Thu, 28 May 2026

Package QUALYPSO updated to version 3.1 with previous version 3.0 dated 2026-05-12

Title: Partitioning Uncertainty Components of an Incomplete Ensemble of Climate Projections
Description: These functions apply an analysis of variance to incomplete ensembles of climate projections. It provides estimates of climate change responses of all simulation chains and of all uncertainty variables. It has been applied to different ensembles of projections simulated to study the impact of climate change: for climate indicators in Evin et al. (2019) <doi:10.1175/JCLI-D-18-0606.1>; seasonal precipitation and temperature in Evin, Somot and Hingray (2021) <doi:10.5194/esd-12-1543-2021>; hydrological variables in Evin et al. (2026) <doi:10.5194/hess-30-1023-2026>; photovoltaic energy in Bichet et al. (2019) <doi:10.1088/1748-9326/ab500a>.
Author: Guillaume Evin [aut, cre]
Maintainer: Guillaume Evin <guillaume.evin@inrae.fr>

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More information about QUALYPSO at CRAN
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Package h3sdm updated to version 0.1.3 with previous version 0.1.2 dated 2026-05-22

Title: Species Distribution Modeling with H3 Grids
Description: Provides tools for species distribution modeling using H3 hexagonal grids (Uber Technologies Inc., 2022, <https://h3geo.org>). Facilitates retrieval of species occurrence records, generation of H3 grids, computation of landscape metrics, and preparation of spatial data for modern species distribution models workflows. Designed for biodiversity and landscape ecology research.
Author: Manuel Spinola [aut, cre]
Maintainer: Manuel Spinola <mspinola10@gmail.com>

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Package fechner readmission to version 1.0-4 with previous version 1.0-3 dated 2016-06-06

Title: Fechnerian Scaling of Discrete Object Sets
Description: Functions and example datasets for Fechnerian scaling of discrete object sets. User can compute Fechnerian distances among objects representing subjective dissimilarities, and other related information. See package?fechner for an overview.
Author: Ali Uenlue [aut, cre], Thomas Kiefer [aut, trl]
Maintainer: Ali Uenlue <aligalibuenlue@gmail.com>

This is a re-admission after prior archival of version 1.0-3 dated 2016-06-06

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Package corteza updated to version 0.6.9 with previous version 0.6.3 dated 2026-05-04

Title: AI Agent Runtime
Description: An agent runtime that gives Large Language Models (LLMs) from 'Anthropic' <https://www.anthropic.com/>, 'OpenAI' <https://openai.com/>, 'Moonshot' <https://www.moonshot.ai/>, and 'Ollama' <https://ollama.com/> direct access to a live R session with managed workspace state. Tools execute as R function calls with provenance tracking, and a deterministic retrieval system keeps relevant objects in context across turns. Three entry points: a shell command-line interface (CLI), a console read-eval-print-loop via chat(), and a Model Context Protocol (MCP) server via serve() for external clients.
Author: Troy Hernandez [aut, cre] , Grant McDermott [ctb] , Jorge Krzyzaniak [ctb], cornball.ai [cph]
Maintainer: Troy Hernandez <troy@cornball.ai>

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Package tidyactuarial updated to version 0.1.3 with previous version 0.1.2 dated 2026-05-17

Title: Tidy Tools for Actuarial Mathematics and Life Contingencies
Description: Provides tidyverse-aligned tools for actuarial mathematics and life contingencies, including life tables, survival probabilities, actuarial present values of cash flows, life annuities, life insurance, premiums, reserves, multiple-life calculations, Monte Carlo simulation, and deterministic cash-flow diagrams. The package emphasizes clear actuarial notation, reproducible workflows, and pipe-friendly tools for actuarial education and applied actuarial analysis.
Author: Julian Fajardo [aut, cre]
Maintainer: Julian Fajardo <julian.fajardo1908@gmail.com>

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Package resevol updated to version 0.4.0.4 with previous version 0.4.0.2 dated 2025-05-01

Title: Simulate Agricultural Production and Evolution of Pesticide Resistance
Description: Simulates individual-based models of agricultural pest management and the evolution of pesticide resistance. Management occurs on a spatially explicit landscape that is divided into an arbitrary number of farms that can grow one of up to 10 crops and apply one of up to 10 pesticides. Pest genomes are modelled in a way that allows for any number of pest traits with an arbitrary covariance structure that is constructed using an evolutionary algorithm in the mine_gmatrix() function. Simulations are then run using the run_farm_sim() function. This package thereby allows for highly mechanistic social-ecological models of the evolution of pesticide resistance under different types of crop rotation and pesticide application regimes.
Author: A. Bradley Duthie [aut, cre] , Rose McKeon [aut, ctr], Rosie Mangan [ctr], Luc Bussi&eacute;re [ctr], Matthew Tinsley [ctr]
Maintainer: A. Bradley Duthie <brad.duthie@gmail.com>

Diff between resevol versions 0.4.0.2 dated 2025-05-01 and 0.4.0.4 dated 2026-05-28

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New package evacpath with initial version 0.1.0
Package: evacpath
Title: Least-Cost Pedestrian Evacuation Modeling
Version: 0.1.0
Description: Tools for road-constrained, least-cost pedestrian evacuation modeling. The package provides reusable functions for preparing hazard zones, generating road-based evacuation origin points, identifying escape/safety points, creating slope-based conductance surfaces, calculating least-cost distance to safety, and converting distance outputs into evacuation-time polygons. It is designed to support workflows like tsunami evacuation modeling while remaining adaptable to other regions and hazards. Tsunami-specific helpers support separate land-only hazard zones, water-combined escape zones, road-aware escape boundaries, and study-area inset cropping for quality assurance and quality control. Methods build on Cordero et al. (2025) <doi:10.1007/s44367-025-00018-y>, Lewis (2021) <doi:10.1007/s10816-021-09522-w>, and Joseph Lewis's 'leastcostpath' package (2023) <https://CRAN.R-project.org/package=leastcostpath>.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1)
Imports: terra, leastcostpath, utils
Suggests: knitr, rmarkdown, testthat (>= 3.0.0), devtools, fields
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-05-22 17:19:23 UTC; ec
Author: Elvin Cordero [aut, cre]
Maintainer: Elvin Cordero <elvin.cordero1@upr.edu>
Repository: CRAN
Date/Publication: 2026-05-28 18:50:02 UTC

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New package Dcurvature with initial version 0.0.3
Package: Dcurvature
Title: Discrete Curvature with 'shiny' Explorer
Version: 0.0.3
Description: Implements discrete curvature estimation for ordered planar point sequences using circumcenter geometry on consecutive triplets, exposed through compiled C plus plus (C++) code via 'Rcpp' for speed and numerical robustness. The package is useful for objective elbow detection in multivariate workflows, especially principal component analysis (PCA), where selecting the number of retained components can be subjective. It provides a 'shiny' interface that supports upload of raw datasets or explained-variance tables, computes Kaiser-Meyer-Olkin (KMO) sampling-adequacy diagnostics, evaluates individual and cumulative variance curves, and reports curvature- based decision rules (m* and m**) with visual summaries for reproducible component-selection decisions. References: Arney et al. (2001); Axler (2024) <doi:10.1007/978-3-031-41026-0>; Bjorklund (2019) <doi:10.1111/evo.13835>; Burden and Faires (2015); Chang et al. (2023) <https://CRAN.R-project.org/package=shiny>; Christen [...truncated...]
License: MIT + file LICENSE
Encoding: UTF-8
Imports: Rcpp, shiny, readxl
Suggests: ggplot2, psych, testthat (>= 3.0.0)
LinkingTo: Rcpp
NeedsCompilation: yes
Packaged: 2026-05-22 21:00:55 UTC; jorgeandresjolahernandez
Author: Aquiles Darghan [aut], Jorge Jola [aut, cre]
Maintainer: Jorge Jola <jjolaher@purdue.edu>
Repository: CRAN
Date/Publication: 2026-05-28 19:00:02 UTC

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Package crystract updated to version 1.0.1 with previous version 1.0.0 dated 2026-03-20

Title: Crystallographic Information File (CIF) Data Processing Tools
Description: Provides a suite of functions to parse Crystallographic Information Files (.cif), extracting essential data such as chemical formulas, unit cell parameters, atomic coordinates, and symmetry operations. It also includes tools to calculate interatomic distances, identify bonded pairs using various algorithms (minimum_distance, brunner_nn_reciprocal, econ_nn, crystal_nn), determine nearest neighbor counts, and calculate bond angles. The package is designed to facilitate the preparation of crystallographic data for further analysis, including machine learning applications in materials science. Methods are described in: Brunner (1977) <doi:10.1107/S0567739477000461>; Hoppe (1979) <doi:10.1524/zkri.1979.150.14.23>; O'Keeffe (1979) <doi:10.1107/S0567739479001765>; Shannon (1976) <doi:10.1107/S0567739476001551>; Pan et al. (2021) <doi:10.1021/acs.inorgchem.0c02996>; Pauling (1960, ISBN:978-0801403330).
Author: Don Ngo [aut, cre] , Anirudh Prabhu [aut] , Julia-Maria Hubner [aut]
Maintainer: Don Ngo <dngo@carnegiescience.edu>

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New package CKNNRLD with initial version 0.1.2
Package: CKNNRLD
Title: Clustering-Based K-Nearest Neighbor Regression for Longitudinal Data
Version: 0.1.2
Description: Implements the 'CKNNRLD' algorithm (Clustering-Based K-Nearest Neighbor Regression for Longitudinal Data) for improving K-Nearest Neighbor ('KNN') regression on longitudinal data through cluster-based partitioning and localized prediction. Offers enhanced computational efficiency and accuracy for high-volume longitudinal datasets. The clustering is performed using the 'latrend' package, which provides a unified interface for various longitudinal clustering methods including 'KML' (K-Means for Longitudinal data). The acronym 'KNN' stands for K-Nearest Neighbor. The acronym 'KML' stands for K-Means for Longitudinal data. References: Loeloe MS, Tabatabaei SM, Sefidkar R, Mehrparvar AH, Jambarsang S (2025). "Boosting K-nearest neighbor regression performance for longitudinal data through a novel learning approach." BMC Bioinformatics, 26, 232. <doi:10.1186/s12859-025-06205-1>; Genolini C, Falissard B (2010). "KmL: k-means for longitudinal data." Computational Statistics, 25(2), 317-3 [...truncated...]
License: GPL-3
Encoding: UTF-8
Imports: Directional, graphics, Rfast, latrend
Depends: R (>= 3.5.0)
NeedsCompilation: no
Language: en-US
Packaged: 2026-05-20 19:59:55 UTC; sadegh-pc
Author: Mohammad Sadegh Loeloe [aut, cre], Seyyed Mohammad Tabatabaei [aut], Reyhane Sefidkar [aut], Amir Houshang Mehrparvar [aut], Sara Jambarsang [aut, ths]
Maintainer: Mohammad Sadegh Loeloe <mslbiostat@gmail.com>
Repository: CRAN
Date/Publication: 2026-05-28 18:40:02 UTC

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Package lakhesis updated to version 1.1.2 with previous version 1.1 dated 2026-04-25

Title: Consensus Seriation for Binary Data
Description: Determining consensus seriations for binary incidence matrices, using a two-step process of Procrustes-fit correspondence analysis for heuristic selection of partial seriations and iterative regression to establish a single consensus. Contains the Lakhesis Calculator, a graphical platform for identifying seriated sequences. Collins-Elliott (2026) "Lakhesis: Consensus Seriation via Iterative Regression of Partial Rankings for Binary Data" <doi:10.1080/02664763.2026.2672564>.
Author: Stephen A. Collins-Elliott [aut, cre]
Maintainer: Stephen A. Collins-Elliott <sce@utk.edu>

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Package zarr updated to version 0.4.0 with previous version 0.3.0 dated 2026-04-18

Title: Native and Extensible R Driver for 'Zarr'
Description: The 'Zarr' specification is widely used to build libraries for the storage and retrieval of n-dimensional array data from data stores ranging from local file systems to the cloud. This package is a native 'Zarr' implementation in R with support for all required features of 'Zarr' version 3. It is designed to be extensible such that new stores, codecs and extensions can be added easily.
Author: Patrick Van Laake [aut, cre, cph]
Maintainer: Patrick Van Laake <patrick@vanlaake.net>

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Package BATSS updated to version 1.2.0 with previous version 1.1.1 dated 2025-10-02

Title: Bayesian Adaptive Trial Simulator Software (BATSS) for Generalised Linear Models
Description: Defines operating characteristics of Bayesian Adaptive Trials considering a generalised linear model response via Monte Carlo simulations of Bayesian GLM fitted via integrated Laplace approximations (INLA).
Author: Dominique-Laurent Couturier [aut, cre] , Liz Ryan [aut] , Rainer Puhr [aut], Thomas Jaki [aut] , Stephane Heritier [aut]
Maintainer: Dominique-Laurent Couturier <dominique.couturier@mrc-bsu.cam.ac.uk>

Diff between BATSS versions 1.1.1 dated 2025-10-02 and 1.2.0 dated 2026-05-28

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Package spray updated to version 1.1-1 with previous version 1.0-27 dated 2025-01-29

Title: Sparse Arrays and Multivariate Polynomials
Description: Sparse arrays interpreted as multivariate polynomials. Uses 'disordR' discipline (Hankin, 2022, <doi:10.48550/ARXIV.2210.03856>). To cite the package in publications please use Hankin (2022) <doi:10.48550/ARXIV.2210.10848>.
Author: Robin K. S. Hankin [aut, cre]
Maintainer: Robin K. S. Hankin <hankin.robin@gmail.com>

Diff between spray versions 1.0-27 dated 2025-01-29 and 1.1-1 dated 2026-05-28

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Package pharmr updated to version 2.1.1 with previous version 2.1.0 dated 2026-05-11

Title: Interface to the 'Pharmpy' 'Pharmacometrics' Library
Description: Interface to the 'Pharmpy' 'pharmacometrics' library. The 'Reticulate' package is used to interface Python from R.
Author: Rikard Nordgren [aut, cre, cph], Stella Belin [aut, cph], Mats O. Karlsson [sad], Andrew C. Hooker [sad], Xiaomei Chen [sad], Sebastian Ueckert [sad] , Simon Buatois [rev], Joao A. Abrantes [rev], Emilie Schindler [rev], F. Hoffmann-La Roche Ltd. [fn [...truncated...]
Maintainer: Rikard Nordgren <rikard.nordgren@uu.se>

Diff between pharmr versions 2.1.0 dated 2026-05-11 and 2.1.1 dated 2026-05-28

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Package nestedLogit updated to version 0.4.2 with previous version 0.4.0 dated 2026-03-06

Title: Nested Dichotomy Logistic Regression Models
Description: Provides functions for specifying and fitting nested dichotomy logistic regression models for a multi-category response and methods for summarising and plotting those models. Nested dichotomies are statistically independent, and hence provide an additive decomposition of tests for the overall 'polytomous' response. When the dichotomies make sense substantively, this method can be a simpler alternative to the standard 'multinomial' logistic model which compares response categories to a reference level. See: J. Fox (2016), "Applied Regression Analysis and Generalized Linear Models", 3rd Ed., ISBN 1452205663.
Author: John Fox [aut] , Michael Friendly [aut, cre] , Achim Zeileis [ctb]
Maintainer: Michael Friendly <friendly@yorku.ca>

Diff between nestedLogit versions 0.4.0 dated 2026-03-06 and 0.4.2 dated 2026-05-28

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Package keypress updated to version 1.3.2 with previous version 1.3.1 dated 2023-12-10

Title: Wait for a Key Press in a Terminal
Description: Wait for a single key press at the 'R' prompt. This works in terminals, but does not currently work in the 'Windows' 'GUI', the 'macOS' 'GUI' ('R.app'), in 'Emacs' 'ESS', in an 'Emacs' shell buffer or in 'R Studio'. In these cases 'keypress' stops with an error message.
Author: Gabor Csardi [aut, cre, cph] , Jon Griffiths [aut], Posit Software, PBC [cph, fnd]
Maintainer: Gabor Csardi <csardi.gabor@gmail.com>

Diff between keypress versions 1.3.1 dated 2023-12-10 and 1.3.2 dated 2026-05-28

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Package CDGHMM updated to version 0.1.4 with previous version 0.1.3 dated 2026-05-27

Title: Hidden Markov Models for Multivariate Panel Data
Description: Estimates hidden Markov models from the family of Cholesky-decomposed Gaussian hidden Markov models (CDGHMM) under various missingness schemes. This family improves upon estimation of traditional Gaussian HMMs by introducing parsimony, as well as, controlling for dropped out observations and non-random missingness. See Neal, Sochaniwsky and McNicholas (2024) <DOI:10.1007/s11222-024-10462-0>.
Author: Mackenzie R. Neal [aut, cre] , Alexa A. Sochaniwsky [aut], Paul D. McNicholas [aut]
Maintainer: Mackenzie R. Neal <nealm6@mcmaster.ca>

Diff between CDGHMM versions 0.1.3 dated 2026-05-27 and 0.1.4 dated 2026-05-28

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Package AutoDeskR updated to version 0.5.0 with previous version 0.1.5 dated 2024-09-10

Title: An Interface to the 'AutoDesk' 'API' Platform
Description: An interface to the 'AutoDesk' Platform Services ('APS') 'API' including the Authentication 'API' for obtaining 'OAuth2' tokens with expiry tracking, Data Management 'API' for managing buckets and objects across the platform's cloud services, Design Automation 'API' for running automated tasks on design files in the cloud, Model Derivative 'API' for translating design files into 'SVF', 'SVF2', 'OBJ', and 'STL' formats and extracting model data, Reality Capture 'API' for generating 3D models from photogrammetry image sets, and Viewer for rendering 2D and 3D models in 'Shiny' applications.
Author: Paul Govan [aut, cre, cph]
Maintainer: Paul Govan <paul.govan2@gmail.com>

Diff between AutoDeskR versions 0.1.5 dated 2024-09-10 and 0.5.0 dated 2026-05-28

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New package SSReliabilityClaytonMWD with initial version 1.0.2
Package: SSReliabilityClaytonMWD
Title: Stress-Strength Reliability Model with MWD Marginals via Clayton Copula
Version: 1.0.2
Description: Implements stress-strength reliability models under a dependent framework, where both stress and strength variables follow modified Weibull distributions and their dependence is modeled using a Clayton copula (Kizilaslan (2026) <doi:10.48550/arXiv.2604.12130>). The package provides several estimation procedures for model parameters and the stress-strength reliability R, including two-step maximum likelihood estimation (MLE), least squares estimation (LSE), weighted least squares estimation (WLSE), and maximum product of spacings (MPS). It also provides interval estimation using asymptotic confidence intervals based on MLE and bootstrap confidence intervals for all methods. In addition, functions are included for parameter estimation of the modified Weibull distribution (Lai et al. (2003) <doi:10.1109/TR.2002.805788>) and the two-parameter Weibull distribution, along with utilities to compute their probability density function, cumulative distribution function, quantile func [...truncated...]
Maintainer: Fatih Kizilaslan <fkizilaslan@yahoo.com>
Copyright: 2026 Fatih Kizilaslan
URL: https://github.com/fatihki/SSReliabilityClaytonMWD, https://fatihki.github.io/SSReliabilityClaytonMWD/
BugReports: https://github.com/fatihki/SSReliabilityClaytonMWD/issues
License: GPL (>= 3)
Depends: R (>= 4.1.0)
Encoding: UTF-8
LazyData: true
Imports: doRNG, knitr, stats
Suggests: rmarkdown, numDeriv, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-05-22 11:42:16 UTC; fatihkizilaslan
Author: Fatih Kizilaslan [aut, cre]
Repository: CRAN
Date/Publication: 2026-05-28 13:40:13 UTC

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New package rwetools with initial version 0.1.2
Package: rwetools
Title: Estimating Propensity Scores (PS), PS-Based Weights, and Effects
Version: 0.1.2
Description: Toolbox that provides a streamlined, end-to-end workflow for propensity score analysis in generating real-world evidence from real-world data. The package covers the full analytic pipeline - from estimating propensity scores via logistic regression, to calculating weights or creating a matched cohort, to generating publication-ready Table 1s with standardized mean differences and weighted balance diagnostics. It also estimates incidence rates, hazard ratios, risk ratios, and risk differences with support for stratified and direct-standardized analyses. All core functions produce formatted 'Excel' reports with embedded 'README' documentation, making results immediately shareable with collaborators and stakeholders. Methods are based on Rosenbaum and Rubin (1983) <doi:10.1093/biomet/70.1.41>, Austin (2011) <doi:10.1080/00273171.2011.568786>, and Desai et al. (2017) <doi:10.1097/EDE.0000000000000595>.
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-US
Imports: stats, utils, parallel, survival, survey
Suggests: openxlsx, ggplot2, MatchIt, testthat (>= 3.0.0)
URL: https://github.com/hanseul0618/rwetools
NeedsCompilation: no
Packaged: 2026-05-22 02:23:19 UTC; hanse
Author: Hanseul Cho [aut, cre], Georg Hahn [aut], Janinne Ortega-Montiel [aut], Julie Paik [aut], Elisabetta Patorno [aut]
Maintainer: Hanseul Cho <hanseul0618@gmail.com>
Repository: CRAN
Date/Publication: 2026-05-28 13:30:02 UTC

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New package remverse with initial version 0.1.0
Package: remverse
Title: A Meta-Package for Relational Event History Analysis
Version: 0.1.0
Maintainer: Joris Mulder <j.mulder3@tilburguniversity.edu>
Description: A unified workflow for relational event modeling by re-exporting core functions from 'remify', 'remstats', and 'remstimate'. Supports tie-oriented and actor-oriented modeling with frequentist and Bayesian estimation. Methods are described in Butts (2008) <doi:10.1111/j.1467-9531.2008.00203.x> and Stadtfeld and Block (2017) <doi:10.1177/0081175017709295>.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.0), remify (>= 4.0.0), remstats (>= 4.0.0), remstimate (>= 3.0.0)
Suggests: knitr, rmarkdown
LazyData: true
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-05-22 09:21:07 UTC; jorismulder
Author: Joris Mulder [aut, cre], Giuseppe Arena [aut], Roger Leenders [aut], Marlyne Meijerink-Bosman [aut], Rumana Lakdawala [aut], Fabio Generoso Vieira [aut], Mahdi Shafiee Kamalabad [ctb], Diana Karimova [ctb]
Repository: CRAN
Date/Publication: 2026-05-28 13:30:08 UTC

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New package remdata with initial version 0.2.0
Package: remdata
Title: A Collection of Empirical and Simulated Relational Event Data Sequences
Version: 0.2.0
Description: Empirical and simulated data for relational event analyses. Each dataset consists of a relational event sequence and optional actor attributes. Individual datasets are redistributed under their original licenses as documented in inst/DATA_LICENSES.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Depends: R (>= 4.0.0)
LazyDataCompression: xz
NeedsCompilation: no
Packaged: 2026-05-22 09:37:57 UTC; jorismulder
Author: Joris Mulder [aut, cre], Roger Leenders [aut], Diana Karimova [aut], Marlyne Meijerink-Bosman [aut], Giuseppe Arena [aut], Rumana Lakdawala [aut], Mahdi Shafiee Kamalabad [ctb], Fabio Generoso Vieira [ctb]
Maintainer: Joris Mulder <j.mulder3@tilburguniversity.edu>
Repository: CRAN
Date/Publication: 2026-05-28 13:30:13 UTC

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Package nara updated to version 1.0.2 with previous version 1.0.1 dated 2026-05-27

Title: Native Raster Image Tools
Description: Native rasters are a core R image format which use a compact color representation. This color representation closely aligns with graphics device internals meaning that these images can be rendered quickly. This package provides functions to quickly create, manipulate and composite native rasters.
Author: Mike Cheng [aut, cre, cph], Julien Vernay [ctb]
Maintainer: Mike Cheng <mikefc@coolbutuseless.com>

Diff between nara versions 1.0.1 dated 2026-05-27 and 1.0.2 dated 2026-05-28

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Package ipeadatar updated to version 0.2.0 with previous version 0.1.6 dated 2022-02-03

Title: API Wrapper for 'Ipeadata'
Description: Provides direct access to the macroeconomic, financial, and regional database maintained by the Institute for Applied Economic Research (Ipea) via the Ipeadata API. For more information, see <https://www.ipeadata.gov.br/>.
Author: Luiz Eduardo Gomes [aut, cre] , Daniel Herszenhut [ctb] , Instituto de Pesquisa Economica Aplicada [cph, fnd]
Maintainer: Luiz Eduardo Gomes <luiz.gomes@ipea.gov.br>

Diff between ipeadatar versions 0.1.6 dated 2022-02-03 and 0.2.0 dated 2026-05-28

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Package influential updated to version 2.3.1 with previous version 2.3.0 dated 2026-02-13

Title: Identification and Classification of the Most Influential Nodes
Description: Provides functions for the identification, classification, and ranking of influential nodes and candidate features from network and omics data. The package implements the Integrated Value of Influence (IVI) for integrative network centrality analysis, the SIR-based Influence Ranking (SIRIR) model for unsupervised influence ranking, and the Experimental data-based Integrative Ranking (ExIR) model for prioritizing candidate driver, biomarker, and mediator features from experimental omics data. Functions are provided for network reconstruction from adjacency matrices and data frames, topological analysis, centrality calculation, assessment of associations between centrality measures, and conditional probability analysis. ExIR supports bulk and single-cell omics data, including matrices, sparse matrices, data frames, tibbles, and Seurat objects.
Author: Adrian Salavaty [aut, cre] , Mirana Ramialison [ths], Peter D. Currie [ths]
Maintainer: Adrian Salavaty <abbas.salavaty@gmail.com>

Diff between influential versions 2.3.0 dated 2026-02-13 and 2.3.1 dated 2026-05-28

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New package gdxtools with initial version 1.1.1
Package: gdxtools
Title: Manipulate 'GDX' Files
Version: 1.1.1
Date: 2026-05-22
SystemRequirements: GAMS (>= 24.2.1) is only required if you call gams()
Description: Read and write 'GDX' files ('GAMS' data exchange) and convert parameters, sets and variables to data frames. Backed by the 'GAMS'-maintained 'gamstransfer' package; no compiled code is shipped. See <https://www.gams.com/latest/docs/UG_GDX.html> for the 'GDX' format.
License: EPL-1.0
URL: https://github.com/lolow/gdxtools
BugReports: https://github.com/lolow/gdxtools/issues
Imports: gamstransfer (>= 3.0)
Suggests: testthat, microbenchmark
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2026-05-22 11:08:27 UTC; lolow
Author: Laurent Drouet [aut, cre]
Maintainer: Laurent Drouet <ldrouet@pm.me>
Repository: CRAN
Date/Publication: 2026-05-28 13:40:02 UTC

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New package demovuln with initial version 0.1.0
Package: demovuln
Title: Demographic Vulnerability Metrics for Matrix Population Models
Version: 0.1.0
Description: Simulates temporally structured perturbations in matrix population models and computes population reduction and integrated demographic vulnerability across perturbation regimes. Perturbations can be applied to adult survival, juvenile survival, fecundity, all demographic entries, or user-defined matrix elements. The package provides tools to simulate individual perturbation trajectories, evaluate perturbation grids, and summarize demographic vulnerability in structured populations.
License: MIT + file LICENSE
Encoding: UTF-8
Suggests: ggplot2, knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
URL: https://github.com/agimenezromero/demovuln-r
BugReports: https://github.com/agimenezromero/demovuln-r/issues
NeedsCompilation: no
Packaged: 2026-05-22 11:12:33 UTC; alex
Author: Àlex Gimenez-Romero [aut, cre] , Meritxell Genovart [aut]
Maintainer: Àlex Gimenez-Romero <alex.gimenez@csic.es>
Repository: CRAN
Date/Publication: 2026-05-28 13:40:07 UTC

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Package bedrockbio updated to version 1.4.0 with previous version 1.3.1 dated 2026-05-18

Title: Open-Access Computational Biology Datasets
Description: Efficiently access the 'Bedrock Bio' library of open-access computational biology datasets. Lazily query datasets backed by 'DuckDB' and 'Apache Iceberg', with support for predicate pushdown and column projection to the cloud storage backend. This enables quick, iterative access to otherwise massive, unwieldy datasets without downloading them in full. See <https://bedrock.bio> for available datasets and documentation.
Author: Liam Abbott [aut, cre, cph]
Maintainer: Liam Abbott <liam@bedrock.bio>

Diff between bedrockbio versions 1.3.1 dated 2026-05-18 and 1.4.0 dated 2026-05-28

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New package SampleCore with initial version 0.1.0
Package: SampleCore
Title: Sampling Strategies for Constructing Core Collections
Version: 0.1.0
Description: Implements multiple allocation and selection strategies of sampling to construct core collections primarily from clustered or grouped germplasm collection data. Provides methods for allocating entries to clusters/groups based on group sizes, group-wise distance-based diversity metrics, and group-wise diversity index estimates. Includes procedures for selecting entries within clusters/groups through random sampling, genetic distance-based approaches, and optimized diversity metric–based selection methods. See the package documentation for more, including full list of references for the methods implemented.
License: GPL (>= 2)
Encoding: UTF-8
BuildManual: TRUE
Imports: cluster, DiversityStats, ggplot2, igraph, MASS, mathjaxr, prospectr, Rdpack, Rtsne, stats, vegan
Suggests: biotools, dbscan, EvaluateCore, fastcluster, knitr, pander, rmarkdown
Copyright: 2024-2026, ICAR-NBPGR
URL: https://github.com/aravind-j/SampleCore https://aravind-j.github.io/SampleCore/
BugReports: https://github.com/aravind-j/SampleCore/issues
Depends: R (>= 3.5)
NeedsCompilation: no
Packaged: 2026-05-21 04:21:51 UTC; Aravind-DGC
Author: J. Aravind [aut, cre] , Suman Roy [aut] , Anju Mahendru Singh [aut] , ICAR-NBGPR [cph]
Maintainer: J. Aravind <j.aravind@icar.org.in>
Repository: CRAN
Date/Publication: 2026-05-28 13:00:02 UTC

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New package SAFEMCN with initial version 1.0.0
Package: SAFEMCN
Title: Network Topology Parameter Analysis with Rarefaction
Version: 1.0.0
Description: Calculate network topology parameters from Operational Taxonomic Unit (OTU) tables with customizable correlation thresholds, parallel processing options, and visualization capabilities including trend fitting, prediction of future sample sizes, and lag-1 autocorrelation (AR1) analysis. Methods are based on co-occurrence network construction via correlation thresholds and graph-theoretic metrics computed with 'igraph'.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 3.5.0)
Imports: igraph, Hmisc, parallel, ggplot2, grDevices, graphics, rlang, stats, utils
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-05-22 01:53:31 UTC; 童小徐
Author: Xiaotong Xu [aut, cre], Yue Zheng [cph]
Maintainer: Xiaotong Xu <xxt19992014@163.com>
Repository: CRAN
Date/Publication: 2026-05-28 13:00:05 UTC

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Package rasterImage updated to version 0.4.1 with previous version 0.4.0 dated 2019-10-14

Title: An Improved Wrapper of image()
Description: This is a wrapper function for image(), which makes reasonable raster plots with nice axis and other useful features.
Author: Martin Seilmayer [aut, cre]
Maintainer: Martin Seilmayer <martin.seilmayer@dhsn.de>

Diff between rasterImage versions 0.4.0 dated 2019-10-14 and 0.4.1 dated 2026-05-28

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Package myTAI updated to version 2.3.6 with previous version 2.3.5 dated 2026-02-05

Title: Evolutionary Transcriptomics
Description: Investigate the evolution of biological processes by capturing evolutionary signatures in transcriptomes (Drost et al. (2018) <doi:10.1093/bioinformatics/btx835>). This package aims to provide a transcriptome analysis environment to quantify the average evolutionary age of genes contributing to a transcriptome of interest.
Author: Hajk-Georg Drost [aut, cre] , Stefan Manolache [aut, ctb] , Jaruwatana Sodai Lotharukpong [aut, ctb] , Nikola Kalabova [aut, ctb] , Filipa Martins Costa [aut, ctb], Kristian K Ullrich [aut, ctb]
Maintainer: Hajk-Georg Drost <hajk-georg.drost@tuebingen.mpg.de>

Diff between myTAI versions 2.3.5 dated 2026-02-05 and 2.3.6 dated 2026-05-28

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New package modeldiag with initial version 0.1.0
Package: modeldiag
Title: Comprehensive Diagnostics for Statistical Models
Version: 0.1.0
Description: Provides a unified framework for diagnosing common issues in statistical models including linear models, generalized linear models (logistic and Poisson regression), and survival models. Implements tests for multicollinearity, heteroscedasticity, autocorrelation, normality, influential observations, overdispersion, zero-inflation, and proportional hazards assumptions. Includes visualization methods for graphical diagnostics. Methods are based on established approaches including Fox and Monette (1992) <doi:10.1080/01621459.1992.10475190>, Breusch and Pagan (1979) <doi:10.2307/1911963>, and Dean and Lawless (1989) <doi:10.1080/01621459.1989.10478792>.
License: MIT + file LICENSE
Encoding: UTF-8
URL: https://github.com/Teniola17/modeldiag
BugReports: https://github.com/Teniola17/modeldiag/issues
Depends: R (>= 3.5.0)
Imports: stats, graphics, car, lmtest, ResourceSelection, survival
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-05-21 14:47:02 UTC; EmmanuelAdewuyi
Author: Emmanuel Adewuyi [aut, cre], Adewale Lukman [aut], Abiola Owolabi [ctb]
Maintainer: Emmanuel Adewuyi <emmanuel.adewuyi@lshtm.ac.uk>
Repository: CRAN
Date/Publication: 2026-05-28 12:40:02 UTC

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New package llmshieldr with initial version 0.1.0
Package: llmshieldr
Title: Safety Guardrails for Large Language Model Workflows
Version: 0.1.0
Description: A model-agnostic safety layer for developers building with large language model (LLM) applications. Maps starter controls to the Open Worldwide Application Security Project Top 10 for Large Language Model Applications 2025 risk categories <https://genai.owasp.org/llm-top-10/> via a modular rule engine. Supports regular-expression rules, lightweight natural language processing (NLP) intent checks, optional scanners, and semantic large language model reviewer checks on prompts, conversations, retrieved context, tool inputs and outputs, streaming chunks, and model outputs. Supports workflows with the 'Ollama' local web service <https://ollama.com/> via 'ellmer', remote reviewer endpoints, and other chat interfaces callable from 'R'. Intended as an experimental guardrail layer that teams should evaluate against their own workflows before relying on it in production.
License: Apache License (>= 2)
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: jsonlite, cli, rlang, digest, stringi
Suggests: ellmer, httr2, processx, filelock, htmltools, covr, lintr, plumber, shiny, testthat (>= 3.0.0), knitr, rmarkdown, withr, dplyr, tokenizers, SnowballC
VignetteBuilder: knitr
URL: https://www.indraneelchakraborty.com/llmshieldr/, https://github.com/ineelhere/llmshieldr, https://genai.owasp.org/llm-top-10/
BugReports: https://github.com/ineelhere/llmshieldr/issues
NeedsCompilation: no
Packaged: 2026-05-21 18:26:34 UTC; neel0
Author: Indraneel Chakraborty [aut, cre, cph]
Maintainer: Indraneel Chakraborty <hello.indraneel@gmail.com>
Repository: CRAN
Date/Publication: 2026-05-28 12:50:02 UTC

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New package fable.bayesRecon with initial version 0.1.0
Package: fable.bayesRecon
Date: 2026-05-05
Title: Bayesian Reconciliation in the 'fable' Framework
Version: 0.1.0
Description: Implements the 'bayesRecon' probabilistic reconciliation methods within the 'fable' framework for hierarchical time series forecasting. Bayesian reconciliation (bayesRecon) methods are accessed via the 'reconcile' verb, following 'fable' conventions. For methodological background, see Corani et al. (2021) <doi:10.1007/978-3-030-67664-3_13>, Zambon et al. (2024a) <doi:10.1007/s11222-023-10343-y>, Zambon et al. (2024b) <https://proceedings.mlr.press/v244/zambon24a.html>, and Carrara et al. (2025) <doi:10.48550/arXiv.2506.19554>.
License: LGPL (>= 3)
URL: https://github.com/dazzimonti/fable.bayesRecon
BugReports: https://github.com/dazzimonti/fable.bayesRecon/issues
Encoding: UTF-8
Imports: stats, bayesRecon, fabletools (>= 0.7.0), purrr, vctrs, distributional, dplyr, tsibble, rlang
Suggests: testthat (>= 3.0.0), cli, fable, tsibbledata, tibble, ggplot2, scales, knitr, rmarkdown
VignetteBuilder: knitr
Depends: R (>= 4.1)
NeedsCompilation: no
Packaged: 2026-05-21 13:56:12 UTC; dario.azzimonti
Author: Dario Azzimonti [aut, cre, cph] , Stefano Damato [aut] , Lorenzo Zambon [aut] , Chiara Carrara [aut] , Giorgio Corani [aut]
Maintainer: Dario Azzimonti <dario.azzimonti@gmail.com>
Repository: CRAN
Date/Publication: 2026-05-28 12:20:06 UTC

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New package ELAplus with initial version 1.0.2
Package: ELAplus
Language: en-US
Title: Energy Landscape Analysis for Ecological Communities
Version: 1.0.2
Date: 2026-05-15
Author: Kenta Suzuki [aut, cre, cph], Sotaro Takano [aut], Hiroaki Fujita [aut], Zeus Sato [ctb], Fumihiko Ayabe [ctb]
Maintainer: Kenta Suzuki <kenta.suzuki.zk@riken.jp>
Encoding: UTF-8
License: BSD_3_clause + file LICENSE
Description: Energy landscape analysis (ELA) is a systematic method for analyzing an energy landscape represented as a weighted network. This R package is especially designed to analyze ecological dynamics, i.e., transitions in community compositions. For details of the analysis framework, please visit Suzuki K et al. (2021) <doi:10.1002/ecm.1469>.
Depends: R (>= 4.1.0)
Imports: Rcpp (>= 1.0.11), doParallel, RColorBrewer, foreach, dplyr, magrittr, stringdist, gtools, ggplot2, purrr, rlang, tidyr, data.table, stringr, igraph
Suggests: cluster, plot3D, fpc, quanteda, slam, stm, topicmodels, tidyverse, Matrix, glmnet, gsubfn, zoo, ggsci, tidygraph, vegan, knitr, rmarkdown
VignetteBuilder: knitr
LinkingTo: Rcpp, RcppArmadillo
NeedsCompilation: yes
LazyData: true
Packaged: 2026-05-15 08:49:40 UTC; str_mac
Repository: CRAN
Date/Publication: 2026-05-28 12:20:11 UTC

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New package DICErClust with initial version 0.1.2
Package: DICErClust
Title: Deep Significance Clustering for Clinical Risk Stratification
Version: 0.1.2
Description: We provide an R implementation of Deep Significance Clustering (DICE), a self-supervised learning framework designed to identify clinically meaningful and risk-stratified patient subgroups from electronic health record (EHR) data. DICE jointly optimizes deep representation learning, clustering, and outcome prediction while enforcing statistical significance between predicted outcomes and cluster membership. This integrated optimization produces subgroups that are both clinically coherent and predictive, addressing a gap where traditional unsupervised clustering methods and supervised risk prediction models alone may fail to generate actionable clinical groupings. See Huang et al. (2021) <doi:10.1093/jamia/ocab203>.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: argparser, ggplot2, torch, pROC
Suggests: knitr, rmarkdown, scales
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-05-21 22:05:42 UTC; sarahayton
Author: Sarah Ayton [aut, cre] , Yiye Zhang [aut]
Maintainer: Sarah Ayton <saa7050@med.cornell.edu>
Repository: CRAN
Date/Publication: 2026-05-28 12:50:09 UTC

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Package CSTools updated to version 5.3.2 with previous version 5.3.1 dated 2026-03-17

Title: Assessing Skill of Climate Forecasts on Seasonal-to-Decadal Timescales
Description: Exploits dynamical seasonal forecasts in order to provide information relevant to stakeholders at the seasonal timescale. The package contains process-based methods for forecast calibration, bias correction, statistical and stochastic downscaling, optimal forecast combination and multivariate verification, as well as basic and advanced tools to obtain tailored products. This package was developed in the context of the ERA4CS project MEDSCOPE and the H2020 S2S4E project and includes contributions from ArticXchange project founded by EU-PolarNet 2. Implements methods described in Pérez-Zanón et al. (2022) <doi:10.5194/gmd-15-6115-2022>, Doblas-Reyes et al. (2005) <doi:10.1111/j.1600-0870.2005.00104.x>, Mishra et al. (2018) <doi:10.1007/s00382-018-4404-z>, Sanchez-Garcia et al. (2019) <doi:10.5194/asr-16-165-2019>, Straus et al. (2007) <doi:10.1175/JCLI4070.1>, Terzago et al. (2018) <doi:10.5194/nhess-18-2825-2018>, Torralba et al. (2017) <doi:10.117 [...truncated...]
Author: Nuria Perez-Zanon [aut] , Louis-Philippe Caron [aut] , Carmen Alvarez-Castro [aut] , Lauriane Batte [aut], Carlos Delgado [aut], Jost von Hardenberg [aut] , Llorenc LLedo [aut], Nicolau Manubens [aut], Lluis Palma [aut], Eroteida Sanchez-Garcia [aut] [...truncated...]
Maintainer: Victoria Agudetse <victoria.agudetse@bsc.es>

Diff between CSTools versions 5.3.1 dated 2026-03-17 and 5.3.2 dated 2026-05-28

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 23 files changed, 1305 insertions(+), 1025 deletions(-)

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New package accbaseballr with initial version 0.1.3
Package: accbaseballr
Title: ACC Baseball Datasets with Advanced Sabermetric Metrics
Version: 0.1.3
Description: Provides curated ACC (Atlantic Coast Conference) baseball datasets at the player-season level, including traditional statistics and advanced sabermetric metrics such as weighted on-base average (wOBA), weighted runs created plus (wRC+), and fielding-independent pitching (FIP).
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
LazyData: true
LazyDataCompression: xz
URL: https://github.com/hvb210/accbaseballr
BugReports: https://github.com/hvb210/accbaseballr/issues
NeedsCompilation: no
Packaged: 2026-05-21 15:15:59 UTC; hbaskin
Author: Hana Baskin [aut, cre, cph]
Maintainer: Hana Baskin <hana.baskin@gmail.com>
Repository: CRAN
Date/Publication: 2026-05-28 12:40:06 UTC

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New package varGuidTS with initial version 0.1.13
Package: varGuidTS
Version: 0.1.13
Date: 2026-05-20
Title: Variance-Guided Time-Series Modeling for Temporal Risk Detection
Author: Zihao Wang [aut], Min Lu [aut, cre]
Maintainer: Min Lu <luminwin@gmail.com>
BugReports: https://github.com/zionwzz/variance-guided-risk-demo/issues
Depends: R (>= 4.1.0)
Imports: stats, glmnet
Suggests: testthat (>= 3.0.0)
Description: Fits balanced-panel autoregressive models with conditional heteroscedasticity for temporal risk detection. The main estimator combines autoregressive exogenous mean modeling with GARCH-X variance modeling, subject-specific baseline terms, shared population coefficients, and L1 penalization for high-dimensional covariates. The package returns conditional mean and variance estimates, coefficient summaries, simulations, and exceedance-based risk scores defined as estimated conditional threshold-exceedance probabilities. The implementation builds on the lasso of Tibshirani (1996) <doi:10.1111/j.2517-6161.1996.tb02080.x>, generalized autoregressive conditional heteroscedasticity of Bollerslev (1986) <doi:10.1016/0304-4076(86)90063-1>, and L1-regularized high-dimensional time-series modeling of Medeiros and Mendes (2016) <doi:10.1016/j.jeconom.2015.10.011>.
License: MIT + file LICENSE
URL: https://github.com/zionwzz/variance-guided-risk-demo
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-05-20 18:10:00 UTC; minlu
Repository: CRAN
Date/Publication: 2026-05-28 11:10:02 UTC

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New package unitcm with initial version 0.1.2
Package: unitcm
Version: 0.1.2
Title: Client for the 'UniTCM' Traditional Chinese Medicine Platform
Description: Provides functions to query the 'UniTCM' API (<https://unitcm.qfxulab.com>), covering herb exploration, compound/ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) data, disease-formula associations, Traditional Chinese Medicine (TCM) ontology, transcriptomics, and gene-disease analysis (MIDAS, Mining Integrated Disease Association Sources).
Author: Xiao Zheng [aut, cre]
Maintainer: Xiao Zheng <12519088@zju.edu.cn>
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: httr2 (>= 1.0.0), tibble (>= 3.0.0), dplyr (>= 1.1.0), rlang (>= 1.0.0), cli, glue
Suggests: igraph (>= 1.4.0), tidygraph, ggplot2 (>= 3.4.0), ggraph, keyring, testthat (>= 3.0.0), httptest2, withr, knitr, rmarkdown, pkgdown
URL: https://zx122ty.github.io/UniTCM_R_Package/, https://github.com/zx122ty/UniTCM_R_Package
BugReports: https://github.com/zx122ty/UniTCM_R_Package/issues
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-05-21 02:10:50 UTC; since
Repository: CRAN
Date/Publication: 2026-05-28 11:10:08 UTC

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New package spima with initial version 0.2.0
Package: spima
Title: Simulated Pseudo-Individual Data Meta-Analysis with ABC-SMC
Version: 0.2.0
Description: Meta-analysis via Approximate Bayesian Computation Sequential Monte Carlo (ABC-SMC) by simulating pseudo-individual data from published group-level summary statistics. Handles binary, continuous, and generic effect-size outcomes within a one-stage mixed-model framework. Supports subgroup analysis.
License: MIT + file LICENSE
Depends: R (>= 3.5.0)
Imports: lme4, parallel, stats, methods, Rcpp
Suggests: ggplot2, testthat, knitr, rmarkdown
LinkingTo: Rcpp, RcppArmadillo
SystemRequirements: GNU make
URL: https://github.com/HaichuanYu0703/SPIMA
BugReports: https://github.com/HaichuanYu0703/SPIMA/issues
Encoding: UTF-8
LazyData: true
NeedsCompilation: yes
Packaged: 2026-05-21 09:13:32 UTC; yu-ha
Author: Yu Haichuan [aut, cre, cph]
Maintainer: Yu Haichuan <yuhaichuan@whu.edu.cn>
Repository: CRAN
Date/Publication: 2026-05-28 11:30:01 UTC

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New package spefa with initial version 0.1.0
Package: spefa
Title: Spatial Stochastic Frontier with Fixed Effects and Endogeneity
Version: 0.1.0
Description: Maximum-likelihood estimation of the spatial autoregressive stochastic frontier model with individual fixed effects (removed by first differencing) and endogenous regressors handled through a Gaussian control function, as in Giannini (2025) <doi:10.1080/17421772.2024.2414962>. Returns coefficient estimates and standard errors, spatially-corrected technical (in)efficiency scores, and direct, indirect and total marginal impacts. Depends only on base R.
License: GPL-3
Encoding: UTF-8
Depends: R (>= 3.5.0)
Imports: stats
LazyData: true
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-05-21 06:32:07 UTC; root
Author: Massimo Giannini [aut, cre]
Maintainer: Massimo Giannini <massimo.giannini@uniroma2.it>
Repository: CRAN
Date/Publication: 2026-05-28 11:10:17 UTC

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Package rSpectral updated to version 1.0.0.16 with previous version 1.0.0.14 dated 2025-12-07

Title: Spectral Modularity Clustering
Description: Implements the network clustering algorithm described in Newman (2006) <doi:10.1103/PhysRevE.74.036104>. The complete iterative algorithm comprises of two steps. In the first step, the network is expressed in terms of its leading eigenvalue and eigenvector and recursively partition into two communities. Partitioning occurs if the maximum positive eigenvalue is greater than the tolerance (10e-5) for the current partition, and if it results in a positive contribution to the Modularity. Given an initial separation using the leading eigen step, 'rSpectral' then continues to maximise for the change in Modularity using a fine-tuning step - or variate thereof. The first stage here is to find the node which, when moved from one community to another, gives the maximum change in Modularity. This node’s community is then fixed and we repeat the process until all nodes have been moved. The whole process is repeated from this new state until the change in the Modularity, between the new and o [...truncated...]
Author: Colin Mclean [aut] , Anatoly Sorokin [aut, cre]
Maintainer: Anatoly Sorokin <lptolik@gmail.com>

Diff between rSpectral versions 1.0.0.14 dated 2025-12-07 and 1.0.0.16 dated 2026-05-28

 DESCRIPTION                        |   10 +++++-----
 MD5                                |   12 ++++++------
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 7 files changed, 28 insertions(+), 13 deletions(-)

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Package rmumps updated to version 5.2.1-43 with previous version 5.2.1-42 dated 2026-05-26

Title: Wrapper for MUMPS Library
Description: Some basic features of 'MUMPS' (Multifrontal Massively Parallel sparse direct Solver) are wrapped in a class whose methods can be used for sequentially solving a sparse linear system (symmetric or not) with one or many right hand sides (dense or sparse). There is a possibility to do separately symbolic analysis, LU (or LDL^t) factorization and system solving. Third part ordering libraries are included and can be used: 'PORD', 'METIS', 'SCOTCH'. 'MUMPS' method was first described in Amestoy et al. (2001) <doi:10.1137/S0895479899358194> and Amestoy et al. (2006) <doi:10.1016/j.parco.2005.07.004>.
Author: Serguei Sokol [aut, cre], Emmanuel Agullo [ctb], Patrick Amestoy [ctb, cph], Maurice Bremond [ctb], Alfredo Buttari [ctb], Philippe Combes [ctb], Marie Durand [ctb], Aurelia Fevre [ctb], Abdou Guermouche [ctb], Guillaume Joslin [ctb], Jacko Koster [c [...truncated...]
Maintainer: Serguei Sokol <sokol@insa-toulouse.fr>

Diff between rmumps versions 5.2.1-42 dated 2026-05-26 and 5.2.1-43 dated 2026-05-28

 DESCRIPTION |    6 +++---
 MD5         |    6 +++---
 NEWS        |   11 ++++++++---
 src/init.c  |    3 ++-
 4 files changed, 16 insertions(+), 10 deletions(-)

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New package OSIRCR with initial version 0.2.9
Package: OSIRCR
Title: Cosine Regression-Based Online Sliced Inverse Regression Algorithm
Version: 0.2.9
Author: Guangbao Guo [aut, cre], Sirui Yan [aut]
Maintainer: Guangbao Guo <ggb11111111@163.com>
Description: In high-dimensional streaming data analysis, extracting core periodic features under real-time constraints remains challenging. Traditional dimension reduction methods fail to adapt to incremental data and yield low accuracy due to irrelevant variables. This package provides the Online Sliced Inverse Regression framework for cosine regression with high-dimensional irrelevant variables. It integrates subspace extraction of sliced inverse regression and incremental learning of online algorithms to efficiently handle periodic streaming data. Cai, Z., Li, R., & Zhu, L. (2020) <doi:10.48550/arXiv.2002.02795>.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 3.5.0)
Imports: stats
NeedsCompilation: no
LazyData: true
Packaged: 2026-05-20 14:17:04 UTC; Lenovo
Language: en-US
Repository: CRAN
Date/Publication: 2026-05-28 11:10:28 UTC

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Package joinpointR updated to version 0.6.2 with previous version 0.6.0 dated 2026-05-19

Title: Tidy Tools for Joinpoint Regression Models
Description: Provides tools to fit joinpoint regression models with a log-linear specification by levels of a categorical variable. The package acts as a wrapper around the 'segmented' package, facilitating model fitting, selection, and interpretation. It includes functions to estimate the Annual Percent Change (APC) and the Average Annual Percent Change (AAPC), along with their 95% confidence intervals, and to generate formatted summary tables and plots of results.
Author: Tamara Ricardo [aut, cre]
Maintainer: Tamara Ricardo <tamararicardo83@gmail.com>

Diff between joinpointR versions 0.6.0 dated 2026-05-19 and 0.6.2 dated 2026-05-28

 DESCRIPTION  |    8 ++++----
 MD5          |    6 +++---
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 4 files changed, 16 insertions(+), 14 deletions(-)

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New package ggspec with initial version 0.1.0
Package: ggspec
Title: Extract and Compare 'ggplot2' Plot Specifications as Tidy Data Frames
Version: 0.1.0
Author: Clement Lee [aut, cre]
Maintainer: Clement Lee <clement.lee.tm@outlook.com>
Description: Inspects 'ggplot' objects by extracting their full declarative specification - layers, aesthetic mappings, scales, facets, coordinate systems, and labels - as tidy data frames. A second tier of functions enables structural comparison of two 'ggplot' objects, supporting automated plot testing, auditing, and framework-agnostic grading workflows. Unlike 'ggcheck', which is designed exclusively for 'learnr'/'gradethis' pipelines and returns ad-hoc objects, 'ggspec' returns rectangular, pipeable output and does not require any grading framework as a dependency.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: ggplot2 (>= 3.4.0), rlang (>= 1.1.0), tibble (>= 3.2.0), dplyr (>= 1.1.0)
Suggests: learnr, palmerpenguins, testthat (>= 3.0.0), knitr, rmarkdown, MASS, covr
VignetteBuilder: knitr
URL: https://github.com/clement-lee/ggspec
BugReports: https://github.com/clement-lee/ggspec/issues
NeedsCompilation: no
Packaged: 2026-05-21 10:14:20 UTC; ntl34
Repository: CRAN
Date/Publication: 2026-05-28 11:30:07 UTC

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Package fdicdata readmission to version 0.1.2 with previous version 0.1.1 dated 2024-09-12

Title: Accessing FDIC Bank Data
Description: A system provides a set of functions for working with data from the Federal Deposit Insurance Corporation (FDIC), including retrieving financial data for FDIC-insured institutions and accessing the data taxonomy.
Author: Ugur Dar [aut, cre], Brian Pillmore [aut, cph]
Maintainer: Ugur Dar <ugurdarr@gmail.com>

This is a re-admission after prior archival of version 0.1.1 dated 2024-09-12

Diff between fdicdata versions 0.1.1 dated 2024-09-12 and 0.1.2 dated 2026-05-28

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 tests/testthat/test-getSummary.R         |    6 +
 34 files changed, 309 insertions(+), 223 deletions(-)

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New package cellkeyperturbation with initial version 3.0.0
Package: cellkeyperturbation
Title: Cell Key Perturbation
Version: 3.0.0
Description: Provides functions to generate frequency tables and apply cell key perturbation to protect against statistical disclosure in tabular outputs. The implemented methods are described in "Cell Key Perturbation User Guide" <https://github.com/ONSdigital/cell-key-perturbation-R/blob/main/documentation/SML_UserDoc_CKP_R.md>. Developed at the UK Office for National Statistics.
License: MIT + file LICENSE
Encoding: UTF-8
Suggests: bigrquery, DBI, knitr, rmarkdown, testthat (>= 3.0.0)
Imports: data.table
Depends: R (>= 3.5.0)
LazyData: true
VignetteBuilder: knitr
URL: https://github.com/ONSdigital/cell-key-perturbation-R
BugReports: https://github.com/ONSdigital/cell-key-perturbation-R/issues
NeedsCompilation: no
Packaged: 2026-05-21 10:57:32 UTC; aydina
Author: Iain Dove [aut, cph], Ahmet Aydin [aut, cre]
Maintainer: Ahmet Aydin <SDC.Queries@ons.gov.uk>
Repository: CRAN
Date/Publication: 2026-05-28 11:40:06 UTC

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New package buzzMed with initial version 0.1.2
Package: buzzMed
Version: 0.1.2
Date: 2026-05-20
Title: Bayesian Understanding for Mediator Selection Framework
Description: A collection of quantitative tools for selecting mediating effects within exploratory Bayesian mediation models. The package accommodates both continuous and dichotomous outcomes, including the dependent variables and the mediators for identifying and analyzing mediation pathways.
License: GPL (>= 3)
Depends: R (>= 4.0.0)
SystemRequirements: JAGS (>= 4.0.0)
Imports: coda, methods, rjags, stats, utils
Suggests: knitr, rmarkdown, spelling, testthat (>= 3.0.0)
ByteCompile: true
VignetteBuilder: knitr
URL: https://github.com/olfactorybulb/buzzMed
BugReports: https://github.com/olfactorybulb/buzzMed/issues
Encoding: UTF-8
Language: en-US
NeedsCompilation: no
Packaged: 2026-05-21 01:46:21 UTC; jesshsing
Author: Dingjing Shi [aut, cre], Tansu Celikel [aut], Dexin Shi [aut], Chih-Chia Hsing [ctb]
Maintainer: Dingjing Shi <dshi32@gatech.edu>
Repository: CRAN
Date/Publication: 2026-05-28 11:20:06 UTC

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Package rsat (with last version 0.1.21) was removed from CRAN

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

2024-02-03 0.1.21

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Package waterquality (with last version 1.0.0) was removed from CRAN

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

2023-08-07 1.0.0
2022-02-09 0.3.0
2020-10-21 0.2.6
2020-10-02 0.2.5
2018-12-18 0.2.2

Permanent link
Package whSample (with last version 0.9.6.2) was removed from CRAN

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

2021-05-13 0.9.6.2
2021-01-14 0.9.4
2020-09-02 0.9.2
2020-08-31 0.9.0
2020-08-28 0.8.9

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Package rGhanaCensus (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:

2022-01-13 0.1.0

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Package primer (with last version 1.2.0) was removed from CRAN

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

2021-01-06 1.2.0
2019-10-07 1.1.1

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New package stringArt with initial version 0.1.0
Package: stringArt
Title: Tools for Generating String Art Figures
Version: 0.1.0
Description: Provides tools to generate, visualize, and audit geometric string art figures for mathematics teaching. The package includes functions for circular, cardioid-like, elliptical, triangular, polygonal, star, parabolic, net-based, radial, hexagonal, lotus-like, rose-like, spiral, Lissajous, grid-based, decimal, and contour-based string art patterns. Each function returns peg coordinates, connection tables, total string length, audit information, and metadata, supporting educational applications in geometry, analytic geometry, modular arithmetic, trigonometry, rational numbers, and visual mathematics.
License: MIT + file LICENSE
Encoding: UTF-8
URL: https://github.com/fsbmat-ufv/stringArt
BugReports: https://github.com/fsbmat-ufv/stringArt/issues
Depends: R (>= 4.1)
Imports: graphics
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-05-20 22:19:16 UTC; fsbmat
Author: Fernando de Souza Bastos [aut, cre], Ivo Moreira Barbosa [aut]
Maintainer: Fernando de Souza Bastos <fernando.bastos@ufv.br>
Repository: CRAN
Date/Publication: 2026-05-28 11:00:02 UTC

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Package rd2d updated to version 1.0.0 with previous version 0.2.0 dated 2026-05-23

Title: Estimation and Inference for Boundary Discontinuity Designs
Description: Provides pointwise and uniform estimation and inference methods for boundary discontinuity (BD) designs, a causal inference design that generalizes univariate regression discontinuity (RD) designs to settings with bivariate scores. Implements local polynomial methods for location-based and distance-based analyses, including sharp and fuzzy designs, data-driven bandwidth selection, pointwise confidence intervals, and uniform confidence bands. Methodology is developed in Cattaneo, Titiunik, and Yu (2026) <doi:10.48550/arXiv.2505.05670> for location-based methods and Cattaneo, Titiunik, and Yu (2026) <doi:10.48550/arXiv.2510.26051> for distance-based methods. For an overview and empirical guidance, see Cattaneo, Titiunik, and Yu (2026) <doi:10.48550/arXiv.2511.06474>. The companion software article is Cattaneo, Titiunik, and Yu (2025) <doi:10.48550/arXiv.2505.07989>.
Author: Matias D. Cattaneo [aut, cre], Rocio Titiunik [aut], Ruiqi Rae Yu [aut]
Maintainer: Matias D. Cattaneo <matias.d.cattaneo@gmail.com>

Diff between rd2d versions 0.2.0 dated 2026-05-23 and 1.0.0 dated 2026-05-28

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 NAMESPACE                                  |   10 
 NEWS.md                                    |   25 
 R/rd2d-package.R                           |    6 
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 R/rd2d_distance.R                          |  186 ++--
 R/rd2d_distance_fn.R                       |  369 +++++++--
 R/rd2d_fn.R                                | 1184 +++++++++++++++++++++--------
 R/rd2d_methods.R                           |only
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 R/rdbw2d_distance.R                        |  105 ++
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Package mdbr updated to version 0.3.1 with previous version 0.3.0 dated 2026-05-23

Title: Work with Microsoft Access Files
Description: Work with Microsoft Access '.mdb' and '.accdb' files using the open source 'MDB Tools' library <https://github.com/mdbtools/mdbtools/>. The library is compiled and bundled with the package, so no external installation is required. Provides high-level helpers for reading tables, exporting to CSV or JSON, inspecting table definitions, and running SQL queries. Also exposes a full read-only 'DBI' interface for use with standard database workflows.
Author: Kiernan Nicholls [aut, cre, cph] , Bruno Tremblay [ctb]
Maintainer: Kiernan Nicholls <k5cents@gmail.com>

Diff between mdbr versions 0.3.0 dated 2026-05-23 and 0.3.1 dated 2026-05-28

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New package anovapowersim with initial version 1.0.0
Package: anovapowersim
Title: Simple Power Simulations for ANOVAs
Version: 1.0.0
Description: A-priori power simulations and power-calculations for within, between and mixed ANOVAs based on target (partial) eta-squared values. Supports complex designs with more than two factors and their interactions with a single function call.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1)
Imports: car, dplyr, future, future.apply, ggplot2, MASS, purrr, rlang, stats, tibble, tidyr
Suggests: knitr, pkgdown, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
URL: https://shaheedazaad.github.io/anovapowersim/, https://github.com/shaheedazaad/anovapowersim
BugReports: https://github.com/shaheedazaad/anovapowersim/issues
NeedsCompilation: no
Packaged: 2026-05-18 18:13:55 UTC; shaheedazaad
Author: Shaheed Azaad [aut, cre]
Maintainer: Shaheed Azaad <sazaad@uni-muenster.de>
Repository: CRAN
Date/Publication: 2026-05-28 11:00:15 UTC

More information about anovapowersim at CRAN
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Package realestatebr (with last version 1.0.0) was removed from CRAN

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

2026-05-27 1.0.0

Permanent link
Package IOBR (with last version 2.2.2) was removed from CRAN

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

2026-05-25 2.2.2
2026-05-15 2.2.1
2026-04-22 2.2.0

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Package miceadds updated to version 3.20-10 with previous version 3.19-16 dated 2026-03-13

Title: Some Additional Multiple Imputation Functions, Especially for 'mice'
Description: Contains functions for multiple imputation which complements existing functionality in R. In particular, several imputation methods for the mice package (van Buuren & Groothuis-Oudshoorn, 2011, <doi:10.18637/jss.v045.i03>) are implemented. Main features of the miceadds package include plausible value imputation (Mislevy, 1991, <doi:10.1007/BF02294457>), multilevel imputation for variables at any level or with any number of hierarchical and non-hierarchical levels (Grund, Luedtke & Robitzsch, 2018, <doi:10.1177/1094428117703686>; van Buuren, 2018, Ch.7, <doi:10.1201/9780429492259>), imputation using partial least squares (PLS) for high dimensional predictors (Robitzsch, Pham & Yanagida, 2016), nested multiple imputation (Rubin, 2003, <doi:10.1111/1467-9574.00217>), substantive model compatible imputation (Bartlett et al., 2015, <doi:10.1177/0962280214521348>), and features for the generation of synthetic datasets (Reiter, 2005, <doi:10. [...truncated...]
Author: Alexander Robitzsch [aut, cre] , Simon Grund [aut] , Thorsten Henke [ctb]
Maintainer: Alexander Robitzsch <robitzsch@ipn.uni-kiel.de>

Diff between miceadds versions 3.19-16 dated 2026-03-13 and 3.20-10 dated 2026-05-28

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Package glmmrBase readmission to version 1.4.1 with previous version 1.4.0 dated 2026-04-29

Title: Monte Carlo Maximum Likelihood and Analysis of Generalised Linear Mixed Models
Description: Specification, analysis, simulation, and fitting of generalised linear mixed models. Monte Carlo Maximum likelihood model fitting for a range of models, non-linear fixed effect specifications, a wide range of flexible covariance functions including Gaussian Process approximations. Methods described in Watson, Wang, and Giorgi (2026) <doi:10.48550/arXiv.2601.16022>.
Author: Sam Watson [aut, cre]
Maintainer: Sam Watson <S.I.Watson@bham.ac.uk>

This is a re-admission after prior archival of version 1.4.0 dated 2026-04-29

Diff between glmmrBase versions 1.4.0 dated 2026-04-29 and 1.4.1 dated 2026-05-28

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Package sampcompR updated to version 0.3.3 with previous version 0.3.2 dated 2025-12-09

Title: Comparing and Visualizing Differences Between Surveys
Description: Easily analyze and visualize differences between samples (e.g., benchmark comparisons, nonresponse comparisons in surveys) on three levels. The comparisons can be univariate, bivariate or multivariate. On univariate level the variables of interest of a survey and a comparison survey (i.e. benchmark) are compared, by calculating one of several difference measures (e.g., relative difference in mean), and an average difference between the surveys. On bivariate level a function can calculate significant differences in correlations for the surveys. And on multivariate levels a function can calculate significant differences in model coefficients between the surveys of comparison. All of those differences can be easily plotted and outputted as a table. For more detailed information on the methods and example use see Rohr, B., Silber, H., & Felderer, B. (2024). Comparing the Accuracy of Univariate, Bivariate, and Multivariate Estimates across Probability and Nonprobability Surveys with Po [...truncated...]
Author: Bjoern Rohr [aut, cre, cph], Barbara Felderer [aut]
Maintainer: Bjoern Rohr <bjoern.rohr@gesis.org>

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Package esviz updated to version 0.0.3 with previous version 0.0.2 dated 2026-02-04

Title: Plotting Functions for Climate Science and Services
Description: A plotting package for climate science and services. Provides a set of functions for visualizing climate data, including maps, time series, scorecards and other diagnostics. Some functions are adapted and extended from the 's2dv' and 'CSTools' packages (Manubens et al. (2018) <doi:10.1016/j.envsoft.2018.01.018>; Pérez-Zanón et al. (2022) <doi:10.5194/gmd-15-6115-2022>), with more consistent and integrated functionalities.
Author: BSC-CNS [aut, cph], An-Chi Ho [aut], Eva Rifa [ctb], Victoria Agudetse [ctb], Ariadna Batalla [ctb, cre], Nuria Perez-Zanon [ctb], Nadia Milders [ctb], Veronica Torralba [ctb], Raul Capellan [ctb], Anindita Patra [ctb]
Maintainer: Ariadna Batalla <ariadna.batalla@bsc.es>

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Package enmpa updated to version 0.2.4 with previous version 0.2.3 dated 2026-01-26

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>

Diff between enmpa versions 0.2.3 dated 2026-01-26 and 0.2.4 dated 2026-05-28

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Package netmeta updated to version 3.5-0 with previous version 3.4-0 dated 2026-04-11

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

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Package MSCquartets updated to version 3.3 with previous version 3.2 dated 2025-03-19

Title: Analyzing Gene Tree Quartets under the Multi-Species Coalescent
Description: Methods for analyzing and using quartets displayed on a collection of gene trees, primarily to make inferences about the species tree or network under the multi-species coalescent model. These include quartet hypothesis tests for the model, as developed by Mitchell et al. (2019) <doi:10.1214/19-EJS1576>, simplex plots of quartet concordance factors as presented by Allman et al. (2020) <doi:10.1101/2020.02.13.948083>, species tree inference methods based on quartet distances of Rhodes (2019) <doi:10.1109/TCBB.2019.2917204> and Yourdkhani and Rhodes (2019) <doi:10.1007/s11538-020-00773-4>, the NANUQ algorithm for inference of level-1 species networks of Allman et al. (2019) <doi:10.1186/s13015-019-0159-2>, the TINNIK algorithm for inference of the tree of blobs of an arbitrary network of Allman et al.(2022) <doi:10.1007/s00285-022-01838-9>, NANUQ+ routines for resolving multifurcations in the tree of blobs to cycles as in Rhodes et al.(2024) <doi:10 [...truncated...]
Author: Elizabeth Allman [aut], Hector Banos [aut], Jonathan Mitchell [aut], Kristina Wicke [aut], John Rhodes [aut, cre]
Maintainer: John Rhodes <j.rhodes@alaska.edu>

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Package mlS3 updated to version 0.1.1 with previous version 0.1.0 dated 2026-04-28

Title: Unified S3 Interface to Machine Learning Models
Description: Provides a unified and consistent S3 interface for training and predicting with a variety of machine learning models in R. The package wraps popular algorithms (e.g., from 'glmnet', 'lightgbm', 'ranger', 'e1071', and 'caret') under a common workflow based on simple wrap_*() and predict() functions, allowing users to switch between models without changing their code structure. It supports both classification and regression tasks and facilitates rapid experimentation, benchmarking, and comparison of models. By abstracting away package-specific APIs while preserving flexibility in parameter specification, the package streamlines machine learning workflows and promotes reproducibility.
Author: T. Moudiki [aut, cre]
Maintainer: T. Moudiki <thierry.moudiki@gmail.com>

Diff between mlS3 versions 0.1.0 dated 2026-04-28 and 0.1.1 dated 2026-05-28

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Package geogrid updated to version 0.1.3 with previous version 0.1.2 dated 2023-08-19

Title: Turn Geospatial Polygons into Regular or Hexagonal Grids
Description: Turn irregular polygons (such as geographical regions) into regular or hexagonal grids. This package enables the generation of regular (square) and hexagonal grids through the package 'sp' and then assigns the content of the existing polygons to the new grid using the Hungarian algorithm, Kuhn (1955) (<doi:10.1007/978-3-540-68279-0_2>). This prevents the need for manual generation of hexagonal grids or regular grids that are supposed to reflect existing geography.
Author: Joseph Bailey [aut, cph], Ryan Hafen [ctb, cre] , Jakub Nowosad [ctb] , Lars Simon Zehnder [ctb]
Maintainer: Ryan Hafen <rhafen@gmail.com>

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Package cards updated to version 0.8.0 with previous version 0.7.1 dated 2025-12-02

Title: Analysis Results Data
Description: Construct CDISC (Clinical Data Interchange Standards Consortium) compliant Analysis Results Data objects. These objects are used and re-used to construct summary tables, visualizations, and written reports. The package also exports utilities for working with these objects and creating new Analysis Results Data objects.
Author: Daniel D. Sjoberg [aut, cre] , Becca Krouse [aut], Emily de la Rua [aut] , Malan Bosman [aut] , F. Hoffmann-La Roche AG [cph, fnd], GlaxoSmithKline Research & Development Limited [cph]
Maintainer: Daniel D. Sjoberg <danield.sjoberg@gmail.com>

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Package bpgmm updated to version 1.3.1 with previous version 1.1.1 dated 2025-10-30

Title: Bayesian Model Selection Approach for Parsimonious Gaussian Mixture Models
Description: Model-based clustering using Bayesian parsimonious Gaussian mixture models. MCMC (Markov chain Monte Carlo) are used for parameter estimation. The RJMCMC (Reversible-jump Markov chain Monte Carlo) is used for model selection. GREEN et al. (1995) <doi:10.1093/biomet/82.4.711>.
Author: Yaoxiang Li [aut, cre], Xiang Lu [aut], Tanzy Love [aut]
Maintainer: Yaoxiang Li <liyaoxiang@outlook.com>

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Package antaresRead updated to version 3.0.1 with previous version 3.0.0 dated 2026-01-28

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

Diff between antaresRead versions 3.0.0 dated 2026-01-28 and 3.0.1 dated 2026-05-28

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Package seededlda updated to version 1.4.4 with previous version 1.4.3 dated 2025-09-28

Title: Seeded Sequential LDA for Topic Modeling
Description: Seeded Sequential LDA can classify sentences of texts into pre-define topics with a small number of seed words (Watanabe & Baturo, 2023) <doi:10.1177/08944393231178605>. Implements Seeded LDA (Lu et al., 2010) <doi:10.1109/ICDMW.2011.125> and Sequential LDA (Du et al., 2012) <doi:10.1007/s10115-011-0425-1> with the distributed LDA algorithm (Newman, et al., 2009) for parallel computing.
Author: Kohei Watanabe [aut, cre, cph], Phan Xuan-Hieu [aut, cph]
Maintainer: Kohei Watanabe <watanabe.kohei@gmail.com>

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Package forestSAS updated to version 2.0.5 with previous version 2.0.4 dated 2024-11-11

Title: Forest Spatial Structure Analysis Systems
Description: Recent years have seen significant interest in neighborhood-based structural parameters that effectively represent the spatial characteristics of tree populations and forest communities, and possess strong applicability for guiding forestry practices. This package provides valuable information that enhances our understanding and analysis of the fine-scale spatial structure of tree populations and forest stands. Reference: Yan L, Tan W, Chai Z, et al (2019) <doi:10.13323/j.cnki.j.fafu(nat.sci.).2019.03.007>.
Author: Zongzheng Chai [aut, cre]
Maintainer: Zongzheng Chai <chaizz@126.com>

Diff between forestSAS versions 2.0.4 dated 2024-11-11 and 2.0.5 dated 2026-05-28

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Package matahari (with last version 0.1.4) was removed from CRAN

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

2026-05-25 0.1.4
2020-02-06 0.1.3
2019-12-10 0.1.2
2019-10-09 0.1.1
2019-05-17 0.1.0

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Package spNNGP updated to version 1.0.2 with previous version 1.0.1 dated 2024-09-23

Title: Spatial Regression Models for Large Datasets using Nearest Neighbor Gaussian Processes
Description: Fits univariate Bayesian spatial regression models for large datasets using Nearest Neighbor Gaussian Processes (NNGP) detailed in Finley, Datta, Banerjee (2022) <doi:10.18637/jss.v103.i05>, Finley, Datta, Cook, Morton, Andersen, and Banerjee (2019) <doi:10.1080/10618600.2018.1537924>, and Datta, Banerjee, Finley, and Gelfand (2016) <doi:10.1080/01621459.2015.1044091>.
Author: Andrew Finley [aut, cre], Abhirup Datta [aut], Sudipto Banerjee [aut]
Maintainer: Andrew Finley <finleya@msu.edu>

Diff between spNNGP versions 1.0.1 dated 2024-09-23 and 1.0.2 dated 2026-05-28

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Package spBayes updated to version 0.4-9 with previous version 0.4-8 dated 2024-09-23

Title: Univariate and Multivariate Spatial-Temporal Modeling
Description: Fits univariate and multivariate spatio-temporal random effects models for point-referenced data using Markov chain Monte Carlo (MCMC). Details are given in Finley, Banerjee, and Gelfand (2015) <doi:10.18637/jss.v063.i13> and Finley and Banerjee <doi:10.1016/j.envsoft.2019.104608>.
Author: Andrew Finley [aut, cre], Sudipto Banerjee [aut]
Maintainer: Andrew Finley <finleya@msu.edu>

Diff between spBayes versions 0.4-8 dated 2024-09-23 and 0.4-9 dated 2026-05-28

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Package rxode2 updated to version 5.1.1 with previous version 5.0.2 dated 2026-03-20

Title: Facilities for Simulating from ODE-Based Models
Description: Facilities for running simulations from ordinary differential equation ('ODE') models, such as pharmacometrics and other compartmental models. A compilation manager translates the ODE model into C, compiles it, and dynamically loads the object code into R for improved computational efficiency. An event table object facilitates the specification of complex dosing regimens (optional) and sampling schedules. NB: The use of this package requires both C and Fortran compilers, for details on their use with R please see Section 6.3, Appendix A, and Appendix D in the "R Administration and Installation" manual. Also the code is mostly released under GPL. The 'VODE' and 'LSODA' are in the public domain. The information is available in the inst/COPYRIGHTS.
Author: Matthew L. Fidler [aut, cre] , Wenping Wang [aut], Alan Hindmarsh [ctb], Arun Srinivasan [ctb], Awad H. Al-Mohy [ctb], Bill Denney [ctb] , Cleve Moler [ctb], David Cooley [ctb], Drew Schmidt [ctb], Ernst Hairer [ctb], Gabriel Staples [ctb], Gerhard W [...truncated...]
Maintainer: Matthew L. Fidler <matthew.fidler@gmail.com>

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Package rvkstat updated to version 3.3.2 with previous version 3.2.0 dated 2021-10-18

Title: R Interface to API 'vk.com'
Description: Load data from vk.com api about your communiti users and views, ads performance, post on user wall and etc. For more information see API Documentation <https://vk.com/dev/first_guide>.
Author: Alexey Seleznev [aut, cre]
Maintainer: Alexey Seleznev <selesnow@gmail.com>

Diff between rvkstat versions 3.2.0 dated 2021-10-18 and 3.3.2 dated 2026-05-28

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Package MBA updated to version 0.1-3 with previous version 0.1-2 dated 2024-09-23

Title: Multilevel B-Spline Approximation
Description: Functions to interpolate irregularly and regularly spaced data using Multilevel B-spline Approximation (MBA). Functions call portions of the SINTEF Multilevel B-spline Library written by Øyvind Hjelle which implements methods developed by Lee, Wolberg and Shin (1997; <doi:10.1109/2945.620490>).
Author: Andrew Finley [aut, cre], Sudipto Banerjee [aut], Oeyvind Hjelle [aut], Roger Bivand [ctb]
Maintainer: Andrew Finley <finleya@msu.edu>

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Package gkwdist updated to version 1.1.4 with previous version 1.1.3 dated 2026-05-21

Title: Generalized Kumaraswamy Distribution Family
Description: Implements the five-parameter Generalized Kumaraswamy ('gkw') distribution proposed by 'Carrasco, Ferrari and Cordeiro (2010)' <doi:10.48550/arXiv.1004.0911> and its seven nested sub-families for modeling bounded continuous data on the unit interval (0,1). The 'gkw' distribution extends the Kumaraswamy distribution described by Jones (2009) <doi:10.1016/j.stamet.2008.04.001>. Provides density, distribution, quantile, and random generation functions, along with analytical log-likelihood, gradient, and Hessian functions implemented in 'C++' via 'RcppArmadillo' for maximum computational efficiency. Suitable for modeling proportions, rates, percentages, and indices exhibiting complex features such as asymmetry, or heavy tails and other shapes not adequately captured by standard distributions like simple Beta or Kumaraswamy.
Author: Jose Evandeilton Lopes [aut, cre]
Maintainer: Jose Evandeilton Lopes <evandeilton@gmail.com>

Diff between gkwdist versions 1.1.3 dated 2026-05-21 and 1.1.4 dated 2026-05-28

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Package gap updated to version 1.15.2 with previous version 1.15.1 dated 2026-05-24

Title: Genetic Analysis Package
Description: As first reported [Zhao, J. H. 2007. "gap: Genetic Analysis Package". J Stat Soft 23(8):1-18. <doi:10.18637/jss.v023.i08>], it is designed as an integrated package for genetic data analysis of both population and family data. Currently, it contains functions for sample size calculations of both population-based and family-based designs, probability of familial disease aggregation, kinship calculation, statistics in linkage analysis, and association analysis involving genetic markers including haplotype analysis with or without environmental covariates. Over years, the package has been developed in-between many projects hence also in line with the name (gap).
Author: Jing Hua Zhao [aut, cre] , Kurt Hornik [ctb], Brian Ripley [ctb], Uwe Ligges [ctb], Achim Zeileis [ctb]
Maintainer: Jing Hua Zhao <jinghuazhao@hotmail.com>

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Package dunn.test updated to version 1.4.0 with previous version 1.3.7 dated 2026-02-13

Title: Dunn's Test of Multiple Comparisons Using Rank Sums
Description: Computes Dunn's test (1964) for stochastic superiority and reports the results among multiple pairwise comparisons after a Kruskal-Wallis test for stochastic superiority among k groups (Kruskal and Wallis, 1952). 'dunn.test' makes k(k-1)/2 multiple pairwise comparisons based on Dunn's z-test-statistic approximations to the actual rank statistics. The null hypothesis for each pairwise comparison is that the probability of observing a randomly selected value from the first group that is larger than a randomly selected value from the second group equals one half; this null hypothesis corresponds to that of the Wilcoxon-Mann-Whitney rank-sum test. 'dunn.test' accounts for tied ranks.
Author: Alexis Dinno [aut, cre, cph]
Maintainer: Alexis Dinno <alexis.dinno@pdx.edu>

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Package DiscreteTests updated to version 0.4.1 with previous version 0.4.0 dated 2026-05-19

Title: Vectorised Computation of P-Values and Their Supports for Several Discrete Statistical Tests
Description: Provides vectorised functions for computing p-values of various common discrete statistical tests, as described e.g. in Agresti (2002) <doi:10.1002/0471249688>, including their distributions. Exact and approximate computation methods are provided. For exact ones, several procedures of determining two-sided p-values are included, which are outlined in more detail in Hirji (2006) <doi:10.1201/9781420036190>.
Author: Florian Junge [cre, aut] , Christina Kihn [aut], Sebastian Doehler [ctb] , Guillermo Durand [ctb]
Maintainer: Florian Junge <diso.fbmn@h-da.de>

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Package dataRetrieval updated to version 2.7.25 with previous version 2.7.24 dated 2026-03-31

Title: Retrieval Functions for USGS and EPA Hydrology and Water Quality Data
Description: Collection of functions to help retrieve U.S. Geological Survey and U.S. Environmental Protection Agency water quality and hydrology data from web services.
Author: Laura DeCicco [aut, cre] , Robert Hirsch [aut] , David Lorenz [aut], Jordan Read [ctb], Jordan Walker [ctb], Lindsay Platt [ctb], David Watkins [aut] , David Blodgett [aut] , Mike Johnson [aut] , Aliesha Krall [ctb] , Lee Stanish [ctb] , Joseph Zemme [...truncated...]
Maintainer: Laura DeCicco <ldecicco@usgs.gov>

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 man/read_waterdata_latest_daily.Rd        |   50 ++++--
 man/read_waterdata_metadata.Rd            |   20 ++
 man/read_waterdata_monitoring_location.Rd |   45 ++++-
 man/read_waterdata_parameter_codes.Rd     |   11 +
 man/read_waterdata_peaks.Rd               |only
 man/read_waterdata_ratings.Rd             |only
 man/read_waterdata_samples.Rd             |   30 ---
 man/read_waterdata_stats.Rd               |   23 ++
 man/read_waterdata_ts_meta.Rd             |   70 +++++---
 man/summarize_waterdata_samples.Rd        |   11 -
 man/whatWQPdata.Rd                        |   20 +-
 man/wqpSpecials.Rd                        |   32 ++--
 man/wqp_check_status.Rd                   |   12 -
 tests/testthat/test_waterdata_stats.R     |   29 +++
 tests/testthat/tests_general.R            |  240 +++++++++++-------------------
 tests/testthat/tests_imports.R            |  212 --------------------------
 tests/testthat/tests_nldi.R               |    1 
 tests/testthat/tests_userFriendly_fxns.R  |  157 +++++++++++--------
 vignettes/dataRetrieval.Rmd               |   28 +--
 85 files changed, 1842 insertions(+), 1878 deletions(-)

More information about dataRetrieval at CRAN
Permanent link

Package admiral updated to version 1.4.2 with previous version 1.4.1 dated 2026-02-03

Title: ADaM in R Asset Library
Description: A toolbox for programming Clinical Data Interchange Standards Consortium (CDISC) compliant Analysis Data Model (ADaM) datasets in R. ADaM datasets are a mandatory part of any New Drug or Biologics License Application submitted to the United States Food and Drug Administration (FDA). Analysis derivations are implemented in accordance with the "Analysis Data Model Implementation Guide" (CDISC Analysis Data Model Team, 2021, <https://www.cdisc.org/standards/foundational/adam>).
Author: Edoardo Mancini [aut, cre] , Stefan Bundfuss [aut] , Matt Bearham [aut], Arianna Cascone [aut] , Kristin Dahnert [aut], Jeffrey Dickinson [aut], Ross Farrugia [aut], Fanny Gautier [aut], Gordon Miller [aut], Lina Patil [aut], Jim Rothstein [aut] , Be [...truncated...]
Maintainer: Edoardo Mancini <edoardo.mancini@roche.com>

Diff between admiral versions 1.4.1 dated 2026-02-03 and 1.4.2 dated 2026-05-28

 DESCRIPTION                         |   19 
 MD5                                 |  346 +++++++++---------
 NEWS.md                             |    4 
 R/data.R                            |    2 
 R/derive_merged.R                   |    2 
 R/derive_var_extreme_flag.R         |    2 
 build/vignette.rds                  |binary
 inst/doc/generic.html               |    4 
 man/adjust_last_day_imputation.Rd   |   12 
 man/admiral-package.Rd              |    4 
 man/assert_date_imputation.Rd       |   12 
 man/assert_db_requirements.Rd       |   36 -
 man/assert_highest_imputation.Rd    |   30 -
 man/assert_parameters_argument.Rd   |   12 
 man/assert_terms.Rd                 |   24 -
 man/assert_time_imputation.Rd       |   12 
 man/basket_select.Rd                |   31 -
 man/call_derivation.Rd              |   24 -
 man/call_user_fun.Rd                |    6 
 man/censor_source.Rd                |   37 -
 man/chr2vars.Rd                     |    6 
 man/compute_age_years.Rd            |   14 
 man/compute_bmi.Rd                  |   14 
 man/compute_bsa.Rd                  |   21 -
 man/compute_dtf.Rd                  |   12 
 man/compute_duration.Rd             |   52 --
 man/compute_egfr.Rd                 |   42 --
 man/compute_framingham.Rd           |   48 --
 man/compute_map.Rd                  |   18 
 man/compute_qtc.Rd                  |   19 
 man/compute_qual_imputation.Rd      |   18 
 man/compute_qual_imputation_dec.Rd  |    6 
 man/compute_rr.Rd                   |    6 
 man/compute_scale.Rd                |   31 -
 man/compute_tmf.Rd                  |   19 
 man/consolidate_metadata.Rd         |   35 -
 man/convert_blanks_to_na.Rd         |    6 
 man/convert_date_to_dtm.Rd          |   50 --
 man/convert_dtc_to_dt.Rd            |   43 --
 man/convert_dtc_to_dtm.Rd           |   51 --
 man/convert_na_to_blanks.Rd         |    6 
 man/convert_xxtpt_to_hours.Rd       |  136 -------
 man/count_vals.Rd                   |   12 
 man/create_period_dataset.Rd        |   18 
 man/create_query_data.Rd            |   18 
 man/create_single_dose_dataset.Rd   |   62 ---
 man/date_source.Rd                  |   24 -
 man/default_qtc_paramcd.Rd          |    7 
 man/derivation_slice.Rd             |   12 
 man/derive_basetype_records.Rd      |   12 
 man/derive_expected_records.Rd      |   22 -
 man/derive_extreme_event.Rd         |  518 ---------------------------
 man/derive_extreme_records.Rd       |  622 --------------------------------
 man/derive_locf_records.Rd          |  195 ----------
 man/derive_param_bmi.Rd             |   55 --
 man/derive_param_bsa.Rd             |   62 ---
 man/derive_param_computed.Rd        |  382 -------------------
 man/derive_param_doseint.Rd         |   67 ---
 man/derive_param_exist_flag.Rd      |   64 ---
 man/derive_param_exposure.Rd        |   34 -
 man/derive_param_extreme_record.Rd  |   43 --
 man/derive_param_framingham.Rd      |   97 -----
 man/derive_param_map.Rd             |   56 --
 man/derive_param_qtc.Rd             |   56 --
 man/derive_param_rr.Rd              |   42 --
 man/derive_param_tte.Rd             |  587 ------------------------------
 man/derive_param_wbc_abs.Rd         |   52 --
 man/derive_summary_records.Rd       |  333 -----------------
 man/derive_var_age_years.Rd         |   25 -
 man/derive_var_analysis_ratio.Rd    |   24 -
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 man/derive_var_base.Rd              |   30 -
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 man/derive_var_extreme_dt.Rd        |   37 -
 man/derive_var_extreme_dtm.Rd       |   37 -
 man/derive_var_extreme_flag.Rd      |  413 ---------------------
 man/derive_var_joined_exist_flag.Rd |  627 --------------------------------
 man/derive_var_merged_ef_msrc.Rd    |   56 --
 man/derive_var_merged_exist_flag.Rd |   65 ---
 man/derive_var_merged_summary.Rd    |   42 --
 man/derive_var_nfrlt.Rd             |  627 --------------------------------
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 man/derive_var_pchg.Rd              |    6 
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 man/derive_vars_extreme_event.Rd    |   60 ---
 man/derive_vars_joined.Rd           |  689 ------------------------------------
 man/derive_vars_joined_summary.Rd   |  359 ------------------
 man/derive_vars_merged.Rd           |  363 ------------------
 man/derive_vars_merged_lookup.Rd    |   74 ---
 man/derive_vars_merged_summary.Rd   |   42 --
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 man/derive_vars_query.Rd            |   12 
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 man/event_source.Rd                 |   31 -
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 man/flag_event.Rd                   |   21 -
 man/format.basket_select.Rd         |   12 
 man/format_imputed_dtc.Rd           |    6 
 man/get_admiral_option.Rd           |    6 
 man/get_dt_dtm_range.Rd             |   12 
 man/get_flagged_records.Rd          |   25 -
 man/get_highest_imputation_level.Rd |   12 
 man/get_hori_data.Rd                |   33 -
 man/get_imputation_target_date.Rd   |   10 
 man/get_imputation_target_time.Rd   |    4 
 man/get_imputation_targets.Rd       |   14 
 man/get_joined_data.Rd              |   84 ----
 man/get_joined_sub_data.Rd          |   62 ---
 man/get_partialdatetime.Rd          |   12 
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 man/get_vars_query.Rd               |   12 
 man/impute_date_time.Rd             |   12 
 man/impute_dtc_dt.Rd                |   43 --
 man/impute_dtc_dtm.Rd               |   51 --
 man/is_partial_datetime.Rd          |    6 
 man/list_all_templates.Rd           |    6 
 man/list_tte_source_objects.Rd      |    6 
 man/max_cond.Rd                     |   12 
 man/min_cond.Rd                     |   12 
 man/negate_vars.Rd                  |    6 
 man/params.Rd                       |    6 
 man/pipe.Rd                         |   12 
 man/print.adam_templates.Rd         |   12 
 man/print.duplicates.Rd             |   12 
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 man/print_named_list.Rd             |   12 
 man/propagate_na_values.Rd          |    6 
 man/query.Rd                        |   37 -
 man/records_source.Rd               |   20 -
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 man/restrict_imputed_dtc_dt.Rd      |   27 -
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 man/set_admiral_options.Rd          |   18 
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 man/tte_source.Rd                   |   37 -
 man/use_ad_template.Rd              |   30 -
 man/validate_basket_select.Rd       |    6 
 man/validate_query.Rd               |    6 
 man/yn_to_numeric.Rd                |    6 
 174 files changed, 1014 insertions(+), 11140 deletions(-)

More information about admiral at CRAN
Permanent link

Package rChEA3 updated to version 1.0.1 with previous version 0.2.0 dated 2025-10-15

Title: R Client for the 'ChEA3' Transcription Factor Enrichment API
Description: Interface to the 'ChEA3' transcription factor enrichment API. 'ChEA3' integrates evidence from ChIP-seq, co-expression, and literature resources to prioritize transcription factors regulating a given set of genes. This package provides convenient R functions to query the API, retrieve ranked results across collections (including integrated scores), and standardize output for downstream analysis in R/Bioconductor workflows. See <https://maayanlab.cloud/chea3/> or Keenan (2019) <doi:10.1093/nar/gkz446> for further details.
Author: Christophe Tav [aut, cre]
Maintainer: Christophe Tav <christophe.tav@gmail.com>

Diff between rChEA3 versions 0.2.0 dated 2025-10-15 and 1.0.1 dated 2026-05-28

 DESCRIPTION          |    8 +++---
 MD5                  |   24 +++++++++----------
 NEWS.md              |   19 +++++++++++++--
 R/queryChEA3.R       |   21 ++++++++++++++--
 README.md            |   38 +++++++++++++++++++++++++++---
 build/partial.rdb    |binary
 build/vignette.rds   |binary
 inst/doc/rChEA3.R    |   14 +++++++++++
 inst/doc/rChEA3.Rmd  |   29 +++++++++++++++++++++++
 inst/doc/rChEA3.html |   64 +++++++++++++++++++++++++++++++++++++--------------
 man/queryChEA3.Rd    |   20 +++++++++++++++
 man/today.Rd         |    2 -
 vignettes/rChEA3.Rmd |   29 +++++++++++++++++++++++
 13 files changed, 224 insertions(+), 44 deletions(-)

More information about rChEA3 at CRAN
Permanent link


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