Wed, 03 Dec 2025

Package rsynthbio updated to version 4.0.0 with previous version 3.0.2 dated 2025-10-29

Title: Synthesize Bio API Wrapper
Description: Access Synthesize Bio models from their API <https://app.synthesize.bio/> using this wrapper that provides a convenient interface to the Synthesize Bio API, allowing users to generate realistic gene expression data based on specified biological conditions. This package enables researchers to easily access AI-generated transcriptomic data for various modalities including bulk RNA-seq, single-cell RNA-seq, microarray data, and more.
Author: Synthesize Bio [aut, cre]
Maintainer: Synthesize Bio <candace@synthesize.bio>

Diff between rsynthbio versions 3.0.2 dated 2025-10-29 and 4.0.0 dated 2025-12-03

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Package randotools updated to version 0.2.4 with previous version 0.2.3 dated 2025-11-07

Title: Create Randomization Lists
Description: Randomization lists are an integral component of randomized clinical trials. 'randotools' provides tools to easily create such lists.
Author: Alan G Haynes [aut, cre]
Maintainer: Alan G Haynes <alan.haynes@unibe.ch>

Diff between randotools versions 0.2.3 dated 2025-11-07 and 0.2.4 dated 2025-12-03

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Package inshiny updated to version 0.1.1 with previous version 0.1.0 dated 2025-09-09

Title: Compact Inline Widgets for 'shiny' Apps
Description: Provides a basic set of compact widgets for 'shiny' apps which occupy less space and can appear inline with surrounding text.
Author: Nick Davies [aut, cre]
Maintainer: Nick Davies <nicholas.davies@lshtm.ac.uk>

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Package binspp updated to version 0.2.3 with previous version 0.2.2 dated 2025-05-05

Title: Bayesian Inference for Neyman-Scott Point Processes
Description: The Bayesian MCMC estimation of parameters for Thomas-type cluster point process with various inhomogeneities. It allows for inhomogeneity in (i) distribution of parent points, (ii) mean number of points in a cluster, (iii) cluster spread. The package also allows for the Bayesian MCMC algorithm for the homogeneous generalized Thomas process. The cluster size is allowed to have a variance that is greater or less than the expected value (cluster sizes are over or under dispersed). Details are described in Dvořák, Remeš, Beránek & Mrkvička (2022) <arXiv: 10.48550/arXiv.2205.07946>.
Author: Mrkvicka Tomas [aut], Dvorak Jiri [aut], Beranek Ladislav [aut], Remes Radim [aut, cre], Park Jaewoo [ctb], Lee Sujeong [ctb]
Maintainer: Remes Radim <inrem@jcu.cz>

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Package teal.modules.general updated to version 0.6.0 with previous version 0.5.1 dated 2025-10-22

Title: General Modules for 'teal' Applications
Description: Prebuilt 'shiny' modules containing tools for viewing data, visualizing data, understanding missing and outlier values within your data and performing simple data analysis. This extends 'teal' framework that supports reproducible research and analysis.
Author: Dawid Kaledkowski [aut, cre], Pawel Rucki [aut], Mahmoud Hallal [aut], Ondrej Slama [ctb], Maciej Nasinski [aut], Konrad Pagacz [aut], Nikolas Burkoff [aut], F. Hoffmann-La Roche AG [cph, fnd]
Maintainer: Dawid Kaledkowski <dawid.kaledkowski@roche.com>

Diff between teal.modules.general versions 0.5.1 dated 2025-10-22 and 0.6.0 dated 2025-12-03

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New package statisR with initial version 1.0.1
Package: statisR
Title: STATIS and STATIS DUAL Multivariate Methods
Version: 1.0.1
Description: Provides tools for the integration and exploration of data tables measured on the same set of observational units. The package includes methods to assess similarities among tables, extract common patterns across variable blocks, and create visual summaries that highlight shared structures in multiblock data.
License: GPL (>= 2)
Encoding: UTF-8
Imports: ggforce, ggplot2, ggrepel
Depends: R (>= 4.1)
Language: en-US
LazyData: true
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2025-11-28 20:49:01 UTC; promidat20
Author: Oldemar Rodriguez [aut, cre], Alejandro Vargas [ctb, prg]
Maintainer: Oldemar Rodriguez <oldemar.rodriguez@ucr.ac.cr>
Repository: CRAN
Date/Publication: 2025-12-03 21:20:02 UTC

More information about statisR at CRAN
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Package SpecHelpers updated to version 0.3.2 with previous version 0.3.1 dated 2025-03-06

Title: Spectroscopy Related Utilities
Description: Utility functions for spectroscopy. 1. Functions to simulate spectra for use in teaching or testing. 2. Functions to process files created by 'LoggerPro' and 'SpectraSuite' software.
Author: Bryan A. Hanson [aut, cre]
Maintainer: Bryan A. Hanson <hanson@depauw.edu>

Diff between SpecHelpers versions 0.3.1 dated 2025-03-06 and 0.3.2 dated 2025-12-03

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Package simest readmission to version 0.4-1-1 with previous version 0.4 dated 2017-04-25

Title: Constrained Single Index Model Estimation
Description: Estimation of function and index vector in single index model ('sim') with (and w/o) shape constraints including different smoothness conditions. See, e.g., Kuchibhotla and Patra (2020) <doi:10.3150/19-BEJ1183>.
Author: Arun Kumar Kuchibhotla [aut] , Rohit Kumar Patra [aut], Martin Maechler [ctb, cre]
Maintainer: Martin Maechler <maechler@stat.math.ethz.ch>

This is a re-admission after prior archival of version 0.4 dated 2017-04-25

Diff between simest versions 0.4 dated 2017-04-25 and 0.4-1-1 dated 2025-12-03

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 simest-0.4-1-1/simest/R/SimEstGcv.r            |  127 ++++-----
 simest-0.4-1-1/simest/R/SmoothPenReg.r         |  152 +++++------
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Package radsafer updated to version 2.4.0 with previous version 2.3.0 dated 2023-07-12

Title: Radiation Safety
Description: Provides functions for radiation safety, also known as "radiation protection" and "radiological control". The science of radiation protection is called "health physics" and its engineering functions are called "radiological engineering". Functions in this package cover many of the computations needed by radiation safety professionals. Examples include: obtaining updated calibration and source check values for radiation monitors to account for radioactive decay in a reference source, simulating instrument readings to better understand measurement uncertainty, correcting instrument readings for geometry and ambient atmospheric conditions. Many of these functions are described in Johnson and Kirby (2011, ISBN-13: 978-1609134198). Utilities are also included for developing inputs and processing outputs with radiation transport codes, such as MCNP, a general-purpose Monte Carlo N-Particle code that can be used for neutron, photon, electron, or coupled neutron/photon/electron transport (Wern [...truncated...]
Author: Mark Hogue [aut, cre]
Maintainer: Mark Hogue <mark.hogue.chp@gmail.com>

Diff between radsafer versions 2.3.0 dated 2023-07-12 and 2.4.0 dated 2025-12-03

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 radsafer-2.4.0/radsafer/NAMESPACE                              |    4 
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 radsafer-2.4.0/radsafer/man/mcnp_cone_angle.Rd                 |    5 
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 radsafer-2.4.0/radsafer/man/mcnp_mesh_bins.Rd                  |  149 ++++-----
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 radsafer-2.4.0/radsafer/man/mcnp_scan2plot.Rd                  |    5 
 radsafer-2.4.0/radsafer/man/mcnp_scan_save.Rd                  |    5 
 radsafer-2.4.0/radsafer/man/mcnp_sdef_erg_hist.Rd              |  115 +++----
 radsafer-2.4.0/radsafer/man/mcnp_sdef_erg_line.Rd              |  161 ++++------
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 49 files changed, 523 insertions(+), 520 deletions(-)

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Package VGAMextra updated to version 0.0-9 with previous version 0.0-8 dated 2025-08-21

Title: Additions and Extensions of the 'VGAM' Package
Description: Extending the functionalities of the 'VGAM' package with additional functions and datasets. At present, 'VGAMextra' comprises new family functions (ffs) to estimate several time series models by maximum likelihood using Fisher scoring, unlike popular packages in CRAN relying on optim(), including ARMA-GARCH-like models, the Order-(p, d, q) ARIMAX model (non- seasonal), the Order-(p) VAR model, error correction models for cointegrated time series, and ARMA-structures with Student-t errors. For independent data, new ffs to estimate the inverse- Weibull, the inverse-gamma, the generalized beta of the second kind and the general multivariate normal distributions are available. In addition, 'VGAMextra' incorporates new VGLM-links for the mean-function, and the quantile-function (as an alternative to ordinary quantile modelling) of several 1-parameter distributions, that are compatible with the class of VGLM/VGAM family functions. Currently, only fixed-effects models are implemented. All fun [...truncated...]
Author: Victor Miranda [aut, cre, cph], Thomas Yee [ctb, ths, cph]
Maintainer: Victor Miranda <victor.miranda@aut.ac.nz>

Diff between VGAMextra versions 0.0-8 dated 2025-08-21 and 0.0-9 dated 2025-12-03

 DESCRIPTION |    8 ++++----
 MD5         |    6 +++---
 NAMESPACE   |    9 +++++----
 NEWS        |    9 ++++++++-
 4 files changed, 20 insertions(+), 12 deletions(-)

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New package taskqueue with initial version 0.2.0
Package: taskqueue
Title: Task Queue for Parallel Computing Based on PostgreSQL
Version: 0.2.0
Description: Implements a task queue system for asynchronous parallel computing using 'PostgreSQL' <https://www.postgresql.org/> as a backend. Designed for embarrassingly parallel problems where tasks do not communicate with each other. Dynamically distributes tasks to workers, handles uneven load balancing, and allows new workers to join at any time. Particularly useful for running large numbers of independent tasks on high-performance computing (HPC) clusters with 'SLURM' <https://slurm.schedmd.com/> job schedulers.
URL: https://taskqueue.bangyou.me/, https://github.com/byzheng/taskqueue
BugReports: https://github.com/byzheng/taskqueue/issues
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
Imports: settings, stats, stringr, RPostgres, ggplot2, whisker, rlang, shiny, DBI, ssh
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2025-11-27 23:59:11 UTC; zhe00a
Author: Bangyou Zheng [aut, cre]
Maintainer: Bangyou Zheng <bangyou.zheng@csiro.au>
Repository: CRAN
Date/Publication: 2025-12-03 20:30:02 UTC

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New package snic with initial version 0.6.0
Package: snic
Title: Superpixel Segmentation with the Simple Non-Iterative Clustering Algorithm
Version: 0.6.0
Maintainer: Rolf Simoes <rolfsimoes@gmail.com>
Description: Implements the Simple Non-Iterative Clustering algorithm for superpixel segmentation of multi-band images, as introduced by Achanta and Susstrunk (2017) <doi:10.1109/CVPR.2017.520>. Supports both standard image arrays and geospatial raster objects, with a design that can be extended to other spatial data frameworks. The algorithm groups adjacent pixels into compact, coherent regions based on spectral similarity and spatial proximity. A high-performance implementation supports images with arbitrary spectral bands.
Depends: R (>= 3.5.0)
Suggests: testthat (>= 3.0.0), terra, spelling, covr, magick, jpeg, png, knitr, rmarkdown
URL: https://github.com/rolfsimoes/snic, https://rolfsimoes.github.io/snic/
BugReports: https://github.com/rolfsimoes/snic/issues
ByteCompile: true
VignetteBuilder: knitr
Encoding: UTF-8
Language: en-US
License: GPL (>= 2)
NeedsCompilation: yes
Packaged: 2025-11-28 03:49:24 UTC; rolf
Author: Rolf Simoes [aut, cre] , Felipe Souza [aut] , Felipe Carlos [aut] , Gilberto Camara [aut, rth]
Repository: CRAN
Date/Publication: 2025-12-03 20:40:02 UTC

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New package SHAKTI with initial version 0.1.0
Package: SHAKTI
Title: Suite for Heat-Related Adsorption Knowledge and Thermodynamic Inference
Description: A comprehensive framework for quantifying the fundamental thermodynamic parameters of adsorption reactions—changes in the standard Gibbs free energy (delta G), enthalpy (delta H), and entropy (delta S)—is essential for understanding the spontaneity, heat effects, and molecular ordering associated with sorption processes. By analysing temperature-dependent equilibrium data, thermodynamic interpretation expands adsorption studies beyond conventional isotherm fitting, offering deeper insight into underlying mechanisms and surface–solute interactions. Such an approach typically involves evaluating equilibrium coefficients across multiple temperatures and non-temperature treatments, deriving thermodynamic parameters using established thermodynamic relationships, and determining delta G as a temperature-specific indicator of adsorption favourability. This analytical pathway is widely applicable across environmental science, soil science, chemistry, materials science, and engineering, where r [...truncated...]
Author: Arkaprava Roy [aut], Debopam Rakshit [aut, cre], Siba Prasad Datta [aut], Kanchikeri Math Manjaiah [aut], Mandira Barman [aut], Debashis Mandal [aut]
Maintainer: Debopam Rakshit <rakshitdebopam@yahoo.com>
Version: 0.1.0
Encoding: UTF-8
License: GPL-3
Imports: dplyr, stats, magrittr
NeedsCompilation: no
Packaged: 2025-11-28 06:43:41 UTC; Debopam
Repository: CRAN
Date/Publication: 2025-12-03 20:40:08 UTC

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New package rtmpinv with initial version 0.1.0
Package: rtmpinv
Title: Tabular Matrix Problems via Pseudoinverse Estimation
Version: 0.1.0
Description: The Tabular Matrix Problems via Pseudoinverse Estimation (TMPinv) is a two-stage estimation method that reformulates structured table-based systems - such as allocation problems, transaction matrices, and input-output tables - as structured least-squares problems. Based on the Convex Least Squares Programming (CLSP) framework, TMPinv solves systems with row and column constraints, block structure, and optionally reduced dimensionality by (1) constructing a canonical constraint form and applying a pseudoinverse-based projection, followed by (2) a convex-programming refinement stage to improve fit, coherence, and regularization (e.g., via Lasso, Ridge, or Elastic Net).
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-US
Depends: R (>= 4.2)
Imports: rclsp
Suggests: testthat (>= 3.0.0)
URL: https://github.com/econcz/rtmpinv
BugReports: https://github.com/econcz/rtmpinv/issues
NeedsCompilation: no
Packaged: 2025-11-28 01:23:45 UTC; ilyabolotov
Author: Ilya Bolotov [aut, cre]
Maintainer: Ilya Bolotov <ilya.bolotov@vse.cz>
Repository: CRAN
Date/Publication: 2025-12-03 20:30:08 UTC

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New package rlppinv with initial version 0.1.0
Package: rlppinv
Title: Linear Programming via Regularized Least Squares
Version: 0.1.0
Description: The Linear Programming via Regularized Least Squares (LPPinv) is a two-stage estimation method that reformulates linear programs as structured least-squares problems. Based on the Convex Least Squares Programming (CLSP) framework, LPPinv solves linear inequality, equality, and bound constraints by (1) constructing a canonical constraint system and computing a pseudoinverse projection, followed by (2) a convex-programming correction stage to refine the solution under additional regularization (e.g., Lasso, Ridge, or Elastic Net). LPPinv is intended for underdetermined and ill-posed linear problems, for which standard solvers fail.
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-US
Depends: R (>= 4.2)
Imports: rclsp
Suggests: testthat (>= 3.0.0)
URL: https://github.com/econcz/rlppinv
BugReports: https://github.com/econcz/rlppinv/issues
NeedsCompilation: no
Packaged: 2025-11-28 01:13:20 UTC; ilyabolotov
Author: Ilya Bolotov [aut, cre]
Maintainer: Ilya Bolotov <ilya.bolotov@vse.cz>
Repository: CRAN
Date/Publication: 2025-12-03 20:30:13 UTC

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New package osrm.backend with initial version 0.1.0
Package: osrm.backend
Title: Bindings for 'Open Source Routing Machine'
Version: 0.1.0
Description: Install and control 'Open Source Routing Machine' ('OSRM') backend executables to prepare routing data and run/stop a local 'OSRM' server. For computations with the running server use the 'osrm' R package (<https://cran.r-project.org/package=osrm>).
License: MIT + file LICENSE
URL: https://github.com/e-kotov/osrm.backend, https://www.ekotov.pro/osrm.backend/
BugReports: https://github.com/e-kotov/osrm.backend/issues
Imports: digest, httr2, jsonlite, processx, ps
Suggests: knitr, osrm, quarto, sf, testthat (>= 3.0.0)
VignetteBuilder: quarto
Encoding: UTF-8
Language: en
SystemRequirements: OSRM backend binaries (>= v5.27.0) <https://github.com/Project-OSRM/osrm-backend>; package downloads binaries automatically if not found
NeedsCompilation: no
Packaged: 2025-11-28 13:24:05 UTC; ek
Author: Egor Kotov [aut, cre, cph]
Maintainer: Egor Kotov <kotov.egor@gmail.com>
Repository: CRAN
Date/Publication: 2025-12-03 21:00:02 UTC

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New package MultiRFM with initial version 1.1.0
Package: MultiRFM
Title: High-Dimensional Multi-Study Robust Factor Model
Version: 1.1.0
Date: 2025-11-28
Author: Wei Liu [aut, cre], Xiaolu Jiang [aut]
Maintainer: Wei Liu <liuweideng@gmail.com>
Description: We introduce a high-dimensional multi-study robust factor model, which learns latent features and accounts for the heterogeneity among source. It could be used for analyzing heterogeneous RNA sequencing data. More details can be referred to Jiang et al. (2025) <doi:10.48550/arXiv.2506.18478>.
License: GPL-3
Depends: R (>= 3.5.0)
Imports: MASS, irlba, LaplacesDemon, mixtools, mvtnorm, Rcpp (>= 1.0.8.3)
URL: https://github.com/feiyoung/MultiRFM
BugReports: https://github.com/feiyoung/MultiRFM/issues
Encoding: UTF-8
Suggests: knitr, rmarkdown
LinkingTo: Rcpp, RcppArmadillo
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2025-11-28 11:25:25 UTC; 10297
Repository: CRAN
Date/Publication: 2025-12-03 20:50:07 UTC

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Package HQM updated to version 1.1 with previous version 1.0 dated 2025-02-01

Title: Superefficient Estimation of Future Conditional Hazards Based on Marker Information
Description: Provides univariate and indexed (multivariate) nonparametric smoothed kernel estimators for the future conditional hazard rate function when time-dependent covariates are present, a bandwidth selector for the estimator's implementation and pointwise and uniform confidence bands. Methods used in the package refer to Bagkavos, Isakson, Mammen, Nielsen and Proust-Lima (2025) <doi:10.1093/biomet/asaf008>.
Author: Dimitrios Bagkavos [aut, cre], Alex Isakson [ctb], Enno Mammen [ctb], Jens Nielsen [ctb], Cecile Proust-Lima [ctb]
Maintainer: Dimitrios Bagkavos <dimitrios.bagkavos@gmail.com>

Diff between HQM versions 1.0 dated 2025-02-01 and 1.1 dated 2025-12-03

 DESCRIPTION                     |    8 -
 MD5                             |   50 +++++++--
 NAMESPACE                       |    2 
 R/Boot.HRandIndex.param.R       |only
 R/Boot.hqm.R                    |only
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 R/Sim.True.Hazard.R             |only
 R/SingleIndCondFutHaz.R         |only
 R/StudentizedBwB.Index.CIs.R    |only
 R/b_selection_index_optim.R     |only
 R/index_optim.R                 |only
 R/lin_interpolate.R             |   15 ++
 R/lin_interpolate_plus.R        |only
 R/prep_cv2.R                    |only
 build/partial.rdb               |binary
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 man/g_xt.Rd                     |    6 -
 man/get_h_x.Rd                  |   82 ++++++++++++++-
 man/get_h_xll.Rd                |  112 +++++++++++++++++----
 man/h_xt.Rd                     |   25 +++-
 man/h_xt_vec.Rd                 |  209 +++++++++++++++++++++++++++++++++++++++-
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 man/llK_b.Rd                    |   14 +-
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 38 files changed, 509 insertions(+), 91 deletions(-)

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New package geopsych with initial version 0.1.0
Package: geopsych
Title: Methods of Applied Psychology and Psychometrics in Geographical Analysis
Version: 0.1.0
Description: Integrating applied psychological and psychometric methods into geographical analysis. With the emergence of geo-referenced questionnaires, spatially explicit psychological and psychometric methods can offer a geographically contextualised approach that reflects latent traits and processes at a more local scale, leading to more tailored research and decision-making processes. The implemented methods include Geographically Weighted Cronbach's alpha and its bandwidth selection. See Zhang & Li (2025) <doi:10.1111/gean.70021>.
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
URL: https://github.com/ZhangSui921/geopsych
Depends: R (>= 3.5)
Imports: sp
NeedsCompilation: no
Packaged: 2025-11-28 11:37:42 UTC; f89389sz
Author: Sui Zhang [aut, cre]
Maintainer: Sui Zhang <sui.zhang@manchester.ac.uk>
Repository: CRAN
Date/Publication: 2025-12-03 20:50:02 UTC

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New package FoRDM with initial version 1.0.0
Package: FoRDM
Title: Forest Many-Objective Robust Decision Making ('FoRDM')
Version: 1.0.0
Maintainer: Marc Djahangard <marc.djahangard@ife.uni-freiburg.de>
Description: Forest Many-Objective Robust Decision Making ('FoRDM') is a R toolkit for supporting robust forest management under deep uncertainty. It provides a forestry-focused application of Many-Objective Robust Decision Making ('MORDM') to forest simulation outputs, enabling users to evaluate robustness using regret- and 'satisficing'-based measures. 'FoRDM' identifies robust solutions, generates Pareto fronts, and offers interactive 2D, 3D, and parallel-coordinate visualizations.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: dplyr (>= 1.0.0), ggplot2 (>= 3.3.0), magrittr (>= 2.0.0), tidyr (>= 1.1.0), rlang (>= 0.4.0), tibble (>= 3.0.0), plotly (>= 4.10.0), emoa (>= 0.5.0), stats
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2025-11-28 12:27:56 UTC; Marc Djahangard
Author: Marc Djahangard [aut, cre], Rasoul Yousefpour [aut]
Repository: CRAN
Date/Publication: 2025-12-03 20:50:11 UTC

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New package CimpleG with initial version 1.0.0
Package: CimpleG
Title: A Method to Identify Single CpG Sites for Classification and Deconvolution
Version: 1.0.0
Date: 2025-11-21
Maintainer: Tiago F.V. Maie <tiagomaie@hotmail.com>
Description: DNA methylation signatures are usually based on multivariate approaches that require hundreds of sites for predictions. 'CimpleG' is a method for the detection of small CpG methylation signatures used for cell-type classification and deconvolution. 'CimpleG' is time efficient and performs as well as top performing methods for cell-type classification of blood cells and other somatic cells, while basing its prediction on a single DNA methylation site per cell type (but users can also select more sites if they so wish). Users can train cell type classifiers ('CimpleG' based, and others) and directly apply these in a deconvolution of cell mixes context. Altogether, 'CimpleG' provides a complete computational framework for the delineation of DNAm signatures and cellular deconvolution. For more details see Maié et al. (2023) <doi:10.1186/s13059-023-03000-0>.
License: GPL (>= 3)
URL: https://github.com/CostaLab/CimpleG, https://costalab.github.io/CimpleG/
BugReports: https://github.com/CostaLab/CimpleG/issues
Depends: R (>= 4.1.0)
Imports: archive, assertthat, broom, butcher, caret, data.table, devtools, dplyr, forcats, ggExtra, ggplot2, ggrepel, ggsci, grDevices, gtools, magrittr, matrixStats, methods, nnls, OneR, parsnip, patchwork, purrr, recipes, rlang, rsample, scales, stats, tibble, tictoc, tidyr, tidyselect, tsutils, tune, utils, vroom, workflows, yardstick
Suggests: Biobase, biomaRt, C50, circlize, EpiDISH, furrr, future, future.apply, GEOquery, ggbeeswarm, ggsignif, glmnet, knitr, minfi, mltools, NMF, nnet, plyr, ranger, RColorBrewer, reshape2, Rfast, rmarkdown, spelling, stringr, SummarizedExperiment, testthat (>= 3.0.0), withr, xgboost
VignetteBuilder: knitr
Encoding: UTF-8
Language: en-US
LazyData: true
NeedsCompilation: no
Packaged: 2025-11-28 09:48:45 UTC; tmaie
Author: Tiago F.V. Maie [aut, cre]
Repository: CRAN
Date/Publication: 2025-12-03 20:50:17 UTC

More information about CimpleG at CRAN
Permanent link

Package ARpLMEC (with last version 2.4.1) was removed from CRAN

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

2022-06-26 2.4.1
2022-05-20 2.4
2022-04-27 2.3
2022-04-07 2.2
2021-09-13 2.1
2020-06-26 1.1
2019-01-09 1.0

Permanent link
Package Rdistance updated to version 4.1.1 with previous version 4.0.5 dated 2025-04-10

Title: Density and Abundance from Distance-Sampling Surveys
Description: Distance-sampling (<doi:10.1007/978-3-319-19219-2>) is a field survey and analytical method that estimates density and abundance of survey targets (e.g., animals) when detection probability declines with observation distance. Distance-sampling is popular in ecology, especially when survey targets are observed from aerial platforms (e.g., airplane or drone), surface vessels (e.g., boat or truck), or along walking transects. Analysis involves fitting smooth (parametric) curves to histograms of observation distances and using those functions to adjust density estimates for missed targets. Routines included here fit curves to observation distance histograms, estimate effective sampling area, density of targets in surveyed areas, and the abundance of targets in a surrounding study area. Confidence interval estimation uses built-in bootstrap resampling. Help files are extensive and have been vetted by multiple authors. Many tutorials are available on the package's website (URL below).
Author: Trent McDonald [cre, aut], Jason Carlisle [aut], Aidan McDonald [aut] , Ryan Nielson [ctb] , Ben Augustine [ctb] , James Griswald [ctb] , Patrick McKann [ctb] , Lacey Jeroue [ctb] , Hoffman Abigail [ctb] , Kleinsausser Michael [ctb] , Joel Reynolds [ [...truncated...]
Maintainer: Trent McDonald <trent@mcdonalddatasciences.com>

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More information about Rdistance at CRAN
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Package PRIMAL updated to version 1.0.3 with previous version 1.0.2 dated 2020-01-22

Title: Parametric Simplex Method for Sparse Learning
Description: Implements a unified framework of parametric simplex method for a variety of sparse learning problems (e.g., Dantzig selector (for linear regression), sparse quantile regression, sparse support vector machines, and compressive sensing) combined with efficient hyper-parameter selection strategies. The core algorithm is implemented in C++ with Eigen3 support for portable high performance linear algebra. For more details about parametric simplex method, see Haotian Pang (2017) <https://papers.nips.cc/paper/6623-parametric-simplex-method-for-sparse-learning.pdf>.
Author: Zichong Li [aut, cre], Qianli Shen [aut]
Maintainer: Zichong Li <zichongli5@gmail.com>

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Permanent link

Package fwsim (with last version 0.3.4) was removed from CRAN

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

2018-10-05 0.3.4
2015-01-16 0.3.3
2014-08-27 0.3.2
2014-04-25 0.3.1
2014-04-07 0.3
2014-03-04 0.2-6
2012-05-11 0.2-5
2012-04-01 0.2-3
2012-02-09 0.2-2
2012-02-02 0.2-1
2012-01-30 0.1-2

Permanent link
Package sdstudio updated to version 0.1.4 with previous version 0.1.3 dated 2025-11-11

Title: Companion Application for the 'surveydown' Survey Platform
Description: Companion package that supports the 'surveydown' survey platform (<https://surveydown.org>). The default method for working with a 'surveydown' survey is to edit the plain text 'survey.qmd' and 'app.R' files. With 'sdstudio', you can create, preview and manage surveys with a 'shiny' application as a graphical user interface.
Author: Pingfan Hu [aut, cre, cph] , John Paul Helveston [aut, cph] , Bogdan Bunea [aut, cph]
Maintainer: Pingfan Hu <pingfan0727@gmail.com>

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Package Ryacas updated to version 1.1.6 with previous version 1.1.5 dated 2023-01-16

Title: R Interface to the 'Yacas' Computer Algebra System
Description: Interface to the 'yacas' computer algebra system (<http://www.yacas.org/>).
Author: Mikkel Meyer Andersen [aut, cre, cph], Rob Goedman [aut, cph], Gabor Grothendieck [aut, cph], Soeren Hoejsgaard [aut, cph], Grzegorz Mazur [aut, cph], Ayal Pinkus [aut, cph], Nemanja Trifunovic [cph] )
Maintainer: Mikkel Meyer Andersen <mikl@math.aau.dk>

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Package RPESE updated to version 1.2.6 with previous version 1.2.5 dated 2022-09-08

Title: Estimates of Standard Errors for Risk and Performance Measures
Description: Estimates of standard errors of popular risk and performance measures for asset or portfolio returns using methods as described in Chen and Martin (2021) <doi:10.21314/JOR.2020.446>.
Author: Anthony Christidis [aut, cre], Xin Chen [aut]
Maintainer: Anthony Christidis <anthony.christidis@stat.ubc.ca>

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Package panstarrs updated to version 0.2.3 with previous version 0.2.2 dated 2024-05-02

Title: Interface to the Pan-STARRS API
Description: An interface to the API for 'Pan-STARRS1', a data archive of the PS1 wide-field astronomical survey. The package allows access to the PS1 catalog and to the PS1 images. (see <https://outerspace.stsci.edu/display/PANSTARRS/> for more information). You can use it to plan astronomical observations, make guidance pictures, find magnitudes in five broadband filters (g, r, i, z, y) and more.
Author: Grigory Uskov [cre, aut]
Maintainer: Grigory Uskov <uskov.russia@gmail.com>

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Package nntmvn updated to version 1.3.0 with previous version 1.2.0 dated 2025-02-08

Title: Draw Samples of Truncated Multivariate Normal Distributions
Description: Draw samples from truncated multivariate normal distribution using the sequential nearest neighbor (SNN) method introduced in "Scalable Sampling of Truncated Multivariate Normals Using Sequential Nearest-Neighbor Approximation" <doi:10.48550/arXiv.2406.17307>.
Author: Jian Cao [aut, cre], Matthias Katzfuss [aut]
Maintainer: Jian Cao <jcao2416@gmail.com>

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Package mlr3 updated to version 1.3.0 with previous version 1.2.0 dated 2025-09-13

Title: Machine Learning in R - Next Generation
Description: Efficient, object-oriented programming on the building blocks of machine learning. Provides 'R6' objects for tasks, learners, resamplings, and measures. The package is geared towards scalability and larger datasets by supporting parallelization and out-of-memory data-backends like databases. While 'mlr3' focuses on the core computational operations, add-on packages provide additional functionality.
Author: Michel Lang [aut] , Bernd Bischl [aut] , Jakob Richter [aut] , Patrick Schratz [aut] , Giuseppe Casalicchio [ctb] , Stefan Coors [ctb] , Quay Au [ctb] , Martin Binder [aut], Florian Pfisterer [aut] , Raphael Sonabend [aut] , Lennart Schneider [ctb] , [...truncated...]
Maintainer: Marc Becker <marcbecker@posteo.de>

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Package ICSKAT updated to version 0.3.0 with previous version 0.2.0 dated 2021-11-25

Title: Interval-Censored Sequence Kernel Association Test
Description: Implements the Interval-Censored Sequence Kernel Association (ICSKAT) test for testing the association between interval-censored time-to-event outcomes and groups of single nucleotide polymorphisms (SNPs). Interval-censored time-to-event data occur when the event time is not known exactly but can be deduced to fall within a given interval. For example, some medical conditions like bone mineral density deficiency are generally only diagnosed at clinical visits. If a patient goes for clinical checkups yearly and is diagnosed at, say, age 30, then the onset of the deficiency is only known to fall between the date of their age 29 checkup and the date of the age 30 checkup. Interval-censored data include right- and left-censored data as special cases. This package also implements the interval-censored Burden test and the ICSKATO test, which is the optimal combination of the ICSKAT and Burden tests. Please see the vignette for a quickstart guide. The paper describing these methods is " Infer [...truncated...]
Author: Ryan Sun [aut, cre], Liang Zhu [aut]
Maintainer: Ryan Sun <ryansun.work@gmail.com>

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Package hdcuremodels updated to version 0.0.6 with previous version 0.0.5 dated 2025-07-31

Title: High-Dimensional Cure Models
Description: Provides functions for fitting various penalized parametric and semi-parametric mixture cure models with different penalty functions, testing for a significant cure fraction, and testing for sufficient follow-up as described in Fu et al (2022)<doi:10.1002/sim.9513> and Archer et al (2024)<doi:10.1186/s13045-024-01553-6>. False discovery rate controlled variable selection is provided using model-X knock-offs.
Author: Han Fu [aut], Kellie J. Archer [aut, cre] , Tung Lam Nguyen [rev] , Panagiotis Papastamoulis [rev]
Maintainer: Kellie J. Archer <archer.43@osu.edu>

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Package distcomp updated to version 1.3-4 with previous version 1.3-3 dated 2022-09-01

Title: Computations over Distributed Data without Aggregation
Description: Implementing algorithms and fitting models when sites (possibly remote) share computation summaries rather than actual data over HTTP with a master R process (using 'opencpu', for example). A stratified Cox model and a singular value decomposition are provided. The former makes direct use of code from the R 'survival' package. (That is, the underlying Cox model code is derived from that in the R 'survival' package.) Sites may provide data via several means: CSV files, Redcap API, etc. An extensible design allows for new methods to be added in the future and includes facilities for local prototyping and testing. Web applications are provided (via 'shiny') for the implemented methods to help in designing and deploying the computations.
Author: Balasubramanian Narasimhan [aut, cre], Marina Bendersky [aut], Sam Gross [aut], Terry M. Therneau [ctb], Thomas Lumley [ctb]
Maintainer: Balasubramanian Narasimhan <naras@stat.Stanford.EDU>

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Package sspm readmission to version 1.1.0 with previous version 1.0.3 dated 2025-02-12

Title: Spatial Surplus Production Model Framework for Northern Shrimp Populations
Description: Implement a GAM-based (Generalized Additive Models) spatial surplus production model (spatial SPM), aimed at modeling northern shrimp population in Atlantic Canada but potentially to any stock in any location. The package is opinionated in its implementation of SPMs as it internally makes the choice to use penalized spatial gams with time lags. However, it also aims to provide options for the user to customize their model. The methods are described in Pedersen et al. (2022, <https://www.dfo-mpo.gc.ca/csas-sccs/Publications/ResDocs-DocRech/2022/2022_062-eng.html>).
Author: Valentin Lucet [aut, cre, cph], Eric Pedersen [aut]
Maintainer: Valentin Lucet <valentin.lucet@gmail.com>

This is a re-admission after prior archival of version 1.0.3 dated 2025-02-12

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Package reconstructKM updated to version 0.4.0 with previous version 0.3.0 dated 2020-11-25

Title: Reconstruct Individual-Level Data from Published KM Plots
Description: Functions for reconstructing individual-level data (time, status, arm) from Kaplan-MEIER curves published in academic journals (e.g. NEJM, JCO, JAMA). The individual-level data can be used for re-analysis, meta-analysis, methodology development, etc. This package was used to generate the data for commentary such as Sun, Rich, & Wei (2018) <doi:10.1056/NEJMc1808567>. Please see the vignette for a quickstart guide.
Author: Ryan Sun [aut, cre]
Maintainer: Ryan Sun <ryansun.work@gmail.com>

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Package rcdf readmission to version 0.1.2 with previous version 0.1.1 dated 2025-10-12

Title: A Comprehensive Toolkit for Working with Encrypted Parquet Files
Description: Utilities for reading, writing, and managing RCDF files, including encryption and decryption support. It offers a flexible interface for handling data stored in encrypted Parquet format, along with metadata extraction, key management, and secure operations using Advanced Encryption Standard (AES) and Rivest-Shamir-Adleman (RSA) encryption.
Author: Bhas Abdulsamad [aut, cre, cph]
Maintainer: Bhas Abdulsamad <aeabdulsamad@gmail.com>

This is a re-admission after prior archival of version 0.1.1 dated 2025-10-12

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Package openesm updated to version 0.1.2 with previous version 0.1.1 dated 2025-11-02

Title: Access the Open Experience Sampling Method Database
Description: Provides programmatic access to the Open Experience Sampling Method ('openESM') database (<https://openesmdata.org>), a collection of harmonized experience sampling datasets. The package enables researchers to discover, download, and work with the datasets while ensuring proper citation and license compliance.
Author: Bjoern S. Siepe [aut, cre, cph] , Matthias Kloft [aut]
Maintainer: Bjoern S. Siepe <bjoernsiepe@gmail.com>

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Package MHD readmission to version 0.1.3 with previous version 0.1.2 dated 2024-01-24

Title: Metric Halfspace Depth
Description: Metric halfspace depth for object data, generalizing Tukey's depth for Euclidean data. Implementing the method described in Dai and Lopez-Pintado (2022) <doi:10.1080/01621459.2021.2011298>.
Author: Xiongtao Dai [aut, cre]
Maintainer: Xiongtao Dai <xiongtao.dai@hotmail.com>

This is a re-admission after prior archival of version 0.1.2 dated 2024-01-24

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Package MetabolomicsBasics updated to version 1.4.7 with previous version 1.4.5 dated 2024-01-31

Title: Basic Functions to Investigate Metabolomics Data Matrices
Description: A set of functions to investigate raw data from (metabol)omics experiments intended to be used on a raw data matrix, i.e. following peak picking and signal deconvolution. Functions can be used to normalize data, detect biomarkers and perform sample classification. A detailed description of best practice usage may be found in the publication <doi:10.1007/978-1-4939-7819-9_20>.
Author: Jan Lisec [aut, cre]
Maintainer: Jan Lisec <jan.lisec@bam.de>

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Package GitAI readmission to version 0.1.3 with previous version 0.1.2 dated 2025-08-22

Title: Extracts Knowledge from 'Git' Repositories
Description: Scan multiple 'Git' repositories, pull specified files content and process it with large language models. You can summarize the content in specific way, extract information and data, or find answers to your questions about the repositories. The output can be stored in vector database and used for semantic search or as a part of a RAG (Retrieval Augmented Generation) prompt.
Author: Kamil Wais [aut, cre], Krystian Igras [aut], Maciej Banas [aut]
Maintainer: Kamil Wais <kamil.wais@gmail.com>

This is a re-admission after prior archival of version 0.1.2 dated 2025-08-22

Diff between GitAI versions 0.1.2 dated 2025-08-22 and 0.1.3 dated 2025-12-03

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Package DIDmultiplegtDYN updated to version 2.2.0 with previous version 2.1.2 dated 2025-01-22

Title: Estimation in Difference-in-Difference Designs with Multiple Groups and Periods
Description: Estimation of heterogeneity-robust difference-in-differences estimators, with a binary, discrete, or continuous treatment, in designs where past treatments may affect the current outcome.
Author: Anzony Quispe [aut, cre], Diego Ciccia [aut], Felix Knau [aut], Melitine Malezieux [aut], Doulo Sow [aut], Clement de Chaisemartin [aut]
Maintainer: Anzony Quispe <anzony.quispe@gmail.com>

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Package rdav updated to version 0.3.0 with previous version 0.2.2 dated 2025-11-13

Title: Simple 'WebDAV' Client
Description: A simple 'WebDAV' client that provides functions to fetch and send files or folders to servers using the 'WebDAV' protocol (see 'RFC' 4918 <https://www.rfc-editor.org/rfc/rfc4918>). Only a subset of the protocol is implemented (e.g. file locks are not yet supported).
Author: Gunther Krauss [aut, cre]
Maintainer: Gunther Krauss <guntherkrauss@uni-bonn.de>

Diff between rdav versions 0.2.2 dated 2025-11-13 and 0.3.0 dated 2025-12-03

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Package matrixCorr updated to version 0.7.2 with previous version 0.6.2 dated 2025-11-15

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>

Diff between matrixCorr versions 0.6.2 dated 2025-11-15 and 0.7.2 dated 2025-12-03

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Package REBayes updated to version 2.59 with previous version 2.56 dated 2024-06-22

Title: Empirical Bayes Estimation and Inference
Description: Kiefer-Wolfowitz maximum likelihood estimation for mixture models and some other density estimation and regression methods based on convex optimization. See Koenker and Gu (2017) REBayes: An R Package for Empirical Bayes Mixture Methods, Journal of Statistical Software, 82, 1--26, <DOI:10.18637/jss.v082.i08>.
Author: Roger Koenker [aut, cre], Jiaying Gu [ctb], Ivan Mizera [ctb]
Maintainer: Roger Koenker <rkoenker@uiuc.edu>

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Package pyinit updated to version 1.1.4 with previous version 1.1.3 dated 2022-04-26

Title: Pena-Yohai Initial Estimator for Robust S-Regression
Description: Deterministic Pena-Yohai initial estimator for robust S estimators of regression. The procedure is described in detail in Pena, D., & Yohai, V. (1999) <doi:10.2307/2670164>.
Author: David Kepplinger [aut, cre], Matias Salibian-Barrera [aut], Gabriela Cohen Freue [aut]
Maintainer: David Kepplinger <david.kepplinger@gmail.com>

Diff between pyinit versions 1.1.3 dated 2022-04-26 and 1.1.4 dated 2025-12-03

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Package typetracer updated to version 0.2.3 with previous version 0.2.2 dated 2023-06-26

Title: Trace Function Parameter Types
Description: The 'R' language includes a set of defined types, but the language itself is "absurdly dynamic" (Turcotte & Vitek (2019) <doi:10.1145/3340670.3342426>), and lacks any way to specify which types are expected by any expression. The 'typetracer' package enables code to be traced to extract detailed information on the properties of parameters passed to 'R' functions. 'typetracer' can trace individual functions or entire packages.
Author: Mark Padgham [aut, cre] , Filip Krikava [ctb] , covr authors [cph]
Maintainer: Mark Padgham <mark.padgham@email.com>

Diff between typetracer versions 0.2.2 dated 2023-06-26 and 0.2.3 dated 2025-12-03

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Package InterpretMSSpectrum updated to version 1.5.2 with previous version 1.4.5 dated 2024-01-31

Title: Interpreting High Resolution Mass Spectra
Description: High resolution mass spectrometry yields often large data sets of spectra from compounds which are not present in available libraries. These spectra need to be annotated and interpreted. 'InterpretMSSpectrum' provides a set of functions to perform such tasks for Electrospray-Ionization and Atmospheric-Pressure-Chemical-Ionization derived data in positive and negative ionization mode.
Author: Jan Lisec [aut, cre] , Jaeger Carsten [aut]
Maintainer: Jan Lisec <jan.lisec@bam.de>

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Package multibridge updated to version 1.3.0 with previous version 1.2.0 dated 2022-11-01

Title: Evaluating Multinomial Order Restrictions with Bridge Sampling
Description: Evaluate hypotheses concerning the distribution of multinomial proportions using bridge sampling. The bridge sampling routine is able to compute Bayes factors for hypotheses that entail inequality constraints, equality constraints, free parameters, and mixtures of all three. These hypotheses are tested against the encompassing hypothesis, that all parameters vary freely or against the null hypothesis that all category proportions are equal. For more information see Sarafoglou et al. (2020) <doi:10.31234/osf.io/bux7p>.
Author: Alexandra Sarafoglou [aut, cre] , Frederik Aust [aut] , Julia M. Haaf [aut] , Joris Goosen [aut], Quentin F. Gronau [aut], Maarten Marsman [aut]
Maintainer: Alexandra Sarafoglou <alexandra.sarafoglou@gmail.com>

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Package mclustAddons updated to version 0.10 with previous version 0.9.2 dated 2025-04-03

Title: Addons for the 'mclust' Package
Description: Extend the functionality of the 'mclust' package for Gaussian finite mixture modeling by including: density estimation for data with bounded support (Scrucca, 2019 <doi:10.1002/bimj.201800174>); modal clustering using MEM (Modal EM) algorithm for Gaussian mixtures (Scrucca, 2021 <doi:10.1002/sam.11527>); entropy estimation via Gaussian mixture modeling (Robin & Scrucca, 2023 <doi:10.1016/j.csda.2022.107582>); Gaussian mixtures modeling of financial log-returns (Scrucca, 2024 <doi:10.3390/e26110907>).
Author: Luca Scrucca [aut, cre, cph]
Maintainer: Luca Scrucca <luca.scrucca@unibo.it>

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Package APTIcalc updated to version 0.1.1 with previous version 0.1.0 dated 2025-05-29

Title: Air Pollution Tolerance Index (APTI) Calculator
Description: It calculates the Air Pollution Tolerance Index (APTI) of plant species using biochemical parameters such as chlorophyll content, leaf extract pH, relative water content, and ascorbic acid content. It helps in identifying tolerant species for greenbelt development and pollution mitigation studies. It includes a 'shiny' app for interactive APTI calculation and visualisation. For method details see, Sahu et al. (2020).<DOI:10.1007/s42452-020-3120-6>.
Author: Nobin Chandra Paul [aut, cre, cph], Rupali Singh [aut, cph], Sangram B Chavan [aut, cph], Navyasree Ponnaganti [aut, cph], K. Sammi Reddy [aut, cph]
Maintainer: Nobin Chandra Paul <ncp375@gmail.com>

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Package mlmi updated to version 1.1.3 with previous version 1.1.2 dated 2023-06-02

Title: Maximum Likelihood Multiple Imputation
Description: Implements proper and so-called Maximum Likelihood Multiple Imputation as described by von Hippel and Bartlett (2021) <doi:10.1214/20-STS793>. A number of different imputation methods are available, by utilising the 'norm', 'cat' and 'mix' packages. Inferences can be performed either using Rubin's rules (for proper imputation), or a modified version for maximum likelihood imputation. For maximum likelihood imputations a likelihood score based approach based on theory by Wang and Robins (1998) <doi:10.1093/biomet/85.4.935> is also available.
Author: Jonathan Bartlett [aut, cre]
Maintainer: Jonathan Bartlett <jonathan.bartlett1@lshtm.ac.uk>

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Package cgaim updated to version 1.0.3 with previous version 1.0.2 dated 2025-06-30

Title: Constrained Groupwise Additive Index Models
Description: Fits constrained groupwise additive index models and provides functions for inference and interpretation of these models. The method is described in Masselot, Chebana, Campagna, Lavigne, Ouarda, Gosselin (2022) "Constrained groupwise additive index models" <doi:10.1093/biostatistics/kxac023>.
Author: Pierre Masselot [aut, cre]
Maintainer: Pierre Masselot <pierre.masselot@lshtm.ac.uk>

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Package shinyMixR updated to version 0.5.3 with previous version 0.5.2 dated 2025-08-22

Title: Interactive 'shiny' Dashboard for 'nlmixr2'
Description: An R shiny user interface for the 'nlmixr2' (Fidler et al (2019) <doi:10.1002/psp4.12445>) package, designed to simplify the modeling process for users. Additionally, this package includes supplementary functions to further enhances the usage of 'nlmixr2'.
Author: Richard Hooijmaijers [aut, cre, cph], Teun Post [aut, cph], LAPP Consultants [fnd, cph], Matthew Fidler [ctb], Veerle van Leemput [ctb]
Maintainer: Richard Hooijmaijers <richardhooijmaijers@gmail.com>

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More information about shinyMixR at CRAN
Permanent link

Package idiolect updated to version 1.1.1 with previous version 1.0.1 dated 2024-08-28

Title: Forensic Authorship Analysis
Description: Carry out comparative authorship analysis of disputed and undisputed texts within the Likelihood Ratio Framework for expressing evidence in forensic science. This package contains implementations of well-known algorithms for comparative authorship analysis, such as Smith and Aldridge's (2011) Cosine Delta <doi:10.1080/09296174.2011.533591> or Koppel and Winter's (2014) Impostors Method <doi:10.1002/asi.22954>, as well as functions to measure their performance and to calibrate their outputs into Log-Likelihood Ratios.
Author: Andrea Nini [aut, cre, cph] , David van Leeuwen [cph]
Maintainer: Andrea Nini <andrea.nini@manchester.ac.uk>

Diff between idiolect versions 1.0.1 dated 2024-08-28 and 1.1.1 dated 2025-12-03

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Package CatReg updated to version 2.0.4 with previous version 2.0.3 dated 2021-06-14

Title: Solution Paths for Linear and Logistic Regression Models with Categorical Predictors, with SCOPE Penalty
Description: Computes solutions for linear and logistic regression models with potentially high-dimensional categorical predictors. This is done by applying a nonconvex penalty (SCOPE) and computing solutions in an efficient path-wise fashion. The scaling of the solution paths is selected automatically. Includes functionality for selecting tuning parameter lambda by k-fold cross-validation and early termination based on information criteria. Solutions are computed by cyclical block-coordinate descent, iterating an innovative dynamic programming algorithm to compute exact solutions for each block.
Author: Benjamin Stokell [aut], Daniel Grose [ctb, cre], Rajen Shah [ctb]
Maintainer: Daniel Grose <dan.grose@lancaster.ac.uk>

Diff between CatReg versions 2.0.3 dated 2021-06-14 and 2.0.4 dated 2025-12-03

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Package xgboost updated to version 3.1.2.1 with previous version 1.7.11.1 dated 2025-05-15

Title: Extreme Gradient Boosting
Description: Extreme Gradient Boosting, which is an efficient implementation of the gradient boosting framework from Chen & Guestrin (2016) <doi:10.1145/2939672.2939785>. This package is its R interface. The package includes efficient linear model solver and tree learning algorithms. The package can automatically do parallel computation on a single machine which could be more than 10 times faster than existing gradient boosting packages. It supports various objective functions, including regression, classification and ranking. The package is made to be extensible, so that users are also allowed to define their own objectives easily.
Author: Tianqi Chen [aut], Tong He [aut], Michael Benesty [aut], Vadim Khotilovich [aut], Yuan Tang [aut] , Hyunsu Cho [aut], Kailong Chen [aut], Rory Mitchell [aut], Ignacio Cano [aut], Tianyi Zhou [aut], Mu Li [aut], Junyuan Xie [aut], Min Lin [aut], Yifen [...truncated...]
Maintainer: Jiaming Yuan <jm.yuan@outlook.com>

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 xgboost-3.1.2.1/xgboost/src/include/xgboost/metric.h                        |   35 
 xgboost-3.1.2.1/xgboost/src/include/xgboost/model.h                         |   13 
 xgboost-3.1.2.1/xgboost/src/include/xgboost/multi_target_tree_model.h       |only
 xgboost-3.1.2.1/xgboost/src/include/xgboost/objective.h                     |  167 
 xgboost-3.1.2.1/xgboost/src/include/xgboost/parameter.h                     |    2 
 xgboost-3.1.2.1/xgboost/src/include/xgboost/predictor.h                     |  157 
 xgboost-3.1.2.1/xgboost/src/include/xgboost/span.h                          |  148 
 xgboost-3.1.2.1/xgboost/src/include/xgboost/string_view.h                   |   60 
 xgboost-3.1.2.1/xgboost/src/include/xgboost/task.h                          |    8 
 xgboost-3.1.2.1/xgboost/src/include/xgboost/tree_model.h                    |  584 +--
 xgboost-3.1.2.1/xgboost/src/include/xgboost/tree_updater.h                  |   67 
 xgboost-3.1.2.1/xgboost/src/include/xgboost/version_config.h                |   10 
 xgboost-3.1.2.1/xgboost/src/include/xgboost/windefs.h                       |only
 xgboost-3.1.2.1/xgboost/src/init.c                                          |   87 
 xgboost-3.1.2.1/xgboost/src/src/CMakeLists.txt                              |   28 
 xgboost-3.1.2.1/xgboost/src/src/c_api/c_api.cc                              | 1140 ++++--
 xgboost-3.1.2.1/xgboost/src/src/c_api/c_api.cu                              |   93 
 xgboost-3.1.2.1/xgboost/src/src/c_api/c_api_error.cc                        |   18 
 xgboost-3.1.2.1/xgboost/src/src/c_api/c_api_error.h                         |   21 
 xgboost-3.1.2.1/xgboost/src/src/c_api/c_api_utils.h                         |  154 
 xgboost-3.1.2.1/xgboost/src/src/c_api/coll_c_api.cc                         |only
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 xgboost-3.1.2.1/xgboost/src/src/collective/communicator-inl.h               |  224 -
 xgboost-3.1.2.1/xgboost/src/src/collective/in_memory_communicator.h         |only
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 xgboost-3.1.2.1/xgboost/src/src/collective/socket.cc                        |  164 
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 xgboost-3.1.2.1/xgboost/src/src/collective/tracker.h                        |only
 xgboost-3.1.2.1/xgboost/src/src/common/algorithm.cuh                        |  387 ++
 xgboost-3.1.2.1/xgboost/src/src/common/algorithm.h                          |   90 
 xgboost-3.1.2.1/xgboost/src/src/common/api_entry.h                          |only
 xgboost-3.1.2.1/xgboost/src/src/common/bitfield.h                           |  151 
 xgboost-3.1.2.1/xgboost/src/src/common/categorical.h                        |   29 
 xgboost-3.1.2.1/xgboost/src/src/common/charconv.cc                          |   20 
 xgboost-3.1.2.1/xgboost/src/src/common/charconv.h                           |    2 
 xgboost-3.1.2.1/xgboost/src/src/common/column_matrix.cc                     |   79 
 xgboost-3.1.2.1/xgboost/src/src/common/column_matrix.h                      |  276 -
 xgboost-3.1.2.1/xgboost/src/src/common/common.cc                            |   80 
 xgboost-3.1.2.1/xgboost/src/src/common/common.cu                            |   40 
 xgboost-3.1.2.1/xgboost/src/src/common/common.h                             |  281 -
 xgboost-3.1.2.1/xgboost/src/src/common/compressed_iterator.h                |  160 
 xgboost-3.1.2.1/xgboost/src/src/common/cuda_context.cuh                     |only
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 xgboost-3.1.2.1/xgboost/src/src/common/device_helpers.cu                    |only
 xgboost-3.1.2.1/xgboost/src/src/common/device_helpers.cuh                   |  968 +----
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 xgboost-3.1.2.1/xgboost/src/src/common/error_msg.h                          |only
 xgboost-3.1.2.1/xgboost/src/src/common/hist_util.cc                         |  207 -
 xgboost-3.1.2.1/xgboost/src/src/common/hist_util.cu                         |  443 +-
 xgboost-3.1.2.1/xgboost/src/src/common/hist_util.cuh                        |  415 +-
 xgboost-3.1.2.1/xgboost/src/src/common/hist_util.h                          |  257 -
 xgboost-3.1.2.1/xgboost/src/src/common/host_device_vector.cc                |   26 
 xgboost-3.1.2.1/xgboost/src/src/common/host_device_vector.cu                |  151 
 xgboost-3.1.2.1/xgboost/src/src/common/io.cc                                |  383 +-
 xgboost-3.1.2.1/xgboost/src/src/common/io.h                                 |  540 ++
 xgboost-3.1.2.1/xgboost/src/src/common/json.cc                              |  208 -
 xgboost-3.1.2.1/xgboost/src/src/common/json_utils.h                         |only
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 xgboost-3.1.2.1/xgboost/src/src/common/linalg_op.cuh                        |  104 
 xgboost-3.1.2.1/xgboost/src/src/common/linalg_op.h                          |  138 
 xgboost-3.1.2.1/xgboost/src/src/common/math.h                               |   70 
 xgboost-3.1.2.1/xgboost/src/src/common/numa_topo.cc                         |only
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 xgboost-3.1.2.1/xgboost/src/src/common/numeric.cu                           |   20 
 xgboost-3.1.2.1/xgboost/src/src/common/numeric.h                            |   48 
 xgboost-3.1.2.1/xgboost/src/src/common/nvtx_utils.h                         |only
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 xgboost-3.1.2.1/xgboost/src/src/common/partition_builder.h                  |  252 -
 xgboost-3.1.2.1/xgboost/src/src/common/pseudo_huber.cc                      |    2 
 xgboost-3.1.2.1/xgboost/src/src/common/pseudo_huber.h                       |    4 
 xgboost-3.1.2.1/xgboost/src/src/common/quantile.cc                          |  303 -
 xgboost-3.1.2.1/xgboost/src/src/common/quantile.cu                          |  231 -
 xgboost-3.1.2.1/xgboost/src/src/common/quantile.cuh                         |  155 
 xgboost-3.1.2.1/xgboost/src/src/common/quantile.h                           |   92 
 xgboost-3.1.2.1/xgboost/src/src/common/quantile_loss_utils.cc               |only
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 xgboost-3.1.2.1/xgboost/src/src/common/stats.cu                             |  133 
 xgboost-3.1.2.1/xgboost/src/src/common/stats.cuh                            |  280 +
 xgboost-3.1.2.1/xgboost/src/src/common/stats.h                              |  146 
 xgboost-3.1.2.1/xgboost/src/src/common/threading_utils.cc                   |  122 
 xgboost-3.1.2.1/xgboost/src/src/common/threading_utils.cuh                  |only
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 xgboost-3.1.2.1/xgboost/src/src/common/timer.cc                             |   45 
 xgboost-3.1.2.1/xgboost/src/src/common/timer.h                              |   15 
 xgboost-3.1.2.1/xgboost/src/src/common/transform.h                          |   49 
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 xgboost-3.1.2.1/xgboost/src/src/data/adapter.h                              |  882 +---
 xgboost-3.1.2.1/xgboost/src/src/data/array_interface.cc                     |only
 xgboost-3.1.2.1/xgboost/src/src/data/array_interface.cu                     |   19 
 xgboost-3.1.2.1/xgboost/src/src/data/array_interface.h                      |  204 -
 xgboost-3.1.2.1/xgboost/src/src/data/batch_utils.cc                         |only
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 xgboost-3.1.2.1/xgboost/src/src/data/columnar.h                             |only
 xgboost-3.1.2.1/xgboost/src/src/data/data.cc                                |  724 ++-
 xgboost-3.1.2.1/xgboost/src/src/data/data.cu                                |  162 
 xgboost-3.1.2.1/xgboost/src/src/data/device_adapter.cu                      |only
 xgboost-3.1.2.1/xgboost/src/src/data/device_adapter.cuh                     |  317 -
 xgboost-3.1.2.1/xgboost/src/src/data/ellpack_page.cc                        |   35 
 xgboost-3.1.2.1/xgboost/src/src/data/ellpack_page.cu                        |  927 +++--
 xgboost-3.1.2.1/xgboost/src/src/data/ellpack_page.cuh                       |  475 +-
 xgboost-3.1.2.1/xgboost/src/src/data/ellpack_page.h                         |only
 xgboost-3.1.2.1/xgboost/src/src/data/ellpack_page_raw_format.cu             |  188 -
 xgboost-3.1.2.1/xgboost/src/src/data/ellpack_page_raw_format.h              |only
 xgboost-3.1.2.1/xgboost/src/src/data/ellpack_page_source.cu                 |  633 +++
 xgboost-3.1.2.1/xgboost/src/src/data/ellpack_page_source.h                  |  397 ++
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 xgboost-3.1.2.1/xgboost/src/src/data/file_iterator.h                        |   77 
 xgboost-3.1.2.1/xgboost/src/src/data/gradient_index.cc                      |  136 
 xgboost-3.1.2.1/xgboost/src/src/data/gradient_index.cu                      |  112 
 xgboost-3.1.2.1/xgboost/src/src/data/gradient_index.h                       |  189 -
 xgboost-3.1.2.1/xgboost/src/src/data/gradient_index_format.cc               |  185 -
 xgboost-3.1.2.1/xgboost/src/src/data/gradient_index_format.h                |only
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 xgboost-3.1.2.1/xgboost/src/src/data/gradient_index_page_source.h           |   94 
 xgboost-3.1.2.1/xgboost/src/src/data/iterative_dmatrix.cc                   |  315 -
 xgboost-3.1.2.1/xgboost/src/src/data/iterative_dmatrix.cu                   |  241 -
 xgboost-3.1.2.1/xgboost/src/src/data/iterative_dmatrix.h                    |  148 
 xgboost-3.1.2.1/xgboost/src/src/data/proxy_dmatrix.cc                       |  117 
 xgboost-3.1.2.1/xgboost/src/src/data/proxy_dmatrix.cu                       |   84 
 xgboost-3.1.2.1/xgboost/src/src/data/proxy_dmatrix.cuh                      |   75 
 xgboost-3.1.2.1/xgboost/src/src/data/proxy_dmatrix.h                        |  363 +-
 xgboost-3.1.2.1/xgboost/src/src/data/quantile_dmatrix.cc                    |only
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 xgboost-3.1.2.1/xgboost/src/src/data/simple_batch_iterator.h                |   22 
 xgboost-3.1.2.1/xgboost/src/src/data/simple_dmatrix.cc                      |  374 +-
 xgboost-3.1.2.1/xgboost/src/src/data/simple_dmatrix.cu                      |   68 
 xgboost-3.1.2.1/xgboost/src/src/data/simple_dmatrix.cuh                     |   55 
 xgboost-3.1.2.1/xgboost/src/src/data/simple_dmatrix.h                       |   40 
 xgboost-3.1.2.1/xgboost/src/src/data/sparse_page_dmatrix.cc                 |  244 -
 xgboost-3.1.2.1/xgboost/src/src/data/sparse_page_dmatrix.cu                 |  100 
 xgboost-3.1.2.1/xgboost/src/src/data/sparse_page_dmatrix.h                  |  186 -
 xgboost-3.1.2.1/xgboost/src/src/data/sparse_page_raw_format.cc              |   81 
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 xgboost-3.1.2.1/xgboost/src/src/data/sparse_page_source.h                   |  595 ++-
 xgboost-3.1.2.1/xgboost/src/src/data/sparse_page_writer.h                   |   95 
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 xgboost-3.1.2.1/xgboost/src/src/encoder                                     |only
 xgboost-3.1.2.1/xgboost/src/src/gbm/gblinear.cc                             |  131 
 xgboost-3.1.2.1/xgboost/src/src/gbm/gblinear_model.cc                       |   14 
 xgboost-3.1.2.1/xgboost/src/src/gbm/gblinear_model.h                        |   51 
 xgboost-3.1.2.1/xgboost/src/src/gbm/gbm.cc                                  |   14 
 xgboost-3.1.2.1/xgboost/src/src/gbm/gbtree.cc                               |  902 ++--
 xgboost-3.1.2.1/xgboost/src/src/gbm/gbtree.cu                               |   44 
 xgboost-3.1.2.1/xgboost/src/src/gbm/gbtree.h                                |  355 -
 xgboost-3.1.2.1/xgboost/src/src/gbm/gbtree_model.cc                         |  182 -
 xgboost-3.1.2.1/xgboost/src/src/gbm/gbtree_model.h                          |  142 
 xgboost-3.1.2.1/xgboost/src/src/global_config.cc                            |   23 
 xgboost-3.1.2.1/xgboost/src/src/learner.cc                                  | 1102 ++----
 xgboost-3.1.2.1/xgboost/src/src/linear/coordinate_common.h                  |  134 
 xgboost-3.1.2.1/xgboost/src/src/linear/linear_updater.cc                    |    4 
 xgboost-3.1.2.1/xgboost/src/src/linear/updater_coordinate.cc                |   57 
 xgboost-3.1.2.1/xgboost/src/src/linear/updater_gpu_coordinate.cu            |   61 
 xgboost-3.1.2.1/xgboost/src/src/linear/updater_shotgun.cc                   |   36 
 xgboost-3.1.2.1/xgboost/src/src/logging.cc                                  |    9 
 xgboost-3.1.2.1/xgboost/src/src/metric/auc.cc                               |  222 -
 xgboost-3.1.2.1/xgboost/src/src/metric/auc.cu                               |  285 -
 xgboost-3.1.2.1/xgboost/src/src/metric/auc.h                                |   63 
 xgboost-3.1.2.1/xgboost/src/src/metric/elementwise_metric.cu                |  251 -
 xgboost-3.1.2.1/xgboost/src/src/metric/metric.cc                            |   34 
 xgboost-3.1.2.1/xgboost/src/src/metric/metric_common.h                      |   67 
 xgboost-3.1.2.1/xgboost/src/src/metric/multiclass_metric.cu                 |   80 
 xgboost-3.1.2.1/xgboost/src/src/metric/rank_metric.cc                       |  550 +--
 xgboost-3.1.2.1/xgboost/src/src/metric/rank_metric.cu                       |  464 +-
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Package shiny updated to version 1.12.0 with previous version 1.11.1 dated 2025-07-03

Title: Web Application Framework for R
Description: Makes it incredibly easy to build interactive web applications with R. Automatic "reactive" binding between inputs and outputs and extensive prebuilt widgets make it possible to build beautiful, responsive, and powerful applications with minimal effort.
Author: Winston Chang [aut] , Joe Cheng [aut], JJ Allaire [aut], Carson Sievert [aut, cre] , Barret Schloerke [aut] , Garrick Aden-Buie [aut] , Yihui Xie [aut], Jeff Allen [aut], Jonathan McPherson [aut], Alan Dipert [aut], Barbara Borges [aut], Posit Softwa [...truncated...]
Maintainer: Carson Sievert <carson@posit.co>

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Package ggtranslate updated to version 0.1.2 with previous version 0.1.1 dated 2025-08-21

Title: A 'ggplot2' Extension for Translating Plot Text
Description: Provides a simple way to translate text elements in 'ggplot2' plots using a dictionary-based approach.
Author: Mathias Leroy [aut, cre]
Maintainer: Mathias Leroy <mathias.leroy.rpkg@gmail.com>

Diff between ggtranslate versions 0.1.1 dated 2025-08-21 and 0.1.2 dated 2025-12-03

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Package romic (with last version 1.1.3) was removed from CRAN

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

2023-09-21 1.1.3
2023-02-02 1.1.1
2021-07-20 1.0.0

Permanent link
Package RKHSMetaMod (with last version 1.1) was removed from CRAN

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

2019-07-06 1.1
2019-07-03 1.0

Permanent link
Package vectorsurvR updated to version 1.6.1 with previous version 1.6.0 dated 2025-11-03

Title: Data Access and Analytical Tools for 'VectorSurv' Users
Description: Allows registered 'VectorSurv' <https://vectorsurv.org/> users access to data through the 'VectorSurv API' <https://api.vectorsurv.org/>. Additionally provides functions for analysis and visualization.
Author: Christina De Cesaris [aut, cre]
Maintainer: Christina De Cesaris <cmdecesaris@ucdavis.edu>

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Package neuralGAM updated to version 2.0.1 with previous version 2.0.0 dated 2025-10-08

Title: Interpretable Neural Network Based on Generalized Additive Models
Description: Neural Additive Model framework based on Generalized Additive Models from Hastie & Tibshirani (1990, ISBN:9780412343902), which trains a different neural network to estimate the contribution of each feature to the response variable. The networks are trained independently leveraging the local scoring and backfitting algorithms to ensure that the Generalized Additive Model converges and it is additive. The resultant Neural Network is a highly accurate and interpretable deep learning model, which can be used for high-risk AI practices where decision-making should be based on accountable and interpretable algorithms.
Author: Ines Ortega-Fernandez [aut, cre, cph] , Marta Sestelo [aut, cph]
Maintainer: Ines Ortega-Fernandez <iortega@gradiant.org>

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Package istat (with last version 1.0) was removed from CRAN

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2024-09-10 1.0

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Package nJira (with last version 0.1.1) was removed from CRAN

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

2020-03-02 0.1.1

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Package gimap (with last version 1.1.1) was removed from CRAN

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

2025-04-30 1.1.1
2025-03-07 1.0.3
2025-02-18 1.0.2
2025-02-03 1.0.1

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Package statcanR (with last version 0.2.6) was removed from CRAN

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

2023-08-17 0.2.6

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Package covid19swiss (with last version 0.1.0) was removed from CRAN

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

2020-09-18 0.1.0

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Package teal.transform updated to version 0.7.1 with previous version 0.7.0 dated 2025-08-20

Title: Functions for Extracting and Merging Data in the 'teal' Framework
Description: A standardized user interface for column selection, that facilitates dataset merging in 'teal' framework.
Author: Dawid Kaledkowski [aut, cre], Pawel Rucki [aut], Mahmoud Hallal [aut], Nikolas Burkoff [aut], Maciej Nasinski [aut], Konrad Pagacz [aut], Junlue Zhao [aut], F. Hoffmann-La Roche AG [cph, fnd]
Maintainer: Dawid Kaledkowski <dawid.kaledkowski@roche.com>

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Package nftbart updated to version 2.3 with previous version 2.2 dated 2025-08-23

Title: Nonparametric Failure Time Bayesian Additive Regression Trees
Description: Nonparametric Failure Time (NFT) Bayesian Additive Regression Trees (BART): Time-to-event Machine Learning with Heteroskedastic Bayesian Additive Regression Trees (HBART) and Low Information Omnibus (LIO) Dirichlet Process Mixtures (DPM). An NFT BART model is of the form Y = mu + f(x) + sd(x) E where functions f and sd have BART and HBART priors, respectively, while E is a nonparametric error distribution due to a DPM LIO prior hierarchy. See the following for a description of the model at <doi:10.1111/biom.13857>.
Author: Rodney Sparapani [aut, cre], Robert McCulloch [aut], Matthew Pratola [ctb], Hugh Chipman [ctb]
Maintainer: Rodney Sparapani <rsparapa@mcw.edu>

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Package hyd1d updated to version 0.5.4 with previous version 0.5.3 dated 2025-02-26

Title: 1d Water Level Interpolation along the Rivers Elbe and Rhine
Description: An S4 class and several functions which utilize internally stored datasets and gauging data enable 1d water level interpolation. The S4 class (WaterLevelDataFrame) structures the computation and visualisation of 1d water level information along the German federal waterways Elbe and Rhine. 'hyd1d' delivers 1d water level data - extracted from the 'FLYS' database - and validated gauging data - extracted from the hydrological database 'WISKI7' - package-internally. For computations near real time gauging data are queried externally from the 'PEGELONLINE REST API' <https://pegelonline.wsv.de/webservice/dokuRestapi>.
Author: Arnd Weber [aut, cre] , Marcus Hatz [aut], Wolfgang Stuermer [ctb], Wilfried Wiechmann [ctb], Benjamin Eberhardt [ctb]
Maintainer: Arnd Weber <arnd.weber@bafg.de>

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Package convdistr updated to version 1.6.3 with previous version 1.6.2 dated 2024-05-05

Title: Convolute Probabilistic Distributions
Description: Convolute probabilistic distributions using the random generator function of each distribution. A new random number generator function is created that perform the mathematical operation on the individual random samples from the random generator function of each distribution. See the documentation for examples.
Author: Aponte John [aut, cre]
Maintainer: Aponte John <john.j.aponte@gmail.com>

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Package calcite updated to version 0.1.1 with previous version 0.1.0 dated 2025-04-01

Title: Bindings to the Calcite Design System 'JavaScript' Component Library
Description: Provides access to the 'Calcite Design System' 'javascript' components via integration with the 'htmltools' and 'shiny' packages. Pre-built and interactive components can be used to generate either static html or interactive web applications. Learn more about the 'Calcite Design System' at <https://developers.arcgis.com/calcite-design-system/>.
Author: Josiah Parry [aut, cre]
Maintainer: Josiah Parry <josiah.parry@gmail.com>

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Package Analitica updated to version 2.2.0 with previous version 2.1.2 dated 2025-10-07

Title: Exploratory Data Analysis, Group Comparison Tools, and Other Procedures
Description: Provides a comprehensive set of tools for descriptive statistics, graphical data exploration, outlier detection, homoscedasticity testing, and multiple comparison procedures. Includes manual implementations of Levene's test, Bartlett's test, and the Fligner-Killeen test, as well as post hoc comparison methods such as Tukey, Scheffé, Games-Howell, Brunner-Munzel, and others. This version introduces two new procedures: the Jonckheere-Terpstra trend test and the Jarque-Bera test with Glinskiy's (2024) correction. Designed for use in teaching, applied statistical analysis, and reproducible research. Additionally you can find a post hoc Test Planner, which helps you to make a decision on which procedure is most suitable.
Author: Carlos Jimenez-Gallardo [aut, cre]
Maintainer: Carlos Jimenez-Gallardo <carlos.jimenez@ufrontera.cl>

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