Sat, 15 Nov 2025

Package WeightIt updated to version 1.5.1 with previous version 1.5.0 dated 2025-09-18

Title: Weighting for Covariate Balance in Observational Studies
Description: Generates balancing weights for causal effect estimation in observational studies with binary, multi-category, or continuous point or longitudinal treatments by easing and extending the functionality of several R packages and providing in-house estimation methods. Available methods include those that rely on parametric modeling, optimization, and machine learning. Also allows for assessment of weights and checking of covariate balance by interfacing directly with the 'cobalt' package. Methods for estimating weighted regression models that take into account uncertainty in the estimation of the weights via M-estimation or bootstrapping are available. See the vignette "Installing Supporting Packages" for instructions on how to install any package 'WeightIt' uses, including those that may not be on CRAN.
Author: Noah Greifer [aut, cre]
Maintainer: Noah Greifer <noah.greifer@gmail.com>

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More information about WeightIt at CRAN
Permanent link

Package versus updated to version 0.3.1 with previous version 0.3.0 dated 2024-01-11

Title: Compare Data Frames
Description: A toolset for interactively exploring the differences between two data frames.
Author: Ryan Dickerson [aut, cre, cph], Eli Pousson [ctb]
Maintainer: Ryan Dickerson <fresh.tent5866@fastmail.com>

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Package hdbayes updated to version 0.2.0 with previous version 0.1.1 dated 2024-08-22

Title: Bayesian Analysis of Generalized Linear Models with Historical Data
Description: User-friendly functions for leveraging (multiple) historical data set(s) in Bayesian analysis of generalized linear models (GLMs) and survival models, along with support for Bayesian model averaging (BMA). The package provides functions for sampling from posterior distributions under various informative priors, including the prior induced by the Bayesian hierarchical model, power prior by Ibrahim and Chen (2000) <doi:10.1214/ss/1009212673>, normalized power prior by Duan et al. (2006) <doi:10.1002/env.752>, normalized asymptotic power prior by Ibrahim et al. (2015) <doi:10.1002/sim.6728>, commensurate prior by Hobbs et al. (2011) <doi:10.1111/j.1541-0420.2011.01564.x>, robust meta-analytic-predictive prior by Schmidli et al. (2014) <doi:10.1111/biom.12242>, latent exchangeability prior by Alt et al. (2024) <doi:10.1093/biomtc/ujae083>, and a normal (or half-normal) prior. The package also includes functions for computing model averaging weights, such [...truncated...]
Author: Ethan M. Alt [aut, cre, cph] , Xinxin Chen [aut], Luiz M. Carvalho [aut], Joseph G. Ibrahim [aut], Xiuya Chang [ctb]
Maintainer: Ethan M. Alt <ethanalt@live.unc.edu>

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Package GSODR updated to version 5.0.0 with previous version 4.1.4 dated 2025-07-31

Title: Global Surface Summary of the Day ('GSOD') Weather Data Client
Description: Provides automated downloading, parsing, cleaning, unit conversion and formatting of Global Surface Summary of the Day ('GSOD') weather data from the from the USA National Centers for Environmental Information ('NCEI'). Units are converted from from United States Customary System ('USCS') units to International System of Units ('SI'). Stations may be individually checked for number of missing days defined by the user, where stations with too many missing observations are omitted. Only stations with valid reported latitude and longitude values are permitted in the final data. Additional useful elements, saturation vapour pressure ('es'), actual vapour pressure ('ea') and relative humidity ('RH') are calculated from the original data using the improved August-Roche-Magnus approximation (Alduchov & Eskridge 1996) and included in the final data set. The resulting metadata include station identification information, country, state, latitude, longitude, elevation, weather observatio [...truncated...]
Author: Adam H. Sparks [aut, cre] , Tomislav Hengl [aut] , Andrew Nelson [aut] , Hugh Parsonage [cph, ctb] , Taras Kaduk [ctb] , Gwenael Giboire [ctb] , Lukasz Pawlik [ctb] , Ross Darnell [ctb] , Tyler Widdison [ctb] ` did not return stations in order of nea [...truncated...]
Maintainer: Adam H. Sparks <adamhsparks@gmail.com>

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Package gkwreg updated to version 2.1.1 with previous version 1.0.10 dated 2025-07-09

Title: Generalized Kumaraswamy Regression Models for Bounded Data
Description: Implements regression models for bounded continuous data in the open interval (0,1) using the five-parameter Generalized Kumaraswamy distribution. Supports modeling all distribution parameters (alpha, beta, gamma, delta, lambda) as functions of predictors through various link functions. Provides efficient maximum likelihood estimation via Template Model Builder ('TMB'), offering comprehensive diagnostics, model comparison tools, and simulation methods. Particularly useful for analyzing proportions, rates, indices, and other bounded response data with complex distributional features not adequately captured by simpler models.
Author: Jose Evandeilton Lopes [aut, cre]
Maintainer: Jose Evandeilton Lopes <evandeilton@gmail.com>

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Package ggseqplot updated to version 0.8.9 with previous version 0.8.8 dated 2025-10-08

Title: Render Sequence Plots using 'ggplot2'
Description: A set of wrapper functions that mainly re-produces most of the sequence plots rendered with TraMineR::seqplot(). Whereas 'TraMineR' uses base R to produce the plots this library draws on 'ggplot2'. The plots are produced on the basis of a sequence object defined with TraMineR::seqdef(). The package automates the reshaping and plotting of sequence data. Resulting plots are of class 'ggplot', i.e. components can be added and tweaked using '+' and regular 'ggplot2' functions.
Author: Marcel Raab [aut, cre]
Maintainer: Marcel Raab <marcel.raab@gmail.com>

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Package devianLM updated to version 1.0.6 with previous version 1.0.5 dated 2025-11-10

Title: Detecting Extremal Values in a Normal Linear Model
Description: Provides a method to detect values poorly explained by a Gaussian linear model. The procedure is based on the maximum of the absolute value of the studentized residuals, which is a parameter-free statistic. This approach generalizes several procedures used to detect abnormal values during longitudinal monitoring of biological markers. For methodological details, see: Berthelot G., Saulière G., Dedecker J. (2025). "DEViaN-LM An R Package for Detecting Abnormal Values in the Gaussian Linear Model". HAL Id: hal-05230549. <https://hal.science/hal-05230549>.
Author: Guillaume Sauliere [aut] , Geoffroy Berthelot [aut, cre] , Jerome Dedecker [aut]
Maintainer: Geoffroy Berthelot <geoffroy.berthelot@insep.fr>

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Package afttest updated to version 4.5.1 with previous version 4.3.2.3 dated 2024-01-16

Title: Model Diagnostics for Accelerated Failure Time Models
Description: A collection of model checking methods for semiparametric accelerated failure time (AFT) models under the rank-based approach. For the (computational) efficiency, Gehan's weight is used. It provides functions to verify whether the observed data fit the specific model assumptions such as a functional form of each covariate, a link function, and an omnibus test. The p-value offered in this package is based on the Kolmogorov-type supremum test and the variance of the proposed test statistics is estimated through the re-sampling method. Furthermore, a graphical technique to compare the shape of the observed residual to a number of the approximated realizations is provided. See the following references; A general model-checking procedure for semiparametric accelerated failure time models, Statistics and Computing, 34 (3), 117 <doi:10.1007/s11222-024-10431-7>; Diagnostics for semiparametric accelerated failure time models with R package 'afttest', arXiv, <doi:10.48550/arXiv.2511.098 [...truncated...]
Author: Woojung Bae [aut, cre] , Dongrak Choi [aut] , Jun Yan [aut] , Sangwook Kang [aut]
Maintainer: Woojung Bae <matt.woojung@gmail.com>

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Package teal.reporter updated to version 0.6.0 with previous version 0.5.0 dated 2025-08-18

Title: Reporting Tools for 'shiny' Modules
Description: Prebuilt 'shiny' modules containing tools for the generation of 'rmarkdown' reports, supporting reproducible research and analysis.
Author: Dawid Kaledkowski [aut, cre] , Kartikeya Kirar [aut] , Marcin Kosinski [aut], Maciej Nasinski [aut], Konrad Pagacz [aut], Mahmoud Hallal [aut], Chendi Liao [rev], Dony Unardi [rev], F. Hoffmann-La Roche AG [cph, fnd]
Maintainer: Dawid Kaledkowski <dawid.kaledkowski@roche.com>

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Package PBSmodelling updated to version 2.70.2 with previous version 2.69.3 dated 2023-11-09

Title: GUI Tools Made Easy: Interact with Models and Explore Data
Description: Provides software to facilitate the design, testing, and operation of computer models. It focuses particularly on tools that make it easy to construct and edit a customized graphical user interface ('GUI'). Although our simplified 'GUI' language depends heavily on the R interface to the 'Tcl/Tk' package, a user does not need to know 'Tcl/Tk'. Examples illustrate models built with other R packages, including 'PBSmapping', 'PBSddesolve', and 'BRugs'. A complete user's guide 'PBSmodelling-UG.pdf' shows how to use this package effectively.
Author: Jon T. Schnute [aut], Alex Couture-Beil [aut], Rowan Haigh [aut], Nicholas Boers [aut], Anisa Egeli [aut], A. R. Kronlund [ctb], Steve Martell [ctb], Norm Olsen [ctb], Nick Fisch [cre]
Maintainer: Nick Fisch <nick.fisch@dfo-mpo.gc.ca>

Diff between PBSmodelling versions 2.69.3 dated 2023-11-09 and 2.70.2 dated 2025-11-15

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Package matrixCorr readmission to version 0.6.2 with previous version 0.5.1 dated 2025-09-22

Title: Collection of Correlation and Association Estimators
Description: Compute correlation and other association matrices from small to high-dimensional datasets with relative simple functions and sensible defaults. Includes options for shrinkage and robustness to improve results in noisy or high-dimensional settings (p >= n), plus convenient print/plot methods for inspection. Implemented with optimised C++ backends using BLAS/OpenMP and memory-aware symmetric updates. Works with base matrices and data frames, returning standard R objects via a consistent S3 interface. Useful across genomics, agriculture, and machine-learning workflows. Supports Pearson, Spearman, Kendall, distance correlation, partial correlation, and robust biweight mid-correlation; Bland–Altman analyses and Lin's concordance correlation coefficient (including repeated-measures extensions). Methods based on Ledoit and Wolf (2004) <doi:10.1016/S0047-259X(03)00096-4>; Schäfer and Strimmer (2005) <doi:10.2202/1544-6115.1175>; Lin (1989) <doi:10.2307/2532051>.
Author: Thiago de Paula Oliveira [aut, cre]
Maintainer: Thiago de Paula Oliveira <thiago.paula.oliveira@gmail.com>

This is a re-admission after prior archival of version 0.5.1 dated 2025-09-22

Diff between matrixCorr versions 0.5.1 dated 2025-09-22 and 0.6.2 dated 2025-11-15

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Package jfa updated to version 0.7.4 with previous version 0.7.3 dated 2025-03-10

Title: Statistical Methods for Auditing
Description: Provides statistical methods for auditing as implemented in JASP for Audit (Derks et al., 2021 <doi:10.21105/joss.02733>). First, the package makes it easy for an auditor to plan a statistical sample, select the sample from the population, and evaluate the misstatement in the sample compliant with international auditing standards. Second, the package provides statistical methods for auditing data, including tests of digit distributions and repeated values. Finally, the package includes methods for auditing algorithms on the aspect of fairness and bias. Next to classical statistical methodology, the package implements Bayesian equivalents of these methods whose statistical underpinnings are described in Derks et al. (2021) <doi:10.1111/ijau.12240>, Derks et al. (2024) <doi:10.2308/AJPT-2021-086>, Derks et al. (2022) <doi:10.31234/osf.io/8nf3e> Derks et al. (2024) <doi:10.31234/osf.io/tgq5z>, and Derks et al. (2025) <doi:10.31234/osf.io/b8tu2>.
Author: Koen Derks [aut, cre] , Lotte Mensink [ctb] , Federica Picogna [ctb]
Maintainer: Koen Derks <k.derks@nyenrode.nl>

Diff between jfa versions 0.7.3 dated 2025-03-10 and 0.7.4 dated 2025-11-15

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Package islasso updated to version 1.6.2 with previous version 1.6.1 dated 2025-11-14

Title: The Induced Smoothed Lasso
Description: An implementation of the induced smoothing (IS) idea to lasso regularization models to allow estimation and inference on the model coefficients (currently hypothesis testing only). Linear, logistic, Poisson and gamma regressions with several link functions are implemented. The algorithm is described in the original paper; see <doi:10.1177/0962280219842890> and discussed in a tutorial <doi:10.13140/RG.2.2.16360.11521>.
Author: Gianluca Sottile [aut, cre], Giovanna Cilluffo [aut, ctb], Vito MR Muggeo [aut, ctb]
Maintainer: Gianluca Sottile <gianluca.sottile@unipa.it>

Diff between islasso versions 1.6.1 dated 2025-11-14 and 1.6.2 dated 2025-11-15

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Package fDMA readmission to version 2.2.9 with previous version 2.2.8 dated 2025-01-24

Title: Dynamic Model Averaging and Dynamic Model Selection for Continuous Outcomes
Description: Allows to estimate dynamic model averaging, dynamic model selection and median probability model. The original methods are implemented, as well as, selected further modifications of these methods. In particular the user might choose between recursive moment estimation and exponentially moving average for variance updating. Inclusion probabilities might be modified in a way using 'Google Trends'. The code is written in a way which minimises the computational burden (which is quite an obstacle for dynamic model averaging if many variables are used). For example, this package allows for parallel computations and Occam's window approach. The package is designed in a way that is hoped to be especially useful in economics and finance. Main reference: Raftery, A.E., Karny, M., Ettler, P. (2010) <doi:10.1198/TECH.2009.08104>.
Author: Krzysztof Drachal [aut, cre]
Maintainer: Krzysztof Drachal <kdrachal@wne.uw.edu.pl>

This is a re-admission after prior archival of version 2.2.8 dated 2025-01-24

Diff between fDMA versions 2.2.8 dated 2025-01-24 and 2.2.9 dated 2025-11-15

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Package FastKRR updated to version 0.1.2 with previous version 0.1.1 dated 2025-10-08

Title: Kernel Ridge Regression using 'RcppArmadillo'
Description: Provides core computational operations in C++ via 'RcppArmadillo', enabling faster performance than pure R, improved numerical stability, and parallel execution with OpenMP where available. On systems without OpenMP support, the package automatically falls back to single-threaded execution with no user configuration required. For efficient model selection, it integrates with 'CVST' to provide sequential-testing cross-validation that identifies competitive hyperparameters without exhaustive grid search. The package offers a unified interface for exact kernel ridge regression and three scalable approximations—Nyström, Pivoted Cholesky, and Random Fourier Features—allowing analyses with substantially larger sample sizes than are feasible with exact KRR. It also integrates with the 'tidymodels' ecosystem via the 'parsnip' model specification 'krr_reg', and the S3 method tunable.krr_reg(). To understand the theoretical background, one can refer to Wainwright (2019) <doi:10.1017/978110862 [...truncated...]
Author: Gyeongmin Kim [aut] , Seyoung Lee [aut] , Miyoung Jang [aut] , Kwan-Young Bak [aut, cre, cph]
Maintainer: Kwan-Young Bak <kybak@sungshin.ac.kr>

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Package ellmer updated to version 0.4.0 with previous version 0.3.2 dated 2025-09-03

Title: Chat with Large Language Models
Description: Chat with large language models from a range of providers including 'Claude' <https://claude.ai>, 'OpenAI' <https://chatgpt.com>, and more. Supports streaming, asynchronous calls, tool calling, and structured data extraction.
Author: Hadley Wickham [aut, cre] , Joe Cheng [aut], Aaron Jacobs [aut], Garrick Aden-Buie [aut] , Barret Schloerke [aut] , Posit Software, PBC [cph, fnd]
Maintainer: Hadley Wickham <hadley@posit.co>

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Package ClimMobTools updated to version 1.8 with previous version 1.6 dated 2025-07-07

Title: API Client for the 'ClimMob' Platform
Description: API client for 'ClimMob', an open source software for decentralized large-N trials with the 'tricot' approach <https://climmob.net/>. Developed by van Etten et al. (2019) <doi:10.1017/S0014479716000739>, it turns the research paradigm on its head; instead of a few researchers designing complicated trials to compare several technologies in search of the best solutions for the target environment, it enables many participants to carry out reasonably simple experiments that taken together can offer even more information. 'ClimMobTools' enables project managers to deep explore and analyse their 'ClimMob' data in R.
Author: Kaue de Sousa [aut, cre] , Jacob van Etten [aut] , Brandon Madriz [aut]
Maintainer: Kaue de Sousa <desousa.kaue@gmail.com>

Diff between ClimMobTools versions 1.6 dated 2025-07-07 and 1.8 dated 2025-11-15

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 ClimMobTools-1.8/ClimMobTools/R/exportTrialMetadata.R           |only
 ClimMobTools-1.8/ClimMobTools/R/exportTricotRanks.R             |only
 ClimMobTools-1.8/ClimMobTools/R/exportVariablesDescription.R    |only
 ClimMobTools-1.8/ClimMobTools/R/rmGeoIdentity.R                 |   17 ++++-
 ClimMobTools-1.8/ClimMobTools/man/ClimMobTools.Rd               |    2 
 ClimMobTools-1.8/ClimMobTools/man/exportBlockData.Rd            |only
 ClimMobTools-1.8/ClimMobTools/man/exportMeasuredTraits.Rd       |only
 ClimMobTools-1.8/ClimMobTools/man/exportTrialMetadata.Rd        |only
 ClimMobTools-1.8/ClimMobTools/man/exportTricotRanks.Rd          |only
 ClimMobTools-1.8/ClimMobTools/man/exportVariablesDescription.Rd |only
 ClimMobTools-1.8/ClimMobTools/man/rmGeoIdentity.Rd              |    9 ++
 19 files changed, 77 insertions(+), 32 deletions(-)

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