Mon, 26 Jan 2026

Package splineCox updated to version 0.0.8 with previous version 0.0.7 dated 2025-12-06

Title: A Two-Stage Estimation Approach to Cox Regression Using M-Spline Function
Description: Implements a two-stage estimation approach for Cox regression using five-parameter M-spline functions to model the baseline hazard. It allows for flexible hazard shapes and model selection based on log-likelihood criteria as described in Teranishi et al.(2025). In addition, the package provides functions for constructing and evaluating B-spline copulas based on five M-spline or I-spline basis functions, allowing users to flexibly model and compute bivariate dependence structures. Both the copula function and its density can be evaluated. Furthermore, the package supports computation of dependence measures such as Kendall's tau and Spearman's rho, derived analytically from the copula parameters.
Author: Ren Teranishi [aut, cre]
Maintainer: Ren Teranishi <ren.teranishi1227@gmail.com>

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Package profileCI updated to version 1.1.1 with previous version 1.1.0 dated 2025-07-11

Title: Profiling a Log-Likelihood to Calculate Confidence Intervals
Description: Provides tools for profiling a user-supplied log-likelihood function to calculate confidence intervals for model parameters. Speed of computation can be improved by adjusting the step sizes in the profiling and/or starting the profiling from limits based on the approximate large sample normal distribution for the maximum likelihood estimator of a parameter. The accuracy of the limits can be set by the user. A plot method visualises the log-likelihood and confidence interval. Cases where the profile log-likelihood flattens above the value at which a confidence limit is defined can be handled, leading to a limit at plus or minus infinity. Disjoint confidence intervals will not be found.
Author: Paul J. Northrop [aut, cre, cph]
Maintainer: Paul J. Northrop <p.northrop@ucl.ac.uk>

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Package insulin.secretion updated to version 0.0.2 with previous version 0.0.1 dated 2025-11-05

Title: Insulin Secretion Rate Deconvolution
Description: Calculates insulin secretion rates from C-peptide values based on the methods described in Van Cauter et al. (1992) <doi:10.2337/diab.41.3.368>. Includes functions to calculate estimated insulin secretion rates using linear or cubic spline interpolation of c-peptide values (see Eaton et al., 1980 <doi:10.1210/jcem-51-3-520> and Polonsky et al., 1986 <doi:10.1172/JCI112308>) and to calculate estimates of input coefficients (volume of distribution, short half life, long half life, and fraction attributed to short half life) as described by Van Cauter. Although the generated coefficients are specific to insulin secretion, the two-compartment secretion model used here is useful for certain applications beyond insulin.
Author: Ken Stier [aut, cre, cph]
Maintainer: Ken Stier <kennethstier99@gmail.com>

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Package pysparklyr updated to version 0.2.0 with previous version 0.1.9 dated 2025-10-07

Title: Provides a 'PySpark' Back-End for the 'sparklyr' Package
Description: It enables 'sparklyr' to integrate with 'Spark Connect', and 'Databricks Connect' by providing a wrapper over the 'PySpark' 'python' library.
Author: Edgar Ruiz [aut, cre], Posit Software, PBC [cph, fnd]
Maintainer: Edgar Ruiz <edgar@posit.co>

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Package puremoe updated to version 1.0.3 with previous version 1.0.2 dated 2024-10-15

Title: Pubmed Unified REtrieval for Multi-Output Exploration
Description: Access a variety of 'PubMed' data through a single, user-friendly interface, including abstracts, bibliometrics from 'iCite', pubtations from 'PubTator3', and full-text records from 'PMC'.
Author: Jason Timm [aut, cre]
Maintainer: Jason Timm <JaTimm@salud.unm.edu>

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Package epanetReader updated to version 1.0.0 with previous version 0.7.3 dated 2018-06-26

Title: Read Epanet Files into R
Description: Reads water network simulation data in 'Epanet' text-based '.inp' and '.rpt' formats into R. Also reads results from 'Epanet-msx'. Provides basic summary information and plots. The README file has a quick introduction. See <https://www.epa.gov/water-research/epanet> for more information on the Epanet software for modeling hydraulic and water quality behavior of water piping systems.
Author: Bradley Eck [aut, cre]
Maintainer: Bradley Eck <brad@bradeck.net>

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Package spectrakit updated to version 0.1.2 with previous version 0.1.1 dated 2025-07-18

Title: Spectral Data Handling and Visualization
Description: Provides functions to combine, normalize and visualize spectral data, perform principal component analysis (PCA), and assemble customizable image grids suitable for publication-quality scientific figures.
Author: Gianluca Pastorelli [aut, cre]
Maintainer: Gianluca Pastorelli <gianluca.pastorelli@gmail.com>

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Package saeSim updated to version 0.13.0 with previous version 0.12.0 dated 2025-10-14

Title: Simulation Tools for Small Area Estimation
Description: Tools for the simulation of data in the context of small area estimation. Combine all steps of your simulation - from data generation over drawing samples to model fitting - in one object. This enables easy modification and combination of different scenarios. You can store your results in a folder or start the simulation in parallel.
Author: Sebastian Warnholz [aut, cre], Timo Schmid [aut]
Maintainer: Sebastian Warnholz <wahani@gmail.com>

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Package starvars updated to version 1.1.11 with previous version 1.1.10 dated 2022-01-17

Title: Vector Logistic Smooth Transition Models Estimation and Prediction
Description: Allows the user to estimate a vector logistic smooth transition autoregressive model via maximum log-likelihood or nonlinear least squares. It further permits to test for linearity in the multivariate framework against a vector logistic smooth transition autoregressive model with a single transition variable. The estimation method is discussed in Terasvirta and Yang (2014, <doi:10.1108/S0731-9053(2013)0000031008>). Also, realized covariances can be constructed from stock market prices or returns, as explained in Andersen et al. (2001, <doi:10.1016/S0304-405X(01)00055-1>).
Author: Andrea Bucci [aut, cre, cph], Giulio Palomba [aut], Eduardo Rossi [aut], Andrea Faragalli [ctb]
Maintainer: Andrea Bucci <andrea.bucci@unimc.it>

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Package sstvars updated to version 1.2.3 with previous version 1.2.2 dated 2025-09-15

Title: Toolkit for Reduced Form and Structural Smooth Transition Vector Autoregressive Models
Description: Penalized and non-penalized maximum likelihood estimation of smooth transition vector autoregressive models with various types of transition weight functions, conditional distributions, and identification methods. Constrained estimation with various types of constraints is available. Residual based model diagnostics, forecasting, simulations, counterfactual analysis, and computation of impulse response functions, generalized impulse response functions, generalized forecast error variance decompositions, as well as historical decompositions. See Heather Anderson, Farshid Vahid (1998) <doi:10.1016/S0304-4076(97)00076-6>, Helmut Lütkepohl, Aleksei Netšunajev (2017) <doi:10.1016/j.jedc.2017.09.001>, Markku Lanne, Savi Virolainen (2025) <doi:10.1016/j.jedc.2025.105162>, Savi Virolainen (2025) <doi:10.48550/arXiv.2404.19707>.
Author: Savi Virolainen [aut, cre]
Maintainer: Savi Virolainen <savi.virolainen@helsinki.fi>

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Package plmmr updated to version 4.2.3 with previous version 4.2.2 dated 2026-01-21

Title: Penalized Linear Mixed Models for Correlated Data
Description: Fits penalized linear mixed models that correct for unobserved confounding factors. 'plmmr' infers and corrects for the presence of unobserved confounding effects such as population stratification and environmental heterogeneity. It then fits a linear model via penalized maximum likelihood. Originally designed for the multivariate analysis of single nucleotide polymorphisms (SNPs) measured in a genome-wide association study (GWAS), 'plmmr' eliminates the need for subpopulation-specific analyses and post-analysis p-value adjustments. Functions for the appropriate processing of 'PLINK' files are also supplied. For examples, see the package homepage. <https://pbreheny.github.io/plmmr/>.
Author: Tabitha K. Peter [aut] , Anna C. Reisetter [aut] , Yujing Lu [aut], Oscar A. Rysavy [aut], Patrick J. Breheny [aut, cre]
Maintainer: Patrick J. Breheny <patrick-breheny@uiowa.edu>

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Package OmicFlow updated to version 1.5.0 with previous version 1.4.2 dated 2025-11-30

Title: Fast and Efficient (Automated) Analysis of Sparse Omics Data
Description: A generalised data structure for fast and efficient loading and data munching of sparse omics data. The 'OmicFlow' requires an up-front validated metadata template from the user, which serves as a guide to connect all the pieces together by aligning them into a single object that is defined as an 'omics' class. Once this unified structure is established, users can perform manual subsetting, visualisation, and statistical analysis, or leverage the automated 'autoFlow' method to generate a comprehensive report.
Author: Alem Gusinac [aut, cre] , Thomas Ederveen [aut] , Annemarie Boleij [aut, fnd]
Maintainer: Alem Gusinac <alem.gusinac@gmail.com>

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Package amadeus updated to version 1.3.2.1 with previous version 1.2.4.9 dated 2025-08-24

Title: Accessing and Analyzing Large-Scale Environmental Data
Description: Functions are designed to facilitate access to and utility with large scale, publicly available environmental data in R. The package contains functions for downloading raw data files from web URLs (download_data()), processing the raw data files into clean spatial objects (process_covariates()), and extracting values from the spatial data objects at point and polygon locations (calculate_covariates()). These functions call a series of source-specific functions which are tailored to each data sources/datasets particular URL structure, data format, and spatial/temporal resolution. The functions are tested, versioned, and open source and open access. For sum_edc() method details, see Messier, Akita, and Serre (2012) <doi:10.1021/es203152a>.
Author: Mitchell Manware [aut, ctb] , Insang Song [aut, ctb] , Eva Marques [aut, ctb] , Mariana Alifa Kassien [aut, ctb] , Elizabeth Scholl [ctb] , Kyle Messier [aut, cre] , Spatiotemporal Exposures and Toxicology Group [cph]
Maintainer: Kyle Messier <kyle.messier@nih.gov>

Diff between amadeus versions 1.2.4.9 dated 2025-08-24 and 1.3.2.1 dated 2026-01-26

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New package uniLasso with initial version 2.11
Package: uniLasso
Title: Univariate-Guided Sparse Regression
Version: 2.11
Date: 2026-01-13
Depends: glmnet, stats, R (>= 3.6.0)
Imports: methods, utils, MASS
Suggests: testthat
Description: Fit a univariate-guided sparse regression (lasso), by a two-stage procedure. The first stage fits p separate univariate models to the response. The second stage gives more weight to the more important univariate features, and preserves their signs. Conveniently, it returns an objects that inherits from class 'glmnet', so that all of the methods for 'glmnet' are available. See Chatterjee, Hastie and Tibshirani (2025) <doi:10.1162/99608f92.c79ff6db> for details.
Encoding: UTF-8
License: GPL-2
NeedsCompilation: no
Packaged: 2026-01-22 00:40:40 UTC; hastie
Author: Trevor Hastie [aut, cre], Rob Tibshirani [aut], Sourav Chatterjee [aut]
Maintainer: Trevor Hastie <hastie@stanford.edu>
Repository: CRAN
Date/Publication: 2026-01-26 17:00:02 UTC

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Package tidytransit updated to version 1.8.0 with previous version 1.7.1 dated 2025-08-21

Title: Read, Validate, Analyze, and Map GTFS Feeds
Description: Read General Transit Feed Specification (GTFS) zipfiles into a list of R dataframes. Perform validation of the data structure against the specification. Analyze the headways and frequencies at routes and stops. Create maps and perform spatial analysis on the routes and stops. Please see the GTFS documentation here for more detail: <https://gtfs.org/>.
Author: Flavio Poletti [aut, cre], Daniel Herszenhut [aut] , Mark Padgham [aut], Tom Buckley [aut], Danton Noriega-Goodwin [aut], Angela Li [ctb], Elaine McVey [ctb], Charles Hans Thompson [ctb], Michael Sumner [ctb], Patrick Hausmann [ctb], Bob Rudis [ctb], [...truncated...]
Maintainer: Flavio Poletti <flavio.poletti@hotmail.ch>

Diff between tidytransit versions 1.7.1 dated 2025-08-21 and 1.8.0 dated 2026-01-26

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Permanent link

New package starling with initial version 0.6.5
Package: starling
Title: Link Infectious Disease Cases to Vaccination and Hospitalization Records
Version: 0.6.5
Description: Facilitates probabilistic record linkage between infectious disease surveillance datasets (notifiable disease registers, outbreak line-lists), vaccination registries, and hospitalization records using methods based on Fellegi and Sunter (1969) <doi:10.1080/01621459.1969.10501049> and Sayers et al. (2016) <doi:10.1093/ije/dyv322>. The package provides core functions for data preparation, linkage, and analysis: clean_the_nest() standardizes variable names and formats across heterogeneous datasets; murmuration() performs machine learning-based record linkage using blocking variables and similarity metrics; molting() deidentifies datasets for secure sharing; homing() re-identifies previously deidentified datasets; plumage() identifies and categorizes comorbidities; and preening() creates analysis-ready variables including age categories and temporal groupings. Designed for epidemiological research linking acute and post-acute disease outcomes to vaccination status and healthcar [...truncated...]
License: GPL (>= 3)
Depends: R (>= 3.5.0)
Imports: dplyr, lubridate, janitor, stringr, tidyr, reclin2, datawizard, digest, rlang, magrittr
Suggests: testthat (>= 3.0.0), knitr, gtsummary, rmarkdown
Encoding: UTF-8
LazyData: true
VignetteBuilder: knitr
Language: en-US
NeedsCompilation: no
Packaged: 2026-01-21 09:11:14 UTC; SmollN
Author: Nicolas Smoll [aut, cre]
Maintainer: Nicolas Smoll <nrsmoll@gmail.com>
Repository: CRAN
Date/Publication: 2026-01-26 16:20:08 UTC

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New package SpatialDownscaling with initial version 0.1.2
Package: SpatialDownscaling
Title: Methods for Spatial Downscaling Using Deep Learning
Version: 0.1.2
Date: 2026-01-21
Imports: stats, tensorflow, keras3, magrittr, Rdpack, raster, abind
Description: The aim of the spatial downscaling is to increase the spatial resolution of the gridded geospatial input data. This package contains two deep learning based spatial downscaling methods, super-resolution deep residual network (SRDRN) (Wang et al., 2021 <doi:10.1029/2020WR029308>) and UNet (Ronneberger et al., 2015 <doi:10.1007/978-3-319-24574-4_28>), along with a statistical baseline method bias correction and spatial disaggregation (Wood et al., 2004 <doi:10.1023/B:CLIM.0000013685.99609.9e>). The SRDRN and UNet methods are implemented to optionally account for cyclical temporal patterns in case of spatio-temporal data. For more details of the methods, see Sipilä et al. (2025) <doi:10.48550/arXiv.2512.13753>.
License: GPL-3
Encoding: UTF-8
LazyData: true
SystemRequirements: Python (>= 3.8), TensorFlow, Keras
Depends: R (>= 4.4.0)
NeedsCompilation: no
Packaged: 2026-01-21 12:18:06 UTC; mikasipila
Author: Mika Sipilae [aut, cre, cph] , Claudia Cappello [aut] , Sandra De Iaco [aut] , Klaus Nordhausen [aut] , Sara Taskinen [aut]
Maintainer: Mika Sipilae <mika.e.sipila@jyu.fi>
Repository: CRAN
Date/Publication: 2026-01-26 16:20:38 UTC

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Package selection.index updated to version 1.2.1 with previous version 1.2.0 dated 2023-09-19

Title: Analysis of Selection Index in Plant Breeding
Description: The aim of most plant breeding programmes is simultaneous improvement of several characters. An objective method involving simultaneous selection for several attributes then becomes necessary. It has been recognised that most rapid improvements in the economic value is expected from selection applied simultaneously to all the characters which determine the economic value of a plant, and appropriate assigned weights to each character according to their economic importance, heritability and correlations between characters. So the selection for economic value is a complex matter. If the component characters are combined together into an index in such a way that when selection is applied to the index, as if index is the character to be improved, most rapid improvement of economic value is expected. Such an index was first proposed by Smith (1937 <doi:10.1111/j.1469-1809.1936.tb02143.x>) based on the Fisher's (1936 <doi:10.1111/j.1469-1809.1936.tb02137.x>) "discriminant function [...truncated...]
Author: Zankrut Goyani [aut, cre, cph]
Maintainer: Zankrut Goyani <zankrut20@gmail.com>

Diff between selection.index versions 1.2.0 dated 2023-09-19 and 1.2.1 dated 2026-01-26

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 tests/testthat/test-rcomb.indices.R   |   12 
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 34 files changed, 1838 insertions(+), 1514 deletions(-)

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New package repfun with initial version 0.1.2
Package: repfun
Title: Create Tables, Listings and Figures using Functions Styled after SAS™ Macros
Version: 0.1.2
Description: Mimic the style of traditional reporting macros for clinical trials. The purpose is to generate tables, listings and figures that support clinical research. This package is well suited for firms or individuals who wish to incorporate R without changing their ways of working as it follows a traditional clinical research workflow. Invoke functions (instead of macros) to summarize data and produce formatted reports. This package differs from others in that it includes tools (wrappers) for both analyzing and reporting data.
License: Apache License (== 2.0)
Encoding: UTF-8
Imports: arrow, data.table, glue, jsonlite, rlang, xportr, Hmisc, r2rtf, haven, dplyr, tidyr, magrittr, stringr
Depends: R (>= 3.5)
Suggests: knitr, rmarkdown, testthat (>= 3.0.0), rprojroot, DT, kableExtra, admiral, tibble, lubridate, ggplot2 (>= 3.5.0), devtools, spelling
VignetteBuilder: knitr
LazyData: true
URL: https://gsk-biostatistics.github.io/repfun/, https://github.com/GSK-Biostatistics/repfun
Language: en-US
BugReports: https://github.com/GSK-Biostatistics/repfun/issues
NeedsCompilation: no
Packaged: 2026-01-21 14:14:56 UTC; cr715052
Author: Chris Rook [aut, cre], Yongwei Wang [aut], GlaxoSmithKline Research & Development Limited [cph, fnd]
Maintainer: Chris Rook <cr883296@gmail.com>
Repository: CRAN
Date/Publication: 2026-01-26 16:40:02 UTC

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New package multiRL with initial version 0.2.3
Package: multiRL
Version: 0.2.3
Title: Reinforcement Learning Tools for Multi-Armed Bandit
Description: A flexible general-purpose toolbox for implementing Rescorla-Wagner models in multi-armed bandit tasks. As the successor and functional extension of the 'binaryRL' package, 'multiRL' modularizes the Markov Decision Process (MDP) into six core components. This framework enables users to construct custom models via intuitive if-else syntax and define latent learning rules for agents. For parameter estimation, it provides both likelihood-based inference (MLE and MAP) and simulation-based inference (ABC and RNN), with full support for parallel processing across subjects. The workflow is highly standardized, featuring four main functions that strictly follow the four-step protocol (and ten rules) proposed by Wilson & Collins (2019) <doi:10.7554/eLife.49547>. Beyond the three built-in models (TD, RSTD, and Utility), users can easily derive new variants by declaring which variables are treated as free parameters.
Maintainer: YuKi <hmz1969a@gmail.com>
URL: https://yuki-961004.github.io/multiRL/
BugReports: https://github.com/yuki-961004/multiRL/issues
License: GPL-3
Encoding: UTF-8
LazyData: TRUE
ByteCompile: TRUE
Depends: R (>= 4.1.0)
Imports: methods, utils, Rcpp, compiler, future, doFuture, foreach, doRNG, progressr, ggplot2, scales, grDevices
LinkingTo: Rcpp
Suggests: stats, GenSA, GA, DEoptim, pso, mlrMBO, mlr, ParamHelpers, smoof, lhs, DiceKriging, rgenoud, cmaes, nloptr, abc, tensorflow, keras, reticulate
NeedsCompilation: yes
Packaged: 2026-01-21 08:36:40 UTC; hmz19
Author: YuKi [aut, cre] , Xinyu [aut]
Repository: CRAN
Date/Publication: 2026-01-26 16:20:14 UTC

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New package muiTreeView with initial version 0.1.1
Package: muiTreeView
Title: 'MUI X Tree View' for 'shiny' Apps and 'Quarto'
Version: 0.1.1
Maintainer: Felix Luginbuhl <felix.luginbuhl@protonmail.ch>
Description: Give access to 'MUI X Tree View' components, which lets users navigate hierarchical lists of data with nested levels that can be expanded and collapsed.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: htmltools, shiny.react (>= 0.4.0)
Suggests: shiny, testthat (>= 3.0.0)
URL: https://felixluginbuhl.com/muiTreeView/
BugReports: https://github.com/lgnbhl/muiTreeView/issues
NeedsCompilation: no
Packaged: 2026-01-21 14:19:20 UTC; felix
Author: Felix Luginbuhl [aut, cre]
Repository: CRAN
Date/Publication: 2026-01-26 16:30:02 UTC

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New package muiMaterial with initial version 0.1.2
Package: muiMaterial
Title: 'Material UI' for 'shiny' Apps and 'Quarto'
Version: 0.1.2
Maintainer: Felix Luginbuhl <felix.luginbuhl@protonmail.ch>
Description: A set of user interface components for building 'shiny' applications and 'quarto' documents, including inputs, layouts, navigation, surfaces, and various utilities. All components 'Material UI' from the company 'MUI' <https://mui.com/> are available and all inputs have usage examples in R.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 3.4)
Imports: htmltools, checkmate, shiny, shiny.react (>= 0.4.0)
Suggests: reactRouter, shiny.router, testthat (>= 3.0.0)
URL: https://felixluginbuhl.com/muiMaterial/
BugReports: https://github.com/lgnbhl/muiMaterial/issues
NeedsCompilation: no
Packaged: 2026-01-21 14:17:32 UTC; felix
Author: Felix Luginbuhl [aut, cre, cph]
Repository: CRAN
Date/Publication: 2026-01-26 16:20:21 UTC

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New package kuzco with initial version 0.1.0
Package: kuzco
Title: Computer Vision with Large Language Models
Version: 0.1.0
Description: Make computer vision tasks approachable in R by leveraging Large Language Models. Providing fine-tuned prompts, boilerplate functions, and input/output helpers for common computer vision workflows, such as classifying and describing images. Functions are designed to take images as input and return structured data, helping users build practical applications with minimal code.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: dplyr, ellmer, graphics, gt, gtExtras, imager, jsonlite, magick, ollamar, rlang, stringr, tidyr, utils
Suggests: knitr, quarto, shiny, bslib, rmarkdown, purrr, mirai, tibble, tictoc, httr
VignetteBuilder: quarto, knitr
URL: https://frankiethull.github.io/kuzco/, https://github.com/frankiethull/kuzco
BugReports: https://github.com/frankiethull/kuzco/issues
NeedsCompilation: no
Packaged: 2026-01-21 20:55:30 UTC; frankiethull
Author: Frank Hull [aut, cre, cph], Johannes Breuer [ctb] , Jordi Rosell [ctb]
Maintainer: Frank Hull <frankiethull@gmail.com>
Repository: CRAN
Date/Publication: 2026-01-26 16:50:02 UTC

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Package hann updated to version 1.2 with previous version 1.1 dated 2025-08-20

Title: Hopfield Artificial Neural Networks
Description: Builds and optimizes Hopfield artificial neural networks (Hopfield, 1982, <doi:10.1073/pnas.79.8.2554>). One-layer and three-layer models are implemented. The energy of the Hopfield network is minimized with formula from Krotov and Hopfield (2016, <doi:10.48550/ARXIV.1606.01164>). Optimization (supervised learning) is done through a gradient-based method. Classification is done with S3 methods predict(). Parallelization with 'OpenMP' is used if available during compilation.
Author: Emmanuel Paradis [aut, cre, cph]
Maintainer: Emmanuel Paradis <Emmanuel.Paradis@ird.fr>

Diff between hann versions 1.1 dated 2025-08-20 and 1.2 dated 2026-01-26

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 31 files changed, 341 insertions(+), 215 deletions(-)

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New package glmSTARMA with initial version 1.0.0
Package: glmSTARMA
Title: (Double) Generalized Linear Models for Spatio-Temporal Data
Version: 1.0.0
Date: 2026-01-14
Author: Steffen Maletz [aut, cre] , Konstantinos Fokianos [aut] , Roland Fried [aut] , Valerie Weismann [ctb]
Maintainer: Steffen Maletz <maletz@statistik.tu-dortmund.de>
Description: Fit spatio-temporal models within a (double) generalized linear modelling framework. The package includes functions for estimation, simulation and inference.
URL: https://github.com/stmaletz/glmSTARMA
BugReports: https://github.com/stmaletz/glmSTARMA/issues
Imports: Rcpp (>= 1.0.10), copula, nloptr (>= 1.2.0)
LinkingTo: Rcpp, RcppArmadillo, roptim, nloptr (>= 1.2.0)
Suggests: Matrix, testthat, spdep
Depends: R (>= 4.5.0)
SystemRequirements: C++17
License: GPL (>= 3)
ByteCompile: true
NeedsCompilation: yes
Encoding: UTF-8
Packaged: 2026-01-21 14:59:00 UTC; steffen
Repository: CRAN
Date/Publication: 2026-01-26 16:30:07 UTC

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New package FishDiveR with initial version 1.1.0
Package: FishDiveR
Title: Classify Aquatic Animal Behaviours from Vertical Movement Data
Version: 1.1.0
Maintainer: Calvin Beale <calvin.beale.8@gmail.com>
Description: Quantitatively analyse depth time-series data from pop-up satellite archival tags (PSATs) through the application of continuous wavelet transformation (CWT) combined with Principal Component Analysis (PCA), and k-means clustering. Import, crop, and plot depth time-depth records (TDRs). Using CWT to detect important signals within the non-stationary data, we create daily wavelet statistics to summarise vertical movements on different wavelet periods and combine with daily and diel depth statistics. Classify depth time-series with unsupervised k-means clustering into 24-hour periods of vertical movement behaviour with distinct patterns of vertical movement. Plot example days from each behaviour cluster, and plot the TDR coloured by cluster. Based on principals of combining CWT with k-means first developed by Sakamoto (2009) <doi:10.1371/journal.pone.0005379> and redeveloped by Beale (2026) <doi:10.21203/rs.3.rs-6907076/v1>.
License: GPL (>= 3)
URL: https://github.com/calvinsbeale/FishDiveR
BugReports: https://github.com/calvinsbeale/FishDiveR/issues
Imports: cluster, cowplot, data.table, dplyr, FactoMineR, geometry, ggplot2, gridExtra, lubridate, moments, patchwork, colorspace, rgl, Rfast, rlang, scales, suncalc, tidyr, WaveletComp
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
Depends: R (>= 3.5.0)
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-01-21 15:29:21 UTC; User
Author: Calvin Beale [aut, cre, cph]
Repository: CRAN
Date/Publication: 2026-01-26 16:30:14 UTC

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Package EviewsR updated to version 0.1.7 with previous version 0.1.6 dated 2023-11-28

Title: A Seamless Integration of 'EViews' and R
Description: It allows running 'EViews' (<https://eviews.com>) program from R, R Markdown and Quarto documents. 'EViews' (Econometric Views) is a statistical software for Econometric analysis. This package integrates 'EViews' and R and also serves as an 'EViews' Knit-Engine for 'knitr' package. Write all your 'EViews' commands in R, R Markdown or Quarto documents. For details, please consult our peer-review article Mati S., Civcir I. and Abba S.I (2023) <doi:10.32614/RJ-2023-045>.
Author: Sagiru Mati [aut, cre]
Maintainer: Sagiru Mati <sagirumati@gmail.com>

Diff between EviewsR versions 0.1.6 dated 2023-11-28 and 0.1.7 dated 2026-01-26

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 EviewsR-0.1.7/EviewsR/man/export.Rd                                         |  126 ++---
 EviewsR-0.1.7/EviewsR/man/export_dataframe.Rd                               |  128 ++---
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 EviewsR-0.1.7/EviewsR/man/set_eviews_path.Rd                                |   94 ++--
 EviewsR-0.1.7/EviewsR/tests/testthat.R                                      |    8 
 EviewsR-0.1.7/EviewsR/vignettes/EviewsR.Rmd                                 |   85 +++
 68 files changed, 1754 insertions(+), 1560 deletions(-)

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New package ditwahLandslide with initial version 1.2.0
Package: ditwahLandslide
Title: Early Warning Information on Landslides in Sri Lanka During the Ditwah Storm
Version: 1.2.0
Description: Provides curated early warning data on landslides in Sri Lanka during the Ditwah storm. It includes structured, machine-readable tidy dataset. This is developed for education and research purposes.
License: GPL (>= 3)
Imports: dplyr, ggplot2, lubridate, plotly, stringr, shiny
Encoding: UTF-8
Depends: R (>= 4.1.0)
LazyData: true
NeedsCompilation: no
Packaged: 2026-01-21 16:55:18 UTC; DELL
Author: Thiyanga S. Talagala [aut, cre] , Geethma R. Jayasinghe [aut], Y. M. Amali P. Rajapaksha [aut], N. G. Shehara Minimuthu [aut], Y. G. D. M. Savindya Thathsarani [aut]
Maintainer: Thiyanga S. Talagala <ttalagala@sjp.ac.lk>
Repository: CRAN
Date/Publication: 2026-01-26 16:40:09 UTC

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New package BERTopic with initial version 0.1.0
Package: BERTopic
Title: Topic Modeling with 'BERTopic'
Version: 0.1.0
Description: Interface to the Python package 'BERTopic' <https://maartengr.github.io/BERTopic/index.html> for transformer-based topic modeling. Provides R wrappers to fit BERTopic models, transform new documents, update and reduce topics, extract topic- and document-level information, and generate interactive visualizations. 'Python' backends and dependencies are managed via the 'reticulate' package.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 3.5)
Imports: reticulate, rlang, tibble, utils
Suggests: Matrix, htmltools, testthat (>= 3.1.0)
LazyData: true
URL: https://github.com/Feng-Ji-Lab/BERTopic
BugReports: https://github.com/Feng-Ji-Lab/BERTopic/issues
Language: en-US
NeedsCompilation: no
Packaged: 2026-01-21 18:28:49 UTC; zby15
Author: Biying Zhou [aut, cre]
Maintainer: Biying Zhou <biying.zhou@psu.edu>
Repository: CRAN
Date/Publication: 2026-01-26 16:50:14 UTC

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New package aquacultuR with initial version 1.1.1
Package: aquacultuR
Title: A Comprehensive R Tool for Zootechnical Metrics
Version: 1.1.1
Description: A collection of functions to compute frequently used metrics for nutrition trials in aquaculture. Implementations include metrics to calculate growth, feed conversion, nutrient use efficiency, and feed digestibility. The package supports reproducible workflows for summarising experimental results and reduces manual calculation errors. For additional information see Machado e Silva, Karthikeyan and Tellbüscher (2025) <doi:10.13140/RG.2.2.27322.04808>.
License: GPL (>= 3)
VignetteBuilder: knitr
URL: https://github.com/TellAnAx/aquacultuR
BugReports: https://github.com/TellAnAx/aquacultuR/issues
Encoding: UTF-8
LazyData: true
Imports: dplyr, magrittr
Suggests: knitr, lubridate, tidyr, rmarkdown, testthat (>= 3.0.0)
Depends: R (>= 3.5)
NeedsCompilation: no
Packaged: 2026-01-21 20:10:14 UTC; anil
Author: Anil Axel Tellbuescher [aut, cre, cph] , Davide Machado e Silva [aut] , Simao Correia [aut] , Madhav Karthikeyan [ctb] , Tomas Penka [dtc]
Maintainer: Anil Axel Tellbuescher <atellbuscher@frov.jcu.cz>
Repository: CRAN
Date/Publication: 2026-01-26 16:50:08 UTC

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Package dfms updated to version 1.0.0 with previous version 0.4.0 dated 2026-01-18

Title: Dynamic Factor Models
Description: Efficient estimation of Dynamic Factor Models using the Expectation Maximization (EM) algorithm or Two-Step (2S) estimation, supporting datasets with missing data and mixed-frequency nowcasting applications. Factors follow a stationary VAR process of order p. Estimation options include: running the Kalman Filter and Smoother once with PCA initial values (2S) as in Doz, Giannone and Reichlin (2011) <doi:10.1016/j.jeconom.2011.02.012>; iterated Kalman Filtering and Smoothing until EM convergence as in Doz, Giannone and Reichlin (2012) <doi:10.1162/REST_a_00225>; or the adapted EM algorithm of Banbura and Modugno (2014) <doi:10.1002/jae.2306>, allowing arbitrary missing-data patterns and monthly-quarterly mixed-frequency datasets. The implementation uses the 'Armadillo' 'C++' library and the 'collapse' package for fast estimation. A comprehensive set of methods supports interpretation and visualization, forecasting, and decomposition of the 'news' content of macroeconomi [...truncated...]
Author: Sebastian Krantz [aut, cre], Rytis Bagdziunas [aut], Santtu Tikka [rev], Eli Holmes [rev]
Maintainer: Sebastian Krantz <sebastian.krantz@graduateinstitute.ch>

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Package tesseract updated to version 5.2.5 with previous version 5.2.4 dated 2025-12-29

Title: Open Source OCR Engine
Description: Bindings to 'Tesseract': a powerful optical character recognition (OCR) engine that supports over 100 languages. The engine is highly configurable in order to tune the detection algorithms and obtain the best possible results.
Author: Jeroen Ooms [aut, cre]
Maintainer: Jeroen Ooms <jeroenooms@gmail.com>

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Package sumup updated to version 1.0.1 with previous version 1.0.0 dated 2025-10-23

Title: Utilizing Automated Text Analysis to Support Interpretation of Narrative Feedback
Description: Combine topic modeling and sentiment analysis to identify individual students' gaps, and highlight their strengths and weaknesses across predefined competency domains and professional activities.
Author: Joyce Moonen - van Loon [aut, cre]
Maintainer: Joyce Moonen - van Loon <j.moonen@maastrichtuniversity.nl>

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Package rUM updated to version 2.3.0 with previous version 2.2.0 dated 2025-07-23

Title: R Templates from the University of Miami
Description: This holds r markdown and quarto templates for academic papers and slide decks. It also has templates to create research projects which contain academic papers as vignettes.
Author: Raymond Balise [aut, cre] , Gabriel Odom [aut] , Kyle Grealis [aut] , Francisco Cardozo [aut] , Frank Gutierrez [ctb]
Maintainer: Raymond Balise <balise@miami.edu>

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Package rsatscan updated to version 1.0.10 with previous version 1.0.9 dated 2025-04-08

Title: Tools for Running the External 'SaTScan' Software using R Classes and Methods
Description: The 'SaTScan'(TM) <https://www.satscan.org> software uses spatial and space-time scan statistics to detect and evaluate spatial and space-time clusters. With the 'rsatscan' package, you can run the external 'SaTScan' software from within R using R data formats. To successfully select appropriate parameter settings within 'rsatscan', you must first learn 'SaTScan'.
Author: Ken Kleinman [aut], Scott Hostovich [cre], Amer Moosa [ctb]
Maintainer: Scott Hostovich <HostovichS@imsweb.com>

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Package bartXViz updated to version 1.0.11 with previous version 1.0.9 dated 2025-12-21

Title: Visualization of BART and BARP using SHAP
Description: Complex machine learning models are often difficult to interpret. Shapley values serve as a powerful tool to understand and explain why a model makes a particular prediction. This package computes variable contributions using permutation-based Shapley values for Bayesian Additive Regression Trees (BART) and its extension with Post-Stratification (BARP). The permutation-based SHAP method proposed by Strumbel and Kononenko (2014) <doi:10.1007/s10115-013-0679-x> is grounded in data obtained via MCMC sampling. Similar to the BART model introduced by Chipman, George, and McCulloch (2010) <doi:10.1214/09-AOAS285>, this package leverages Bayesian posterior samples generated during model estimation, allowing variable contributions to be computed without requiring additional sampling. The BART model is designed to work with the following R packages: 'BART' <doi:10.18637/jss.v097.i01>, 'bartMachine' <doi:10.18637/jss.v070.i04>, and 'dbarts' <https://CRAN.R-project.org/ [...truncated...]
Author: Dong-eun Lee [aut, cre], Eun-Kyung Lee [aut]
Maintainer: Dong-eun Lee <ldongeun.leel@gmail.com>

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Package VennItem updated to version 1.1.0 with previous version 1.0.0 dated 2026-01-19

Title: Generate Venn Diagrams with Items Listed in the Sections
Description: Generate Venn diagrams from two or three sets, displaying the overlapping items as lists in the appropriate sections. The lists can be split into columns or shortened for large sets and the plot is generated using 'ggplot2' allowing further customisations.
Author: Matthew Jackson-Wood [aut, cre]
Maintainer: Matthew Jackson-Wood <mattjackson4@gmail.com>

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Package dawai updated to version 1.2.8 with previous version 1.2.7 dated 2024-10-15

Title: Discriminant Analysis with Additional Information
Description: In applications it is usual that some additional information is available. This package dawai (an acronym for Discriminant Analysis With Additional Information) performs linear and quadratic discriminant analysis with additional information expressed as inequality restrictions among the populations means. It also computes several estimations of the true error rate.
Author: David Conde [aut, cre], Miguel A. Fernandez [aut], Bonifacio Salvador [aut]
Maintainer: David Conde <daconrio@gmail.com>

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Package cogmapr updated to version 0.9.5 with previous version 0.9.3 dated 2022-01-04

Title: Cognitive Mapping Tools Based on Coding of Textual Sources
Description: Functions for building cognitive maps based on qualitative data. Inputs are textual sources (articles, transcription of qualitative interviews of agents,...). These sources have been coded using relations and are linked to (i) a table describing the variables (or concepts) used for the coding and (ii) a table describing the sources (typology of agents, ...). Main outputs are Individual Cognitive Maps (ICM), Social Cognitive Maps (all sources or group of sources) and a list of quotes linked to relations. This package is linked to the work done during the PhD of Frederic M. Vanwindekens (CRA-W / UCL) hold the 13 of May 2014 at University of Louvain in collaboration with the Walloon Agricultural Research Centre (project MIMOSA, MOERMAN fund).
Author: Frederic M. Vanwindekens [aut, cre] , Didier Stilmant [aut, ths], Philippe V. Baret [aut, ths]
Maintainer: Frederic M. Vanwindekens <FrdVnW@proton.me>

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Package CAST updated to version 1.0.4 with previous version 1.0.3 dated 2025-01-09

Title: 'caret' Applications for Spatial-Temporal Models
Description: Supporting functionality to run 'caret' with spatial or spatial-temporal data. 'caret' is a frequently used package for model training and prediction using machine learning. CAST includes functions to improve spatial or spatial-temporal modelling tasks using 'caret'. It includes the newly suggested 'Nearest neighbor distance matching' cross-validation to estimate the performance of spatial prediction models and allows for spatial variable selection to selects suitable predictor variables in view to their contribution to the spatial model performance. CAST further includes functionality to estimate the (spatial) area of applicability of prediction models. Methods are described in Meyer et al. (2018) <doi:10.1016/j.envsoft.2017.12.001>; Meyer et al. (2019) <doi:10.1016/j.ecolmodel.2019.108815>; Meyer and Pebesma (2021) <doi:10.1111/2041-210X.13650>; Milà et al. (2022) <doi:10.1111/2041-210X.13851>; Meyer and Pebesma (2022) <doi:10.1038/s41467-022-29838-9>; L [...truncated...]
Author: Hanna Meyer [cre, aut], Carles Mila [aut], Marvin Ludwig [aut], Jan Linnenbrink [aut], Fabian Schumacher [aut], Philipp Otto [ctb], Chris Reudenbach [ctb], Thomas Nauss [ctb], Edzer Pebesma [ctb], Jakub Nowosad [ctb]
Maintainer: Hanna Meyer <hanna.meyer@uni-muenster.de>

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Package biomod2 updated to version 4.3-4-4 with previous version 4.3-4-3 dated 2025-12-22

Title: Ensemble Platform for Species Distribution Modeling
Description: Functions for species distribution modeling, calibration and evaluation, ensemble of models, ensemble forecasting and visualization. The package permits to run consistently up to 10 single models on a presence/absences (resp presences/pseudo-absences) dataset and to combine them in ensemble models and ensemble projections. Some bench of other evaluation and visualisation tools are also available within the package.
Author: Maya Gueguen [aut, cre], Helene Blancheteau [aut], Remi Lemaire-Patin [aut], Wilfried Thuiller [aut]
Maintainer: Maya Gueguen <maya.gueguen@univ-grenoble-alpes.fr>

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Package ONAM updated to version 1.0.1 with previous version 1.0.0 dated 2025-11-11

Title: Fitting Interpretable Neural Additive Models Using Orthogonalization
Description: An algorithm for fitting interpretable additive neural networks for identifiable and visualizable feature effects using post hoc orthogonalization. Fit custom neural networks intuitively using established 'R' 'formula' notation, including interaction effects of arbitrary order while preserving identifiability to enable a functional decomposition of the prediction function. For more details see Koehler et al. (2025) <doi:10.1038/s44387-025-00033-7>.
Author: David Koehler [aut, cre]
Maintainer: David Koehler <koehler@imbie.uni-bonn.de>

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Package manureshed updated to version 0.1.1 with previous version 0.1.0 dated 2025-12-22

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 injurytools updated to version 2.0.1 with previous version 2.0.0 dated 2025-11-28

Title: A Toolkit for Sports Injury and Illness Data Analysis
Description: Sports Injury Data analysis aims to identify and describe the magnitude of the injury problem, and to gain more insights (e.g. determine potential risk factors) by statistical modelling approaches. The 'injurytools' package provides standardized routines and utilities that simplify such analyses. It offers functions for data preparation, informative visualizations and descriptive and model-based analyses.
Author: Lore Zumeta Olaskoaga [aut, cre] , Dae-Jin Lee [ctb]
Maintainer: Lore Zumeta Olaskoaga <lorezumeta@gmail.com>

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Package geoBayes updated to version 0.7.5 with previous version 0.7.4 dated 2024-10-07

Title: Analysis of Geostatistical Data using Bayes and Empirical Bayes Methods
Description: Functions to fit geostatistical data. The data can be continuous, binary or count data and the models implemented are flexible. Conjugate priors are assumed on some parameters while inference on the other parameters can be done through a full Bayesian analysis of by empirical Bayes methods.
Author: Evangelos Evangelou [aut, cre], Vivekananda Roy [aut]
Maintainer: Evangelos Evangelou <e.evangelou@maths.bath.ac.uk>

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Package enmpa updated to version 0.2.3 with previous version 0.2.2 dated 2025-12-14

Title: Ecological Niche Modeling using Presence-Absence Data
Description: A set of tools to perform Ecological Niche Modeling with presence-absence data. It includes algorithms for data partitioning, model fitting, calibration, evaluation, selection, and prediction. Other functions help to explore signals of ecological niche using univariate and multivariate analyses, and model features such as variable response curves and variable importance. Unique characteristics of this package are the ability to exclude models with concave quadratic responses, and the option to clamp model predictions to specific variables. These tools are implemented following principles proposed in Cobos et al., (2022) <doi:10.17161/bi.v17i.15985>, Cobos et al., (2019) <doi:10.7717/peerj.6281>, and Peterson et al., (2008) <doi:10.1016/j.ecolmodel.2007.11.008>.
Author: Luis F. Arias-Giraldo [aut, cre] , Marlon E. Cobos [aut] , A. Townsend Peterson [ctb]
Maintainer: Luis F. Arias-Giraldo <lfarias.giraldo@gmail.com>

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Package recluster updated to version 3.5 with previous version 3.4 dated 2026-01-25

Title: Ordination Methods for the Analysis of Beta-Diversity Indices
Description: The analysis of different aspects of biodiversity requires specific algorithms. For example, in regionalisation analyses, the high frequency of ties and zero values in dissimilarity matrices produced by Beta-diversity turnover produces hierarchical cluster dendrograms whose topology and bootstrap supports are affected by the order of rows in the original matrix. Moreover, visualisation of biogeographical regionalisation can be facilitated by a combination of hierarchical clustering and multi-dimensional scaling. The recluster package provides robust techniques to visualise and analyse patterns of biodiversity and to improve occurrence data for cryptic taxa.
Author: Leonardo Dapporto [aut, cre], Matteo Ramazzotti [aut], Simone Fattorini [aut], Roger Vila [aut], Gerard Talavera [aut], Roger H.L. Dennis [aut]
Maintainer: Leonardo Dapporto <leondap@gmail.com>

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Package invitroTKstats updated to version 0.0.14 with previous version 0.0.13 dated 2025-08-19

Title: In Vitro Toxicokinetic Data Processing and Analysis Pipeline
Description: A set of tools for processing and analyzing in vitro toxicokinetic measurements in a standardized and reproducible pipeline. The package was developed to perform frequentist and Bayesian estimation on a variety of in vitro toxicokinetic measurements including -- but not limited to -- chemical fraction unbound in the presence of plasma (f_up), intrinsic hepatic clearance (Clint, uL/min/million hepatocytes), and membrane permeability for oral absorption (Caco2). The methods provided by the package were described in Wambaugh et al. (2019) <doi:10.1093/toxsci/kfz205>.
Author: John Wambaugh [aut] , Caroline Ring [cre] , Sarah E. Davidson-Fritz [aut] , Lindsay Knupp [ctb], Barbara A. Wetmore [ctb] , Zhao Zhihui [ctb], Chantel Nicolas [ctb] , Anna Kreutz [ctb] , U.S. Federal Government [cph]
Maintainer: Caroline Ring <ring.caroline@epa.gov>

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Package wdpar updated to version 1.3.9 with previous version 1.3.8 dated 2024-10-07

Title: Interface to the World Database on Protected Areas
Description: Fetch and clean data from the World Database on Protected Areas (WDPA) and the World Database on Other Effective Area-Based Conservation Measures (WDOECM). Data is obtained from Protected Planet <https://www.protectedplanet.net/en>. To augment data cleaning procedures, users can install the 'prepr' R package (available at <https://github.com/prioritizr/prepr>). For more information on this package, see Hanson (2022) <doi:10.21105/joss.04594>.
Author: Jeffrey O Hanson [aut, cre]
Maintainer: Jeffrey O Hanson <jeffrey.hanson@uqconnect.edu.au>

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Package DySS readmission to version 1.0.1 with previous version 1.0 dated 2022-07-16

Title: Dynamic Screening Systems
Description: In practice, we will encounter problems where the longitudinal performance of processes needs to be monitored over time. Dynamic screening systems (DySS) are methods that aim to identify and give signals to processes with poor performance as early as possible. This package is designed to implement dynamic screening systems and the related methods. References: Qiu, P. and Xiang, D. (2014) <doi:10.1080/00401706.2013.822423>; Qiu, P. and Xiang, D. (2015) <doi:10.1002/sim.6477>; Li, J. and Qiu, P. (2016) <doi:10.1080/0740817X.2016.1146423>; Li, J. and Qiu, P. (2017) <doi:10.1002/qre.2160>; You, L. and Qiu, P. (2019) <doi:10.1080/00949655.2018.1552273>; Qiu, P., Xia, Z., and You, L. (2020) <doi:10.1080/00401706.2019.1604434>; You, L., Qiu, A., Huang, B., and Qiu, P. (2020) <doi:10.1002/bimj.201900127>; You, L. and Qiu, P. (2021) <doi:10.1080/00224065.2020.1767006>.
Author: Lu You [aut, cre], Peihua Qiu [aut]
Maintainer: Lu You <Lu.You@epi.usf.edu>

This is a re-admission after prior archival of version 1.0 dated 2022-07-16

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Package DLFM readmission to version 0.2.2 with previous version 0.1.4 dated 2025-12-06

Title: Distributed Laplace Factor Model
Description: Distributed estimation method is based on a Laplace factor model to solve the estimates of load and specific variance. The philosophy of the package is described in Guangbao Guo. (2022). <doi:10.1007/s00180-022-01270-z>.
Author: Guangbao Guo [aut, cre], Siqi Liu [aut]
Maintainer: Guangbao Guo <ggb11111111@163.com>

This is a re-admission after prior archival of version 0.1.4 dated 2025-12-06

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Package cycleTrendR updated to version 0.3.0 with previous version 0.2.0 dated 2026-01-22

Title: Adaptive Cycle and Trend Analysis for Irregular Time Series
Description: Provides adaptive trend estimation, cycle detection, Fourier harmonic selection, bootstrap confidence intervals, change-point detection, and rolling-origin forecasting. Supports LOESS (Locally Estimated Scatterplot Smoothing), GAM (Generalized Additive Model), and GAMM (Generalized Additive Mixed Model), and automatically handles irregular sampling using the Lomb-Scargle periodogram. Methods implemented in this package are described in Cleveland et al. (1990) <doi:10.2307/2289548>, Wood (2017) <doi:10.1201/9781315370279>, and Scargle (1982) <doi:10.1086/160554>.
Author: Pietro Piu [aut, cre]
Maintainer: Pietro Piu <pietro.piu.si@gmail.com>

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Package covfefe updated to version 1.0.0 with previous version 0.1.0 dated 2017-06-06

Title: Political Linguistics Toolkit - Gaffes, Phonetics, and Text Transformation
Description: A comprehensive toolkit for political linguistics featuring a museum of famous digital gaffes, phonetic transformation algorithms (Soundex, consonant shifts), QWERTY keyboard geometry for typo simulation, syllable parsing, word blending (portmanteau creation), and text corruption analysis. Originally inspired by the infamous "covfefe" tweet of 2017.
Author: Michael Kirchner [aut, cre]
Maintainer: Michael Kirchner <michael@kirchner.io>

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Package bunchr updated to version 1.2.1 with previous version 1.2.0 dated 2017-01-30

Title: Analyze Bunching in a Kink or Notch Setting
Description: View and analyze data where bunching is expected. Estimate counter- factual distributions. For earnings data, estimate the compensated elasticity of earnings w.r.t. the net-of-tax rate.
Author: Itai Trilnick [aut, cre]
Maintainer: Itai Trilnick <itai.trilnick@gmail.com>

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Package notebookutils updated to version 1.6.2 with previous version 1.5.3 dated 2024-04-07

Title: Dummy R APIs Used in 'Azure Synapse Analytics' for Local Developments
Description: This is a pure dummy interfaces package which mirrors 'MsSparkUtils' APIs <https://learn.microsoft.com/en-us/azure/synapse-analytics/spark/microsoft-spark-utilities?pivots=programming-language-r> of 'Azure Synapse Analytics' <https://learn.microsoft.com/en-us/azure/synapse-analytics/> for R users, customer of Azure Synapse can download this package from CRAN for local development.
Author: runtimeexp [aut, cre], Microsoft [cph]
Maintainer: runtimeexp <runtimeexpdg@microsoft.com>

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More information about notebookutils at CRAN
Permanent link

Package bslib updated to version 0.10.0 with previous version 0.9.0 dated 2025-01-30

Title: Custom 'Bootstrap' 'Sass' Themes for 'shiny' and 'rmarkdown'
Description: Simplifies custom 'CSS' styling of both 'shiny' and 'rmarkdown' via 'Bootstrap' 'Sass'. Supports 'Bootstrap' 3, 4 and 5 as well as their various 'Bootswatch' themes. An interactive widget is also provided for previewing themes in real time.
Author: Carson Sievert [aut, cre] , Joe Cheng [aut], Garrick Aden-Buie [aut] , Posit Software, PBC [cph, fnd], Bootstrap contributors [ctb] , Twitter, Inc [cph] , Javi Aguilar [ctb, cph] , Thomas Park [ctb, cph] , PayPal [ctb, cph]
Maintainer: Carson Sievert <carson@posit.co>

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 276 files changed, 2749 insertions(+), 1527 deletions(-)

More information about bslib at CRAN
Permanent link

Package GDILM.SEIRS (with last version 0.0.5) was removed from CRAN

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

2025-11-02 0.0.5
2025-09-30 0.0.4
2025-01-13 0.0.3
2024-12-07 0.0.2
2024-12-05 0.0.1

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Package mongolstats updated to version 0.1.1 with previous version 0.1.0 dated 2026-01-18

Title: Mongolian 'NSO' 'PXWeb' Data and Boundaries (Tidy Client)
Description: A 'tidyverse'-friendly client for the National Statistics Office of Mongolia 'PXWeb' API <https://data.1212.mn/> with helpers to discover tables, variables, and fetch statistical data. Also includes utilities to retrieve Mongolia administrative boundaries (ADM0-ADM2) as 'sf' objects from open sources for mapping and spatial analysis.
Author: Temuulen Enebish [aut, cre, cph]
Maintainer: Temuulen Enebish <temuulen@gmail.com>

Diff between mongolstats versions 0.1.0 dated 2026-01-18 and 0.1.1 dated 2026-01-26

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 LICENSE                                  |    2 
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Package rSPDE updated to version 2.5.2 with previous version 2.5.1 dated 2025-03-21

Title: Rational Approximations of Fractional Stochastic Partial Differential Equations
Description: Functions that compute rational approximations of fractional elliptic stochastic partial differential equations. The package also contains functions for common statistical usage of these approximations. The main references for rSPDE are Bolin, Simas and Xiong (2023) <doi:10.1080/10618600.2023.2231051> for the covariance-based method and Bolin and Kirchner (2020) <doi:10.1080/10618600.2019.1665537> for the operator-based rational approximation. These can be generated by the citation function in R.
Author: David Bolin [cre, aut], Alexandre Simas [aut], Finn Lindgren [ctb]
Maintainer: David Bolin <davidbolin@gmail.com>

Diff between rSPDE versions 2.5.1 dated 2025-03-21 and 2.5.2 dated 2026-01-26

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More information about rSPDE at CRAN
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Package NHPoisson updated to version 3.4 with previous version 3.3 dated 2020-02-19

Title: Modelling and Validation of Non Homogeneous Poisson Processes
Description: Tools for modelling, ML estimation, validation analysis and simulation of non homogeneous Poisson processes in time.
Author: Ana C. Cebrian [aut, cre]
Maintainer: Ana C. Cebrian <acebrian@unizar.es>

Diff between NHPoisson versions 3.3 dated 2020-02-19 and 3.4 dated 2026-01-26

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Package neldermead updated to version 1.0-13 with previous version 1.0-12 dated 2022-02-01

Title: R Port of the 'Scilab' Neldermead Module
Description: Provides several direct search optimization algorithms based on the simplex method. The provided algorithms are direct search algorithms, i.e. algorithms which do not use the derivative of the cost function. They are based on the update of a simplex. The following algorithms are available: the fixed shape simplex method of Spendley, Hext and Himsworth (unconstrained optimization with a fixed shape simplex, 1962) <doi:10.1080/00401706.1962.10490033>, the variable shape simplex method of Nelder and Mead (unconstrained optimization with a variable shape simplex made, 1965) <doi:10.1093/comjnl/7.4.308>, and Box's complex method (constrained optimization with a variable shape simplex, 1965) <doi: 10.1093/comjnl/8.1.42>.
Author: Sebastien Bihorel [aut, cre], Michael Baudin [cph]
Maintainer: Sebastien Bihorel <sb.pmlab@gmail.com>

Diff between neldermead versions 1.0-12 dated 2022-02-01 and 1.0-13 dated 2026-01-26

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More information about neldermead at CRAN
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Package insight updated to version 1.4.5 with previous version 1.4.4 dated 2025-12-06

Title: Easy Access to Model Information for Various Model Objects
Description: A tool to provide an easy, intuitive and consistent access to information contained in various R models, like model formulas, model terms, information about random effects, data that was used to fit the model or data from response variables. 'insight' mainly revolves around two types of functions: Functions that find (the names of) information, starting with 'find_', and functions that get the underlying data, starting with 'get_'. The package has a consistent syntax and works with many different model objects, where otherwise functions to access these information are missing.
Author: Daniel Luedecke [aut, cre] , Dominique Makowski [aut, ctb] , Indrajeet Patil [aut, ctb] , Philip Waggoner [aut, ctb] , Mattan S. Ben-Shachar [aut, ctb] , Brenton M. Wiernik [aut, ctb] , Vincent Arel-Bundock [aut, ctb] , Etienne Bacher [aut, ctb] , Ale [...truncated...]
Maintainer: Daniel Luedecke <officialeasystats@gmail.com>

Diff between insight versions 1.4.4 dated 2025-12-06 and 1.4.5 dated 2026-01-26

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More information about insight at CRAN
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Package ijtiff updated to version 3.2.0 with previous version 3.1.3 dated 2025-04-05

Title: Comprehensive TIFF I/O with Full Support for 'ImageJ' TIFF Files
Description: General purpose TIFF file I/O for R users. Currently the only such package with read and write support for TIFF files with floating point (real-numbered) pixels, and the only package that can correctly import TIFF files that were saved from 'ImageJ' and write TIFF files than can be correctly read by 'ImageJ' <https://imagej.net/ij/>. Also supports text image I/O.
Author: Rory Nolan [aut, cre] , Kent Johnson [aut], Simon Urbanek [ctb], Sergi Padilla-Parra [ths] , Jeroen Ooms [rev, ctb] , Jon Clayden [rev]
Maintainer: Rory Nolan <rorynoolan@gmail.com>

Diff between ijtiff versions 3.1.3 dated 2025-04-05 and 3.2.0 dated 2026-01-26

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