@isu.edu>
Repository: CRAN
Date/Publication: 2026-06-01 08:30:15 UTC

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New package opencesp with initial version 0.4.0
Package: opencesp
Title: Generation and Evaluation of Synthetic Tabular Datasets
Version: 0.4.0
Maintainer: Remy Chapelle <remy.chapelle@universite-paris-saclay.fr>
Description: Various tools developed as part of the Open-CESP (Centre de recherche en Epidémiologie et Santé des Populations) initiative to generate and evaluate synthetic datasets for statistical disclosure control. This includes tools to investigate the risk-utility tradeoff achievable with given synthesis methods, as well as statistical tools to estimate (conditional) probability distributions. The main eventual aim is to help researchers and statisticians disseminate open research data.
License: GPL-3
URL: https://opencesp.vjf.inserm.fr/en
Encoding: UTF-8
NeedsCompilation: yes
Imports: stats, cluster, rpart, parallel, fastmap, PCAmixdata, randomForest, mice
Suggests: gbm
Language: en-US
Packaged: 2026-05-27 22:04:49 UTC; remyc
Author: Remy Chapelle [aut, cre] , Centre de recherche en Epidemiologie et Sante des Populations [cph]
Repository: CRAN
Date/Publication: 2026-06-01 08:30:09 UTC

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New package nVennR2 with initial version 2.0.1
Package: nVennR2
Title: An Interface to 'nVenn2'
Version: 2.0.1
Date: 2026-05-15
Description: Creates quasi-proportional Venn diagrams with an arbitrary number of sets. It is related to the old 'nVennR' package, but the algorithm and use have been reworked.
License: MIT + file LICENSE
Imports: Rcpp (>= 1.0.14)
LinkingTo: Rcpp
Encoding: UTF-8
Suggests: knitr, rmarkdown, rsvg, graphics, grImport2, testthat (>= 3.0.0)
Depends: R (>= 4.1)
LazyData: true
VignetteBuilder: knitr
URL: https://github.com/vqf/nVennR2
BugReports: https://github.com/vqf/nVennR2/issues
NeedsCompilation: yes
Packaged: 2026-05-28 13:20:55 UTC; vqf
Author: Victor Quesada [aut, cre, cph]
Maintainer: Victor Quesada <quesadavictor@uniovi.es>
Repository: CRAN
Date/Publication: 2026-06-01 09:00:20 UTC

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New package mqqr with initial version 1.0.0
Package: mqqr
Title: Multivariate Quantile-on-Quantile Regression
Version: 1.0.0
Description: Implements Multivariate Quantile-on-Quantile Regression (m-QQR) of Sinha, Ghosh, Hussain, Nguyen and Das (2023) <doi:10.1016/j.eneco.2023.107021>, extending the bivariate Quantile-on-Quantile regression of Sim and Zhou (2015) <doi:10.1016/j.jbankfin.2015.01.013> to include exogenous moderators and controls with optional interaction terms. For each pair of quantile levels (theta of the response and tau of the regressor) the package fits a locally-weighted quantile regression of y on the principal regressor x, a lagged dependent variable, moderators Z and the x*Z interaction terms, using Gaussian kernel weights on the empirical cumulative distribution function (CDF) distance. Bootstrap standard errors and Koenker-Machado pseudo R-squared are reported. Visualisations include 'MATLAB'-style 'Parula' and 'Jet' 3D surfaces, heatmaps and contour plots through 'plotly'.
License: GPL-3
Encoding: UTF-8
Depends: R (>= 3.5.0)
Imports: quantreg (>= 5.0), plotly (>= 4.0.0), stats, utils, grDevices
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
URL: https://github.com/merwanroudane/multiqqr
BugReports: https://github.com/merwanroudane/multiqqr/issues
NeedsCompilation: no
Packaged: 2026-05-28 12:54:19 UTC; HP
Author: Merwan Roudane [aut, cre, cph], Avik Sinha [ctb] , Nicholas Sim [ctb] , Hongtao Zhou [ctb]
Maintainer: Merwan Roudane <merwanroudane920@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-01 09:00:26 UTC

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New package mqqcause with initial version 1.0.0
Package: mqqcause
Title: Multivariate Quantile-on-Quantile Granger Causality
Version: 1.0.0
Description: Implements bivariate and Multivariate Quantile-on-Quantile Granger causality tests building on the Quantile-on-Quantile regression framework of Sim and Zhou (2015) <doi:10.1016/j.jbankfin.2015.01.013> and the quantile Granger causality test of Troster (2018) <doi:10.1080/07474938.2016.1172400>. The bivariate test estimates the local-linear slope in the quantile regression of y_t on lagged x_t with lagged y_t as control, using Gaussian kernel weights, and tests it against zero by paired bootstrap. The multivariate (conditional) test additionally conditions on a set of moderators Z and optional x times Z interaction terms, in the spirit of Sinha, Ghosh, Hussain, Nguyen and Das (2023) <doi:10.1016/j.eneco.2023.107021>. A Sup-Wald summary across the quantile grid is also provided. Heatmaps and 3D surfaces default to the 'MATLAB' 'Parula' colour map.
License: GPL-3
Encoding: UTF-8
Depends: R (>= 3.5.0)
Imports: quantreg (>= 5.0), plotly (>= 4.0.0), stats, utils, grDevices
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
URL: https://github.com/merwanroudane/qqcaus
BugReports: https://github.com/merwanroudane/qqcaus/issues
NeedsCompilation: no
Packaged: 2026-05-28 13:02:20 UTC; HP
Author: Merwan Roudane [aut, cre, cph], Avik Sinha [ctb] , Nicholas Sim [ctb] , Hongtao Zhou [ctb]
Maintainer: Merwan Roudane <merwanroudane920@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-01 09:00:31 UTC

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New package eiIT with initial version 0.0.1-1
Package: eiIT
Title: Ecological Inference via Information Theory
Version: 0.0.1-1
Description: Estimates RxC transfer matrices from aggregated marginal data using a two-stage (GME+IPF) information-theoretic approach within a two-step (global+local) estimation procedure. The resulting matrices are consistent with observed row and column marginals across collections of subtables (e.g. precincts, polling stations, or districts). References: Golan, A., Judge, G., & Miller, D. (1996). Maximum Entropy Econometrics: Robust Estimation with Limited Data. Wiley. Judge, G., Miller, D.J., & Cho, W.K.T. (2004). An information theoretic approach to ecological estimation and inference. In G. King, O. Rosen, & M. A. Tanner (Eds.), Ecological Inference: New Methodological Strategies (pp. 162–187). Cambridge University Press. Mittelhammer, R., Judge, G., & Miller, D. (2000). Econometric Foundations. Cambridge University Press. Pavia, J.M. (2023) <doi:10.1007/s43545-023-00658-y> Acknowledgements: The author wish to thank Conselleria de Economia, Hacienda y Administracion Publ [...truncated...]
License: GPL (>= 2)
Encoding: UTF-8
Imports: stats, utils, nloptr
Suggests: ggplot2, scales
NeedsCompilation: no
Packaged: 2026-05-27 17:23:34 UTC; pavia
Author: Jose M. Pavia [aut, cre]
Maintainer: Jose M. Pavia <jose.m.pavia@uv.es>
Repository: CRAN
Date/Publication: 2026-06-01 08:40:07 UTC

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New package CSwR with initial version 0.1.3
Package: CSwR
Title: Companion to the Book "Computational Statistics with R"
Version: 0.1.3
Description: Provides data sets and functions used in the book "Computational Statistics with R" (<https://cswr.nrhstat.org>).
Depends: R (>= 3.5.0)
Imports: bench, ggplot2, rlang
Suggests: covr, spelling, testthat (>= 2.1.0)
Encoding: UTF-8
LazyData: true
Language: en-US
URL: https://jolars.github.io/CSwR-Package/, https://cswr.nrhstat.org/
BugReports: https://github.com/jolars/CSwR-Package/issues
License: MIT + file LICENSE
NeedsCompilation: no
Packaged: 2026-05-28 07:19:54 UTC; jola
Author: Niels Richard Hansen [aut] , Johan Larsson [aut, cre]
Maintainer: Johan Larsson <johan@jolars.co>
Repository: CRAN
Date/Publication: 2026-06-01 08:40:20 UTC

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New package connector.sharepoint with initial version 0.1.0
Package: connector.sharepoint
Title: 'Microsoft SharePoint' Interface for the 'connector' Package
Version: 0.1.0
Description: Extends the 'connector' package to provide a convenient interface for accessing and interacting with 'Microsoft SharePoint' directly from 'R'. Supports listing, reading, writing, uploading, downloading, and removing files and directories on 'SharePoint' document libraries. Authentication is handled through 'Azure' tokens via the 'AzureAuth' package.
License: Apache License (>= 2)
URL: https://novonordisk-opensource.github.io/connector.sharepoint/, https://github.com/novonordisk-opensource/connector.sharepoint
BugReports: https://github.com/NovoNordisk-OpenSource/connector.sharepoint/issues
Depends: R (>= 4.1.0)
Imports: AzureAuth, checkmate, cli, connector (>= 1.0.0), Microsoft365R, R6, tools, zephyr, rlang
Suggests: knitr, rmarkdown, testthat (>= 3.0.0), tibble, withr, whirl (>= 0.2.0), glue, mockery
VignetteBuilder: knitr, rmarkdown
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-05-28 10:07:34 UTC; vlob
Author: Vladimir Obucina [aut, cre] , Cervan Girard [aut], Aksel Thomsen [aut], Steffen Falgreen Larsen [aut], Novo Nordisk A/S [cph]
Maintainer: Vladimir Obucina <vlob@novonordisk.com>
Repository: CRAN
Date/Publication: 2026-06-01 08:50:06 UTC

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New package BayesRTMB with initial version 0.1.1
Package: BayesRTMB
Title: Bayesian Inference Using 'RTMB'
Version: 0.1.1
Description: Provides tools for Markov chain Monte Carlo (MCMC) and Maximum A Posteriori (MAP) estimation utilizing the 'RTMB' package. It supports various statistical models including generalized linear mixed models, factor analysis, item response theory, and multidimensional unfolding. The package allows users to easily transition between frequentist and Bayesian paradigms using a unified interface. Automatic differentiation and Laplace approximation follow Kristensen et al. (2016) <doi:10.18637/jss.v070.i05>, and MCMC sampling uses the No-U-Turn Sampler described by Hoffman and Gelman (2014) <https://jmlr.org/papers/v15/hoffman14a.html>.
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-US
LazyData: true
Depends: R (>= 4.1.0), RTMB
Imports: R6, MASS
URL: https://github.com/norimune/BayesRTMB, https://norimune.github.io/BayesRTMB/
BugReports: https://github.com/norimune/BayesRTMB/issues
Suggests: knitr, rmarkdown, GPArotation, future, future.apply, progressr
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-05-28 07:39:58 UTC; norimune
Author: Hiroshi Shimizu [aut, cre]
Maintainer: Hiroshi Shimizu <simizu706@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-01 08:40:26 UTC

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Sat, 30 May 2026

New package ViralEntropR with initial version 0.6.2
Package: ViralEntropR
Title: A Computational Pipeline for Entropy-Informed Detection of Emerging Viral Variants
Version: 0.6.2
Description: Implements an entropy-informed pipeline for detecting emerging variants in viral amino acid sequence data, extending prior clustering-based approaches including hemagglutinin clustering methods (Li et al., 2015) <doi:10.1142/9789814667944_0018>. Provides a fully vectorized FASTA preprocessing toolkit covering header parsing, two-pass date and country extraction, ambiguous-residue filtering, and integer encoding under a 25-symbol amino acid alphabet. Computes per-site Shannon entropy across user-defined cumulative, sliding, or disjoint temporal partitions and clusters per-site entropy values using Gaussian mixture models via 'mclust' (Scrucca et al., 2016) <doi:10.32614/RJ-2016-021>. Quantifies temporal distributional shifts between partitions using the Hellinger distance (van der Vaart, 1998) <doi:10.1017/CBO9780511802256>, and detects temporal change points non-parametrically using energy statistics (Matteson and James, 2014) <doi:10.1080/01621459.2013.849605> [...truncated...]
License: MIT + file LICENSE
Language: en-GB
Date: 2026-05-07
URL: https://github.com/vadimtyuryaev/ViralEntropR, https://doi.org/10.5281/zenodo.19040165, https://vadimtyuryaev.github.io/ViralEntropR/
BugReports: https://github.com/vadimtyuryaev/ViralEntropR/issues
Encoding: UTF-8
LazyData: true
Imports: ggplot2 (>= 3.4.0), grDevices, HDcpDetect, ecp, kableExtra, lubridate, magrittr, mclust, rlang, stats, stringr, utils, zoo
Suggests: Biostrings, DT, dplyr, here, knitr, readxl, rmarkdown, R.rsp, testthat (>= 3.0.0)
VignetteBuilder: knitr, R.rsp
NeedsCompilation: no
Packaged: 2026-05-27 18:20:05 UTC; vadim
Author: Vadim Tyuryaev [aut, cre] , Jane Heffernan [aut], Hanna Jankowski [aut]
Maintainer: Vadim Tyuryaev <vadim.tyuryaev@gmail.com>
Depends: R (>= 3.5.0)
Repository: CRAN
Date/Publication: 2026-05-30 13:40:21 UTC

More information about ViralEntropR at CRAN
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New package tmfast with initial version 0.1.1
Package: tmfast
Title: Fast Topic Models Using Varimax
Version: 0.1.1
Description: Fits topic models using varimax-rotated principal component analysis (PCA), following the "vintage factor analysis" approach of Rohe & Zheng (2020) <doi:10.48550/arXiv.2004.05387>. Leverages truncated PCA via 'irlba' for sparse matrices, enabling fast model fitting on large corpora. Includes an information-theoretic approach to vocabulary selection, 'broom'-compatible tidiers for extracting word-topic and topic-document matrices into a tidy data workflow, and samplers for constructing simulated corpora for benchmarking and method evaluation.
License: GPL (>= 3)
Encoding: UTF-8
Imports: assertthat, purrr, dplyr, tidyr, magrittr, rlang, stringr, tibble, tidyselect, irlba, tidytext, glue, Matrix, generics, psych, cli
Suggests: testthat (>= 3.0.0), knitr, rmarkdown, ggbeeswarm, ggplot2, Rtsne, umap, lpSolve, janeaustenr, stm, tictoc, furrr, reshape2, tmfast.realbooks
Additional_repositories: https://dhicks.github.io/drat/
VignetteBuilder: knitr
URL: https://dhicks.github.io/tmfast/, https://github.com/dhicks/tmfast
BugReports: https://github.com/dhicks/tmfast/issues
NeedsCompilation: no
Packaged: 2026-05-27 18:09:22 UTC; danhicks
Author: D. Hicks [aut, cre, cph]
Maintainer: D. Hicks <hicks.daniel.j@gmail.com>
Depends: R (>= 4.1.0)
Repository: CRAN
Date/Publication: 2026-05-30 13:40:02 UTC

More information about tmfast at CRAN
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New package TemporalHazard with initial version 1.0.3
Package: TemporalHazard
Title: Temporal Parametric Hazard Modeling
Version: 1.0.3
URL: https://ehrlinger.github.io/temporal_hazard/, https://github.com/ehrlinger/temporal_hazard
BugReports: https://github.com/ehrlinger/temporal_hazard/issues
Description: Provides native R implementations of the multiphase parametric hazard model of Blackstone, Naftel, and Turner (1986) <doi:10.1080/01621459.1986.10478314> with a focus on behavioral parity, transparent numerics, and reproducible validation against reference outputs from the original 'C'/'SAS' HAZARD program, originally developed at the University of Alabama at Birmingham (UAB). The 'SAS'/'C' code and this R package are currently developed and maintained at The Cleveland Clinic Foundation, and the R code was wholly developed at The Cleveland Clinic Foundation. The generalized temporal decomposition family extends to longitudinal mixed-effects settings (Rajeswaran et al. 2018 <doi:10.1177/0962280215623583>). The package is intentionally implemented in pure R first; performance-critical paths may later be accelerated with 'Rcpp' without changing the public interface.
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-US
VignetteBuilder: quarto
Depends: R (>= 4.1.0)
Imports: survival
Suggests: covr, ggplot2, knitr, lintr, numDeriv, pkgdown, quarto, roxygen2, rmarkdown, scales, testthat (>= 3.0.0)
LazyData: true
NeedsCompilation: no
Packaged: 2026-05-27 16:10:29 UTC; ehrlinj
Author: John Ehrlinger [aut, cre, cph]
Maintainer: John Ehrlinger <john.ehrlinger@gmail.com>
Repository: CRAN
Date/Publication: 2026-05-30 13:30:08 UTC

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New package scanCP with initial version 0.1.0
Package: scanCP
Title: Deep Learning–Based Changepoint Detection with Local Neural Models
Version: 0.1.0
Description: Implementation of deep learning–based changepoint detection algorithm designed for time series with smooth local fluctuations. The method fits localized feed‑forward neural networks to approximate the underlying smooth component and constructs a residual‑based detector that isolates abrupt structural changes. A fully data‑adaptive empirical cumulative distribution function (ECDF) based thresholding rule and refinement procedures yield accurate changepoint localization without parametric assumptions on noise or trend structure.
License: GPL-2
Encoding: UTF-8
Imports: plotly, RSNNS, foreach, doSNOW, parallel, pracma, stats, magrittr, tidyr
NeedsCompilation: no
Packaged: 2026-05-27 18:21:15 UTC; arman
Author: Arman Azizyan [aut, cre], Abolfazl Safikhani [aut]
Maintainer: Arman Azizyan <arman.azizyan@gmail.com>
Repository: CRAN
Date/Publication: 2026-05-30 13:40:08 UTC

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New package kronxNBC with initial version 0.1.1
Package: kronxNBC
Title: Clock of Regimes Naive Bayes Classifier (Student-t)
Version: 0.1.1
Description: Computes and fits a heavy-tailed Student-t Naive Bayes classifier for non-stationary financial market regime analysis (Clock of Regimes, COR). The core innovation is a profile grid search over the degrees-of-freedom parameter nu that prevents numerical underflow and structural classification failures when identifying fat-tailed Stress regimes. Provides S3 methods for fitting, prediction, summarising, plotting, and parameter extraction.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: stats, graphics, utils, naivebayes
Suggests: zoo, testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-05-27 19:22:36 UTC; olinaresmd
Author: Oscar Linares [aut, cre]
Maintainer: Oscar Linares <olinares@umich.edu>
Repository: CRAN
Date/Publication: 2026-05-30 13:50:02 UTC

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New package griddy with initial version 0.1.0
Package: griddy
Title: Geospatial Distribution Dynamics for Simple Features
Version: 0.1.0
Description: Tools for exploratory geospatial distribution dynamics with 'sf' objects and tidy data. Provides pooled and time-specific classification of longitudinal spatial values, classic discrete Markov transition matrices, spatial Markov matrices conditioned on spatial-lag classes, endpoint and adjacent rank mobility summaries, and 'ggplot2' visualizations. Methods follow Rey (2001) <doi:10.1111/j.1538-4632.2001.tb00444.x> and Rey et al. (2016) <doi:10.1007/s10109-016-0234-x>; design is inspired by the Python 'PySAL' 'giddy' package <https://pysal.org/giddy/>.
URL: https://github.com/dshkol/griddy, https://dshkol.github.io/griddy/
BugReports: https://github.com/dshkol/griddy/issues
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-US
Depends: R (>= 4.2)
Imports: dplyr, ggplot2, rlang, scales, sf, spdep, tibble, tidyr
Suggests: cancensus, knitr, microbenchmark, pkgdown, rmarkdown, sfdep, spData, testthat (>= 3.0.0), tidycensus
VignetteBuilder: knitr
LazyData: true
NeedsCompilation: no
Packaged: 2026-05-27 16:36:40 UTC; dmitryshkolnik
Author: Dmitry Shkolnik [aut, cre]
Maintainer: Dmitry Shkolnik <shkolnikd@gmail.com>
Repository: CRAN
Date/Publication: 2026-05-30 13:30:02 UTC

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New package fiber with initial version 0.1.2
Package: fiber
Title: S7 Data Structures for Diffusion MRI Tractography
Version: 0.1.2
Description: Provides three S7 classes — streamline, bundle, and bundle_set — for representing diffusion MRI tractography data in R, together with a concise set of methods for computing shape descriptors (arc-length, curvature, torsion, sinuosity), the Hausdorff distance between streamlines, arc-length reparametrization of streamlines and bundles onto uniform grids, combination of streamlines or bundles into a single bundle, combination of bundles from multiple subjects or sessions into a bundle_set, and coercion to and from the dwiFiber S4 class of the 'dti' package. See Dell'Acqua, F., Descoteaux, M. and Leemans, A. (2024) "Handbook of Diffusion MR Tractography" <doi:10.1016/C2018-0-02520-7> for more about the mathematical and computational underpinnings of diffusion MRI tractography.
License: MIT + file LICENSE
Encoding: UTF-8
URL: https://github.com/tractoverse/fiber, https://tractoverse.github.io/fiber/
BugReports: https://github.com/tractoverse/fiber/issues
Imports: cli, methods, S7
Suggests: dti, tinytest
LinkingTo: cpp11
NeedsCompilation: yes
Packaged: 2026-05-27 17:37:49 UTC; stamm-a
Author: Aymeric Stamm [aut, cre]
Maintainer: Aymeric Stamm <aymeric.stamm@cnrs.fr>
Repository: CRAN
Date/Publication: 2026-05-30 13:40:15 UTC

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New package courieR with initial version 0.2.0
Package: courieR
Title: Migrate Installed R Packages Between R Versions
Version: 0.2.0
Description: Detects all R installations on the current machine and migrates installed R packages between them. Provides find_routes() to discover R versions, manifest() to scan package libraries via 'subprocess', inventory() to compare two libraries, and ship() to install packages into a target R version using 'pak'. Includes a Shiny dashboard (open_hub()) for interactive one-way and two-way migration.
License: MIT + file LICENSE
URL: https://github.com/lennon-li/courieR
BugReports: https://github.com/lennon-li/courieR/issues
Language: en-US
Encoding: UTF-8
Imports: processx (>= 3.8.0), callr (>= 3.7.0), pak (>= 0.7.0), jsonlite (>= 1.8.0), desc (>= 1.4.0), fs (>= 1.6.0), cli (>= 3.6.0), data.table (>= 1.14.0), shiny (>= 1.8.0), bslib (>= 0.7.0), bsicons (>= 0.1.2), DT (>= 0.31), stringr (>= 1.5.0)
Suggests: testthat (>= 3.0.0), withr (>= 3.0.0), mockery (>= 0.4.4), knitr (>= 1.45), rmarkdown (>= 2.26)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-05-27 14:08:51 UTC; yeli
Author: Lennon Li [aut, cre]
Maintainer: Lennon Li <yeli@biostats.ai>
Repository: CRAN
Date/Publication: 2026-05-30 13:20:02 UTC

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New package bean with initial version 0.2.0
Package: bean
Title: Data Thinning of Species Occurrences in Environmental Space
Version: 0.2.0
Maintainer: Paanwaris Paansri <paanwaris@vt.edu>
Description: A suite of tools to mitigate sampling bias in species occurrence records by thinning data in the environmental space (E-space). This process can improve the accuracy and precision of species distribution models (SDM, also known as ecological niche models, ENM). The package offers a data-driven protocol to determine thinning parameters using kernel-density bandwidth selection. Two thinning methods are provided (stochastic and deterministic) to reduce over-sampled environmental conditions and down-weight outlier observations. The name 'bean' reflects the core principle of the method: each 'pod' (a grid cell in E-space) is allowed to contain only a limited number of 'beans' (occurrence points). See Silverman (1986, ISBN:978-0-412-24620-3) and Rousseeuw and Leroy (2003, ISBN:978-0-471-48855-2) for the underlying statistical methods.
License: MIT + file LICENSE
URL: https://github.com/paanwaris/bean, https://paanwaris.github.io/bean/
BugReports: https://github.com/paanwaris/bean/issues
Encoding: UTF-8
LazyData: true
Depends: R (>= 4.0)
Imports: MASS, stats, terra
Suggests: covr, knitr, rmarkdown, testthat (>= 3.0.0), ggplot2, rgl
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-05-27 14:37:15 UTC; paanw
Author: Paanwaris Paansri [cre, aut] , Luis E. Escobar [aut, ctb]
Repository: CRAN
Date/Publication: 2026-05-30 13:50:07 UTC

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New package ThSQCA with initial version 2.0.0
Package: ThSQCA
Title: Threshold-Sweep QCA
Version: 2.0.0
Description: Provides threshold sweep methods for Qualitative Comparative Analysis ('QCA'). Implements Condition Threshold Sweep-Single (CTS-S), Condition Threshold Sweep-Multiple (CTS-M), Outcome Threshold Sweep (OTS), and Dual Threshold Sweep (DTS) for systematic exploration of threshold calibration effects on crisp-set 'QCA' results. These methods extend traditional robustness approaches by treating threshold variation as an exploratory tool for discovering causal structures. Also provides Fiss (2011) <doi:10.5465/amj.2011.60263120> core/peripheral condition classification via compute_fiss_core() and generate_fiss_chart(), enabling four-symbol configuration charts that distinguish core conditions (present in both parsimonious and intermediate solutions) from peripheral conditions (intermediate only). Built on top of the 'QCA' package by Dusa (2019) <doi:10.1007/978-3-319-75668-4>, with function arguments following 'QCA' conventions. Based on set-theoretic methods by Ragin (2008) < [...truncated...]
Depends: R (>= 4.0)
Imports: QCA
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
License: MIT + file LICENSE
URL: https://github.com/im-research-yt/ThSQCA, https://doi.org/10.5281/zenodo.17899390
BugReports: https://github.com/im-research-yt/ThSQCA/issues
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2026-05-27 14:10:22 UTC; yukit
Author: Yuki Toyoda [aut, cre], Japan Society for the Promotion of Science [fnd]
Maintainer: Yuki Toyoda <yuki.toyoda.ds@hosei.ac.jp>
Repository: CRAN
Date/Publication: 2026-05-30 09:00:08 UTC

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New package texanshootR with initial version 0.1.0
Package: texanshootR
Title: Reproducible Audit Trails for Indefensible Research
Version: 0.1.0
Description: Provides a structured, terminal-first interface for exploratory model search, including transformation grids, predictor-subset enumeration, interaction screening, principled- sounding sample restrictions, outcome engineering, and model-form escalation (polynomial / spline wraps, robust M-estimation, generalized linear model (GLM) family swaps, random-intercept lifts). Persistent run history, achievement tracking, and reportable output generators (manuscript, presentation, funding letter, graphical abstract, reviewer response) are included.
License: MIT + file LICENSE
URL: https://gillescolling.com/texanshootR/, https://github.com/gcol33/texanshootR
BugReports: https://github.com/gcol33/texanshootR/issues
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: cli, yaml, jsonlite, stats, utils, tools, splines, Rcpp
LinkingTo: Rcpp
Suggests: ggplot2, officer, rmarkdown, xml2, quarto, tinytex, withr, testthat (>= 3.0.0), knitr, pkgdown
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2026-05-27 09:21:36 UTC; Gilles Colling
Author: Gilles Colling [aut, cre]
Maintainer: Gilles Colling <gilles.colling051@gmail.com>
Repository: CRAN
Date/Publication: 2026-05-30 08:30:02 UTC

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New package StatisticTeach1 with initial version 0.1.0
Package: StatisticTeach1
Title: Interactive Tool for Statistics and Probability Teaching
Version: 0.1.0
Description: A 'shiny' application designed to support the learning of basic concepts in statistics and probability. Provides an interactive interface that allows students to explore and visualize descriptive statistics, frequency tables, and probability distributions intuitively.
License: GPL-3
Imports: descriptr, DescTools, dplyr, ggplot2, magrittr, mixdist, RColorBrewer, readxl, rlang, shiny, shinyBS, shinydashboard, shinyjs, shinyWidgets, tibble, tidyr, colourpicker
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-05-26 23:05:32 UTC; jdelahoz
Author: Javier De La Hoz Maestre [cre, aut] , Humberto Llinas Solano [aut]
Maintainer: Javier De La Hoz Maestre <jdelahoz@unimagdalena.edu.co>
Repository: CRAN
Date/Publication: 2026-05-30 08:20:02 UTC

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New package nomads with initial version 0.0.1
Package: nomads
Title: Nomadic Pectoral Sandpiper Movement Data
Version: 0.0.1
Description: Provides satellite tracking data from nomadic pectoral sandpipers published in Kempenaers and Valcu (2017) <doi:10.1038/nature20813>. The data can also serve as benchmark data for clustering movement tracks.
License: CC BY 4.0
Encoding: UTF-8
Depends: R (>= 4.0)
Suggests: data.table
LazyData: true
NeedsCompilation: no
Packaged: 2026-05-27 14:57:35 UTC; mihai
Author: Mihai Valcu [aut, cre] , Bart Kempenaers [ctb]
Maintainer: Mihai Valcu <mvalcu@gwdg.de>
Repository: CRAN
Date/Publication: 2026-05-30 09:00:02 UTC

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Fri, 29 May 2026

New package LangevinFlow with initial version 0.1.0
Package: LangevinFlow
Title: Langevin Diffusion Samplers with a C++ Backend
Version: 0.1.0
Description: Provides lightweight, dependency-minimal implementations of Langevin diffusion based Markov chain Monte Carlo samplers, including the Unadjusted Langevin Algorithm (ULA) and the Metropolis-Adjusted Langevin Algorithm (MALA). The core sampling loops are written in C++ via 'Rcpp' and 'RcppArmadillo' for performance, while exposing a simple R-level interface where the user supplies the gradient of the negative log-density (and, for MALA, the negative log-density itself). Intended as a building block for Bayesian inference and stochastic optimization rather than a full probabilistic programming framework. Methods follow Roberts and Tweedie (1996) <doi:10.2307/3318418> and Roberts and Rosenthal (1998) <doi:10.1111/1467-9868.00123>.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 3.5.0)
Imports: Rcpp (>= 1.0.0), stats, graphics
LinkingTo: Rcpp, RcppArmadillo
Suggests: testthat (>= 3.0.0), knitr, rmarkdown, covr
VignetteBuilder: knitr
URL: https://github.com/BehroozMoosavi/LangevinFlow
BugReports: https://github.com/BehroozMoosavi/LangevinFlow/issues
NeedsCompilation: yes
Packaged: 2026-05-26 20:57:48 UTC; behroozmoosavi
Author: Behrooz Moosavi [aut, cre]
Maintainer: Behrooz Moosavi <bem159@pitt.edu>
Repository: CRAN
Date/Publication: 2026-05-29 12:30:03 UTC

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New package ElicitationWizard with initial version 0.1.0
Package: ElicitationWizard
Title: LLM-Based Bayesian Prior Elicitation Wizard
Version: 0.1.0
Date: 2026-05-18
Description: 'Shiny' application for eliciting Bayesian prior distributions using large language models (LLMs). Supports multiple LLM experts, linear opinion pooling, and the Delphi method for iterative consensus. For more details see J. R. Falconer et al. (2022) <doi:10.1287/deca.2022.0451> and D. Selby et al. (2025) <doi:10.1002/sta4.70054>.
License: MIT + file LICENSE
Encoding: UTF-8
URL: https://github.com/JefferyAyiti/Automated_Elicitation
BugReports: https://github.com/JefferyAyiti/Automated_Elicitation/issues
Imports: shiny, bslib, ellmer, future, promises, shinyjs, commonmark
Suggests: testthat (>= 3.0.0), knitr, rmarkdown, pak
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-05-26 20:38:28 UTC; griff
Author: Jeffery A. Kportufe [aut, cre]
Maintainer: Jeffery A. Kportufe <ayitikpo@rptu.de>
Repository: CRAN
Date/Publication: 2026-05-29 12:30:08 UTC

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New package climniche with initial version 0.0.1
Package: climniche
Title: Niche Climate Exposure
Version: 0.0.1
Description: Assesses niche climate exposure by interpreting projected climate change relative to the climate conditions a species currently occupies. Using occurrence records, range data or thresholded SDM suitability maps, current environmental rasters and future projections, the package separates climate change amount, change in distance to the current niche centre, composition change and exceedance beyond an empirical niche boundary.
License: GPL (>= 3)
URL: https://github.com/Bohao0813/climniche, https://bohao0813.github.io/climniche/
BugReports: https://github.com/Bohao0813/climniche/issues
Encoding: UTF-8
Imports: grid, methods
Suggests: ggplot2, knitr, patchwork, raster, rmarkdown, terra
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-05-26 13:11:44 UTC; Bohao He
Author: Bohao He [aut, cre]
Maintainer: Bohao He <bohao.he@polimi.it>
Repository: CRAN
Date/Publication: 2026-05-29 12:20:02 UTC

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New package okBATHTUB with initial version 0.1.10
Package: okBATHTUB
Title: Empirical Reservoir Eutrophication Modelling with Oklahoma Calibration
Version: 0.1.10
Description: Empirical reservoir water quality modelling using Walker's 'BATHTUB' Model 1 (second-order available-phosphorus sedimentation) from Walker (1985) <https://hdl.handle.net/11681/13884> and Walker (1996) <https://hdl.handle.net/11681/4353> as the default retention model. The Vollenweider (1976) hydraulic- residence form and the equivalent formulation of Larsen and Mercier (1976) are available as alternatives. Predicts in-lake total phosphorus, total nitrogen, chlorophyll-a, and Secchi depth from tributary nutrient and hydraulic loading inputs, and computes Carlson (1977) <doi:10.4319/lo.1977.22.2.0361> Trophic State Indices. Optional Oklahoma-specific chlorophyll and Secchi regression coefficients are provided, calibrated from publicly available state lake monitoring data. Supports single-segment and multi-segment reservoir configurations and load-reduction scenario analysis. Designed to complement watershed loading models such as the Soil and Water Assessment Tool ('SWA [...truncated...]
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: utils
Suggests: ggplot2 (>= 3.4.0), dplyr (>= 1.1.0), tidyr (>= 1.3.0), stringr (>= 1.5.0), knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
LazyData: true
URL: https://0011235813.github.io/Oklahoma-BATHTUB/, https://github.com/0011235813/Oklahoma-BATHTUB
BugReports: https://github.com/0011235813/Oklahoma-BATHTUB/issues
NeedsCompilation: no
Packaged: 2026-05-23 15:22:21 UTC; 364483
Author: Jordon Henderson [aut, cre, cph]
Maintainer: Jordon Henderson <jordon.henderson@owrb.ok.gov>
Repository: CRAN
Date/Publication: 2026-05-29 11:30:02 UTC

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New package inequantiles with initial version 0.1.0
Package: inequantiles
Title: Quantile-Based Inequality Indicators for Complex Survey Data
Version: 0.1.0
Description: Estimates quantile-based inequality indicators from complex survey data, including the quantile ratio index (QRI), quintile share Ratio (QSR), Palma ratio, and percentile ratios, together with the Gini coefficient. Influence functions are provided for linearization and variance estimation, along with a rescaled bootstrap for complex sampling designs. Estimation from grouped data is also supported. See Scarpa et al. (2025) <doi:10.1093/jssam/smaf024> for details.
License: MIT + file LICENSE
URL: https://silviascarpa.github.io/inequantiles/, https://github.com/silviascarpa/inequantiles/
BugReports: https://github.com/silviascarpa/inequantiles/issues/
Encoding: UTF-8
Language: en-US
Depends: R (>= 3.5)
LazyData: true
Imports: Rdpack
Suggests: knitr, rmarkdown, ggplot2, scales, kableExtra, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-05-26 12:52:36 UTC; scarp
Author: Silvia Scarpa [aut, cre, cph] , Stefan Sperlich [aut]
Maintainer: Silvia Scarpa <silvia.scarpa@unimore.it>
Repository: CRAN
Date/Publication: 2026-05-29 12:00:02 UTC

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New package EraBrewer with initial version 0.2.0
Package: EraBrewer
Title: Color Palettes from the Album Covers of Each Taylor Swift Era
Version: 0.2.0
URL: https://s-m.ac/EraBrewer/, https://github.com/mathias-sm/EraBrewer
BugReports: https://github.com/mathias-sm/EraBrewer/issues
Description: Provides discrete and continuous color palettes derived from the album cover artwork of each Taylor Swift Era. Each palette ships with a curated order-of-use so that smaller discrete subsets remain harmonious, and supports continuous interpolation via 'grDevices::colorRampPalette()' for arbitrary 'n'. Designed to plug into 'ggplot2' workflows through standard manual and gradient scales.
License: CC0
Encoding: UTF-8
Language: en-US
Imports: ggplot2, grDevices
Suggests: knitr, rmarkdown, ragg
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-05-23 19:38:37 UTC; msm
Author: Mathias Sable-Meyer [aut, cre, cph] , Sandra Reinert [aut]
Maintainer: Mathias Sable-Meyer <mat-git@s-m.ac>
Repository: CRAN
Date/Publication: 2026-05-29 11:30:20 UTC

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New package saCI with initial version 0.1.0
Package: saCI
Title: Stochastic Approximation Confidence Interval for Correlation
Version: 0.1.0
Description: Implements stochastic approximation method for constructing nonparametric confidence intervals for correlation coefficient, based on Xiong & Xu (2016).
License: GPL (>= 3)
Encoding: UTF-8
Imports: boot, MASS, mvtnorm
Suggests: testthat (>= 3.0.0), shiny
NeedsCompilation: no
Packaged: 2026-05-26 06:54:10 UTC; 14482
Author: Pengyu Chen Group1 [aut, cre]
Maintainer: Pengyu Chen Group1 <1448207797@qq.com>
Repository: CRAN
Date/Publication: 2026-05-29 10:40:02 UTC

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New package potentiomap with initial version 0.1.0
Package: potentiomap
Title: Build Potentiometric Surfaces and Flow Arrows
Version: 0.1.0
Author: Elvin Cordero [aut, cre]
Maintainer: Elvin Cordero <elvin.cordero@seamountgeo.com>
Description: Builds potentiometric surface products from groundwater monitoring data. The package prepares groundwater observations from direct water-level measurements or depth-to-water data paired with land-surface elevations, interpolates thin-plate spline surfaces by default, supports alternative and user-supplied interpolation methods, exports raster and contour products, and derives hydraulic-gradient flow arrows. Raster operations use methods from Hijmans (2025) <doi:10.32614/CRAN.package.terra>, thin-plate spline interpolation uses methods from Nychka et al. (2021) <doi:10.5065/D6W957CT>, and geostatistical interpolation uses methods from Pebesma (2004) <doi:10.1016/j.cageo.2004.03.012>.
License: GPL-3
Encoding: UTF-8
LazyData: true
Depends: R (>= 4.1)
Imports: fields, grDevices, graphics, gstat, sf, stats, terra
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-05-25 04:22:47 UTC; ec
Repository: CRAN
Date/Publication: 2026-05-29 10:10:02 UTC

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New package ModLR with initial version 0.1.29
Package: ModLR
Title: Information-Theoretic Approach for Moderation Analysis
Version: 0.1.29
Description: Provides a robust implementation of information-theoretic moderation analysis using multi-model inference based on Akaike's Information Criterion (AIC) and its small-sample corrected form (Corrected AIC). The package enables researchers to compare competing model specifications and helps distinguish true interaction effects from nonlinear relationships that may produce spurious moderation. The methods build on Daryanto (2019) <doi:10.1016/j.jbusres.2019.06.012>.
License: MIT + file LICENSE
Encoding: UTF-8
URL: https://github.com/ahdar1/ModLR
Imports: stats, ggplot2, broom, lmtest, sandwich, rlang
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-05-24 15:44:51 UTC; antob
Author: Ahmad Daryanto [aut, cre]
Maintainer: Ahmad Daryanto <ahdar_2000@yahoo.com>
Repository: CRAN
Date/Publication: 2026-05-29 10:10:08 UTC

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New package GREENREG with initial version 0.1.0
Package: GREENREG
Title: Tool for Statistical and Environmental Analysis
Version: 0.1.0
Description: Provides a set of accessible and automated functions to apply statistical models such as Simple Linear Regression (RLS, from the Spanish 'Regresión Lineal Simple'), Multiple Linear Regression (RLM, from the Spanish 'Regresión Lineal Múltiple'), Generalized Linear Models (GLM), and time series analysis through Autoregressive Integrated Moving Average (ARIMA) models. Designed to support teaching at the Universidad Autónoma Chapingo, it facilitates results interpretation and assumption validation through automatic graphical diagnostics. Methods for regression and time series are based on Montgomery et al. (2021, ISBN:978-1119570141) and Box & Jenkins (1970, ISBN:978-0816211043).
License: GPL-3
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.5)
Imports: ggplot2, ggrepel, stats, lmtest,
Suggests: pROC, broom, car, rmarkdown, tseries
NeedsCompilation: no
Packaged: 2026-05-25 03:56:12 UTC; dbaza
Author: Dayron Jared Bazan Guzman [aut, cre]
Maintainer: Dayron Jared Bazan Guzman <dbazanguzman@gmail.com>
Repository: CRAN
Date/Publication: 2026-05-29 10:10:14 UTC

More information about GREENREG at CRAN
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New package BioIndex with initial version 0.6.4
Package: BioIndex
Title: Biological Indicators and Indices for MEDITS Survey Data
Version: 0.6.4
Date: 2026-04-29
Author: Walter Zupa [aut, cre], Loredana Casciaro [rev], Cosmidano Neglia [rev], Isabella Bitetto [rev], Maria Teresa Spedicato [aut]
Maintainer: Walter Zupa <zupa@fondazionecoispa.org>
Description: Supports the standardized analysis of Mediterranean International Bottom Trawl Survey (MEDITS) data and the calculation of biological indicators for selected species and population components. The package provides functions to estimate abundance and biomass indices, analyse size structure and length frequency distributions, derive sex ratio and maturity related metrics, explore spatial patterns, and assess temporal trends across surveys. Developed for integration within the Regional Database for Fisheries (RDBFIS) framework, it is intended to work on quality checked input data and to produce reproducible outputs that can support monitoring, comparative analyses among Geographical Sub-Areas (GSAs) and countries, and fishery management.
License: GPL-3
Encoding: UTF-8
LazyData: TRUE
LazyDataCompression: xz
Depends: R (>= 4.1)
Imports: dplyr, ggplot2, gridExtra, hms, magrittr, marmap, methods, mgcv, reshape2, shiny, shinyjs, stringr, terra, tidyterra, zip
Suggests: knitr, mapproj, maps (>= 3.4.1), rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-05-25 16:18:21 UTC; Walter
Repository: CRAN
Date/Publication: 2026-05-29 10:30:02 UTC

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New package acsmoe with initial version 0.1.0
Package: acsmoe
Title: Propagate Uncertainty for ACS Tabular Estimates
Version: 0.1.0
Description: Utilities for propagating uncertainty in American Community Survey tabular workflows that use published estimates and margins of error, following U.S. Census Bureau derived-estimate guidance and complementing 'tidycensus' margin-of-error workflows. Includes covariance-aware derived estimates, simulation helpers, geographic aggregation, confidence-interval conversion, and reliability diagnostics.
License: MIT + file LICENSE
URL: https://dshkol.github.io/acsmoe/, https://github.com/dshkol/acsmoe
BugReports: https://github.com/dshkol/acsmoe/issues
Encoding: UTF-8
Language: en-US
Imports: stats
Suggests: dplyr, ggplot2, knitr, rmarkdown, scales, sf, testthat (>= 3.0.0), tidycensus
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-05-26 02:01:42 UTC; dmitryshkolnik
Author: Dmitry Shkolnik [aut, cre]
Maintainer: Dmitry Shkolnik <shkolnikd@gmail.com>
Repository: CRAN
Date/Publication: 2026-05-29 10:40:07 UTC

More information about acsmoe at CRAN
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New package varGuid with initial version 0.1.4
Package: varGuid
Title: Variance-Guided Regression for Heteroscedastic Linear Models
Version: 0.1.4
Date: 2026-05-23
Author: Sibei Liu [aut], Min Lu [aut, cre]
Maintainer: Min Lu <luminwin@gmail.com>
License: GPL (>= 2)
Depends: R (>= 3.5.0)
Imports: glmnet, lmtest, sandwich
Description: Fits variance-guided linear regression models for heteroscedastic data using an iteratively reweighted least squares estimator or an iteratively reweighted lasso estimator. This CRAN release focuses on the global linear mean-variance model in Section 2 of the accompanying preprint <doi:10.36227/techrxiv.177004877.75352102/v1>. The grouping-based nonlinear prediction extension from Section 3 is available in the development version on GitHub.
Encoding: UTF-8
LazyData: true
URL: https://github.com/luminwin/varGuid
BugReports: https://github.com/luminwin/varGuid/issues
NeedsCompilation: no
Packaged: 2026-05-23 02:20:00 UTC; minlu
Repository: CRAN
Date/Publication: 2026-05-29 09:30:02 UTC

More information about varGuid at CRAN
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New package shinyStep with initial version 0.5.1
Package: shinyStep
Title: User-Editable R Functions in 'Shiny' Apps with a Step Debugger
Version: 0.5.1
Description: A pair of 'Shiny' modules that let end users of a 'Shiny' application author their own R functions directly in the browser. Host apps can expose these modules as extension points where user-supplied code augments or replaces built-in logic, without requiring users to modify the app's source. Each module embeds an 'Ace' editor with a structured argument table, an in-frame R console rooted in the paused function's local environment, and a step debugger that handles for, while, repeat, and if/else blocks at any nesting depth. Two module flavours are provided: solo editors for testing a function in isolation with literal argument values, and embedded editors for pausing a function mid-execution inside a larger host program.
License: MIT + file LICENSE
Encoding: UTF-8
URL: https://github.com/zhangh12/shinyStep
BugReports: https://github.com/zhangh12/shinyStep/issues
Imports: shiny (>= 1.7.0), shinyAce (>= 0.4.0)
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-05-23 04:07:15 UTC; zhhan
Author: Han Zhang [aut, cre]
Maintainer: Han Zhang <zhangh.ustc@gmail.com>
Repository: CRAN
Date/Publication: 2026-05-29 09:30:07 UTC

More information about shinyStep at CRAN
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New package schmear with initial version 0.1.0
Package: schmear
Title: Build Structured Data Frame Subtypes
Version: 0.1.0
Description: Provides developer-focused helper functions and S3 classes to ease the creation of structured subtypes of data frames. Developers can require certain columns and types to be present, and can enforce crossing and nesting relationships between values in different columns. Type-specific metadata and attributes are preserved through common data frame manipulations.
Imports: rlang, cli, vctrs
Suggests: dplyr, pillar, testthat (>= 3.0.0)
License: MIT + file LICENSE
Encoding: UTF-8
URL: https://corymccartan.com/schmear/, https://github.com/CoryMcCartan/schmear
BugReports: https://github.com/CoryMcCartan/schmear/issues
NeedsCompilation: no
Packaged: 2026-05-22 23:34:42 UTC; cmccartan
Author: Cory McCartan [aut, cre, cph]
Maintainer: Cory McCartan <mccartan@psu.edu>
Repository: CRAN
Date/Publication: 2026-05-29 09:30:11 UTC

More information about schmear at CRAN
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New package RSSRMR with initial version 0.1.0
Package: RSSRMR
Title: Robust Self-Representation Sparse Reconstruction and Manifold Regularization
Version: 0.1.0
Description: Feature selection and clustering classification under the presence of multivariate outliers in high-dimensional unlabeled data.
License: GPL-3
Encoding: UTF-8
Imports: robustbase, stats
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-05-23 07:09:27 UTC; cvalley
Author: Abdul Wahid [aut, cre]
Maintainer: Abdul Wahid <ab_wahid1996@yahoo.com>
Repository: CRAN
Date/Publication: 2026-05-29 09:50:07 UTC

More information about RSSRMR at CRAN
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New package PPTS with initial version 1.0
Package: PPTS
Title: Point Process Time Series
Version: 1.0
Date: 2026-05-09
Author: Daniel Gervini [aut, cre], Simon Kopischke [aut]
Maintainer: Daniel Gervini <gervini@uwm.edu>
Description: Provides functions for point process time series. Autocorrelation functions for spatial and temporal time series, and estimation of trend-plus-seasonality models for temporal and spatial time series. See Gervini (2025) <doi:10.1111/jtsa.70018> and Gervini and Kopischke (2026) <doi:10.48550/arXiv.2605.21884>.
License: MIT + file LICENSE
LazyData: true
NeedsCompilation: no
Depends: R (>= 3.5.0)
Packaged: 2026-05-23 03:05:56 UTC; simonkopischke
Repository: CRAN
Date/Publication: 2026-05-29 09:30:16 UTC

More information about PPTS at CRAN
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New package pcreg with initial version 0.1.0
Package: pcreg
Title: Advanced Methods for Principal Component Analysis and Principal Component Regression
Version: 0.1.0
Author: Dr. Pramit Pandit [aut, cre], Dr. Halagundegowda G R [aut], Dr. Kamidi Rahul [aut], Dr. S. Gandhi Doss [aut]
Description: Provides a unified framework for principal component analysis (PCA) and principal component regression (PCR), including standard PCA, sparse PCA, robust PCA, and supervised PCA. The package supports automatic selection of the number of components using cumulative variance and elbow methods and integrates PCA with regression modelling through PCR models. It includes tools for PCA suitability assessment using Bartlett's test of sphericity and the Kaiser-Meyer-Olkin (KMO) measure. Visualisation utilities such as scree plots and biplots are provided for interpretation. The methods are designed to handle multicollinearity, outliers, and high-dimensional data, making them suitable for applied statistical modelling and data analysis. The methodology is based on established approaches described in Jolliffe (2002) <doi:10.1007/b98835>, Zou et al. (2006) <doi:10.1111/j.1467-9868.2005.00503.x>, and Hubert et al. (2005) <doi:10.1198/004017004000000563>.
License: GPL-3
Encoding: UTF-8
Imports: stats, ggplot2, ggrepel, gridExtra, scales, psych, elasticnet, robustbase, grid
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-05-24 16:17:56 UTC; prami
Maintainer: Dr. Pramit Pandit <pramitpandit@gmail.com>
Repository: CRAN
Date/Publication: 2026-05-29 09:50:02 UTC

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New package multiswc with initial version 0.1.2
Package: multiswc
Title: Multi-Regime Marginal Structural Cox Model for Multi-Way Treatment Switching in Oncology Clinical Trials with Survival Endpoints
Version: 0.1.2
Description: Estimate the causal effect of sustained treatment strategies on overall survival in clinical trials with possible treatment crossover and switch to subsequent therapy. Simulate faithful longitudinal clinical trials data with survival endpoints and multi-way treatment switches allowing for time-dependent prognostic factors. For more on methodological background, please see: Keogh and colleagues (2021) <doi:10.1002/bimj.202000040> and Suarez and colleagues (2008) <doi:10.1016/j.jclinepi.2007.11.007>.
License: MIT + file LICENSE
Imports: nnet, survival
Encoding: UTF-8
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
URL: https://github.com/tonyhbc/multiswc
BugReports: https://github.com/tonyhbc/multiswc/issues
NeedsCompilation: no
Packaged: 2026-05-25 03:13:12 UTC; tonyhchen
Author: Haobin Chen [aut, cre], Yuxuan Chen [aut], Philip He [aut]
Maintainer: Haobin Chen <tony.haobin.chen@alumni.emory.edu>
Repository: CRAN
Date/Publication: 2026-05-29 10:00:02 UTC

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New package adjustr with initial version 0.2.0
Package: adjustr
Encoding: UTF-8
Title: Stan Model Adjustments and Sensitivity Analyses using Importance Sampling
Version: 0.2.0
Description: Assess the sensitivity of a Bayesian model (fitted using 'Stan' via 'rstan', 'brms', or 'cmdstanr') to the specification of its likelihood and priors. Users provide a series of alternate sampling specifications, and the package uses Pareto-smoothed importance sampling (PSIS) to estimate posterior quantities of interest under each specification, without needing to refit the model. Methods are based on Vehtari, Simpson, Gelman, Yao, and Gabry (2024) <doi:10.48550/arXiv.1507.02646>.
License: MIT + file LICENSE
Depends: R (>= 3.6.0), dplyr (>= 1.0.0)
Imports: rlang, tidyselect, rstan, loo
Suggests: ggplot2, extraDistr, tidyr, testthat, covr, knitr, rmarkdown
URL: https://corymccartan.com/adjustr/
BugReports: https://github.com/CoryMcCartan/adjustr/issues
LazyData: true
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-05-22 22:09:00 UTC; cmccartan
Author: Cory McCartan [aut, cre, cph]
Maintainer: Cory McCartan <mccartan@psu.edu>
Repository: CRAN
Date/Publication: 2026-05-29 09:20:02 UTC

More information about adjustr at CRAN
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Thu, 28 May 2026

New package evacpath with initial version 0.1.0
Package: evacpath
Title: Least-Cost Pedestrian Evacuation Modeling
Version: 0.1.0
Description: Tools for road-constrained, least-cost pedestrian evacuation modeling. The package provides reusable functions for preparing hazard zones, generating road-based evacuation origin points, identifying escape/safety points, creating slope-based conductance surfaces, calculating least-cost distance to safety, and converting distance outputs into evacuation-time polygons. It is designed to support workflows like tsunami evacuation modeling while remaining adaptable to other regions and hazards. Tsunami-specific helpers support separate land-only hazard zones, water-combined escape zones, road-aware escape boundaries, and study-area inset cropping for quality assurance and quality control. Methods build on Cordero et al. (2025) <doi:10.1007/s44367-025-00018-y>, Lewis (2021) <doi:10.1007/s10816-021-09522-w>, and Joseph Lewis's 'leastcostpath' package (2023) <https://CRAN.R-project.org/package=leastcostpath>.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1)
Imports: terra, leastcostpath, utils
Suggests: knitr, rmarkdown, testthat (>= 3.0.0), devtools, fields
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-05-22 17:19:23 UTC; ec
Author: Elvin Cordero [aut, cre]
Maintainer: Elvin Cordero <elvin.cordero1@upr.edu>
Repository: CRAN
Date/Publication: 2026-05-28 18:50:02 UTC

More information about evacpath at CRAN
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New package Dcurvature with initial version 0.0.3
Package: Dcurvature
Title: Discrete Curvature with 'shiny' Explorer
Version: 0.0.3
Description: Implements discrete curvature estimation for ordered planar point sequences using circumcenter geometry on consecutive triplets, exposed through compiled C plus plus (C++) code via 'Rcpp' for speed and numerical robustness. The package is useful for objective elbow detection in multivariate workflows, especially principal component analysis (PCA), where selecting the number of retained components can be subjective. It provides a 'shiny' interface that supports upload of raw datasets or explained-variance tables, computes Kaiser-Meyer-Olkin (KMO) sampling-adequacy diagnostics, evaluates individual and cumulative variance curves, and reports curvature- based decision rules (m* and m**) with visual summaries for reproducible component-selection decisions. References: Arney et al. (2001); Axler (2024) <doi:10.1007/978-3-031-41026-0>; Bjorklund (2019) <doi:10.1111/evo.13835>; Burden and Faires (2015); Chang et al. (2023) <https://CRAN.R-project.org/package=shiny>; Christen [...truncated...]
License: MIT + file LICENSE
Encoding: UTF-8
Imports: Rcpp, shiny, readxl
Suggests: ggplot2, psych, testthat (>= 3.0.0)
LinkingTo: Rcpp
NeedsCompilation: yes
Packaged: 2026-05-22 21:00:55 UTC; jorgeandresjolahernandez
Author: Aquiles Darghan [aut], Jorge Jola [aut, cre]
Maintainer: Jorge Jola <jjolaher@purdue.edu>
Repository: CRAN
Date/Publication: 2026-05-28 19:00:02 UTC

More information about Dcurvature at CRAN
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New package CKNNRLD with initial version 0.1.2
Package: CKNNRLD
Title: Clustering-Based K-Nearest Neighbor Regression for Longitudinal Data
Version: 0.1.2
Description: Implements the 'CKNNRLD' algorithm (Clustering-Based K-Nearest Neighbor Regression for Longitudinal Data) for improving K-Nearest Neighbor ('KNN') regression on longitudinal data through cluster-based partitioning and localized prediction. Offers enhanced computational efficiency and accuracy for high-volume longitudinal datasets. The clustering is performed using the 'latrend' package, which provides a unified interface for various longitudinal clustering methods including 'KML' (K-Means for Longitudinal data). The acronym 'KNN' stands for K-Nearest Neighbor. The acronym 'KML' stands for K-Means for Longitudinal data. References: Loeloe MS, Tabatabaei SM, Sefidkar R, Mehrparvar AH, Jambarsang S (2025). "Boosting K-nearest neighbor regression performance for longitudinal data through a novel learning approach." BMC Bioinformatics, 26, 232. <doi:10.1186/s12859-025-06205-1>; Genolini C, Falissard B (2010). "KmL: k-means for longitudinal data." Computational Statistics, 25(2), 317-3 [...truncated...]
License: GPL-3
Encoding: UTF-8
Imports: Directional, graphics, Rfast, latrend
Depends: R (>= 3.5.0)
NeedsCompilation: no
Language: en-US
Packaged: 2026-05-20 19:59:55 UTC; sadegh-pc
Author: Mohammad Sadegh Loeloe [aut, cre], Seyyed Mohammad Tabatabaei [aut], Reyhane Sefidkar [aut], Amir Houshang Mehrparvar [aut], Sara Jambarsang [aut, ths]
Maintainer: Mohammad Sadegh Loeloe <mslbiostat@gmail.com>
Repository: CRAN
Date/Publication: 2026-05-28 18:40:02 UTC

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New package SSReliabilityClaytonMWD with initial version 1.0.2
Package: SSReliabilityClaytonMWD
Title: Stress-Strength Reliability Model with MWD Marginals via Clayton Copula
Version: 1.0.2
Description: Implements stress-strength reliability models under a dependent framework, where both stress and strength variables follow modified Weibull distributions and their dependence is modeled using a Clayton copula (Kizilaslan (2026) <doi:10.48550/arXiv.2604.12130>). The package provides several estimation procedures for model parameters and the stress-strength reliability R, including two-step maximum likelihood estimation (MLE), least squares estimation (LSE), weighted least squares estimation (WLSE), and maximum product of spacings (MPS). It also provides interval estimation using asymptotic confidence intervals based on MLE and bootstrap confidence intervals for all methods. In addition, functions are included for parameter estimation of the modified Weibull distribution (Lai et al. (2003) <doi:10.1109/TR.2002.805788>) and the two-parameter Weibull distribution, along with utilities to compute their probability density function, cumulative distribution function, quantile func [...truncated...]
Maintainer: Fatih Kizilaslan <fkizilaslan@yahoo.com>
Copyright: 2026 Fatih Kizilaslan
URL: https://github.com/fatihki/SSReliabilityClaytonMWD, https://fatihki.github.io/SSReliabilityClaytonMWD/
BugReports: https://github.com/fatihki/SSReliabilityClaytonMWD/issues
License: GPL (>= 3)
Depends: R (>= 4.1.0)
Encoding: UTF-8
LazyData: true
Imports: doRNG, knitr, stats
Suggests: rmarkdown, numDeriv, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-05-22 11:42:16 UTC; fatihkizilaslan
Author: Fatih Kizilaslan [aut, cre]
Repository: CRAN
Date/Publication: 2026-05-28 13:40:13 UTC

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New package rwetools with initial version 0.1.2
Package: rwetools
Title: Estimating Propensity Scores (PS), PS-Based Weights, and Effects
Version: 0.1.2
Description: Toolbox that provides a streamlined, end-to-end workflow for propensity score analysis in generating real-world evidence from real-world data. The package covers the full analytic pipeline - from estimating propensity scores via logistic regression, to calculating weights or creating a matched cohort, to generating publication-ready Table 1s with standardized mean differences and weighted balance diagnostics. It also estimates incidence rates, hazard ratios, risk ratios, and risk differences with support for stratified and direct-standardized analyses. All core functions produce formatted 'Excel' reports with embedded 'README' documentation, making results immediately shareable with collaborators and stakeholders. Methods are based on Rosenbaum and Rubin (1983) <doi:10.1093/biomet/70.1.41>, Austin (2011) <doi:10.1080/00273171.2011.568786>, and Desai et al. (2017) <doi:10.1097/EDE.0000000000000595>.
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-US
Imports: stats, utils, parallel, survival, survey
Suggests: openxlsx, ggplot2, MatchIt, testthat (>= 3.0.0)
URL: https://github.com/hanseul0618/rwetools
NeedsCompilation: no
Packaged: 2026-05-22 02:23:19 UTC; hanse
Author: Hanseul Cho [aut, cre], Georg Hahn [aut], Janinne Ortega-Montiel [aut], Julie Paik [aut], Elisabetta Patorno [aut]
Maintainer: Hanseul Cho <hanseul0618@gmail.com>
Repository: CRAN
Date/Publication: 2026-05-28 13:30:02 UTC

More information about rwetools at CRAN
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New package remverse with initial version 0.1.0
Package: remverse
Title: A Meta-Package for Relational Event History Analysis
Version: 0.1.0
Maintainer: Joris Mulder <j.mulder3@tilburguniversity.edu>
Description: A unified workflow for relational event modeling by re-exporting core functions from 'remify', 'remstats', and 'remstimate'. Supports tie-oriented and actor-oriented modeling with frequentist and Bayesian estimation. Methods are described in Butts (2008) <doi:10.1111/j.1467-9531.2008.00203.x> and Stadtfeld and Block (2017) <doi:10.1177/0081175017709295>.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.0), remify (>= 4.0.0), remstats (>= 4.0.0), remstimate (>= 3.0.0)
Suggests: knitr, rmarkdown
LazyData: true
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-05-22 09:21:07 UTC; jorismulder
Author: Joris Mulder [aut, cre], Giuseppe Arena [aut], Roger Leenders [aut], Marlyne Meijerink-Bosman [aut], Rumana Lakdawala [aut], Fabio Generoso Vieira [aut], Mahdi Shafiee Kamalabad [ctb], Diana Karimova [ctb]
Repository: CRAN
Date/Publication: 2026-05-28 13:30:08 UTC

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New package remdata with initial version 0.2.0
Package: remdata
Title: A Collection of Empirical and Simulated Relational Event Data Sequences
Version: 0.2.0
Description: Empirical and simulated data for relational event analyses. Each dataset consists of a relational event sequence and optional actor attributes. Individual datasets are redistributed under their original licenses as documented in inst/DATA_LICENSES.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Depends: R (>= 4.0.0)
LazyDataCompression: xz
NeedsCompilation: no
Packaged: 2026-05-22 09:37:57 UTC; jorismulder
Author: Joris Mulder [aut, cre], Roger Leenders [aut], Diana Karimova [aut], Marlyne Meijerink-Bosman [aut], Giuseppe Arena [aut], Rumana Lakdawala [aut], Mahdi Shafiee Kamalabad [ctb], Fabio Generoso Vieira [ctb]
Maintainer: Joris Mulder <j.mulder3@tilburguniversity.edu>
Repository: CRAN
Date/Publication: 2026-05-28 13:30:13 UTC

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New package gdxtools with initial version 1.1.1
Package: gdxtools
Title: Manipulate 'GDX' Files
Version: 1.1.1
Date: 2026-05-22
SystemRequirements: GAMS (>= 24.2.1) is only required if you call gams()
Description: Read and write 'GDX' files ('GAMS' data exchange) and convert parameters, sets and variables to data frames. Backed by the 'GAMS'-maintained 'gamstransfer' package; no compiled code is shipped. See <https://www.gams.com/latest/docs/UG_GDX.html> for the 'GDX' format.
License: EPL-1.0
URL: https://github.com/lolow/gdxtools
BugReports: https://github.com/lolow/gdxtools/issues
Imports: gamstransfer (>= 3.0)
Suggests: testthat, microbenchmark
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2026-05-22 11:08:27 UTC; lolow
Author: Laurent Drouet [aut, cre]
Maintainer: Laurent Drouet <ldrouet@pm.me>
Repository: CRAN
Date/Publication: 2026-05-28 13:40:02 UTC

More information about gdxtools at CRAN
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New package demovuln with initial version 0.1.0
Package: demovuln
Title: Demographic Vulnerability Metrics for Matrix Population Models
Version: 0.1.0
Description: Simulates temporally structured perturbations in matrix population models and computes population reduction and integrated demographic vulnerability across perturbation regimes. Perturbations can be applied to adult survival, juvenile survival, fecundity, all demographic entries, or user-defined matrix elements. The package provides tools to simulate individual perturbation trajectories, evaluate perturbation grids, and summarize demographic vulnerability in structured populations.
License: MIT + file LICENSE
Encoding: UTF-8
Suggests: ggplot2, knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
URL: https://github.com/agimenezromero/demovuln-r
BugReports: https://github.com/agimenezromero/demovuln-r/issues
NeedsCompilation: no
Packaged: 2026-05-22 11:12:33 UTC; alex
Author: Àlex Gimenez-Romero [aut, cre] , Meritxell Genovart [aut]
Maintainer: Àlex Gimenez-Romero <alex.gimenez@csic.es>
Repository: CRAN
Date/Publication: 2026-05-28 13:40:07 UTC

More information about demovuln at CRAN
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New package SampleCore with initial version 0.1.0
Package: SampleCore
Title: Sampling Strategies for Constructing Core Collections
Version: 0.1.0
Description: Implements multiple allocation and selection strategies of sampling to construct core collections primarily from clustered or grouped germplasm collection data. Provides methods for allocating entries to clusters/groups based on group sizes, group-wise distance-based diversity metrics, and group-wise diversity index estimates. Includes procedures for selecting entries within clusters/groups through random sampling, genetic distance-based approaches, and optimized diversity metric–based selection methods. See the package documentation for more, including full list of references for the methods implemented.
License: GPL (>= 2)
Encoding: UTF-8
BuildManual: TRUE
Imports: cluster, DiversityStats, ggplot2, igraph, MASS, mathjaxr, prospectr, Rdpack, Rtsne, stats, vegan
Suggests: biotools, dbscan, EvaluateCore, fastcluster, knitr, pander, rmarkdown
Copyright: 2024-2026, ICAR-NBPGR
URL: https://github.com/aravind-j/SampleCore https://aravind-j.github.io/SampleCore/
BugReports: https://github.com/aravind-j/SampleCore/issues
Depends: R (>= 3.5)
NeedsCompilation: no
Packaged: 2026-05-21 04:21:51 UTC; Aravind-DGC
Author: J. Aravind [aut, cre] , Suman Roy [aut] , Anju Mahendru Singh [aut] , ICAR-NBGPR [cph]
Maintainer: J. Aravind <j.aravind@icar.org.in>
Repository: CRAN
Date/Publication: 2026-05-28 13:00:02 UTC

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New package SAFEMCN with initial version 1.0.0
Package: SAFEMCN
Title: Network Topology Parameter Analysis with Rarefaction
Version: 1.0.0
Description: Calculate network topology parameters from Operational Taxonomic Unit (OTU) tables with customizable correlation thresholds, parallel processing options, and visualization capabilities including trend fitting, prediction of future sample sizes, and lag-1 autocorrelation (AR1) analysis. Methods are based on co-occurrence network construction via correlation thresholds and graph-theoretic metrics computed with 'igraph'.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 3.5.0)
Imports: igraph, Hmisc, parallel, ggplot2, grDevices, graphics, rlang, stats, utils
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-05-22 01:53:31 UTC; 童小徐
Author: Xiaotong Xu [aut, cre], Yue Zheng [cph]
Maintainer: Xiaotong Xu <xxt19992014@163.com>
Repository: CRAN
Date/Publication: 2026-05-28 13:00:05 UTC

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New package modeldiag with initial version 0.1.0
Package: modeldiag
Title: Comprehensive Diagnostics for Statistical Models
Version: 0.1.0
Description: Provides a unified framework for diagnosing common issues in statistical models including linear models, generalized linear models (logistic and Poisson regression), and survival models. Implements tests for multicollinearity, heteroscedasticity, autocorrelation, normality, influential observations, overdispersion, zero-inflation, and proportional hazards assumptions. Includes visualization methods for graphical diagnostics. Methods are based on established approaches including Fox and Monette (1992) <doi:10.1080/01621459.1992.10475190>, Breusch and Pagan (1979) <doi:10.2307/1911963>, and Dean and Lawless (1989) <doi:10.1080/01621459.1989.10478792>.
License: MIT + file LICENSE
Encoding: UTF-8
URL: https://github.com/Teniola17/modeldiag
BugReports: https://github.com/Teniola17/modeldiag/issues
Depends: R (>= 3.5.0)
Imports: stats, graphics, car, lmtest, ResourceSelection, survival
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-05-21 14:47:02 UTC; EmmanuelAdewuyi
Author: Emmanuel Adewuyi [aut, cre], Adewale Lukman [aut], Abiola Owolabi [ctb]
Maintainer: Emmanuel Adewuyi <emmanuel.adewuyi@lshtm.ac.uk>
Repository: CRAN
Date/Publication: 2026-05-28 12:40:02 UTC

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New package llmshieldr with initial version 0.1.0
Package: llmshieldr
Title: Safety Guardrails for Large Language Model Workflows
Version: 0.1.0
Description: A model-agnostic safety layer for developers building with large language model (LLM) applications. Maps starter controls to the Open Worldwide Application Security Project Top 10 for Large Language Model Applications 2025 risk categories <https://genai.owasp.org/llm-top-10/> via a modular rule engine. Supports regular-expression rules, lightweight natural language processing (NLP) intent checks, optional scanners, and semantic large language model reviewer checks on prompts, conversations, retrieved context, tool inputs and outputs, streaming chunks, and model outputs. Supports workflows with the 'Ollama' local web service <https://ollama.com/> via 'ellmer', remote reviewer endpoints, and other chat interfaces callable from 'R'. Intended as an experimental guardrail layer that teams should evaluate against their own workflows before relying on it in production.
License: Apache License (>= 2)
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: jsonlite, cli, rlang, digest, stringi
Suggests: ellmer, httr2, processx, filelock, htmltools, covr, lintr, plumber, shiny, testthat (>= 3.0.0), knitr, rmarkdown, withr, dplyr, tokenizers, SnowballC
VignetteBuilder: knitr
URL: https://www.indraneelchakraborty.com/llmshieldr/, https://github.com/ineelhere/llmshieldr, https://genai.owasp.org/llm-top-10/
BugReports: https://github.com/ineelhere/llmshieldr/issues
NeedsCompilation: no
Packaged: 2026-05-21 18:26:34 UTC; neel0
Author: Indraneel Chakraborty [aut, cre, cph]
Maintainer: Indraneel Chakraborty <hello.indraneel@gmail.com>
Repository: CRAN
Date/Publication: 2026-05-28 12:50:02 UTC

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