New package ratingtables with initial version 0.2.0
Package: ratingtables
Title: Table-Driven Insurance Rating
Version: 0.2.0
Description: Provides a lightweight, table-driven engine for executing insurance rating plans, including coverage-specific rating specifications, entity aggregation, and trace output for auditing. Given policy data, an ordered rating specification, and rating factor tables, it returns rated policies and, optionally, a step-by-step trace of the calculation.
License: MIT + file LICENSE
URL: https://github.com/gs-actuary/ratingtables
BugReports: https://github.com/gs-actuary/ratingtables/issues
Encoding: UTF-8
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-08-04 22:03:58 UTC; yagre
Author: Greg Sollenberger [aut, cre, cph]
Maintainer: Greg Sollenberger <yagreg7@yahoo.com>
Repository: CRAN
Date/Publication: 2026-08-09 08:40:02 UTC

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New package rapsimng.decide.core with initial version 0.1.0
Package: rapsimng.decide.core
Title: Decision-Oriented Analysis Core for APSIM Next Generation Outputs
Version: 0.1.0
Description: Provides a low-level interface for analysing APSIM Next Generation simulation outputs to support structured decision-making workflows.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Suggests: testthat (>= 3.0.0)
URL: https://core.decide.rapsimng.bangyou.me/, https://github.com/byzheng/rapsimng.decide.core
BugReports: https://github.com/byzheng/rapsimng.decide.core/issues
NeedsCompilation: no
Packaged: 2026-08-05 01:16:10 UTC; zhe00a
Author: Bangou Zheng [aut, cre]
Maintainer: Bangou Zheng <zheng.bangyou@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-09 08:40:08 UTC

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New package ProgVine with initial version 0.1.0
Package: ProgVine
Title: Progressive Regularized Vine Copula for Masked Competing Risks
Version: 0.1.0
Description: Implements Progressive Regularized Vine Copula (Prog-Vine) frameworks for high-dimensional dependent competing risks with masked failure causes under Progressive Type-II Censoring. Fits Weibull marginals, estimates pair-copula trees using Expectation-Maximization (EM) algorithms, computes Louis observed information confidence intervals, and implements Data Augmentation Gibbs Samplers for Bayesian credible intervals.
License: GPL-3
Encoding: UTF-8
Imports: stats
NeedsCompilation: no
Packaged: 2026-08-05 06:57:36 UTC; Dr. O. J. Obulezi
Author: Okechukwu J. Obulezi [aut, cre]
Maintainer: Okechukwu J. Obulezi <oj.obulezi@unizik.edu.ng>
Repository: CRAN
Date/Publication: 2026-08-09 08:10:10 UTC

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New package PINNProgCens with initial version 0.1.0
Package: PINNProgCens
Title: Physics-Informed Neural Networks for Progressive Censoring
Version: 0.1.0
Description: Implementation of Physics-Informed Neural Networks ('PINN') for lifetime estimation under progressive Type-II censoring schemes. Combines parametric baseline hazards with physical differential degradation models.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: deSolve, stats
NeedsCompilation: no
Packaged: 2026-08-05 07:02:56 UTC; Dr. O. J. Obulezi
Author: Okechukwu J. Obulezi [aut, cre]
Maintainer: Okechukwu J. Obulezi <oj.obulezi@unizik.edu.ng>
Repository: CRAN
Date/Publication: 2026-08-09 08:10:15 UTC

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New package phontrast with initial version 2.3.1
Package: phontrast
Title: Contrast and Separation Metrics for Phonological Categories
Version: 2.3.1
Author: Grant M. Berry [aut, cre]
Maintainer: Grant M. Berry <berry.grant@gmail.com>
Description: Computes and compares multiple measures of separation and overlap between phonological categories (for example vowels or consonants) in arbitrary multi-dimensional acoustic spaces such as formant values, mel-frequency cepstral coefficients (MFCCs), duration, or learned embeddings. The main entry point, phontrast(), reports several contrast metrics in one call -- Jensen-Shannon divergence and distance (Lin, 1991) <doi:10.1109/18.61115>, the Pillai-Bartlett trace, Bhattacharyya distance and affinity, Mahalanobis distance, and proportional overlap -- globally or by group on a common separation-oriented scale, with bootstrap confidence intervals. Also provides utilities for preparing estimates for downstream modelling such as generalized additive models and mixed-effects models. Formerly released as 'phonJSD'.
License: MIT + file LICENSE
URL: https://github.com/berrygrant/phontrast
BugReports: https://github.com/berrygrant/phontrast/issues
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: ks, dplyr, purrr, tibble, rlang, stats, grDevices, utils
Suggests: ggplot2, mgcv, mvtnorm, tuneR, testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-04 21:26:44 UTC; grantberry
Repository: CRAN
Date/Publication: 2026-08-09 08:30:02 UTC

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New package palettecore with initial version 0.4.1
Package: palettecore
Title: Derive, Optimise and Audit a Scientific Colour Palette from One Seed Colour
Version: 0.4.1
Description: Generates sequential, diverging and categorical colour palettes from a single seed colour in OKLCH (the cylindrical lightness-chroma-hue representation of the Oklab perceptual colour space), with spacing measured by the CIEDE2000 colour-difference formula of the International Commission on Illumination. Audits every palette under simulated colour-vision deficiency, greyscale conversion, the standard Red Green Blue (sRGB) gamut and Web Content Accessibility Guidelines (WCAG) contrast. Colour-vision deficiency is simulated at severity 1.0 with the model of Machado, Oliveira and Fernandes (2009) <doi:10.1109/TVCG.2009.113>; the design rationale follows Crameri, Shephard and Heron (2020) <doi:10.1038/s41467-020-19160-7>. Mirrors the 'Python' reference implementation maintained in the same repository and is validated against shared parity fixtures. Thresholds are configurable design rules, not established accessibility cut-offs.
License: Apache License (>= 2)
Encoding: UTF-8
Depends: R (>= 4.1)
Imports: stats, utils
Suggests: ggplot2, jsonlite
URL: https://github.com/heidihelena/palettecore
BugReports: https://github.com/heidihelena/palettecore/issues
NeedsCompilation: no
Packaged: 2026-08-03 20:36:25 UTC; root
Author: Heidi Helena Andersen [aut, cre]
Maintainer: Heidi Helena Andersen <andersenheidihelena@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-09 08:10:02 UTC

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New package NeutroBasicDesignsAnalysis with initial version 0.0.1
Package: NeutroBasicDesignsAnalysis
Title: Neutrosophic Analysis of Completely Randomized Designs and Randomized Complete Block Designs
Version: 0.0.1
Maintainer: Vinaykumar L.N. <vinaymandya123@gmail.com>
Description: Provides neutrosophic statistical methods for interval-valued data from completely randomized and randomized complete block designs. Methods include neutrosophic analysis of variance, analysis of covariance, multivariate analysis of variance, pooled analysis of variance, Levene's test, and Aitken transformation. When the lower and upper bounds are equal (crisp data), the methods reduce to their corresponding classical statistical analyses. The basic concept of neutrosophic statistics is based on Smarandache (2014) <https://fs.unm.edu/NeutrosophicStatistics.pdf>, while the statistical analysis procedures implemented in this package are newly developed.
License: GPL (>= 3)
Encoding: UTF-8
Imports: MASS, stats
NeedsCompilation: no
Packaged: 2026-08-05 04:16:59 UTC; admin
Author: Neethu R.S. [aut, ctb], Boyina Devi Priyanka [aut, ctb], Cini Varghese [aut, ctb], Susheel Kumar Sarkar [aut, ctb], Mohd Harun [aut, ctb], Vinaykumar L.N. [aut, cre], Anindita Datta [aut, ctb]
Repository: CRAN
Date/Publication: 2026-08-09 08:40:13 UTC

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New package ModToppLeone with initial version 0.1.0
Package: ModToppLeone
Title: Modified Topp-Leone Distribution: Properties, Estimation, and Applications
Version: 0.1.0
Description: Provides density, cumulative distribution function, quantile function, random number generation, survival function, hazard rate function, statistical properties, classical point and interval estimation (maximum likelihood, ordinary least squares, weighted least squares, Cramer-von Mises, and maximum product of spacings), Bayesian estimation under symmetric and asymmetric loss functions (squared error, entropy, precautionary, and generalized entropy loss functions) with highest posterior density intervals, censoring schemes (random, Type-I, Type-II, and progressive Type-II censoring), and real data applications for the 'Modified Topp-Leone' distribution. Methods are based on Singh et al. (2025) <https://statassoc.or.th>, Cheng and Amin (1983) <doi:10.1111/j.2517-6161.1983.tb01267.x>, Swain et al. (1988) <doi:10.1080/00949658808811094>, Chen and Shao (1999) <doi:10.1080/10618600.1999.10474802>, and Balakrishnan and Aggarwala (2000) <doi:10.1007/978-1-4612-1178- [...truncated...]
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.5.0)
Imports: stats, graphics
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-05 02:51:05 UTC; shikhar tyagi
Author: Shikhar Tyagi [aut, cre] , Abhishek Tyagi [aut], Arvind Pandey [aut], Bhupendra Singh [aut], Vrijesh Tripathi [aut]
Maintainer: Shikhar Tyagi <shikhar1093tyagi@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-09 08:40:18 UTC

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New package MiCT with initial version 2.0.0
Package: MiCT
Title: Minimal Important Change and Threshold Estimation
Version: 2.0.0
Description: Provides methods for estimating minimal important change (MIC) and interpretation thresholds for multi-item questionnaires and single-item continuous or ordinal measures. Methods include predictive modelling, adjusted predictive modelling, improved adjusted predictive modelling using anchor reliability, confirmatory factor analysis for anchor reliability, longitudinal confirmatory factor analysis for MIC estimation, longitudinal confirmatory factor analysis-based MIC estimation for single-item measures, and confirmatory factor analysis-based threshold estimation for single-item and multi-item measures. Implemented methods include those developed by Terluin et al. (2015) <doi:10.1016/j.jclinepi.2015.03.015>, Terluin et al. (2017) <doi:10.1016/j.jclinepi.2016.12.015>, Terluin et al. (2022) <doi:10.1016/j.jclinepi.2022.04.018>, Terluin et al. (2023) <doi:10.1007/s11136-023-03355-8>, Terluin et al. (2024) <doi:10.1007/s11136-023-03577-w>, Terluin et al. (2024) [...truncated...]
Depends: R (>= 4.1.0)
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: lavaan, MASS, mirt, pROC
Suggests: testthat (>= 3.0.0)
URL: https://github.com/yhpua/MiCT, https://yhpua.github.io/MiCT/
BugReports: https://github.com/yhpua/MiCT/issues
NeedsCompilation: no
Packaged: 2026-08-04 22:25:38 UTC; PYH
Author: Iris Eekhout [aut] , Berend Terluin [aut], Yong-Hao Pua [aut, cre]
Maintainer: Yong-Hao Pua <gmspuyh@duke-nus.edu.sg>
Repository: CRAN
Date/Publication: 2026-08-09 08:30:08 UTC

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New package IntegMultiReg with initial version 0.1.0
Package: IntegMultiReg
Title: Integrative Bayesian Multiple Regression for Multi-Platform Biomarkers
Version: 0.1.0
Description: A Bayesian framework that integrates several regression models to identify a parsimonious set of biomarkers shared across disparate data platforms (for example genomic, transcriptomic and proteomic assays). Subjects are partitioned into subgroups defined by their pattern of platform availability, so that no subject with partially missing platform data is excluded, and information is borrowed across subgroups through a Markov random field prior on the variable-selection indicators together with non-local (product moment) priors on the regression effects. The methodology was introduced for time-to-event outcomes by Chekouo, Stingo, Doecke and Do (2017) <doi:10.1111/biom.12587>; this package additionally supports continuous (Gaussian) and binary (probit) outcomes. Posterior inference is carried out by a Markov chain Monte Carlo sampler implemented in C for computational efficiency.
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
Depends: R (>= 4.0.0)
Imports: graphics, grDevices, stats, utils
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
SystemRequirements: GSL (>= 2.0)
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2026-08-05 01:44:33 UTC; tchekouo
Author: Sinian Zhang [aut], Jianfeng Wang [aut], Thierry Chekouo [aut, cre]
Maintainer: Thierry Chekouo <tchekouo@umn.edu>
Repository: CRAN
Date/Publication: 2026-08-09 08:20:07 UTC

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New package gofLorenz with initial version 0.1.0
Package: gofLorenz
Title: Goodness-of-Fit Tests for Location-Scale Distributions via Lorenz Curve
Version: 0.1.0
Description: Implements goodness-of-fit test statistics and graphical methods for symmetric and asymmetric location-scale distributions under progressive Type-II censoring using the modified Lorenz curve and ratio modified sample Lorenz curve, as proposed by Lee (2024) <doi:10.3390/sym16020202>. Also provides order statistics distance test statistics based on Pakyari and Balakrishnan (2013) <doi:10.1080/00949655.2011.625424>. Supports calculation of test statistics, Monte Carlo p-values, critical values, and L-plot visual diagnostics for complete and progressively Type-II censored data.
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
Depends: R (>= 4.0.0)
Imports: stats, graphics
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-05 02:30:42 UTC; shikhar tyagi
Author: Shikhar Tyagi [aut, cre] , Arvind Pandey [aut], Bhupendra Singh [aut], Vrijesh Tripathi [aut]
Maintainer: Shikhar Tyagi <shikhar1093tyagi@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-09 08:20:02 UTC

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New package GLHD with initial version 1.1-1
Package: GLHD
Title: Grouped Latin Hypercube Designs with Controlled Correlations
Version: 1.1-1
Description: We provide a method of constructing grouped Latin hypercube designs by controlling correlations. Details of the algorithm can be found in Wenlong Li, Jian-Feng Yang and Peter Chien (2026). Grouped Latin hypercube designs with controlled correlations. Technometrics, published online. Important function in this package is "GLHD_CC".
License: LGPL (>= 3)
Imports: stats
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-08-05 06:47:10 UTC; wenlo
Author: Wenlong Li [aut, cre], Jian-Feng Yang [aut], Peter Chien [aut]
Maintainer: Wenlong Li <wlli1@bjtu.edu.cn>
Repository: CRAN
Date/Publication: 2026-08-09 08:10:19 UTC

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New package exactGMH with initial version 0.1.0
Package: exactGMH
Title: Exact and Permutation-Based Mantel Tests for Differential Item Functioning in Dichotomous and Polytomous Items
Version: 0.1.0
Description: Screens dichotomous and polytomous test items for Differential Item Functioning (DIF) using an extension of the Mantel (1963) <doi:10.1080/01621459.1963.10500879> and generalized Mantel-Haenszel statistic, with statistical significance computed via permutation rather than the conventional asymptotic chi-square approximation. Following Hemerik and Goeman (2018) <doi:10.1007/s11749-017-0571-1>, the permutation p-value is exact at the nominal level rather than an approximation, even for a finite number of permutations. This makes the test valid for small samples (fewer than 200 examinees per group), a condition common in classroom-, program-, and institution-level assessment where existing exact-inference options in other software are restricted to dichotomous items only. An optional Benjamini-Hochberg or Bonferroni correction addresses multiple comparisons when screening many items at once.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.0)
Imports: stats
Suggests: testthat (>= 3.0.0), shiny
URL: https://github.com/exactGMH-project/exactGMH
BugReports: https://github.com/exactGMH-project/exactGMH/issues
NeedsCompilation: no
Packaged: 2026-08-04 16:17:04 UTC; root
Author: Tri Zahra Ningsih [aut, cre], Aman [aut], Ahmad Nasrulloh [aut], Hera Hastuti [aut], Suci Kurnia Putri [aut]
Maintainer: Tri Zahra Ningsih <trizahra10019@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-09 08:10:06 UTC

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Package scimesh (with last version 0.3.0) was removed from CRAN

Previous versions (as known to CRANberries) which should be available via the Archive link are:

2026-08-09 0.3.0

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New package smartcor with initial version 1.0.1
Package: smartcor
Title: Automatic Correlation Method Selection Based on Variable Types
Version: 1.0.1
Description: Detects variable types (continuous, count, binary, ordinal, categorical) and selects the appropriate correlation method for each pair. Supports Pearson, Spearman, Kendall's tau, point-biserial, rank-biserial, phi, tetrachoric, polychoric, polyserial, Cramer's V, Tschuprow's T, Theil's U, Yule's Q, and Goodman-Kruskal's gamma, each with a confidence interval and p-value. Explains the selection rationale in the output, follows tidy data principles, and works in both interactive and scripted workflows. The methodology is described in Harshvardhan and Ranjan (2026) <doi:10.48550/arXiv.2607.22285>.
License: GPL (>= 3)
URL: https://harshvardhaniimi.github.io/smartcor/, https://github.com/harshvardhaniimi/smartcor
BugReports: https://github.com/harshvardhaniimi/smartcor/issues
Encoding: UTF-8
Depends: R (>= 3.6.0)
Imports: cli (>= 3.0.0), generics, ggplot2 (>= 3.4.0), graphics, grDevices, mvtnorm, polycor, rlang (>= 1.0.0), stats, tibble, utils, withr
Suggests: knitr, MASS, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-04 17:52:25 UTC; harshvardhan
Author: M. Harshvardhan [aut, cre, cph], Pritam Ranjan [aut, cph]
Maintainer: M. Harshvardhan <harshvardhan@aus.edu>
Repository: CRAN
Date/Publication: 2026-08-09 07:30:02 UTC

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New package PLSsemEngine with initial version 1.3.0
Package: PLSsemEngine
Title: Transparent PLS-SEM Estimation for Composite-Based Reflective Models
Version: 1.3.0
Date: 2026-07-24
Description: A transparent and modular implementation of Partial Least Squares Structural Equation Modeling (PLS-SEM) focused on reflective measurement models (Mode A). The package separates estimation, bootstrap inference, and predictive evaluation into independent components, emphasising algorithmic transparency, reproducibility, and researcher-controlled analysis. Methods are based on Tenenhaus, Esposito Vinzi, Chatelin & Lauro (2005) <doi:10.1016/j.csda.2004.03.005>, Hair, Risher, Sarstedt & Ringle (2019) <doi:10.1108/EBR-11-2018-0203>, and Henseler, Ringle & Sarstedt (2015) <doi:10.1007/s11747-014-0403-8>.
License: MIT + file LICENSE
URL: https://github.com/msoto-perez/PLSsemEngine
Encoding: UTF-8
Depends: R (>= 4.0.0)
Imports: stats, graphics, grDevices
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-04 15:20:07 UTC; msoto
Author: Manuel Soto-Perez [aut, cre]
Maintainer: Manuel Soto-Perez <msoto@up.edu.mx>
Repository: CRAN
Date/Publication: 2026-08-09 07:30:15 UTC

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New package metabodeconplus with initial version 0.22.0
Package: metabodeconplus
Title: Deconvolution, Alignment and Model Fitting of 1d NMR Spectra
Version: 0.22.0
Author: Tobias Schmidt [aut, cre, cph], Martina Haeckl [aut, cph], Yanren Linda Hu [ctb], Wolfram Gronwald [aut, cph]
Maintainer: Tobias Schmidt <tobias.schmidt331@gmail.com>
Description: An integrated framework for deconvolution, alignment and postprocessing of 1-dimensional (1d) nuclear magnetic resonance (NMR) spectra, extended with end-to-end model fitting that turns the resulting matrix of aligned signal integrals into classification models. The deconvolution part uses the algorithm described in Koh et al. (2009) <doi:10.1016/j.jmr.2009.09.003>. The alignment part is based on functions from the 'speaq' package, described in Beirnaert et al. (2018) <doi:10.1371/journal.pcbi.1006018> and Vu et al. (2011) <doi:10.1186/1471-2105-12-405>. A detailed description and evaluation of an early version of the package can be found in Haeckl et al. (2021) <doi:10.3390/metabo11070452>. 'metabodeconplus' is the actively developed successor to the 'metabodecon' package and introduces backwards-incompatible API changes.
License: GPL (>= 3)
URL: https://github.com/spang-lab/metabodeconplus/, https://spang-lab.github.io/metabodeconplus/
BugReports: https://github.com/spang-lab/metabodeconplus/issues
Encoding: UTF-8
Depends: R (>= 3.5.0)
Imports: mathjaxr, ranger, readJDX, toscutil (>= 2.8.0), withr
Suggests: BiocManager, cachem, covr, devtools, diffobj, digest, doParallel, e1071, glmnet, glue, impute, inline, knitr, lifecycle, MassSpecWavelet, mdrb, microbenchmark, multtest, pkgbuild, pkgload, pROC, R.devices, rcmdcheck, remotes, rlang, rmarkdown, rpart, speaq, styler, testthat (>= 3.0.0), usethis, V8, vdiffr, waldo
LazyData: true
LazyDataCompression: xz
BuildManual: TRUE
Language: en-US
Additional_repositories: https://spang-lab.r-universe.dev
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2026-08-04 18:43:02 UTC; tschmidt
Repository: CRAN
Date/Publication: 2026-08-09 07:30:08 UTC

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New package gp3bayes with initial version 0.1.1
Package: gp3bayes
Title: Contract-First Bayesian Workflows for Hierarchical Behavioural Data
Version: 0.1.1
Description: Provides transparent, contract-first infrastructure for Bayesian analysis of repeated-measures and hierarchical behavioural data. It supports approved Bernoulli-logit and positive lognormal duration workflows with readiness audits, deterministic simulation, explicit preparation, inspectable priors, prior and posterior predictive checks, restricted optional fitting through 'brms' and 'rstan', sampling diagnostics, prior sensitivity, parameter recovery, and conservative reporting. Core contracts and prior checks remain backend-independent.
License: MIT + file LICENSE
URL: https://stefanosbalaskas.github.io/gp3bayes/, https://github.com/stefanosbalaskas/gp3bayes
BugReports: https://github.com/stefanosbalaskas/gp3bayes/issues
Encoding: UTF-8
Imports: withr
Suggests: bayesplot, brms, knitr, posterior, rmarkdown, rstan, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-04 18:24:13 UTC; Stefanos-PC
Author: Stefanos Balaskas [aut, cre, cph]
Maintainer: Stefanos Balaskas <s.balaskas@ac.upatras.gr>
Repository: CRAN
Date/Publication: 2026-08-09 07:10:02 UTC

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New package FPScausal with initial version 0.1.0
Package: FPScausal
Title: Functional Propensity Score for Causal Inference
Version: 0.1.0
Description: Implements functional propensity score (FPS) weighting for causal inference with functional treatments. Weights are estimated by maximising the empirical likelihood subject to covariate-balancing constraints and solving the resulting dual problem via the BFGS quasi-Newton algorithm, following Ciardulli, S. and Fontana, N. (2026). The package supports scalar, binary, and functional outcomes, as well as functional covariates.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: fda (>= 6.0.0), ggplot2 (>= 3.4.0), tidyr (>= 1.2.0), MASS (>= 7.3-0), wCorr, patchwork (>= 1.1.0), progress (>= 1.2.0), stats, utils
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-05 07:31:09 UTC; nicole.fontana
Author: Nicole Fontana [aut, cre], Simone Ciardulli [aut]
Maintainer: Nicole Fontana <nicole.fontana@polimi.it>
Repository: CRAN
Date/Publication: 2026-08-09 08:00:02 UTC

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New package FINN with initial version 0.1.0
Package: FINN
Title: Forest Informed Neural Networks
Version: 0.1.0
Maintainer: Yannek Kaeber <y.kaeber@posteo.de>
Description: A hybrid dynamic forest (gap) model (FINN) that can be configured as a fully mechanistic, process-based model, like classic forest gap models, or with its demographic processes (growth, mortality, regeneration) replaced by deep neural networks (DNNs), or any combination of the two. Provides functions to define a model and its mechanistic or empirical components, calibrate it to forest inventory data, and interpret the calibrated processes. FINN is implemented with the 'torch' package, which supplies GPU support and the automatic differentiation used to calibrate the model by stochastic gradient descent; no knowledge of 'torch' is required. The hybrid modeling approach is described in Pichler and Käber (2026) <doi:10.1111/2041-210x.70347>.
License: GPL (>= 3)
Encoding: UTF-8
URL: https://github.com/FINNverse/FINN, https://finnverse.github.io/FINN/
BugReports: https://github.com/FINNverse/FINN/issues
Depends: R (>= 4.1.0)
LinkingTo: Rcpp
Imports: abind, cli, stats, utils, data.table, coro, Rcpp, torch, ggplot2, glue
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2026-08-05 08:00:45 UTC; yannekkaber
Author: Yannek Kaeber [aut, cre] , Maximilian Pichler [aut]
Repository: CRAN
Date/Publication: 2026-08-09 08:00:08 UTC

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New package expoquimR with initial version 0.1.0
Package: expoquimR
Title: Qualitative and Quantitative Assessment of Occupational Chemical Exposure Risk
Version: 0.1.0
Description: Provides a unified toolkit for occupational chemical exposure risk assessment, implementing three internationally recognised methods end to end: the qualitative control-banding methods COSHH Essentials (UK Health and Safety Executive) and the method of the French National Research and Safety Institute (INRS), together with the quantitative statistical procedure of the UNE-EN 689 standard for comparing measured exposure levels against occupational exposure limits. Every step of each method, from hazard banding and exposure scoring to lognormal or normal distribution fitting, one-sided tolerance limits, and monitoring-interval recommendations, is implemented as a small, independently callable, and unit-tested function, so assessments are reproducible and auditable without depending on any graphical interface. Optional 'shiny' applications provide a guided, interactive workflow for occupational hygienists and health and safety practitioners who prefer not to write code. References: UK Hea [...truncated...]
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-GB
URL: https://github.com/Aguilar-Elena/expoquimR
BugReports: https://github.com/Aguilar-Elena/expoquimR/issues
Depends: R (>= 4.1.0)
Imports: stats
Suggests: DT, ggplot2, kableExtra, knitr, readxl, rmarkdown, shiny, shinyjs, testthat (>= 3.0.0), tibble, usethis
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-04 18:00:50 UTC; okashi
Author: Raul Aguilar Elena [aut, cre] , Ana Delgado-Garcia [aut] , Alejandro Guillem-Riquelme [aut]
Maintainer: Raul Aguilar Elena <raguilar@universidadviu.com>
Repository: CRAN
Date/Publication: 2026-08-09 07:10:07 UTC

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New package DropCens with initial version 0.1.0
Package: DropCens
Title: Distributionally Robust Progressive Type-II Censoring Inference
Version: 0.1.0
Description: Implements distributionally robust optimization algorithms for progressive Type-II censored Weibull lifetime data under Wasserstein ambiguity balls. Provides primal-dual convex optimization solvers and robust inference bounds.
License: GPL-3
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-08-05 07:37:30 UTC; Dr. O. J. Obulezi
Author: Okechukwu J. Obulezi [aut, cre]
Maintainer: Okechukwu J. Obulezi <oj.obulezi@unizik.edu.ng>
Repository: CRAN
Date/Publication: 2026-08-09 08:00:17 UTC

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New package scimesh with initial version 0.3.0
Package: scimesh
Title: Headless Publication-Quality 3D Mesh Rendering Engine
Version: 0.3.0
Description: A fast, GPU-free 3D software renderer written in modern C++17 with native R bindings. Renders triangle meshes to publication-quality images entirely on the CPU, requiring no display server or graphics hardware. Features multi-light Blinn-Phong shading, screen-space ambient occlusion, anti-aliasing, depth fog, transparency, wireframe rendering, texture mapping, and procedural geometry generation. Supports standard mesh file formats with PNG and PPM output. Works on high-performance computing clusters, headless servers, containers, and continuous integration pipelines, making it suitable for scientific visualization across neuro-imaging, molecular structures, and general 3D graphics.
License: MIT + file LICENSE
URL: https://github.com/dfsp-spirit/scimesh
BugReports: https://github.com/dfsp-spirit/scimesh/issues
Imports: Rcpp (>= 1.0.0)
LinkingTo: Rcpp
Suggests: testthat (>= 3.0.0), png, freesurferformats, viridisLite, knitr, rmarkdown
VignetteBuilder: knitr
SystemRequirements: C++17
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2026-08-03 13:33:29 UTC; timschaefer
Author: Tim Schaefer [aut, cre], Martin Horeňovsky [ctb] ), Christophe Riccio [ctb] ), Dimitri Diakopoulos [ctb] ), Syoyo Fujita [ctb] ), Tim Schaefer [ctb] ), Sebastian Reiter [ctb] ), Sean Barrett [ctb] )
Maintainer: Tim Schaefer <ts+code@rcmd.org>
Repository: CRAN
Date/Publication: 2026-08-09 07:00:02 UTC

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New package qvivid with initial version 0.1.2
Package: qvivid
Title: Fast Quantum Simulation and Vivid Visualizations
Version: 0.1.2
Description: Builds, simulates, inspects, and animates gate-based quantum circuits. The package provides a readable reference implementation and compiled state-vector kernels, reproducible shot sampling, circuit diagrams, phase-aware state plots, reduced-state Bloch spheres, journal-sized figure export, and animated trajectories. For background on the implemented methods, see Nielsen and Chuang (2010, ISBN:9781107002173).
License: MIT + file LICENSE
URL: https://github.com/SanmiAndreSofa/qvivid
BugReports: https://github.com/SanmiAndreSofa/qvivid/issues
Encoding: UTF-8
Depends: R (>= 4.2.0)
Imports: grDevices, graphics
Suggests: gifski, ggplot2 (>= 3.4.0), knitr, ragg (>= 1.2.0), rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2026-08-01 00:47:13 UTC; runner
Author: Sanmi Adenaiye [aut, cre, cph]
Maintainer: Sanmi (Oluwasanmi) Adenaiye <dradenaiyesanmi@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-09 06:50:02 UTC

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New package netsimhelpers with initial version 0.1.0
Package: netsimhelpers
Title: Helper Functions for Simulation Studies in Network Psychometrics
Version: 0.1.0
Date: 2026-08-04
Maintainer: Ria H. A. Hoekstra <h.a.hoekstra@uva.nl>
Description: Helper functions for setting up simulations in network psychometrics.
License: GPL (>= 2)
Language: en-US
Encoding: UTF-8
Imports: mvtnorm, stats, bootnet, qgraph
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-08-04 12:18:08 UTC; ria
Author: Ria H. A. Hoekstra [aut, cre], Sacha Epskamp [aut]
Repository: CRAN
Date/Publication: 2026-08-09 06:50:07 UTC

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New package gghotelling with initial version 0.2.1
Package: gghotelling
Title: Hotelling's T² Ellipses and Outlier Detection for 'ggplot2'
Version: 0.2.1
Description: Calculate Hotelling's T² ellipses and detect multivariate outliers both for base R plots and 'ggplot2' plots. Optionally, uses robust covariance estimation to reduce the influence of outliers on the ellipses. Also included: bagplots, kernel density plots and outlier diagnostic plots.
URL: https://github.com/january3/gghotelling/, https://january3.github.io/gghotelling/
License: MIT + file LICENSE
Encoding: UTF-8
Imports: ggplot2, grDevices, MASS, mrfDepth, robustbase
Suggests: testthat (>= 3.0.0), ggrepel, knitr, rmarkdown, HDclassif, spelling, cowplot
VignetteBuilder: knitr
Language: en-US
NeedsCompilation: no
Packaged: 2026-08-04 10:38:51 UTC; january
Author: January Weiner [aut, cre, cph]
Maintainer: January Weiner <january.weiner@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-09 06:50:13 UTC

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New package FusionForests with initial version 1.0.1
Package: FusionForests
Title: Bayesian Tree Ensembles for Data Fusion and Causal Inference
Version: 1.0.1
Date: 2026-08-01
Maintainer: Tijn Jacobs <t.jacobs@vu.nl>
Description: Bayesian tree ensemble models for data fusion and causal inference. The main model FusionForest() combines data from a randomised controlled trial and an observational study using separate tree forests, allowing for unmeasured confounding in the observational data. Continuous and (interval-)censored survival outcomes are supported. Posterior summaries of treatment effect estimates and interpretable linear projections are provided.
URL: https://github.com/tijn-jacobs/FusionForests
BugReports: https://github.com/tijn-jacobs/FusionForests/issues
License: MIT + file LICENSE
Depends: R (>= 3.5.0)
Imports: Rcpp, ShrinkageTrees
LinkingTo: Rcpp (>= 1.0.11)
Suggests: survival, testthat (>= 3.0.0)
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2026-08-01 16:49:27 UTC; tijnjacobs
Author: Tijn Jacobs [aut, cre]
Repository: CRAN
Date/Publication: 2026-08-09 06:40:10 UTC

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New package bscm with initial version 1.0.1
Package: bscm
Title: Bayesian Synthetic Control Models
Version: 1.0.1
Description: Implements the synthetic control method of Abadie, Diamond, and Hainmueller (2010) <doi:10.1198/jasa.2009.ap08746> within a Bayesian framework, enabling straightforward uncertainty quantification of treatment effects and other quantities of interest. Supports time-varying covariates with potentially time-varying effects, single or multiple treated units, and staggered treatment adoption. Provides methods for model assessment, comparison, and selection based on placebo studies, cross-validation, and posterior predictive checks. Posterior sampling is performed using Markov chain Monte Carlo via Stan.
License: GPL (>= 3)
Encoding: UTF-8
Biarch: true
Depends: R (>= 4.1.0)
Imports: checkmate, cli, dplyr, ggplot2, loo, methods, posterior, progressr, projpred, quadprog, Rcpp (>= 0.12.0), RcppParallel (>= 5.0.1), rlang, rstan (>= 2.32.7), rstantools (>= 2.6.0), tidyr
LinkingTo: BH (>= 1.66.0), Rcpp (>= 0.12.0), RcppEigen (>= 0.3.3.3.0), RcppParallel (>= 5.0.1), rstan (>= 2.32.7), StanHeaders (>= 2.32.10)
SystemRequirements: GNU make
LazyData: true
LazyDataCompression: xz
URL: https://github.com/helske/bscm
BugReports: https://github.com/helske/bscm/issues
Suggests: testthat (>= 3.0.0)
NeedsCompilation: yes
Packaged: 2026-07-31 12:11:26 UTC; jvhels
Author: Jouni Helske [aut, cre]
Maintainer: Jouni Helske <jouni.helske@iki.fi>
Repository: CRAN
Date/Publication: 2026-08-09 06:40:02 UTC

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