Wed, 28 Jan 2026

Package portalr updated to version 0.4.5 with previous version 0.4.4 dated 2025-06-30

Title: Create Useful Summaries of the Portal Data
Description: Download and generate summaries for the rodent, plant, ant, and weather data from the Portal Project. Portal is a long-term (and ongoing) experimental monitoring site in the Chihuahuan desert. The raw data files can be found at <https://github.com/weecology/portaldata>.
Author: Glenda M. Yenni [aut, cre] , Hao Ye [aut] , Erica M. Christensen [aut] , Juniper L. Simonis [aut] , Ellen K. Bledsoe [aut] , Renata M. Diaz [aut] , Shawn D. Taylor [aut] , Ethan P, White [aut] , S.K. Morgan Ernest [aut] , Weecology [cph]
Maintainer: Glenda M. Yenni <glenda@weecology.org>

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Package nhlscraper updated to version 0.4.2 with previous version 0.4.1 dated 2025-12-17

Title: Scraper for National Hockey League Data
Description: Scrapes and cleans data from the 'NHL' and 'ESPN' APIs into data.frames and lists. Wraps 125+ endpoints documented in <https://github.com/RentoSaijo/nhlscraper/wiki> from high-level multi-season summaries and award winners to low-level decisecond replays and bookmakers' odds, making them more accessible. Features cleaning and visualization tools, primarily for play-by-plays.
Author: Rento Saijo [aut, cre, cph] , Lars Skytte [ctb]
Maintainer: Rento Saijo <rentosaijo0527@gmail.com>

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Package lcda updated to version 0.3.3 with previous version 0.3.2 dated 2024-02-15

Title: Latent Class Discriminant Analysis
Description: Providing a method for Local Discrimination via Latent Class Models. The approach is described in <https://www.r-project.org/conferences/useR-2009/abstracts/pdf/Bucker.pdf>.
Author: Michael Buecker [aut, cre]
Maintainer: Michael Buecker <michael.buecker@fh-muenster.de>

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Package edgemodelr updated to version 0.1.5 with previous version 0.1.4 dated 2026-01-22

Title: Local Large Language Model Inference Engine
Description: Enables R users to run large language models locally using 'GGUF' model files and the 'llama.cpp' inference engine. Provides a complete R interface for loading models, generating text completions, and streaming responses in real-time. Supports local inference without requiring cloud APIs or internet connectivity, ensuring complete data privacy and control. Based on the 'llama.cpp' project by Georgi Gerganov (2023) <https://github.com/ggml-org/llama.cpp>.
Author: Pawan Rama Mali [aut, cre, cph], Georgi Gerganov [aut, cph] , The ggml authors [cph] , Jeffrey Quesnelle [ctb, cph] , Bowen Peng [ctb, cph] , pi6am [ctb] , Ivan Yurchenko [ctb] , Dirk Eddelbuettel [ctb, rev]
Maintainer: Pawan Rama Mali <prm@outlook.in>

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Package bayesianVARs updated to version 0.1.6 with previous version 0.1.5 dated 2024-11-13

Title: MCMC Estimation of Bayesian Vectorautoregressions
Description: Efficient Markov Chain Monte Carlo (MCMC) algorithms for the fully Bayesian estimation of vectorautoregressions (VARs) featuring stochastic volatility (SV). Implements state-of-the-art shrinkage priors following Gruber & Kastner (2025) <doi:10.1016/j.ijforecast.2025.02.001>. Efficient equation-per-equation estimation following Kastner & Huber (2020) <doi:10.1002/for.2680> and Carrerio et al. (2021) <doi:10.1016/j.jeconom.2021.11.010>.
Author: Luis Gruber [cph, aut, cre] , Stefan Haan [aut], Gregor Kastner [aut, ths]
Maintainer: Luis Gruber <Luis.Gruber@aau.at>

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Package xhaz updated to version 2.1.0 with previous version 2.0.2 dated 2024-06-29

Title: Excess Hazard Modelling Considering Inappropriate Mortality Rates
Description: Fits relative survival regression models with or without proportional excess hazards and with the additional possibility to correct for background mortality by one or more parameter(s). These models are relevant when the observed mortality in the studied group is not comparable to that of the general population or in population-based studies where the available life tables used for net survival estimation are insufficiently stratified. In the latter case, the proposed model by Touraine et al. (2020) <doi:10.1177/0962280218823234> can be used. The user can also fit a model that relaxes the proportional expected hazards assumption considered in the Touraine et al. excess hazard model. This extension was proposed by Mba et al. (2020) <doi:10.1186/s12874-020-01139-z> to allow non-proportional effects of the additional variable on the general population mortality. In non-population-based studies, researchers can identify non-comparability source of bias in terms of expected mort [...truncated...]
Author: Juste Goungounga [aut, cre] , Hadrien Charvat [aut] , Darlin Mba [aut] , Nathalie Graffeo [aut] , Roch Giorgi [aut]
Maintainer: Juste Goungounga <juste.goungounga@ehesp.fr>

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Package INLAvaan updated to version 0.2.3 with previous version 0.2.2 dated 2026-01-27

Title: Approximate Bayesian Latent Variable Analysis
Description: Implements approximate Bayesian inference for Structural Equation Models (SEM) using a custom adaptation of the Integrated Nested Laplace Approximation as described in Rue et al. (2009) <doi:10.1111/j.1467-9868.2008.00700.x>. Provides a computationally efficient alternative to Markov Chain Monte Carlo (MCMC) for Bayesian estimation, allowing users to fit latent variable models using the 'lavaan' syntax.
Author: Haziq Jamil [aut, cre, cph] , Havard Rue [ctb] , Alvin Bong [ctb]
Maintainer: Haziq Jamil <haziq.jamil@gmail.com>

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Package traj updated to version 3.0.0 with previous version 2.2.1 dated 2025-02-01

Title: Feature-Based Clustering of Longitudinal Trajectories
Description: Identifies clusters of individual longitudinal trajectories. In the spirit of Leffondre et al. (2004), the procedure involves identifying each trajectory to a point in the space of measures. In this context, a measure is a quantity meant to capture a certain characteristic feature of the trajectory. The points in the space of measures are then clustered using a version of spectral clustering.
Author: Marie-Pierre Sylvestre [aut], Laurence Boulanger [aut, cre], Gillis Delmas Tchouangue Dinkou [ctb], Dan Vatnik [ctb]
Maintainer: Laurence Boulanger <laurence.boulanger@umontreal.ca>

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Package tepr updated to version 1.1.14 with previous version 1.1.13 dated 2025-12-11

Title: Transcription Elongation Profiling
Description: The general principle relies on calculating the cumulative signal of nascent RNA sequencing over the gene body of any given gene or transcription unit. 'tepr' can identify transcription attenuation sites by comparing profile to a null model which assumes uniform read density over the entirety of the transcription unit. It can also identify increased or diminished transcription attenuation by comparing two conditions. Besides rigorous statistical testing and high sensitivity, a major feature of 'tepr' is its ability to provide the elongation pattern of each individual gene, including the position of the main attenuation point when such a phenomenon occurs. Using 'tepr', users can visualize and refine genome-wide aggregated analyses of elongation patterns to robustly identify effects specific to subsets of genes. These metrics are suitable for internal comparisons (between genes in each condition) and for studying elongation of the same gene in different conditions or comparing it to a p [...truncated...]
Author: Nicolas Descostes [cre], Victor Billon [aut], Gael Cristofari [aut]
Maintainer: Nicolas Descostes <nicolas.descostes@gmail.com>

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Package optimall updated to version 1.3.1 with previous version 1.3.0 dated 2025-09-08

Title: Allocate Samples Among Strata
Description: Functions for the design process of survey sampling, with specific tools for multi-wave and multi-phase designs. Perform optimum allocation using Neyman (1934) <doi:10.2307/2342192> or Wright (2012) <doi:10.1080/00031305.2012.733679> allocation, split strata based on quantiles or values of known variables, randomly select samples from strata, allocate sampling waves iteratively, and organize a complex survey design. Also includes a Shiny application for observing the effects of different strata splits. A paper on this package was published in the Journal of Statistical Software <doi:10.18637/jss.v114.i10>.
Author: Jasper Yang [aut, cre], Pamela Shaw [aut], Bryan Shepherd [ctb], Thomas Lumley [ctb], Gustavo Amorim [rev]
Maintainer: Jasper Yang <jbyang@uw.edu>

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New package rregm with initial version 1.0
Package: rregm
Title: Reparameterized Regression Models
Version: 1.0
Maintainer: Diego Gallardo <dgallardo@ubiobio.cl>
Description: Provides estimation and data generation tools for several new regression models, including the gamma, beta, inverse gamma and beta prime distributions. These models can be parameterized based on the mean, median, mode, geometric mean and harmonic mean, as specified by the user. For details, see Bourguignon and Gallardo (2025a) <doi:10.1016/j.chemolab.2025.105382> and Bourguignon and Gallardo (2025b) <doi:10.1111/stan.70007>.
Depends: R (>= 4.0.0), stats
Imports: extraDistr, pracma, gamlss, gamlss.dist, invgamma
License: GPL (>= 2)
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-01-25 02:44:06 UTC; Diego
Author: Diego Gallardo [aut, cre], Marcelo Bourguignon [aut], Marcia Brandao [aut]
Repository: CRAN
Date/Publication: 2026-01-28 19:10:02 UTC

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New package evalHTE with initial version 0.1.0
Package: evalHTE
Title: Evaluating Heterogeneous Treatment Effects
Version: 0.1.0
Description: Provides various statistical methods for evaluating heterogeneous treatment effects (HTE) in randomized experiments. The package includes tools to estimate uniform confidence bands for estimation of the group average treatment effect sorted by generic machine learning algorithms (GATES). It also provides the tools to identify a subgroup of individuals who are likely to benefit from a treatment the most "exceptional responders" or those who are harmed by it. Detailed reference in Imai and Li (2023) <doi:10.48550/arXiv.2310.07973>.
License: MIT + file LICENSE
Depends: R (>= 3.50), dplyr (>= 1.0.10)
Imports: cli, evalITR, ggplot2, ggthemes, rlang, zoo, furrr, ggdist, scales, tidyr, stats, purrr, Matrix, MASS, quadprog, caret
Encoding: UTF-8
Suggests: knitr, rmarkdown, future, grf, magrittr, tibble
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-01-24 22:35:01 UTC; shazn
Author: Michael Lingzhi Li [aut, cre], Kosuke Imai [aut], Jialu Li [ctb]
Maintainer: Michael Lingzhi Li <mili@hbs.edu>
Repository: CRAN
Date/Publication: 2026-01-28 19:10:08 UTC

More information about evalHTE at CRAN
Permanent link

Package diffMeshGP readmission to version 0.1.1 with previous version 0.1.0 dated 2017-05-12

Title: Multi-Fidelity Computer Experiments Using the Tuo-Wu-Yu Model
Description: This R function implements the nonstationary Kriging model proposed by Tuo, Wu and Yu (2014) <DOI:10.1080/00401706.2013.842935> for analyzing multi-fidelity computer outputs. This function computes the maximum likelihood estimates for the model parameters as well as the predictive means and variances of the exact solution.
Author: Wenjia Wang [aut, cre], Rui Tuo [aut], C. F. Jeff Wu [aut]
Maintainer: Wenjia Wang <1992wangwenjia@gmail.com>

This is a re-admission after prior archival of version 0.1.0 dated 2017-05-12

Diff between diffMeshGP versions 0.1.0 dated 2017-05-12 and 0.1.1 dated 2026-01-28

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Permanent link

New package vazul with initial version 1.0.0
Package: vazul
Title: Analysis Blinding Tools
Version: 1.0.0
Description: Provides tools for analysis blinding in confirmatory research contexts by masking and scrambling test-relevant aspects of data. Vector-, data frame-, and row-wise operations support blinding for hierarchical and repeated-measures designs. For more details see MacCoun and Perlmutter (2015) <doi:10.1038/526187a> and Dutilh, Sarafoglou, and Wagenmakers (2019) <doi:10.1007/s11229-019-02456-7>.
License: MIT + file LICENSE
URL: https://nthun.github.io/vazul/
BugReports: https://github.com/nthun/vazul/issues
Depends: R (>= 4.1.0)
Imports: dplyr, lifecycle, rlang, tidyselect, stats
Suggests: testthat, covr, knitr, quarto
VignetteBuilder: quarto
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2026-01-24 21:34:30 UTC; thoma
Author: Tamas Nagy [aut, cre] , Alexandra Sarafoglou [aut, dtc] , Marton Kovacs [aut]
Maintainer: Tamas Nagy <nagytamas.hungary@gmail.com>
Repository: CRAN
Date/Publication: 2026-01-28 18:50:02 UTC

More information about vazul at CRAN
Permanent link

New package SignalY with initial version 1.1.0
Package: SignalY
Title: Signal Extraction from Panel Data via Bayesian Sparse Regression and Spectral Decomposition
Version: 1.1.0
Author: Jose Mauricio Gomez Julian [aut, cre]
Maintainer: Jose Mauricio Gomez Julian <isadore.nabi@pm.me>
Description: Provides a comprehensive toolkit for extracting latent signals from panel data through multivariate time series analysis. Implements spectral decomposition methods including wavelet multiresolution analysis via maximal overlap discrete wavelet transform, Percival and Walden (2000) <doi:10.1017/CBO9780511841040>, empirical mode decomposition for non-stationary signals, Huang et al. (1998) <doi:10.1098/rspa.1998.0193>, and Bayesian trend extraction via the Grant-Chan embedded Hodrick-Prescott filter, Grant and Chan (2017) <doi:10.1016/j.jedc.2016.12.007>. Features Bayesian variable selection through regularized Horseshoe priors, Piironen and Vehtari (2017) <doi:10.1214/17-EJS1337SI>, for identifying structurally relevant predictors from high-dimensional candidate sets. Includes dynamic factor model estimation, principal component analysis with bootstrap significance testing, and automated technical interpretation of signal morphology and variance topology.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: stats, graphics, grDevices, utils, parallel, waveslim (>= 1.8.4), EMD (>= 1.5.9), urca (>= 1.3.3)
Suggests: GPArotation, plotly, cmdstanr (>= 0.7.0), posterior (>= 1.5.0), bayesplot (>= 1.10.0), loo (>= 2.6.0), projpred (>= 2.6.0), testthat (>= 3.0.0), knitr, rmarkdown, patchwork
Additional_repositories: https://mc-stan.org/r-packages/
VignetteBuilder: knitr
URL: https://github.com/IsadoreNabi/SignalY
BugReports: https://github.com/IsadoreNabi/SignalY/issues
NeedsCompilation: no
Packaged: 2026-01-24 19:18:05 UTC; ROG
Repository: CRAN
Date/Publication: 2026-01-28 18:50:17 UTC

More information about SignalY at CRAN
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Package robustlmm updated to version 3.4-2 with previous version 3.3-3 dated 2025-05-26

Title: Robust Linear Mixed Effects Models
Description: Implements the Robust Scoring Equations estimator to fit linear mixed effects models robustly. Robustness is achieved by modification of the scoring equations combined with the Design Adaptive Scale approach.
Author: Manuel Koller [aut, cre]
Maintainer: Manuel Koller <kollerma@proton.me>

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Package robsurvey updated to version 0.7-1 with previous version 0.7 dated 2024-08-22

Title: Robust Survey Statistics Estimation
Description: Robust (outlier-resistant) estimators of finite population characteristics like of means, totals, ratios, regression, etc. Available methods are M- and GM-estimators of regression, weight reduction, trimming, and winsorization. The package extends the 'survey' <https://CRAN.R-project.org/package=survey> package.
Author: Beat Hulliger [aut] , Tobias Schoch [aut, cre] , Martin Sterchi [ctr, com], R-core [ctb, cph]
Maintainer: Tobias Schoch <tobias.schoch@fhnw.ch>

Diff between robsurvey versions 0.7 dated 2024-08-22 and 0.7-1 dated 2026-01-28

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Package rixpress updated to version 0.11.2 with previous version 0.10.1 dated 2025-10-14

Title: Build Reproducible Analytical Pipelines with 'Nix'
Description: Streamlines the creation of reproducible analytical pipelines using 'default.nix' expressions generated via the 'rix' package for reproducibility. Define derivations in 'R', 'Python' or 'Julia', chain them into a composition of pure functions and build the resulting pipeline using 'Nix' as the underlying end-to-end build tool. Functions to plot the pipeline as a directed acyclic graph are included, as well as functions to load and inspect intermediary results for interactive analysis. User experience heavily inspired by the 'targets' package.
Author: Bruno Rodrigues [aut, cre] , William Michael Landau [rev] for rOpenSci, see <https://github.com/ropensci/software-review/issues/706>), Anthony Martinez [rev] for rOpenSci, see <https://github.com/ropensci/software-review/issues/625>)
Maintainer: Bruno Rodrigues <bruno@brodrigues.co>

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Package rix updated to version 0.18.1 with previous version 0.17.4 dated 2026-01-16

Title: Reproducible Data Science Environments with 'Nix'
Description: Simplifies the creation of reproducible data science environments using the 'Nix' package manager, as described in Dolstra (2006) <ISBN 90-393-4130-3>. The included `rix()` function generates a complete description of the environment as a `default.nix` file, which can then be built using 'Nix'. This results in project specific software environments with pinned versions of R, packages, linked system dependencies, and other tools or programming languages such as Python or Julia. Additional helpers make it easy to run R code in 'Nix' software environments for testing and production.
Author: Bruno Rodrigues [aut, cre] , Philipp Baumann [aut] , David Watkins [rev] for rOpenSci, see <https://github.com/ropensci/software-review/issues/625>), Jacob Wujiciak-Jens [rev] for rOpenSci, see <https://github.com/ropensci/software-review/issues/62 [...truncated...]
Maintainer: Bruno Rodrigues <bruno@brodrigues.co>

Diff between rix versions 0.17.4 dated 2026-01-16 and 0.18.1 dated 2026-01-28

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Package kerntools updated to version 1.2.1 with previous version 1.2.0 dated 2025-02-19

Title: Kernel Functions and Tools for Machine Learning Applications
Description: Kernel functions for diverse types of data (including, but not restricted to: nonnegative and real vectors, real matrices, categorical and ordinal variables, sets, strings), plus other utilities like kernel similarity, kernel Principal Components Analysis (PCA) and features' importance for Support Vector Machines (SVMs), which expand other 'R' packages like 'kernlab'.
Author: Elies Ramon [aut, cre, cph]
Maintainer: Elies Ramon <eramon@everlyrusher.com>

Diff between kerntools versions 1.2.0 dated 2025-02-19 and 1.2.1 dated 2026-01-28

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Permanent link

New package EQUALPrognosis with initial version 0.1.0
Package: EQUALPrognosis
Title: Analysing Prognostic Studies
Version: 0.1.0
Date: 2026-01-16
Author: Kurinchi Gurusamy [aut, cre]
Maintainer: Kurinchi Gurusamy <k.gurusamy@ucl.ac.uk>
Depends: stats, ggplot2, survival
Imports: base64enc, CalibrationCurves, mime, predtools, pROC, stringr
Description: Functions that help with analysis of prognostic study data. This allows users with little experience of developing models to develop models and assess the performance of the prognostic models. This also summarises the information, so the performance of multiple models can be displayed simultaneously. Gurusamy, K (2026)<https://github.com/kurinchi2k/EQUALPrognosis>.
License: GPL (>= 3)
Encoding: UTF-8
URL: https://sites.google.com/view/equal-group/home
NeedsCompilation: no
Packaged: 2026-01-24 08:38:37 UTC; kurin
Repository: CRAN
Date/Publication: 2026-01-28 18:40:16 UTC

More information about EQUALPrognosis at CRAN
Permanent link

New package DataQualityDashboard with initial version 2.8.6
Package: DataQualityDashboard
Title: Execute and View Data Quality Checks on OMOP CDM Database
Version: 2.8.6
Date: 2026-01-22
Author: Katy Sadowski [aut, cre], Clair Blacketer [aut], Maxim Moinat [aut], Ajit Londhe [aut], Anthony Sena [aut], Anthony Molinaro [aut], Frank DeFalco [aut], Pavel Grafkin [aut]
Maintainer: Katy Sadowski <sadowski@ohdsi.org>
Description: Assesses data quality in Observational Medical Outcomes Partnership Common Data Model (OMOP CDM) databases. Executes data quality checks and provides an R `shiny` application to view the results.
License: Apache License 2.0
VignetteBuilder: knitr
URL: https://github.com/OHDSI/DataQualityDashboard
BugReports: https://github.com/OHDSI/DataQualityDashboard/issues
Depends: R (>= 3.2.2), DatabaseConnector (>= 2.0.2)
Imports: magrittr, ParallelLogger, dplyr, jsonlite, rJava, SqlRender (>= 1.10.1), plyr, stringr, rlang, tidyselect, readr
Suggests: testthat, knitr, rmarkdown, markdown, shiny, ggplot2, Eunomia (>= 2.0.0), duckdb, R.utils, devtools
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-01-24 18:39:14 UTC; katysadowski
Repository: CRAN
Date/Publication: 2026-01-28 18:50:23 UTC

More information about DataQualityDashboard at CRAN
Permanent link

Package wintime updated to version 0.4.3 with previous version 0.4.2 dated 2025-12-17

Title: Win Time Methods for Time-to-Event Data in Clinical Trials
Description: Performs an analysis of time-to-event clinical trial data using various "win time" methods, including 'ewt', 'ewtr', 'rmt', 'ewtp', 'rewtp', 'ewtpr', 'rewtpr', 'max', 'wtr', 'rwtr', 'pwt', and 'rpwt'. These methods are used to calculate and compare treatment effects on ordered composite endpoints. The package handles event times, event indicators, and treatment arm indicators and supports calculations on observed and resampled data. Detailed explanations of each method and usage examples are provided in "Use of win time for ordered composite endpoints in clinical trials," by Troendle et al. (2024)<https://pubmed.ncbi.nlm.nih.gov/38417455/>. For more information, see the package documentation or the vignette titled "Introduction to wintime."
Author: James Troendle [aut, cre], Samuel Lawrence [aut]
Maintainer: James Troendle <james.troendle@nih.gov>

Diff between wintime versions 0.4.2 dated 2025-12-17 and 0.4.3 dated 2026-01-28

 DESCRIPTION                    |    6 +++---
 MD5                            |   14 +++++++-------
 R/ewt.R                        |    2 +-
 R/ewtp.R                       |   15 +++++++++++++++
 R/km.R                         |   18 ++++++++++++------
 R/rmt.R                        |   18 ++++++++++++++++--
 R/wintime.R                    |   32 +++++++++++++++++++++++++-------
 inst/doc/wintime_vignette.html |   36 ++++++++++++++++++------------------
 8 files changed, 97 insertions(+), 44 deletions(-)

More information about wintime at CRAN
Permanent link

Package omopgenerics updated to version 1.3.6 with previous version 1.3.5 dated 2025-12-10

Title: Methods and Classes for the OMOP Common Data Model
Description: Provides definitions of core classes and methods used by analytic pipelines that query the OMOP (Observational Medical Outcomes Partnership) common data model.
Author: Marti Catala [aut, cre] , Edward Burn [aut] , Mike Du [ctb] , Yuchen Guo [ctb] , Adam Black [ctb] , Marta Alcalde-Herraiz [ctb]
Maintainer: Marti Catala <marti.catalasabate@ndorms.ox.ac.uk>

Diff between omopgenerics versions 1.3.5 dated 2025-12-10 and 1.3.6 dated 2026-01-28

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 305 files changed, 39159 insertions(+), 39088 deletions(-)

More information about omopgenerics at CRAN
Permanent link

Package OlinkAnalyze updated to version 4.5.0 with previous version 4.4.0 dated 2025-12-02

Title: Facilitate Analysis of Proteomic Data from Olink
Description: A collection of functions to facilitate analysis of proteomic data from Olink, primarily NPX data that has been exported from Olink Software. The functions also work on QUANT data from Olink by log- transforming the QUANT data. The functions are focused on reading data, facilitating 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 help users extract biological insights from proteomic data run on the Olink platform.
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>

Diff between OlinkAnalyze versions 4.4.0 dated 2025-12-02 and 4.5.0 dated 2026-01-28

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 OlinkAnalyze-4.5.0/OlinkAnalyze/tests/testthat/test-olink_lod.R                   |    3 
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 36 files changed, 2386 insertions(+), 1110 deletions(-)

More information about OlinkAnalyze at CRAN
Permanent link

Package antaresRead updated to version 3.0.0 with previous version 2.9.3 dated 2025-11-06

Title: Import, Manipulate and Explore the Results of an 'Antares' Simulation
Description: Import, manipulate and explore results generated by 'Antares', a powerful open source software developed by RTE (Réseau de Transport d’Électricité) to simulate and study electric power systems (more information about 'Antares' here : <https://antares-simulator.org/>).
Author: Tatiana Vargas [aut, cre], Jalal-Edine ZAWAM [aut], Frederic Breant [ctb], Francois Guillem [aut], Benoit Thieurmel [aut], Titouan Robert [aut], Victor Perrier [ctb], Etienne Sanchez [ctb], Assil Mansouri [ctb], Clement Berthet [ctb], Kamel Kemiha [c [...truncated...]
Maintainer: Tatiana Vargas <tatiana.vargas@rte-france.com>

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Package affiner updated to version 0.2.1 with previous version 0.1.3 dated 2024-12-02

Title: A Finer Way to Render 3D Illustrated Objects in 'grid' Using Affine Transformations
Description: Dilate, permute, project, reflect, rotate, shear, and translate 2D and 3D points. Supports parallel projections including oblique projections such as the cabinet projection as well as axonometric projections such as the isometric projection. Use 'grid's "affine transformation" feature to render illustrated flat surfaces.
Author: Trevor L. Davis [aut, cre]
Maintainer: Trevor L. Davis <trevor.l.davis@gmail.com>

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Package CohortCharacteristics updated to version 1.1.1 with previous version 1.1.0 dated 2025-11-19

Title: Summarise and Visualise Characteristics of Patients in the OMOP CDM
Description: Summarise and visualise the characteristics of patients in data mapped to the Observational Medical Outcomes Partnership (OMOP) common data model (CDM).
Author: Marti Catala [aut, cre] , Yuchen Guo [aut] , Mike Du [ctb] , Kim Lopez-Guell [aut] , Edward Burn [aut] , Nuria Mercade-Besora [aut] , Marta Alcalde [aut]
Maintainer: Marti Catala <marti.catalasabate@ndorms.ox.ac.uk>

Diff between CohortCharacteristics versions 1.1.0 dated 2025-11-19 and 1.1.1 dated 2026-01-28

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More information about CohortCharacteristics at CRAN
Permanent link

Package DrugUtilisation updated to version 1.1.0 with previous version 1.0.5 dated 2025-11-19

Title: Summarise Patient-Level Drug Utilisation in Data Mapped to the OMOP Common Data Model
Description: Summarise patient-level drug utilisation cohorts using data mapped to the Observational Medical Outcomes Partnership (OMOP) common data model. New users and prevalent users cohorts can be generated and their characteristics, indication and drug use summarised.
Author: Marti Catala [aut, cre] , Mike Du [ctb] , Yuchen Guo [aut] , Kim Lopez-Guell [aut] , Edward Burn [aut] , Xintong Li [ctb] , Marta Alcalde-Herraiz [ctb] , Nuria Mercade-Besora [aut] , Xihang Chen [aut]
Maintainer: Marti Catala <marti.catalasabate@ndorms.ox.ac.uk>

Diff between DrugUtilisation versions 1.0.5 dated 2025-11-19 and 1.1.0 dated 2026-01-28

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Package timeDate updated to version 4052.112 with previous version 4051.111 dated 2025-10-17

Title: Rmetrics - Chronological and Calendar Objects
Description: The 'timeDate' class fulfils the conventions of the ISO 8601 standard as well as of the ANSI C and POSIX standards. Beyond these standards it provides the "Financial Center" concept which allows to handle data records collected in different time zones and mix them up to have always the proper time stamps with respect to your personal financial center, or alternatively to the GMT reference time. It can thus also handle time stamps from historical data records from the same time zone, even if the financial centers changed day light saving times at different calendar dates.
Author: Diethelm Wuertz [aut] , Tobias Setz [aut], Yohan Chalabi [aut], Martin Maechler [ctb] , Joe W. Byers [ctb], Georgi N. Boshnakov [cre, aut]
Maintainer: Georgi N. Boshnakov <georgi.boshnakov@manchester.ac.uk>

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Package R.AlphA.Home readmission to version 2.0.2 with previous version 1.1.0 dated 2025-09-15

Title: Feel at Home using R, Thanks to Shortcuts Functions Making it Simple
Description: A collection of personal functions designed to simplify and streamline common R programming tasks. This package provides reusable tools and shortcuts for frequently used calculations and workflows.
Author: Raphael Flambard [aut, cre], Adrien Cocuaud [ctb]
Maintainer: Raphael Flambard <raphael@ralpha.fr>

This is a re-admission after prior archival of version 1.1.0 dated 2025-09-15

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Package MonteCarloSEM updated to version 2.0.0 with previous version 0.0.8 dated 2024-04-05

Title: Monte Carlo Simulation for Structural Equation Modeling
Description: Provides tools to conduct Monte Carlo simulations under different conditions (e.g., varying sample size, data normality) for structural equation models (SEMs). Data can be simulated based on user-defined factor loadings and correlations, with optional non-normality added via Fleishman's power method (1978) <doi:10.1007/BF02293811>. Once generated, models can be estimated using 'lavaan'. This package facilitates testing model performance across multiple simulation scenarios. When data generation is completed (or when generated data sets are given) model tests can also be run. Please cite as "Orçan, F. (2021). MonteCarloSEM An R Package to Simulate Data for SEM. International Journal of Assessment Tools in Education, 8 (3), 704-713."
Author: Fatih Orcan [aut, cre]
Maintainer: Fatih Orcan <fatihorcan84@gmail.com>

Diff between MonteCarloSEM versions 0.0.8 dated 2024-04-05 and 2.0.0 dated 2026-01-28

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Package maestro updated to version 1.0.0 with previous version 0.7.1 dated 2025-12-09

Title: Orchestration of Data Pipelines
Description: Framework for creating and orchestrating data pipelines. Organize, orchestrate, and monitor multiple pipelines in a single project. Use tags to decorate functions with scheduling parameters and configuration.
Author: Will Hipson [cre, aut, cph] , Ryan Garnett [aut, ctb, cph]
Maintainer: Will Hipson <will.e.hipson@gmail.com>

Diff between maestro versions 0.7.1 dated 2025-12-09 and 1.0.0 dated 2026-01-28

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Package PowRPriori updated to version 0.1.2 with previous version 0.1.1 dated 2025-12-14

Title: Power Analysis via Data Simulation for (Generalized) Linear Mixed Effects Models
Description: Conduct a priori power analyses via Monte-Carlo style data simulation for linear and generalized linear mixed-effects models (LMMs/GLMMs). Provides a user-friendly workflow with helper functions to easily define fixed and random effects as well as diagnostic functions to evaluate the adequacy of the results of the power analysis.
Author: Markus Grill [aut, cre]
Maintainer: Markus Grill <markus.grill@uni-wh.de>

Diff between PowRPriori versions 0.1.1 dated 2025-12-14 and 0.1.2 dated 2026-01-28

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Package PhenotypeR updated to version 0.3.1 with previous version 0.3.0 dated 2026-01-12

Title: Assess Study Cohorts Using a Common Data Model
Description: Phenotype study cohorts in data mapped to the Observational Medical Outcomes Partnership Common Data Model. Diagnostics are run at the database, code list, cohort, and population level to assess whether study cohorts are ready for research.
Author: Edward Burn [aut, cre] , Marti Catala [aut] , Xihang Chen [aut] , Marta Alcalde-Herraiz [aut] , Nuria Mercade-Besora [aut] , Albert Prats-Uribe [aut]
Maintainer: Edward Burn <edward.burn@ndorms.ox.ac.uk>

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Package evoper updated to version 0.6.0 with previous version 0.5.0 dated 2018-08-30

Title: Evolutionary Parameter Estimation for 'Repast Simphony' Models
Description: The EvoPER, Evolutionary Parameter Estimation for Individual-based Models is an extensible package providing optimization driven parameter estimation methods using metaheuristics and evolutionary computation techniques (Particle Swarm Optimization, Simulated Annealing, Ant Colony Optimization for continuous domains, Tabu Search, Evolutionary Strategies, ...) which could be more efficient and require, in some cases, fewer model evaluations than alternatives relying on experimental design. Currently there are built in support for models developed with 'Repast Simphony' Agent-Based framework (<https://repast.github.io/>) and with NetLogo (<https://www.netlogo.org/>) which are the most used frameworks for Agent-based modeling.
Author: Antonio Prestes Garcia [aut, cre], Alfonso Rodriguez-Paton [aut, ths]
Maintainer: Antonio Prestes Garcia <antonio.pgarcia@alumnos.upm.es>

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Package evmissing updated to version 1.0.1 with previous version 1.0.0 dated 2026-01-08

Title: Extreme Value Analyses with Missing Data
Description: Performs likelihood-based extreme value inferences with adjustment for the presence of missing values based on Simpson and Northrop (2026). A Generalised Extreme Value distribution is fitted to block maxima using maximum likelihood estimation, with the location and scale parameters reflecting the numbers of non-missing raw values in each block. A Bayesian version is also provided. For the purposes of comparison, there are options to make no adjustment for missing values or to discard any block maximum for which greater than a percentage of the underlying raw values are missing. Example datasets containing missing values are provided.
Author: Paul J. Northrop [aut, cre, cph], Emma S. Simpson [aut, cph]
Maintainer: Paul J. Northrop <p.northrop@ucl.ac.uk>

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Package EMOTIONS updated to version 1.1 with previous version 1.0 dated 2025-06-18

Title: Ensemble Models for Lactation Curves
Description: Lactation curves describe temporal changes in milk yield and are key to breeding and managing dairy animals more efficiently. The use of ensemble modeling, which consists of combining predictions from multiple models, has the potential to yields more accurate and robust estimates of lactation patterns than relying solely on single model estimates. The package EMOTIONS fits 47 models for lactation curves and creates ensemble models using model averaging based on Akaike information criterion (AIC), Bayesian information criterion (BIC), root mean square percentage error (RMSPE) and mean squared error (MAE), variance of the predictions, cosine similarity for each model's predictions, and Bayesian Model Average (BMA). The daily production values predicted through the ensemble models can be used to estimate resilience indicators in the package. The package allows the graphical visualization of the model ranks and the predicted lactation curves. Additionally, the packages allows the user to d [...truncated...]
Author: Pablo Fonseca [aut, cre], Marcos Prates [aut], Aroa Suarez-Vega [aut], Ruth Arribas Gonzalo [aut], Beatriz Gutierrez-Gil [aut], Juan Jose Arranz [aut]
Maintainer: Pablo Fonseca <p.fonseca@csic.es>

Diff between EMOTIONS versions 1.0 dated 2025-06-18 and 1.1 dated 2026-01-28

 DESCRIPTION                                                                 |   14 
 MD5                                                                         |   86 
 NAMESPACE                                                                   |  114 
 R/BMAweight_gamma.R                                                         |  132 
 R/CosSquaredWeight.R                                                        |   54 
 R/GetLacModelsMetrics.R                                                     |   86 
 R/LacCurveFit.R                                                             |   91 
 R/LacData.R                                                                 |   38 
 R/ModelRankRange.R                                                          |   60 
 R/ModelsLac.R                                                               |  712 +--
 R/ParDef.R                                                                  |  118 
 R/PlotMilkLoss.R                                                            |only
 R/PlotWeightLac.R                                                           |   53 
 R/ResInd.R                                                                  |  237 -
 R/RidgeModels.R                                                             |   63 
 R/VarWeight.R                                                               |   36 
 R/global_variables.R                                                        |   11 
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 R/model_pars.R                                                              |   36 
 R/models_EMOTIONS.R                                                         |   42 
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 inst/doc/EMOTIONS.Rmd                                                       |  765 ++-
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 man/BMAweight_gamma.Rd                                                      |   44 
 man/CosSquaredWeight.Rd                                                     |   40 
 man/GetLacModelsMetrics.Rd                                                  |   44 
 man/LacCurveFit.Rd                                                          |   80 
 man/LacData.Rd                                                              |    8 
 man/ModelRankRange.Rd                                                       |   38 
 man/ModelsLac.Rd                                                            |   87 
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 man/PlotWeightLac.Rd                                                        |   92 
 man/ResInd.Rd                                                               |   74 
 man/RidgeModels.Rd                                                          |   38 
 man/VarWeight.Rd                                                            |   40 
 man/imp_my.Rd                                                               |only
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 man/model_pars.Rd                                                           |    4 
 man/models_EMOTIONS.Rd                                                      |   10 
 vignettes/EMOTIONS.Rmd                                                      |  765 ++-
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Package campsis updated to version 1.8.1 with previous version 1.7.0 dated 2025-04-04

Title: Generic PK/PD Simulation Platform Campsis
Description: A generic, easy-to-use and intuitive pharmacokinetic/pharmacodynamic (PK/PD) simulation platform based on the R packages 'rxode2' and 'mrgsolve'. Campsis provides an abstraction layer over the underlying processes of defining a PK/PD model, assembling a custom dataset and running a simulation. The package has a strong dependency on the R package 'campsismod', which allows models to be read from and written to files, including through a JSON-based interface, and to be adapted further on the fly in the R environment. In addition, 'campsis' allows users to assemble datasets in an intuitive manner, including via a JSON-based interface to import Campsis datasets defined using formal JSON schemas distributed with the package. Once the dataset is ready, the package prepares the simulation, calls 'rxode2' or 'mrgsolve' (at the user's choice), and returns the results for the given model, dataset and desired simulation settings. The package itself is licensed under the GPL (>= 3); the JSON sc [...truncated...]
Author: Nicolas Luyckx [aut, cre]
Maintainer: Nicolas Luyckx <nicolas.luyckx@calvagone.com>

Diff between campsis versions 1.7.0 dated 2025-04-04 and 1.8.1 dated 2026-01-28

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 campsis-1.8.1/campsis/MD5                                                                                   |  207 +++-
 campsis-1.8.1/campsis/NAMESPACE                                                                             |  436 +++++-----
 campsis-1.8.1/campsis/NEWS.md                                                                               |   11 
 campsis-1.8.1/campsis/R/arm.R                                                                               |    2 
 campsis-1.8.1/campsis/R/bootstrap.R                                                                         |   18 
 campsis-1.8.1/campsis/R/check.R                                                                             |   18 
 campsis-1.8.1/campsis/R/covariate.R                                                                         |   11 
 campsis-1.8.1/campsis/R/dataset.R                                                                           |   75 +
 campsis-1.8.1/campsis/R/dataset_config.R                                                                    |    8 
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 campsis-1.8.1/campsis/R/distribution.R                                                                      |  117 ++
 campsis-1.8.1/campsis/R/dose_adaptation.R                                                                   |    9 
 campsis-1.8.1/campsis/R/events.R                                                                            |    2 
 campsis-1.8.1/campsis/R/generic.R                                                                           |   25 
 campsis-1.8.1/campsis/R/hardware_settings.R                                                                 |   13 
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 campsis-1.8.1/campsis/R/observations.R                                                                      |   95 +-
 campsis-1.8.1/campsis/R/observations_set.R                                                                  |   10 
 campsis-1.8.1/campsis/R/plan_setup.R                                                                        |    8 
 campsis-1.8.1/campsis/R/protocol.R                                                                          |    9 
 campsis-1.8.1/campsis/R/repeated_schedule.R                                                                 |   31 
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 campsis-1.8.1/campsis/R/scenarios.R                                                                         |   19 
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 campsis-1.8.1/campsis/R/simulate_preprocess.R                                                               |    5 
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 campsis-1.8.1/campsis/R/treatment.R                                                                         |   17 
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 campsis-1.8.1/campsis/R/utilities.R                                                                         |   31 
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 campsis-1.8.1/campsis/man/Scenario.Rd                                                                       |    4 
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 campsis-1.8.1/campsis/man/getTimes.Rd                                                                       |   20 
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 campsis-1.8.1/campsis/tests/testthat/testObservations.R                                                     |   12 
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 campsis-1.8.1/campsis/tests/testthat/testSimulateBolusInfusionSameCmt.R                                     |    4 
 campsis-1.8.1/campsis/tests/testthat/testSimulateReplicates.R                                               |    6 
 campsis-1.8.1/campsis/tests/testthat/testSimulateScenarios.R                                                |   16 
 campsis-1.8.1/campsis/tests/testthat/testUtils.R                                                            |   23 
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Package nser updated to version 1.6.0 with previous version 1.5.8 dated 2026-01-10

Title: Bhavcopy and Live Market Data from National Stock Exchange (NSE) & Bombay Stock Exchange (BSE) India
Description: Download Current & Historical Bhavcopy. Get Live Market data from NSE India of Equities and Derivatives (F&O) segment. Data source <https://www.nseindia.com/>.
Author: Nandan Patil [cre, aut]
Maintainer: Nandan Patil <tryanother609@gmail.com>

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Package mlr3oml updated to version 0.12.0 with previous version 0.11.0 dated 2025-08-26

Title: Connector Between 'mlr3' and 'OpenML'
Description: Provides an interface to 'OpenML.org' to list and download machine learning data, tasks and experiments. The 'OpenML' objects can be automatically converted to 'mlr3' objects. For a more sophisticated interface with more upload options, see the 'OpenML' package.
Author: Michel Lang [aut] , Sebastian Fischer [cre, aut]
Maintainer: Sebastian Fischer <sebf.fischer@gmail.com>

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Package manureshed updated to version 0.1.2 with previous version 0.1.1 dated 2026-01-26

Title: Spatiotemporal Nutrient Balance Analysis Across Agricultural and Municipal Systems
Description: A comprehensive framework for analyzing agricultural nutrient balances across multiple spatial scales (county, 'HUC8', 'HUC2') with integration of wastewater treatment plant ('WWTP') effluent loads for both nitrogen and phosphorus. Supports classification of spatial units as nutrient sources, sinks, or balanced areas based on agricultural surplus and deficit calculations. Includes visualization tools, spatial transition probability analysis, and nutrient flow network mapping. Built-in datasets include agricultural nutrient balance data from the Nutrient Use Geographic Information System ('NuGIS'; The Fertilizer Institute and Plant Nutrition Canada, 1987-2016) <https://nugis.tfi.org/tabular_data/> and U.S. Environmental Protection Agency ('EPA') wastewater discharge data from the 'ECHO' Discharge Monitoring Report ('DMR') Loading Tool (2007-2016) <https://echo.epa.gov/trends/loading-tool/water-pollution-search>. Data are downloaded on demand from the Open Science Framework ( [...truncated...]
Author: Olatunde D. Akanbi [aut, cre, cph] , Vibha Mandayam [aut] , Atharva Gupta [aut] , K. Colton Flynn [aut] , Jeffrey Yarus [aut] , Erika I. Barcelos [aut, cph] , Roger H. French [aut, cph]
Maintainer: Olatunde D. Akanbi <olatunde.akanbi@case.edu>

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Package JMbayes2 updated to version 0.6-0 with previous version 0.5-7 dated 2025-06-16

Title: Extended Joint Models for Longitudinal and Time-to-Event Data
Description: Fit joint models for longitudinal and time-to-event data under the Bayesian approach. Multiple longitudinal outcomes of mixed type (continuous/categorical) and multiple event times (competing risks and multi-state processes) are accommodated. Rizopoulos (2012, ISBN:9781439872864).
Author: Dimitris Rizopoulos [aut, cre] , Pedro Miranda-Afonso [aut] , Grigorios Papageorgiou [aut]
Maintainer: Dimitris Rizopoulos <d.rizopoulos@erasmusmc.nl>

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Package rqlm updated to version 4.3-1 with previous version 4.2-2 dated 2025-12-22

Title: Modified Poisson Regression for Binary Outcome and Related Methods
Description: Modified Poisson, logistic and least-squares regression analyses for binary outcomes of Zou (2004) <doi:10.1093/aje/kwh090>, Noma (2025)<Forthcoming>, and Cheung (2007) <doi:10.1093/aje/kwm223> have been standard multivariate analysis methods to estimate risk ratio and risk difference in clinical and epidemiological studies. This R package involves an easy-to-handle function to implement these analyses by simple commands. Missing data analysis tools (multiple imputation) are also involved. In addition, recent studies have shown the ordinary robust variance estimator possibly has serious bias under small or moderate sample size situations for these methods. This package also provides computational tools to calculate alternative accurate confidence intervals.
Author: Hisashi Noma [aut, cre]
Maintainer: Hisashi Noma <noma@ism.ac.jp>

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Package RobinCar updated to version 1.1.0 with previous version 1.0.0 dated 2025-05-24

Title: Robust Inference for Covariate Adjustment in Randomized Clinical Trials
Description: Performs robust estimation and inference when using covariate adjustment and/or covariate-adaptive randomization in randomized clinical trials. Ting Ye, Jun Shao, Yanyao Yi, Qinyuan Zhao (2023) <doi:10.1080/01621459.2022.2049278>. Ting Ye, Marlena Bannick, Yanyao Yi, Jun Shao (2023) <doi:10.1080/24754269.2023.2205802>. Ting Ye, Jun Shao, Yanyao Yi (2023) <doi:10.1093/biomet/asad045>. Marlena Bannick, Jun Shao, Jingyi Liu, Yu Du, Yanyao Yi, Ting Ye (2024) <doi:10.1093/biomet/asaf029>. Xiaoyu Qiu, Yuhan Qian, Jaehwan Yi, Jinqiu Wang, Yu Du, Yanyao Yi, Ting Ye (2025) <doi:10.48550/arXiv.2408.12541>.
Author: Marlena Bannick [cre, aut] , Yuhan Qian [aut], Ting Ye [aut], Yanyao Yi [aut], Faith Bian [aut]
Maintainer: Marlena Bannick <marlena.bannick@outlook.com>

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Package NMA updated to version 3.1-1 with previous version 2.1-2 dated 2026-01-11

Title: Network Meta-Analysis Based on Multivariate Meta-Analysis and Meta-Regression Models
Description: Network meta-analysis tools based on contrast-based approach using the multivariate meta-analysis and meta-regression models (Noma et al. (2025) <doi:10.1101/2025.09.15.25335823>). Comprehensive analysis tools for network meta-analysis and meta-regression (e.g., synthesis analysis, ranking analysis, and creating league table) are available through simple commands. For inconsistency assessment, the local and global inconsistency tests based on the Higgins' design-by-treatment interaction model are available. In addition, the side-splitting methods and Jackson's random inconsistency model can be applied. Standard graphical tools for network meta-analysis, including network plots, ranked forest plots, and transitivity analyses, are also provided. For the synthesis analyses, the Noma-Hamura's improved REML (restricted maximum likelihood)-based methods (Noma et al. (2023) <doi:10.1002/jrsm.1652> <doi:10.1002/jrsm.1651>) are adopted as the default methods.
Author: Hisashi Noma [aut, cre] , Kazushi Maruo [aut], Shiro Tanaka [aut], Toshi A. Furukawa [aut]
Maintainer: Hisashi Noma <noma@ism.ac.jp>

Diff between NMA versions 2.1-2 dated 2026-01-11 and 3.1-1 dated 2026-01-28

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Package duckdb updated to version 1.4.4 with previous version 1.4.3 dated 2025-12-10

Title: DBI Package for the DuckDB Database Management System
Description: The DuckDB project is an embedded analytical data management system with support for the Structured Query Language (SQL). This package includes all of DuckDB and an R Database Interface (DBI) connector.
Author: Hannes Muehleisen [aut] , Mark Raasveldt [aut] , Kirill Mueller [cre] , Stichting DuckDB Foundation [cph], Apache Software Foundation [cph], PostgreSQL Global Development Group [cph], The Regents of the University of California [cph], Cameron Desrocher [...truncated...]
Maintainer: Kirill Mueller <kirill@cynkra.com>

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Package ggsem updated to version 0.9.9 with previous version 0.9.8 dated 2026-01-17

Title: Interactive Structural Equation Modeling (SEM) and Multi-Group Path Diagrams
Description: Provides an interactive workflow for visualizing structural equation modeling (SEM), multi-group path diagrams, and network diagrams in R. Users can directly manipulate nodes and edges to create publication-quality figures while maintaining statistical model integrity. Supports integration with 'lavaan', 'OpenMx', 'tidySEM', and 'blavaan' etc. Features include parameter-based aesthetic mapping, generative AI assistance, and complete reproducibility by exporting metadata for script-based workflows.
Author: Seung Hyun Min [aut, cre]
Maintainer: Seung Hyun Min <seung.min@mail.mcgill.ca>

Diff between ggsem versions 0.9.8 dated 2026-01-17 and 0.9.9 dated 2026-01-28

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Package GAPR updated to version 0.1.5 with previous version 0.1.4 dated 2025-06-06

Title: Generalized Association Plots
Description: Provides a comprehensive framework for visualizing associations and interaction structures in matrix-formatted data using Generalized Association Plots (GAP). The package implements multiple proximity computation methods (e.g., correlation, distance metrics), ordering techniques including hierarchical clustering (HCT) and Rank-2-Ellipse (R2E) seriation, and optional flipping strategies to enhance visual symmetry. It supports a variety of covariate-based color annotations, allows flexible customization of layout and output, and is suitable for analyzing multivariate data across domains such as social sciences, genomics, and medical research. The method is based on Generalized Association Plots introduced by Chen (2002) <https://www3.stat.sinica.edu.tw/statistica/J12N1/J12N11/J12N11.html> and further extended by Wu, Tien, and Chen (2010) <doi:10.1016/j.csda.2008.09.029>.
Author: Shu-Yu Lin [aut, cre], Chiun-How Kao [aut, ctb], Chun-Houh Chen [aut, ctb]
Maintainer: Shu-Yu Lin <shuyuuu89@gmail.com>

Diff between GAPR versions 0.1.4 dated 2025-06-06 and 0.1.5 dated 2026-01-28

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Package SLOPE updated to version 2.0.0 with previous version 1.2.0 dated 2025-11-11

Title: Sorted L1 Penalized Estimation
Description: Efficient implementations for Sorted L-One Penalized Estimation (SLOPE): generalized linear models regularized with the sorted L1-norm (Bogdan et al. 2015). Supported models include ordinary least-squares regression, binomial regression, multinomial regression, and Poisson regression. Both dense and sparse predictor matrices are supported. In addition, the package features predictor screening rules that enable fast and efficient solutions to high-dimensional problems.
Author: Johan Larsson [aut, cre] , Jonas Wallin [aut] , Malgorzata Bogdan [aut] , Ewout van den Berg [aut], Chiara Sabatti [aut], Emmanuel Candes [aut], Evan Patterson [aut], Weijie Su [aut], Jakub Kala [aut], Krystyna Grzesiak [aut], Mathurin Massias [aut], [...truncated...]
Maintainer: Johan Larsson <johan@jolars.co>

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Package rlas updated to version 1.8.3 with previous version 1.8.2 dated 2025-05-16

Title: Read and Write 'las' and 'laz' Binary File Formats Used for Remote Sensing Data
Description: Read and write 'las' and 'laz' binary file formats. The LAS file format is a public file format for the interchange of 3-dimensional point cloud data between data users. The LAS specifications are approved by the American Society for Photogrammetry and Remote Sensing <https://community.asprs.org/leadership-restricted/leadership-content/public-documents/standards>. The LAZ file format is an open and lossless compression scheme for binary LAS format versions 1.0 to 1.4 <https://laszip.org/>.
Author: Jean-Romain Roussel [aut, cre, cph], Florian De Boissieu [aut, ctb] , Martin Isenburg [cph] , David Auty [ctb] , Pierrick Marie [ctb] , Tiago de Conto [ctb]
Maintainer: Jean-Romain Roussel <info@r-lidar.com>

Diff between rlas versions 1.8.2 dated 2025-05-16 and 1.8.3 dated 2026-01-28

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Package plumber updated to version 1.3.3 with previous version 1.3.2 dated 2025-12-23

Title: An API Generator for R
Description: Gives the ability to automatically generate and serve an HTTP API from R functions using the annotations in the R documentation around your functions.
Author: Barret Schloerke [cre, aut] , Jeff Allen [aut, ccp], Bruno Tremblay [ctb], Frans van Dunne [ctb], Sebastiaan Vandewoude [ctb], Posit Software, PBC [cph, fnd]
Maintainer: Barret Schloerke <barret@posit.co>

Diff between plumber versions 1.3.2 dated 2025-12-23 and 1.3.3 dated 2026-01-28

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Package nlsic updated to version 1.2.0 with previous version 1.1.1 dated 2025-06-27

Title: Non Linear Least Squares with Inequality Constraints
Description: We solve non linear least squares problems with optional equality and/or inequality constraints. Non linear iterations are globalized with back-tracking method. Linear problems are solved by dense QR decomposition from 'LAPACK' which can limit the size of treated problems. On the other side, we avoid condition number degradation which happens in classical quadratic programming approach. Inequality constraints treatment on each non linear iteration is based on 'NNLS' method (by Lawson and Hanson). We provide an original function 'lsi_ln' for solving linear least squares problem with inequality constraints in least norm sens. Thus if Jacobian of the problem is rank deficient a solution still can be provided. However, truncation errors are probable in this case. Equality constraints are treated by using a basis of Null-space. User defined function calculating residuals must return a list having residual vector (not their squared sum) and Jacobian. If Jacobian is not in the returned list, [...truncated...]
Author: Serguei Sokol [aut, cre]
Maintainer: Serguei Sokol <sokol@insa-toulouse.fr>

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Package netmeta updated to version 3.3-1 with previous version 3.2-0 dated 2025-04-10

Title: Network Meta-Analysis using Frequentist Methods
Description: A comprehensive set of functions providing frequentist methods for network meta-analysis (Balduzzi et al., 2023) <doi:10.18637/jss.v106.i02> and supporting Schwarzer et al. (2015) <doi:10.1007/978-3-319-21416-0>, Chapter 8 "Network Meta-Analysis": - frequentist network meta-analysis following Rücker (2012) <doi:10.1002/jrsm.1058>; - additive network meta-analysis for combinations of treatments (Rücker et al., 2020) <doi:10.1002/bimj.201800167>; - network meta-analysis of binary data using the Mantel-Haenszel or non-central hypergeometric distribution method (Efthimiou et al., 2019) <doi:10.1002/sim.8158>, or penalised logistic regression (Evrenoglou et al., 2022) <doi:10.1002/sim.9562>; - rankograms and ranking of treatments by the Surface under the cumulative ranking curve (SUCRA) (Salanti et al., 2013) <doi:10.1016/j.jclinepi.2010.03.016>; - ranking of treatments using P-scores (frequentist analogue of SUCRAs without resampling) according to [...truncated...]
Author: Gerta Ruecker [aut] , Ulrike Krahn [aut], Jochem Koenig [aut] , Orestis Efthimiou [aut] , Annabel Davies [aut] , Theodoros Papakonstantinou [aut] , Theodoros Evrenoglou [ctb] , Krzysztof Ciomek [ctb] , Nana-Adjoa Kwarteng [ctb] , Guido Schwarzer [aut, [...truncated...]
Maintainer: Guido Schwarzer <guido.schwarzer@uniklinik-freiburg.de>

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Package misc3d updated to version 0.9-2 with previous version 0.9-1 dated 2021-10-07

Title: Miscellaneous 3D Plots
Description: A collection of miscellaneous 3d plots, including isosurfaces.
Author: Luke Tierney [aut, cre], Dai Feng [aut]
Maintainer: Luke Tierney <luke-tierney@uiowa.edu>

Diff between misc3d versions 0.9-1 dated 2021-10-07 and 0.9-2 dated 2026-01-28

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Package flexdashboard updated to version 0.6.3 with previous version 0.6.2 dated 2023-08-11

Title: R Markdown Format for Flexible Dashboards
Description: Format for converting an R Markdown document to a grid oriented dashboard. The dashboard flexibly adapts the size of it's components to the containing web page.
Author: Garrick Aden-Buie [aut, cre] , Carson Sievert [aut] , Richard Iannone [aut] , JJ Allaire [aut], Barbara Borges [aut], Posit Software, PBC [cph, fnd], Keen IO [ctb, cph] , Abdullah Almsaeed [ctb, cph] , Jonas Mosbech [ctb, cph] , Noel Bossart [ctb, cp [...truncated...]
Maintainer: Garrick Aden-Buie <garrick@posit.co>

Diff between flexdashboard versions 0.6.2 dated 2023-08-11 and 0.6.3 dated 2026-01-28

 DESCRIPTION                                   |   15 ++++++++-------
 MD5                                           |   18 +++++++++---------
 NEWS.md                                       |    8 ++++++++
 R/bslib.R                                     |    8 +++++++-
 R/flex_dashboard.R                            |    4 ++--
 inst/www/flex_dashboard/flexdashboard.min.css |    2 +-
 inst/www/flex_dashboard/flexdashboard.scss    |    5 +++++
 man/flex_dashboard.Rd                         |    6 +++---
 tests/testthat/_snaps/format.md               |    4 ++--
 tests/testthat/test_built_css.R               |    9 ++++++---
 10 files changed, 51 insertions(+), 28 deletions(-)

More information about flexdashboard at CRAN
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Built and running on Debian GNU/Linux using R, littler and blosxom. Styled with Bootstrap.