Mon, 16 Mar 2026

Package wrGraph updated to version 1.3.13 with previous version 1.3.12 dated 2026-03-09

Title: Graphics in the Context of Analyzing High-Throughput Data
Description: Additional options for making graphics in the context of analyzing high-throughput data are available here. This includes automatic segmenting of the current device (eg window) to accommodate multiple new plots, automatic checking for optimal location of legends in plots, small histograms to insert as legends, histograms re-transforming axis labels to linear when plotting log2-transformed data, a violin-plot <doi:10.1080/00031305.1998.10480559> function for a wide variety of input-formats, principal components analysis (PCA) <doi:10.1080/14786440109462720> with bag-plots <doi:10.1080/00031305.1999.10474494> to highlight and compare the center areas for groups of samples, generic MA-plots (differential- versus average-value plots) <doi:10.1093/nar/30.4.e15>, staggered count plots and generation of mouse-over interactive html pages.
Author: Wolfgang Raffelsberger [aut, cre]
Maintainer: Wolfgang Raffelsberger <w.raffelsberger@gmail.com>

Diff between wrGraph versions 1.3.12 dated 2026-03-09 and 1.3.13 dated 2026-03-16

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Package trud updated to version 0.2.1 with previous version 0.2.0 dated 2025-08-18

Title: Query the 'NHS TRUD API'
Description: Provides a convenient R interface to the 'National Health Service NHS Technology Reference Update Distribution (TRUD) API', allowing users to list available releases for their subscribed items, retrieve metadata, and download release files. For more information on the API, see <https://isd.digital.nhs.uk/trud/users/guest/filters/0/api>.
Author: Alasdair Warwick [aut, cre, cph] , Robert Luben [aut] , Abraham Olvera-Barrios [aut] , Chuin Ying Ung [aut] , Jon Clayden [rev] , Alexandros Kouretsis [rev]
Maintainer: Alasdair Warwick <alasdair.warwick.19@ucl.ac.uk>

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Package tsqn updated to version 1.2.0 with previous version 1.0.0 dated 2017-03-29

Title: Applications of the Qn Estimator to Time Series (Univariate and Multivariate)
Description: Time Series Qn is a package with applications of the Qn estimator of Rousseeuw and Croux (1993) <doi:10.1080/01621459.1993.10476408> to univariate and multivariate Time Series in time and frequency domains. More specifically, the robust estimation of autocorrelation or autocovariance matrix functions from Ma and Genton (2000, 2001) <doi:10.1111/1467-9892.00203>, <doi:10.1006/jmva.2000.1942> and Cotta (2017) <doi:10.13140/RG.2.2.14092.10883> are provided. The robust pseudo-periodogram of Molinares et. al. (2009) <doi:10.1016/j.jspi.2008.12.014> is also given. This packages also provides the M-estimator of the long-memory parameter d based on the robustification of the GPH estimator proposed by Reisen et al. (2017) <doi:10.1016/j.jspi.2017.02.008>.
Author: Higor Cotta [aut, cre], Valderio Reisen [aut], Pascal Bondon [aut], Celine Levy-Leduc [aut]
Maintainer: Higor Cotta <cotta.higor@gmail.com>

Diff between tsqn versions 1.0.0 dated 2017-03-29 and 1.2.0 dated 2026-03-16

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Package tidyquant updated to version 1.0.12 with previous version 1.0.11 dated 2025-02-13

Title: Tidy Quantitative Financial Analysis
Description: Bringing business and financial analysis to the 'tidyverse'. The 'tidyquant' package provides a convenient wrapper to various 'xts', 'zoo', 'quantmod', 'TTR' and 'PerformanceAnalytics' package functions and returns the objects in the tidy 'tibble' format. The main advantage is being able to use quantitative functions with the 'tidyverse' functions including 'purrr', 'dplyr', 'tidyr', 'ggplot2', 'lubridate', etc. See the 'tidyquant' website for more information, documentation and examples.
Author: Matt Dancho [aut, cre], Davis Vaughan [aut]
Maintainer: Matt Dancho <mdancho@business-science.io>

Diff between tidyquant versions 1.0.11 dated 2025-02-13 and 1.0.12 dated 2026-03-16

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Package btw updated to version 1.2.0 with previous version 1.1.0 dated 2025-12-22

Title: A Toolkit for Connecting R and Large Language Models
Description: A complete toolkit for connecting 'R' environments with Large Language Models (LLMs). Provides utilities for describing 'R' objects, package documentation, and workspace state in plain text formats optimized for LLM consumption. Supports multiple workflows: interactive copy-paste to external chat interfaces, programmatic tool registration with 'ellmer' chat clients, batteries-included chat applications via 'shinychat', and exposure to external coding agents through the Model Context Protocol. Project configuration files enable stable, repeatable conversations with project-specific context and preferred LLM settings.
Author: Garrick Aden-Buie [aut, cre] , Simon Couch [aut] , Joe Cheng [aut], Posit Software, PBC [cph, fnd], Google [cph] , Microsoft [cph] , Jamie Perkins [cph]
Maintainer: Garrick Aden-Buie <garrick@adenbuie.com>

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Package tidysynthesis updated to version 0.1.3 with previous version 0.1.2 dated 2025-11-11

Title: A Common API for Synthesizing Data
Description: A system built on 'tidymodels' for generating synthetic tabular data. We provide tools for ordering a sequential synthesis, feature and target engineering, sampling, hyperparameter tuning, enforcing constraints, and adding extra noise during a synthesis.
Author: Aaron R. Williams [aut, cre] , Kyle Ueyama [aut], Gabe Morrison [aut] , Jeremy Seeman [aut] , Elyse McFalls [ctb], Claire Morton [ctb], Livia Mucciolo [ctb], Madeline Pickens [ctb], Noah Zwiefel [ctb], The Urban Institute [cph]
Maintainer: Aaron R. Williams <awilliams@urban.org>

Diff between tidysynthesis versions 0.1.2 dated 2025-11-11 and 0.1.3 dated 2026-03-16

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More information about tidysynthesis at CRAN
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New package tvrmst with initial version 0.0.6
Package: tvrmst
Title: Time-Varying Restricted Mean Survival Time from Survival Matrices
Version: 0.0.6
Author: Imad EL BADISY [aut, cre]
Maintainer: Imad EL BADISY <elbadisyimad@gmail.com>
Description: Utilities for restricted mean survival time (RMST) and time-varying restricted mean survival time quantities computed from survival curves provided on a time grid. The package is model-agnostic and accepts only a time vector and survival matrices, returning RMST-based quantities and bootstrap summaries. For restricted mean survival time methodology, see Royston and Parmar (2013) <doi:10.1186/1471-2288-13-152>.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: stats
Suggests: ggplot2, survival, testthat (>= 3.0.0), roxygen2 (>= 7.0.0)
NeedsCompilation: no
Packaged: 2026-03-11 15:19:35 UTC; imad-el-badisy
Repository: CRAN
Date/Publication: 2026-03-16 19:40:02 UTC

More information about tvrmst at CRAN
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New package snakeplot with initial version 0.3.0
Package: snakeplot
Title: Serpentine Plots for Long Timeline, Sequential and Survey Data
Version: 0.3.0
Description: Visualize long timelines, extended sequences and temporally chained survey responses and experience sampling data using intuitive serpentine (snake) plots. Supports distribution bars, tick-mark plots, inter-item correlation arcs, faceted multi-construct panels, and daily time-of-day positioning for ecological momentary assessment data.
License: MIT + file LICENSE
Depends: R (>= 3.5.0)
Imports: graphics, grDevices, stats
LazyData: true
URL: https://github.com/mohsaqr/snakeplot
BugReports: https://github.com/mohsaqr/snakeplot/issues
Encoding: UTF-8
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-03-11 14:44:23 UTC; mohammedsaqr
Author: Mohammed Saqr [aut, cre, cph], Sonsoles Lopez-Pernas [aut]
Maintainer: Mohammed Saqr <saqr@saqr.me>
Repository: CRAN
Date/Publication: 2026-03-16 19:30:03 UTC

More information about snakeplot at CRAN
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New package scimetr with initial version 1.2.0
Package: scimetr
Title: Analysis of Scientific Publication Data with R
Version: 1.2.0
Date: 2026-03-01
Description: Tools for quantitative research in scientometrics and bibliometrics. This package provides routines for importing bibliographic data from Clarivate Web of Science (<https://www.webofscience.com/wos/>) and performing bibliometric analysis.
Depends: R (>= 4.1.0), graphics
Imports: dplyr, tidyr, stringr, stringi, scales, ggplot2, rlang, openxlsx
Suggests: DT, rmarkdown, knitr
License: GPL (>= 2)
URL: https://rubenfcasal.github.io/scimetr/, https://github.com/rubenfcasal/scimetr/
BugReports: https://github.com/rubenfcasal/scimetr/issues/
Encoding: UTF-8
VignetteBuilder: knitr
LazyData: true
NeedsCompilation: no
Packaged: 2026-03-11 19:22:35 UTC; ruben
Author: Ruben Fernandez-Casal [aut, cre] , Borja Lafuente-Rego [aut] , Maria Jose Lombardia [aut] , Javier Tarrio-Saavedra [aut] , Julian Costa-Bouzas [aut] , Yesica Fernandez-Ramos [ctb], Guillermo Lopez-Taboada [ctb]
Maintainer: Ruben Fernandez-Casal <rubenfcasal@gmail.com>
Repository: CRAN
Date/Publication: 2026-03-16 20:00:02 UTC

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Package robscale updated to version 0.2.1 with previous version 0.1.5 dated 2026-03-09

Title: Accelerated Estimation of Robust Location and Scale
Description: Estimates robust location and scale parameters using platform-specific Single Instruction, Multiple Data (SIMD) vectorization and Intel Threading Building Blocks (TBB) for parallel processing. Implements a novel variance-weighted ensemble estimator that adaptively combines all available statistics. Included methods feature logistic M-estimators, the estimators of Rousseeuw and Croux (1993), the Gini mean difference, the scaled Median Absolute Deviation (MAD), the scaled Interquartile Range (IQR), and unbiased standard deviations. Achieves substantial speedups over existing implementations through an 'Rcpp' backend and a unified dispatcher that automatically selects the optimal estimator based on sample size.
Author: Dennis Alexis Valin Dittrich [aut, cre, cph]
Maintainer: Dennis Alexis Valin Dittrich <davd@economicscience.net>

Diff between robscale versions 0.1.5 dated 2026-03-09 and 0.2.1 dated 2026-03-16

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 robscale-0.2.1/robscale/R/qn.R                                    |   42 
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 robscale-0.2.1/robscale/R/sn.R                                    |   42 
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 robscale-0.2.1/robscale/configure                                 |   85 
 robscale-0.2.1/robscale/inst/CITATION                             |   28 
 robscale-0.2.1/robscale/inst/WORDLIST                             |  946 ----------
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 robscale-0.2.1/robscale/src/Makevars.in                           |    4 
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 robscale-0.2.1/robscale/src/RcppExports.cpp                       |  129 +
 robscale-0.2.1/robscale/src/adm.cpp                               |   37 
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 robscale-0.2.1/robscale/src/qnsn_dispatcher.h                     |   17 
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 robscale-0.2.1/robscale/src/qnsn_sort_utils.h                     |   15 
 robscale-0.2.1/robscale/src/rob_loc.cpp                           |   87 
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 83 files changed, 1490 insertions(+), 1546 deletions(-)

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New package ROCModels with initial version 1.0.0
Package: ROCModels
Title: ROC Models and AUC Estimation
Version: 1.0.0
Description: The receiver operating characteristic (ROC) curve is one of the most widely used tools for evaluating diagnostic and prognostic biomarkers across diverse scientific fields, particularly in medicine. Despite its ubiquity, ROC estimation and testing methods differ substantially in their assumptions and resulting curve properties. This package provides a unified framework for constructing, visualizing, and comparing parametric, nonparametric, semiparametric, and Bayesian ROC curves. 'ROCModels' helps researchers identify and implement ROC inference methods most suitable for their data. See the accompanying vignette 'ROCModels_Package_Doc' for a detailed introduction. Alonzo, T. A., and Pepe, M. S. (2002) <doi: 10.1093/biostatistics/3.3.421>, Andrews, D. F., and Herzberg, A. M. (1985) <doi: 10.1007/978-1-4612-5098-2>, Bamber, D. (1975) <doi: 10.1016/0022-2496(75)90001-2>, Cox, D. R. (1972) <doi:10.1111/j.2517-6161.1972.tb00899.x>, Cox, D. R. (1975) <doi: 10.1093/ [...truncated...]
License: MIT + file LICENSE
Encoding: UTF-8
Imports: ggplot2, kedd, dplyr, survival, nleqslv, HDInterval, ROCit, doParallel, foreach, pbivnorm, nor1mix, parallel, readr, MASS, doRNG
Depends: R (>= 3.5)
LazyData: true
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-03-11 18:31:53 UTC; rsn11
Author: Ruhul Ali Khan [aut], Ruhul Ali Khan [aut, cre], Raja Sanjeev Kumar Nakka [aut], Musie Ghebremichael [aut]
Maintainer: Ruhul Ali Khan <ruhulali.khan@gmail.com>
Repository: CRAN
Date/Publication: 2026-03-16 19:50:13 UTC

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Package readaec updated to version 0.1.2 with previous version 0.1.1 dated 2026-03-10

Title: Access Australian Electoral Commission Data
Description: Provides clean, tidy access to Australian Electoral Commission (AEC) federal election data. Includes results for the House of Representatives and Senate from 2007 onwards, at both division and polling place level. Data is downloaded directly from the AEC <https://results.aec.gov.au> on first use and cached locally for subsequent calls.
Author: Charles Coverdale [aut, cre]
Maintainer: Charles Coverdale <charlesfcoverdale@gmail.com>

Diff between readaec versions 0.1.1 dated 2026-03-10 and 0.1.2 dated 2026-03-16

 DESCRIPTION                |    8 ++++----
 MD5                        |   42 +++++++++++++++++++++---------------------
 NEWS.md                    |    7 +++++++
 R/candidates.R             |    8 ++++++++
 R/house.R                  |   12 ++++++++++++
 R/senate.R                 |    2 ++
 R/swing.R                  |    2 ++
 R/utils.R                  |    4 +++-
 README.md                  |   16 +++++++++++-----
 man/clear_cache.Rd         |    2 ++
 man/get_candidates.Rd      |    2 ++
 man/get_enrolment.Rd       |    2 ++
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 man/get_members_elected.Rd |    2 ++
 man/get_polling_places.Rd  |    2 ++
 man/get_senate.Rd          |    2 ++
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 man/get_tpp_by_booth.Rd    |    2 ++
 man/get_turnout.Rd         |    2 ++
 22 files changed, 96 insertions(+), 31 deletions(-)

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New package r4sub with initial version 0.1.0
Package: r4sub
Title: Easily Install and Load the R4SUB Ecosystem
Version: 0.1.0
Description: The 'r4sub' package is a meta-package that installs and loads core packages of the R4SUB (R for Regulatory Submission) clinical submission readiness ecosystem. Loading 'r4sub' attaches 'r4subcore', 'r4subtrace', 'r4subscore', 'r4subrisk', 'r4subdata', and 'r4subprofile'.
License: MIT + file LICENSE
URL: https://github.com/R4SUB/r4sub
BugReports: https://github.com/R4SUB/r4sub/issues
Depends: R (>= 4.2)
Imports: cli, r4subcore, r4subdata, r4subprofile, r4subrisk, r4subscore, r4subtrace, rlang, tibble, utils
Suggests: testthat (>= 3.0.0)
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-03-06 12:15:09 UTC; aeroe
Author: Pawan Rama Mali [aut, cre, cph]
Maintainer: Pawan Rama Mali <prm@outlook.in>
Repository: CRAN
Date/Publication: 2026-03-16 19:20:02 UTC

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Package mixedBayes updated to version 0.2.3 with previous version 0.2.2 dated 2026-03-15

Title: Bayesian Longitudinal Regularized Quantile Mixed Model
Description: With high-dimensional omics features, repeated measure ANOVA leads to longitudinal gene-environment interaction studies that have intra-cluster correlations, outlying observations and structured sparsity arising from the ANOVA design. In this package, we have developed robust sparse Bayesian mixed effect models tailored for the above studies (Fan et al. (2025) <doi:10.1093/jrsssc/qlaf027>). An efficient Gibbs sampler has been developed to facilitate fast computation. The Markov chain Monte Carlo algorithms of the proposed and alternative methods are efficiently implemented in 'C++'. The development of this software package and the associated statistical methods have been partially supported by an Innovative Research Award from Johnson Cancer Research Center, Kansas State University.
Author: Kun Fan [aut, cre], Shejuty Devnath [aut], Cen Wu [aut]
Maintainer: Kun Fan <kfan@ksu.edu>

Diff between mixedBayes versions 0.2.2 dated 2026-03-15 and 0.2.3 dated 2026-03-16

 DESCRIPTION               |    8 +--
 MD5                       |   78 ++++++++++++++---------------
 NEWS.md                   |    6 ++
 R/GE.R                    |   10 +++
 R/LONBGLSS.R              |   39 +-------------
 R/LONBGLSS_1.R            |   37 --------------
 R/LONRBGLSS.R             |   36 -------------
 R/LONRBGLSS_1.R           |   37 --------------
 R/RcppExports.R           |   28 +++++-----
 R/data.R                  |   14 +++--
 R/mixedBayes-package.R    |    4 -
 R/mixedBayes.R            |  121 ++++++++++++++++++++++++++++++++++++----------
 R/predict_mixedBayes.R    |   37 +++++++++-----
 R/reformat.R              |   41 +++++++++++----
 R/selection.R             |    7 +-
 README.md                 |    8 +--
 man/GE.Rd                 |    4 -
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 man/mixedBayes-package.Rd |    4 -
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 man/reformat.Rd           |    4 -
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 src/BGL.cpp               |   51 ++++++++++---------
 src/BGL2.cpp              |   77 ++++++++++++++---------------
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 src/BGLSS2.cpp            |   80 +++++++++++++++---------------
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 src/RBL2.cpp              |   67 ++++++++++++-------------
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 src/RcppExports.cpp       |   56 ++++++++++-----------
 40 files changed, 796 insertions(+), 799 deletions(-)

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New package lumbermark with initial version 0.9.0
Package: lumbermark
Title: Resistant Clustering via Chopping Up Mutual Reachability Minimum Spanning Trees
Version: 0.9.0
Date: 2026-03-09
Description: Implements a fast and resistant divisive clustering algorithm which identifies a specified number of clusters: 'lumbermark' iteratively chops off sizeable limbs that are joined by protruding segments of a dataset's mutual reachability minimum spanning tree; see Gagolewski (2026) <https://lumbermark.gagolewski.com/>. The use of a mutual reachability distance pulls peripheral points farther away from each other. When combined with the 'deadwood' package, it can act as an outlier detector. The 'Python' version of 'lumbermark' is available via 'PyPI'.
BugReports: https://github.com/gagolews/lumbermark/issues
URL: https://lumbermark.gagolewski.com/, https://clustering-benchmarks.gagolewski.com/, https://github.com/gagolews/lumbermark
License: AGPL-3
Imports: Rcpp, deadwood
Suggests: datasets,
LinkingTo: Rcpp
Encoding: UTF-8
SystemRequirements: OpenMP
NeedsCompilation: yes
Packaged: 2026-03-10 09:48:46 UTC; gagolews
Author: Marek Gagolewski [aut, cre, cph]
Maintainer: Marek Gagolewski <marek@gagolewski.com>
Repository: CRAN
Date/Publication: 2026-03-16 19:10:02 UTC

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New package golden with initial version 0.0.1
Package: golden
Title: Framework for Patient-Level Microsimulation of Risk Factor Trajectories & Hazard-Based Events
Version: 0.0.1
Date: 2026-03-04
Description: Fast, flexible, patient-level microsimulation. Time-stepped simulation with a 'C++' back-end from user-supplied initial population, trajectories, hazards, and corresponding event transitions. User-defined aggregate time series histories are returned together with the final population. Designed for simulation of chronic diseases with continuous and evolving risk factors, but could easily be applied more generally.
License: MIT + file LICENSE
Imports: Rcpp (>= 1.1.0), data.table
LinkingTo: Rcpp
Suggests: testthat (>= 3.0.0), SciViews, knitr, rmarkdown, ggplot2
Depends: R (>= 3.5)
LazyData: true
Encoding: UTF-8
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2026-03-11 15:06:54 UTC; runner
Author: Pete Dodd [aut, cre] , Robert Chisholm [aut] , University of Sheffield [cph], Horizon Europe [fnd]
Maintainer: Pete Dodd <p.j.dodd@sheffield.ac.uk>
Repository: CRAN
Date/Publication: 2026-03-16 19:50:02 UTC

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New package ebx with initial version 1.0.0
Package: ebx
Title: 'Earth Blox' API Client
Version: 1.0.0
Maintainer: Neil Mayo <n.mayo@earthblox.io>
Description: Client library for the 'Earth Blox' API (<https://api.earthblox.io/>). Provides authentication and endpoints for interacting with 'Earth Blox' geospatial analytics services. Compatible with 'Shiny' applications.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.0.0)
Imports: httr2 (>= 1.0.0), jsonlite (>= 1.7.0), R6 (>= 2.5.0), base64enc (>= 0.1-3)
Suggests: testthat (>= 3.0.0), withr (>= 2.5.0), shiny (>= 1.7.0)
NeedsCompilation: no
Packaged: 2026-03-11 12:26:05 UTC; nmayo
Author: Neil Mayo [aut, cre], Quosient Ltd. [cph]
Repository: CRAN
Date/Publication: 2026-03-16 19:10:07 UTC

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New package easyEWAS with initial version 1.0.1
Package: easyEWAS
Title: Perform and Visualize EWAS Analysis
Version: 1.0.1
Description: Tools for conducting epigenome-wide association studies (EWAS) and visualizing results. Users provide sample metadata and methylation matrices to run EWAS with linear models, linear mixed-effects models, or Cox models. The package supports downstream visualization, bootstrap validation, enrichment analysis, batch effect correction, and differentially methylated region (DMR) analysis with optional parallel computing. Methods are described in Wang et al. (2025) <doi:10.1093/bioadv/vbaf026>, Johnson et al. (2007) <doi:10.1093/biostatistics/kxj037>, and Peters et al. (2015) <doi:10.1186/1756-8935-8-6>.
License: GPL (>= 3)
URL: https://github.com/ytwangZero/easyEWAS, https://easyewas-tutorial.github.io/
BugReports: https://github.com/ytwangZero/easyEWAS/issues
Encoding: UTF-8
Imports: R6, boot, CMplot, ddpcr, doParallel, dplyr, foreach, lmerTest, magrittr, parallel, readxl, survival, tictoc, vroom, withr, R.utils, lubridate
Suggests: AnnotationHub, ExperimentHub, DMRcate, sva, BiocParallel, clusterProfiler, enrichplot, org.Hs.eg.db, knitr, rmarkdown
Depends: R (>= 4.4.0)
LazyData: true
NeedsCompilation: no
Packaged: 2026-03-11 09:43:59 UTC; yuting
Author: Yuting Wang [aut, cre], Xu Gao [aut]
Maintainer: Yuting Wang <ytwang@pku.edu.cn>
Repository: CRAN
Date/Publication: 2026-03-16 19:10:14 UTC

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New package dyadicMarkov with initial version 0.1.0
Package: dyadicMarkov
Title: Pattern Identification for Dyadic Sequences Using Transition Matrices
Version: 0.1.0
Description: Provides methods for analyzing dyadic interaction sequences using transition matrices within the Actor-Partner Interdependence Model. The package supports the computation of empirical transition counts, maximum likelihood estimation of transition probabilities and identification of interaction patterns in univariate and bivariate dyadic interaction sequences.
License: MIT + file LICENSE
URL: https://github.com/BoellenruecherM/dyadicMarkov-public
BugReports: https://github.com/BoellenruecherM/dyadicMarkov-public/issues
Encoding: UTF-8
Language: en-US
Depends: R (>= 4.1.0)
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-03-11 16:44:22 UTC; bolle
Author: Mattia Boellenruecher [aut, cre, cph], Megane Bollenrucher [aut], Jean-Philippe Antonietti [aut]
Maintainer: Mattia Boellenruecher <mattia.boellenruecher@student.unisg.ch>
Repository: CRAN
Date/Publication: 2026-03-16 19:50:08 UTC

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New package a5R with initial version 0.2.0
Package: a5R
Title: 'A5' Discrete Global Grid System
Version: 0.2.0
Description: Bindings for the "A5 geospatial index" <https://a5geo.org/>. 'A5' partitions the Earth's surface into pentagonal cells across 31 resolution levels using an equal-area projection onto a dodecahedron. Provides functions for indexing coordinates to cells, traversing the cell hierarchy, computing cell boundaries, and compacting/uncompacting cell sets. Powered by the 'A5' 'Rust' crate via 'extendr'.
License: Apache License (>= 2)
URL: https://github.com/belian-earth/a5R, https://belian-earth.github.io/a5R/
BugReports: https://github.com/belian-earth/a5R/issues
Depends: R (>= 4.2)
Imports: cli, rlang (>= 1.1.0), units, vctrs (>= 0.6.0), wk (>= 0.9.0)
Suggests: knitr, pillar, rmarkdown, sf, testthat (>= 3.0.0), tibble, withr
VignetteBuilder: knitr
SystemRequirements: Cargo (Rust's package manager), rustc
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2026-03-11 10:37:40 UTC; hugh
Author: Hugh Graham [aut, cre], belian.earth [cph]
Maintainer: Hugh Graham <hugh@belian.earth>
Repository: CRAN
Date/Publication: 2026-03-16 19:10:19 UTC

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New package WaveST with initial version 0.1.0
Package: WaveST
Title: Wavelet-Based Spatial Time Series Models
Version: 0.1.0
Maintainer: Dr. Ranjit Kumar Paul <ranjitstat@gmail.com>
Description: An integrated wavelet-based spatial time series modelling framework designed to enhance predictive accuracy under noisy and nonstationary conditions by jointly exploiting multi-resolution (wavelet) information and spatial dependence. The package implements WaveSARIMA() (Wavelet Based Spatial AutoRegressive Integrated Moving Average model using regression features with forecast::auto.arima()) and WaveSNN() (Wavelet Based Spatial Neural Network model using neuralnet with hyperparameter search). Both functions support spatial transformation via a user-supplied spatial matrix, lag feature construction, MODWT-based wavelet sub-series feature generation, time-ordered train/test splitting, and performance evaluation (Root Mean Square Error (RMSE), Mean Absolute Error (MAE), R-squared (R²), and Mean Absolute Percentage Error (MAPE)), returning fitted models and actual vs predicted values for train and test sets. The package has been developed using the algorithm of Paul et al. (2023) <doi:1 [...truncated...]
Encoding: UTF-8
Imports: forecast, stats, neuralnet, tsutils, wavelets
Suggests: devtools, roxygen2, usethis
License: GPL-3
NeedsCompilation: no
Packaged: 2026-03-11 05:54:57 UTC; YEASIN
Author: Dr. Md Yeasin [aut], Dr. Ranjit Kumar Paul [aut, cre], Akarsh Kumar Singh [aut]
Repository: CRAN
Date/Publication: 2026-03-16 18:50:02 UTC

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New package RenyiExtropy with initial version 0.4.0
Package: RenyiExtropy
Title: Entropy and Extropy Measures for Probability Distributions
Version: 0.4.0
Description: Provides functions to compute Shannon entropy, Renyi entropy, Tsallis entropy, and related extropy measures for discrete probability distributions. Includes joint and conditional entropy, KL divergence, Jensen-Shannon divergence, cross-entropy, normalized entropy, and Renyi extropy (including the conditional and maximum forms). All measures use the natural logarithm (nats). Useful for information theory, statistics, and machine learning applications.
License: MIT + file LICENSE
URL: https://github.com/itsmdivakaran/RenyiExtropy
BugReports: https://github.com/itsmdivakaran/RenyiExtropy/issues
Encoding: UTF-8
Depends: R (>= 3.5.0)
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-03-11 08:32:16 UTC; maheshdivakaran
Author: Divakaran Mahesh [aut, cre] , G Rajesh [aut] , Sreekumar Jayalekshmi [aut]
Maintainer: Divakaran Mahesh <itsmdivakaran@gmail.com>
Repository: CRAN
Date/Publication: 2026-03-16 19:00:08 UTC

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New package causalplot with initial version 0.2.1
Package: causalplot
Title: Create Publication-Ready Causal Diagrams
Version: 0.2.1
Description: Creates publication-ready causal diagrams using 'ggplot2'. Provides simple templates for common causal diagrams (e.g., mediating mechanisms and parallel pathways) with customizable labels, colors, fonts, and export-friendly defaults.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: ggforce, ggplot2, ggtext
Suggests: shiny, shinythemes
URL: https://github.com/sebastianvanbaalen/causalplot
BugReports: https://github.com/sebastianvanbaalen/causalplot/issues
NeedsCompilation: no
Packaged: 2026-03-11 06:55:23 UTC; sebastian
Author: Sebastian van Baalen [aut, cre, cph]
Maintainer: Sebastian van Baalen <sebastian.van-baalen@pcr.uu.se>
Repository: CRAN
Date/Publication: 2026-03-16 19:00:02 UTC

More information about causalplot at CRAN
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New package widr with initial version 0.1.0
Package: widr
Title: Interface to the World Inequality Database (WID)
Version: 0.1.0
Description: Interface to the World Inequality Database (WID) API <https://wid.world>. Downloads distributional national accounts data with filters for country, year, percentile, age group, and population type. Includes code validation and reference tables. Independent implementation unaffiliated with the World Inequality Lab (WIL) or the Paris School of Economics.
License: GPL-3
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: base64enc, jsonlite, digest, ggplot2, httr2, scales, tools, utils
Suggests: testthat (>= 3.0.0), covr, knitr, rmarkdown, withr
VignetteBuilder: knitr
URL: https://github.com/cherylisabella/widr
BugReports: https://github.com/cherylisabella/widr/issues
LazyData: true
NeedsCompilation: no
Packaged: 2026-03-10 18:39:50 UTC; Isabella
Author: Cheryl Isabella Lim [aut, cre]
Maintainer: Cheryl Isabella Lim <cheryl.academic@gmail.com>
Repository: CRAN
Date/Publication: 2026-03-16 16:40:02 UTC

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New package UnitMix with initial version 0.0.1
Package: UnitMix
Title: Detecting Measurement-Unit Errors via Gaussian Mixture Models
Version: 0.0.1
Description: Tools to detect and correct measurement-unit errors in multivariate numeric data using model-based clustering. Gaussian mixture models with user-defined translation vectors identify clusters of records that differ in scale or unit. Core functionality includes cluster assignment via the EM algorithm, error correction based on posterior probabilities and pairwise scatterplot visualizations. For more details see Di Zio, Guarnera and Luzi (2005) <https://www150.statcan.gc.ca/n1/en/pub/12-001-x/2005001/article/8087-eng.pdf>.
License: GPL-3
Encoding: UTF-8
Imports: mvtnorm
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-03-10 08:22:53 UTC; UTENTE
Author: Cristina Faricelli [aut, cre], Renato Magistro [aut]
Maintainer: Cristina Faricelli <cristina.faricelli@istat.it>
Repository: CRAN
Date/Publication: 2026-03-16 16:30:14 UTC

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New package rmedsem with initial version 1.0.0
Package: rmedsem
Title: Statistical Mediation Analysis for SEMs
Version: 1.0.0
Description: Conducts mediation analysis for structural equation models (SEM) estimated with 'lavaan', 'blavaan', 'cSEM', or 'modsem'. Implements the Baron and Kenny (1986) <doi:10.1037/0022-3514.51.6.1173> and Zhao, Lynch & Chen (2010) <doi:10.1086/651257> approaches to determine the presence and type of mediation. Supports covariance-based SEM, partial least squares SEM, Bayesian SEM, and moderated mediation models. Reports indirect effects with standard errors from Sobel, Delta, Monte-Carlo, and bootstrap methods, along with effect size measures (RIT, RID).
License: MIT + file LICENSE
Encoding: UTF-8
Imports: lavaan, mvtnorm, ggplot2, dplyr, purrr, stats
URL: https://github.com/ihrke/rmedsem, https://ihrke.github.io/rmedsem/
BugReports: https://github.com/ihrke/rmedsem/issues
Depends: R (>= 4.1.0)
LazyData: true
Suggests: blavaan, boot, cSEM, HDInterval, modsem, semPlot, rmarkdown, testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-03-10 21:13:16 UTC; mmi041
Author: Mehmet Mehmetoglu [aut] , Matthias Mittner [aut, cre] , Kjell Slupphaug [aut]
Maintainer: Matthias Mittner <matthias.mittner@uit.no>
Repository: CRAN
Date/Publication: 2026-03-16 16:50:02 UTC

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New package rangen with initial version 0.0.1
Package: rangen
Title: Random Number Generators and Utilities
Description: Provides a collection of random number generators for common and custom distributions, along with utility functions for sampling and simulation.
Version: 0.0.1
Date: 2026-03-09
Maintainer: Manos Papadakis <papadakm95@gmail.com>
License: GPL-3
Imports: Rcpp (>= 0.12.3)
LinkingTo: Rcpp (>= 0.12.3), RcppArmadillo, zigg
Depends: R (>= 3.5.0)
SystemRequirements: C++17
NeedsCompilation: yes
Packaged: 2026-03-09 11:05:25 UTC; epapadakis
Author: Manos Papadakis [aut, cre, cph], Michail Tsagris [ctb], Omar Alzeley [ctb]
Repository: CRAN
Date/Publication: 2026-03-16 16:30:02 UTC

More information about rangen at CRAN
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New package MultiSpline with initial version 0.1.1
Package: MultiSpline
Title: Spline-Based Nonlinear Modeling for Multilevel and Longitudinal Data
Version: 0.1.1
Description: Provides tools for fitting, predicting, and visualizing nonlinear relationships in single-level, multilevel, and longitudinal regression models. Nonlinear functional forms are represented using natural cubic splines from 'splines' and smooth terms from 'mgcv'. The package offers a unified interface for specifying nonlinear effects, interactions with time variables, random-intercept clustering structures, and additional linear covariates. Utilities are included to generate prediction grids and produce effect plots, facilitating interpretation and visualization of nonlinear relationships in applied regression workflows. The implementation builds on established methods for spline-based regression and mixed-effects modeling (Hastie and Tibshirani, 1990 <doi:10.1201/9780203738535>; Bates et al., 2015 <doi:10.18637/jss.v067.i01>; Wood, 2017 <doi:10.1201/9781315370279>). Applications include hierarchical and longitudinal data structures common in education, health, and socia [...truncated...]
Depends: R (>= 4.2.0)
Imports: stats, lme4, mgcv, dplyr, ggplot2, rlang
Suggests: lmerTest, knitr, rmarkdown, reformulas, testthat (>= 3.0.0)
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-US
NeedsCompilation: no
Packaged: 2026-03-10 13:44:08 UTC; Subir
Author: Subir Hait [aut, cre]
Maintainer: Subir Hait <haitsubi@msu.edu>
Repository: CRAN
Date/Publication: 2026-03-16 16:40:33 UTC

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New package mtgjsonsdk with initial version 0.1.0
Package: mtgjsonsdk
Title: 'DuckDB'-Backed Query Client for 'MTGJSON' Card Data
Version: 0.1.0
Description: Auto-downloads Parquet data from the 'MTGJSON' CDN and exposes the full Magic: The Gathering dataset through R6-based query interfaces backed by 'DuckDB'.
URL: https://mtgjson.com
BugReports: https://github.com/mtgjson/mtgjson-sdk-r/issues
Depends: R (>= 4.1.0)
License: MIT + file LICENSE
Encoding: UTF-8
Imports: R6, DBI, duckdb, httr2, jsonlite
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-03-10 03:02:26 UTC; zach
Author: Zachary Halpern [aut, cre], Robert Pratt [aut]
Maintainer: Zachary Halpern <zach@mtgjson.com>
Repository: CRAN
Date/Publication: 2026-03-16 16:20:02 UTC

More information about mtgjsonsdk at CRAN
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New package MSMGOptimizer with initial version 0.1.0
Package: MSMGOptimizer
Title: Mine Sustainability Modeling Group (MSMG) 'SimaPro' CSV Optimizer
Version: 0.1.0
Description: A 'Shiny' application for converting 'Excel'-based Life Cycle Inventory (LCI) data into 'SimaPro' CSV (Comma-Separated Values) format for use in Life Cycle Assessment (LCA) modeling. Developed by the Mine Sustainability Modeling Group (MSMG) at Missouri University of Science and Technology under NSF (National Science Foundation) funding (Award No. 2219086). See Pizzol (2022) <https://github.com/massimopizzol/Simapro-CSV-converter> for the original 'Python' implementation that inspired this tool.
URL: https://github.com/Duah-Philip/MSMGOptimizer
BugReports: https://github.com/Duah-Philip/MSMGOptimizer/issues
Depends: R (>= 4.0.0)
License: Apache License (>= 2)
Encoding: UTF-8
Imports: shiny (>= 1.10.0), shinydashboard (>= 0.7.3), readxl (>= 1.4.5), dplyr (>= 1.1.0), DT (>= 0.33), waiter (>= 0.2.5), htmltools (>= 0.5.8.1), zip (>= 2.3.0)
Suggests: knitr, rmarkdown, spelling, testthat (>= 3.0.0)
VignetteBuilder: knitr
Language: en-US
NeedsCompilation: no
Packaged: 2026-03-10 09:25:23 UTC; dpbxc
Author: Philip Duah [aut, cre], Kwame Awuah-Offei [aut]
Maintainer: Philip Duah <dpbxc@mst.edu>
Repository: CRAN
Date/Publication: 2026-03-16 16:30:19 UTC

More information about MSMGOptimizer at CRAN
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Package mlflow updated to version 3.10.1 with previous version 3.9.0 dated 2026-02-03

Title: Interface to 'MLflow'
Description: R interface to 'MLflow', open source platform for the complete machine learning life cycle, see <https://mlflow.org/>. This package supports installing 'MLflow', tracking experiments, creating and running projects, and saving and serving models.
Author: Ben Wilson [aut, cre], Matei Zaharia [aut], Javier Luraschi [aut], Kevin Kuo [aut] , RStudio [cph]
Maintainer: Ben Wilson <benjamin.wilson@databricks.com>

Diff between mlflow versions 3.9.0 dated 2026-02-03 and 3.10.1 dated 2026-03-16

 DESCRIPTION |    6 +++---
 MD5         |    2 +-
 2 files changed, 4 insertions(+), 4 deletions(-)

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New package marimekko with initial version 0.1.0
Package: marimekko
Title: Marimekko Plots for 'ggplot2'
Version: 0.1.0
Description: Create marimekko (mosaic) plots as a 'ggplot2' layer. Column widths encode marginal proportions of one categorical variable and segment heights encode conditional proportions of a second categorical variable.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: ggplot2 (>= 3.5.0)
Suggests: knitr, pkgdown, plotly, rmarkdown, testthat (>= 3.0.0), vdiffr (>= 1.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-03-10 11:52:23 UTC; dawidkaledkowski
Author: Dawid Kaledkowski [aut, cre]
Maintainer: Dawid Kaledkowski <dawid.kaledkowski@gmail.com>
Repository: CRAN
Date/Publication: 2026-03-16 16:40:09 UTC

More information about marimekko at CRAN
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Package LaMa updated to version 2.1.0 with previous version 2.0.6 dated 2025-09-23

Title: Fast Numerical Maximum Likelihood Estimation for Latent Markov Models
Description: A variety of latent Markov models, including hidden Markov models, hidden semi-Markov models, state-space models and continuous-time variants can be formulated and estimated within the same framework via directly maximising the likelihood function using the so-called forward algorithm. Applied researchers often need custom models that standard software does not easily support. Writing tailored 'R' code offers flexibility but suffers from slow estimation speeds. We address these issues by providing easy-to-use functions (written in 'C++' for speed) for common tasks like the forward algorithm. These functions can be combined into custom models in a Lego-type approach, offering up to 10-20 times faster estimation via standard numerical optimisers. To aid in building fully custom likelihood functions, several vignettes are included that show how to simulate data from and estimate all the above model classes.
Author: Jan-Ole Fischer [aut, cre]
Maintainer: Jan-Ole Fischer <jan-ole.fischer@mailbox.org>

Diff between LaMa versions 2.0.6 dated 2025-09-23 and 2.1.0 dated 2026-03-16

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 LaMa-2.0.6/LaMa/man/pseudo_res_discrete.Rd                                                               |only
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 LaMa-2.1.0/LaMa/DESCRIPTION                                                                              |   26 
 LaMa-2.1.0/LaMa/LICENSE                                                                                  |only
 LaMa-2.1.0/LaMa/MD5                                                                                      |  202 +-
 LaMa-2.1.0/LaMa/NAMESPACE                                                                                |   38 
 LaMa-2.1.0/LaMa/R/LaMa-package.R                                                                         |    2 
 LaMa-2.1.0/LaMa/R/RcppExports.R                                                                          |    4 
 LaMa-2.1.0/LaMa/R/decoding_functions.R                                                                   |   89 
 LaMa-2.1.0/LaMa/R/distribution_functions.R                                                               |  184 --
 LaMa-2.1.0/LaMa/R/forward_algorithms.R                                                                   |  919 ++++++----
 LaMa-2.1.0/LaMa/R/helper_functions.R                                                                     |   38 
 LaMa-2.1.0/LaMa/R/hsmm_functions_old.R                                                                   |    4 
 LaMa-2.1.0/LaMa/R/mcreport.R                                                                             |only
 LaMa-2.1.0/LaMa/R/model_matrix_functions.R                                                               |   25 
 LaMa-2.1.0/LaMa/R/qreml_functions.R                                                                      |   85 
 LaMa-2.1.0/LaMa/R/report.R                                                                               |only
 LaMa-2.1.0/LaMa/R/residual_functions.R                                                                   |  546 ++---
 LaMa-2.1.0/LaMa/R/stationary_functions.R                                                                 |   26 
 LaMa-2.1.0/LaMa/R/tpm_functions.R                                                                        |  202 +-
 LaMa-2.1.0/LaMa/R/zzz.R                                                                                  |only
 LaMa-2.1.0/LaMa/README.md                                                                                |   40 
 LaMa-2.1.0/LaMa/build/vignette.rds                                                                       |binary
 LaMa-2.1.0/LaMa/inst/doc/Continuous_time_HMMs.R                                                          |    8 
 LaMa-2.1.0/LaMa/inst/doc/Continuous_time_HMMs.Rmd                                                        |   20 
 LaMa-2.1.0/LaMa/inst/doc/Continuous_time_HMMs.html                                                       |   24 
 LaMa-2.1.0/LaMa/inst/doc/HSMMs.R                                                                         |    2 
 LaMa-2.1.0/LaMa/inst/doc/HSMMs.Rmd                                                                       |   16 
 LaMa-2.1.0/LaMa/inst/doc/HSMMs.html                                                                      |   40 
 LaMa-2.1.0/LaMa/inst/doc/Inhomogeneous_HMMs.R                                                            |    2 
 LaMa-2.1.0/LaMa/inst/doc/Inhomogeneous_HMMs.Rmd                                                          |   20 
 LaMa-2.1.0/LaMa/inst/doc/Inhomogeneous_HMMs.html                                                         |   32 
 LaMa-2.1.0/LaMa/inst/doc/Intro_to_LaMa.R                                                                 |    2 
 LaMa-2.1.0/LaMa/inst/doc/Intro_to_LaMa.Rmd                                                               |   16 
 LaMa-2.1.0/LaMa/inst/doc/Intro_to_LaMa.html                                                              |   42 
 LaMa-2.1.0/LaMa/inst/doc/LaMa_and_RTMB.R                                                                 |   60 
 LaMa-2.1.0/LaMa/inst/doc/LaMa_and_RTMB.Rmd                                                               |   63 
 LaMa-2.1.0/LaMa/inst/doc/LaMa_and_RTMB.html                                                              |  106 -
 LaMa-2.1.0/LaMa/inst/doc/Longitudinal_data.Rmd                                                           |    2 
 LaMa-2.1.0/LaMa/inst/doc/Longitudinal_data.html                                                          |   10 
 LaMa-2.1.0/LaMa/inst/doc/MMMPPs.R                                                                        |   10 
 LaMa-2.1.0/LaMa/inst/doc/MMMPPs.Rmd                                                                      |   20 
 LaMa-2.1.0/LaMa/inst/doc/MMMPPs.html                                                                     |   36 
 LaMa-2.1.0/LaMa/inst/doc/Penalised_splines.R                                                             |    7 
 LaMa-2.1.0/LaMa/inst/doc/Penalised_splines.Rmd                                                           |   29 
 LaMa-2.1.0/LaMa/inst/doc/Penalised_splines.html                                                          |   34 
 LaMa-2.1.0/LaMa/inst/doc/Periodic_HMMs.Rmd                                                               |   18 
 LaMa-2.1.0/LaMa/inst/doc/Periodic_HMMs.html                                                              |   30 
 LaMa-2.1.0/LaMa/inst/doc/State_space_models.R                                                            |    2 
 LaMa-2.1.0/LaMa/inst/doc/State_space_models.Rmd                                                          |   12 
 LaMa-2.1.0/LaMa/inst/doc/State_space_models.html                                                         |   16 
 LaMa-2.1.0/LaMa/man/LaMa-package.Rd                                                                      |    4 
 LaMa-2.1.0/LaMa/man/MCreport.Rd                                                                          |only
 LaMa-2.1.0/LaMa/man/cosinor.Rd                                                                           |    2 
 LaMa-2.1.0/LaMa/man/figures/README-visualization-1.png                                                   |binary
 LaMa-2.1.0/LaMa/man/forward.Rd                                                                           |   29 
 LaMa-2.1.0/LaMa/man/forward_g.Rd                                                                         |   42 
 LaMa-2.1.0/LaMa/man/forward_hsmm.Rd                                                                      |    2 
 LaMa-2.1.0/LaMa/man/forward_ihsmm.Rd                                                                     |    2 
 LaMa-2.1.0/LaMa/man/forward_p.Rd                                                                         |    2 
 LaMa-2.1.0/LaMa/man/forward_phsmm.Rd                                                                     |    2 
 LaMa-2.1.0/LaMa/man/forward_sp.Rd                                                                        |    4 
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 LaMa-2.1.0/LaMa/man/make_matrices.Rd                                                                     |    4 
 LaMa-2.1.0/LaMa/man/penalty.Rd                                                                           |    2 
 LaMa-2.1.0/LaMa/man/penalty2.Rd                                                                          |    4 
 LaMa-2.1.0/LaMa/man/plot.LaMaResiduals.Rd                                                                |   59 
 LaMa-2.1.0/LaMa/man/predict.LaMa_matrices.Rd                                                             |    4 
 LaMa-2.1.0/LaMa/man/pseudo_res.Rd                                                                        |   54 
 LaMa-2.1.0/LaMa/man/qreml.Rd                                                                             |    4 
 LaMa-2.1.0/LaMa/man/qreml_old.Rd                                                                         |   39 
 LaMa-2.1.0/LaMa/man/report.Rd                                                                            |only
 LaMa-2.1.0/LaMa/man/rgmrf.Rd                                                                             |only
 LaMa-2.1.0/LaMa/man/stateprobs.Rd                                                                        |   11 
 LaMa-2.1.0/LaMa/man/stateprobs_g.Rd                                                                      |   11 
 LaMa-2.1.0/LaMa/man/stateprobs_p.Rd                                                                      |   12 
 LaMa-2.1.0/LaMa/man/stationary_p_sparse.Rd                                                               |    2 
 LaMa-2.1.0/LaMa/man/tpm.Rd                                                                               |    7 
 LaMa-2.1.0/LaMa/man/tpm_cont.Rd                                                                          |    5 
 LaMa-2.1.0/LaMa/man/tpm_g.Rd                                                                             |   18 
 LaMa-2.1.0/LaMa/man/tpm_phsmm.Rd                                                                         |    2 
 LaMa-2.1.0/LaMa/man/trigBasisExp.Rd                                                                      |   14 
 LaMa-2.1.0/LaMa/man/vm.Rd                                                                                |    2 
 LaMa-2.1.0/LaMa/man/wrpcauchy.Rd                                                                         |    8 
 LaMa-2.1.0/LaMa/src/Makevars                                                                             |    7 
 LaMa-2.1.0/LaMa/src/RcppExports.cpp                                                                      |   15 
 LaMa-2.1.0/LaMa/src/tpm_functions.cpp                                                                    |   41 
 LaMa-2.1.0/LaMa/vignettes/Continuous_time_HMMs.Rmd                                                       |   20 
 LaMa-2.1.0/LaMa/vignettes/HSMMs.Rmd                                                                      |   16 
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 LaMa-2.1.0/LaMa/vignettes/Inhomogeneous_HMMs.Rmd                                                         |   20 
 LaMa-2.1.0/LaMa/vignettes/Intro_to_LaMa.Rmd                                                              |   16 
 LaMa-2.1.0/LaMa/vignettes/LaMa_and_RTMB.Rmd                                                              |   63 
 LaMa-2.1.0/LaMa/vignettes/Longitudinal_data.Rmd                                                          |    2 
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 LaMa-2.1.0/LaMa/vignettes/MMMPPs.Rmd                                                                     |   20 
 LaMa-2.1.0/LaMa/vignettes/Penalised_splines.Rmd                                                          |   29 
 LaMa-2.1.0/LaMa/vignettes/Periodic_HMMs.Rmd                                                              |   18 
 LaMa-2.1.0/LaMa/vignettes/State_space_models.Rmd                                                         |   12 
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 LaMa-2.1.0/LaMa/vignettes/refs.bib                                                                       |   10 
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New package icecdr with initial version 1.0.0
Package: icecdr
Title: Download Sea Ice Concentration Data from the NSIDC Climate Data Record
Version: 1.0.0
Description: Programmatic access to NSIDC's sea ice concentration CDR versions 4 and 5 via its ERDAPP server. Supports caching results and optional fixes for some inconsistencies of the raw files.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.3.0)
Suggests: here, ncdf4, rcdo, testthat (>= 3.0.0), vcr
Imports: checkmate, cli, digest, glue, httr2, rlang
URL: https://github.com/eliocamp/icecdr
BugReports: https://github.com/eliocamp/icecdr/issues
NeedsCompilation: no
Packaged: 2026-03-10 03:28:36 UTC; user1
Author: Elio Campitelli [cre, aut, cph]
Maintainer: Elio Campitelli <eliocampitelli@gmail.com>
Repository: CRAN
Date/Publication: 2026-03-16 16:20:09 UTC

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New package Fiscal with initial version 1.0.0
Package: Fiscal
Title: Income Tax Calculations (UK)
Version: 1.0.0
Date: 2026-03-09
Description: Income tax calculations for England, Northern Ireland and Wales. Estimate annual income tax within the different taxation bands at specified levels of both taxable income and the Personal Allowance, emulating the results obtained at <https://www.gov.uk/estimate-income-tax>. Calculate the standard Personal Allowance at various levels of taxable income. Estimate the personal allowance required to recoup a specified amount of income tax.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
NeedsCompilation: no
Packaged: 2026-03-09 21:13:38 UTC; frzmce
Author: Mark Eisler [aut, cre, cph]
Maintainer: Mark Eisler <mark@markeisler.com>
Repository: CRAN
Date/Publication: 2026-03-16 16:10:03 UTC

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New package essentialstools with initial version 0.1.2
Package: essentialstools
Title: Datasets and Utilities for Essentials of Statistics for the Behavioral Sciences
Version: 0.1.2
Description: Provides instructional datasets and simple wrapper functions for selected analyses used in 'Essentials of Statistics for the Behavioral Sciences'. The package is intended to support textbook examples by distributing data in a form that is easy for students and instructors to access within R. Current functionality includes packaged datasets and convenience wrappers for functions from 'ez', 'pwr', and 'WebPower' for analysis of variance and statistical power calculations. The package is designed as a companion resource for teaching and learning in introductory and intermediate statistics courses.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 3.5)
LazyData: true
Imports: ez, WebPower, pwr
NeedsCompilation: no
Packaged: 2026-03-10 13:33:04 UTC; Jim
Author: James Witnauer [aut, cre]
Maintainer: James Witnauer <jwitnaue@brockport.edu>
Repository: CRAN
Date/Publication: 2026-03-16 16:40:16 UTC

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Package ergmclust readmission to version 1.0.1 with previous version 1.0.0 dated 2021-02-01

Title: Exponential-Family Random Graph Models for Network Clustering
Description: Implements clustering and estimates parameters in Exponential-Family Random Graph Models for static undirected and directed networks, developed in Vu et al. (2013) <https://projecteuclid.org/euclid.aoas/1372338477>.
Author: Amal Agarwal [aut], Kevin H. Lee [aut], Lingzhou Xue [aut, ths, cre], Anna Yinqi Zhang [com]
Maintainer: Lingzhou Xue <lzxue@psu.edu>

This is a re-admission after prior archival of version 1.0.0 dated 2021-02-01

Diff between ergmclust versions 1.0.0 dated 2021-02-01 and 1.0.1 dated 2026-03-16

 DESCRIPTION                              |   26 
 MD5                                      |   52 
 NAMESPACE                                |    1 
 R/RcppExports.R                          |  242 ++-
 R/ergmclust.R                            | 2173 +++++++++++++++++++------------
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 34 files changed, 2021 insertions(+), 1231 deletions(-)

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New package demofit with initial version 0.1.1
Package: demofit
Title: Parametric Mortality Curve Fitting and Mortality Forecasting Tools
Version: 0.1.1
Author: Jackie Li [aut, cre, cph]
Maintainer: Jackie Li <jackieli@smu.edu.sg>
Description: Provides tools for fitting parametric mortality curves. Implements multiple optimisation strategies to enhance robustness and stability of parameter estimation. Offers tools for forecasting mortality rates guided by mortality curves. For modelling details see: Tabeau (2001) <doi:10.1007/0-306-47562-6_1>, Renshaw and Haberman (2006) <doi:10.1016/j.insmatheco.2005.12.001>, Cairns et al. (2009) <doi:10.1080/10920277.2009.10597538>.
License: GPL-3
Encoding: UTF-8
Imports: forecast, minpack.lm, MortalityLaws, NlcOptim, stats, graphics, grDevices
NeedsCompilation: no
Packaged: 2026-03-10 20:31:15 UTC; Jackie
Repository: CRAN
Date/Publication: 2026-03-16 16:50:08 UTC

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New package chomper with initial version 0.1.3
Package: chomper
Title: A Comprehensive Hit or Miss Probabilistic Entity Resolution Model
Version: 0.1.3
Description: Provides Bayesian probabilistic methods for record linkage and entity resolution across multiple datasets using the Comprehensive Hit Or Miss Probabilistic Entity Resolution (CHOMPER) model. The package implements three main inference approaches: (1) Evolutionary Variational Inference for record Linkage (EVIL), (2) Coordinate Ascent Variational Inference (CAVI), and (3) Markov Chain Monte Carlo (MCMC) with split and merge process. The model supports both discrete and continuous fields, and it performs locally-varying hit mechanism for the attributes with multiple truths. It also provides tools for performance evaluation based on either approximated variational factors or posterior samples. The package is designed to support parallel computing with multi-threading support for EVIL to estimate the linkage structure faster.
License: GPL (>= 3)
Encoding: UTF-8
LinkingTo: Rcpp, RcppArmadillo, RcppThread
Imports: Rcpp
Depends: R (>= 3.5)
LazyData: true
Suggests: blink, ggplot2, knitr, patchwork, rmarkdown, salso, spelling
VignetteBuilder: knitr
URL: https://github.com/hjkim8987/chomper
BugReports: https://github.com/hjkim8987/chomper/issues
Language: en-US
NeedsCompilation: yes
Packaged: 2026-03-10 19:14:49 UTC; hyungjoonkim
Author: Hyungjoon Kim [aut, cre], Andee Kaplan [aut], Matthew Koslovsky [aut]
Maintainer: Hyungjoon Kim <hjkim8987@gmail.com>
Repository: CRAN
Date/Publication: 2026-03-16 16:40:26 UTC

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Package vegdata (with last version 1.9.15) was removed from CRAN

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

2025-12-01 1.9.15
2024-01-29 0.9.12
2022-12-17 0.9.11.4
2022-06-17 0.9.11.3
2022-01-09 0.9.10
2020-05-13 0.9.8
2019-11-05 0.9.7
2018-10-24 0.9.5
2018-10-02 0.9.3
2017-08-21 0.9.1
2016-07-15 0.9
2016-03-14 0.8.9
2016-02-23 0.8.7
2015-11-20 0.8.6
2015-11-06 0.8.5
2015-09-11 0.8.1
2015-09-10 0.8
2015-07-08 0.7
2015-04-18 0.6.9
2014-11-01 0.6-7
2014-01-24 0.6-6
2013-11-26 0.6.5
2013-09-06 0.6.4
2013-08-29 0.6.3
2013-04-15 0.6.2
2013-04-03 0.6.1
2013-02-08 0.6
2012-04-04 0.5.7
2012-03-22 0.5.6
2012-03-20 0.5.5
2012-01-16 0.5.4
2012-01-12 0.5.3
2011-11-07 0.5.1
2011-10-12 0.5
2011-10-05 0.4.1
2011-09-30 0.4
2011-07-02 0.3.2
2011-06-30 0.3.1
2011-05-19 0.3
2010-11-28 0.2.1
2010-10-15 0.2
2010-07-24 0.1.8
2010-03-16 0.1.5
2009-11-24 0.1.1
2009-11-11 0.1

Permanent link
Package vegtable (with last version 0.1.10) was removed from CRAN

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

2025-09-11 0.1.10
2023-03-14 0.1.8
2021-10-13 0.1.7

Permanent link
New package xtbreakcoint with initial version 1.0.4
Package: xtbreakcoint
Title: Panel Cointegration Tests with Structural Breaks
Version: 1.0.4
Date: 2026-03-09
Description: Implements panel cointegration tests allowing for structural breaks and cross-section dependence following the methodology of Banerjee and Carrion-i-Silvestre (2015) <doi:10.1002/jae.2348>. The package provides iterative factor-break estimation, individual ADF tests on defactored residuals, standardized panel test statistics, and the Bai and Ng (2004) <doi:10.1111/j.1468-0262.2004.00528.x> MQ test for identifying common stochastic trends. Supports five model specifications with varying deterministic components and break structures.
License: GPL-3
URL: https://github.com/muhammedalkhalaf/xtbreakcoint
BugReports: https://github.com/muhammedalkhalaf/xtbreakcoint/issues
Encoding: UTF-8
Depends: R (>= 3.5.0)
Imports: stats
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
NeedsCompilation: no
Packaged: 2026-03-09 17:54:28 UTC; acad_
Author: Muhammad Alkhalaf [aut, cre, cph] , Anindya Banerjee [ctb] , Josep Lluis Carrion-i-Silvestre [ctb]
Maintainer: Muhammad Alkhalaf <muhammedalkhalaf@gmail.com>
Repository: CRAN
Date/Publication: 2026-03-16 16:00:03 UTC

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New package usportsR with initial version 1.0.0
Package: usportsR
Title: Access U SPORTS Data
Version: 1.0.0
Description: Tools package to extract and analyze data from U SPORTS, the governing body of university sport in Canada.
License: MIT + file LICENSE
Imports: dplyr, magrittr, tibble
Encoding: UTF-8
URL: https://github.com/uwaggs/usportsR, https://uwaggs.github.io/usportsR/
BugReports: https://github.com/uwaggs/usportsR/issues
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-03-09 17:03:51 UTC; pierreaucoin
Author: Shamar Phillips [aut, cre], Matthew Chow [aut] , Rithika Silva [aut], Aucoin Pierre [aut] , David Awosoga [aut] , University of Waterloo Analytics Group for Games and Sports [cph]
Maintainer: Shamar Phillips <slphilli@uwaterloo.ca>
Repository: CRAN
Date/Publication: 2026-03-16 15:50:02 UTC

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Package TSEAL readmission to version 0.1.4 with previous version 0.1.3 dated 2024-07-02

Title: Time Series Analysis Library
Description: The library allows to perform a multivariate time series classification based on the use of Discrete Wavelet Transform for feature extraction, a step wise discriminant to select the most relevant features and finally, the use of a linear or quadratic discriminant for classification. Note that all these steps can be done separately which allows to implement new steps. Velasco, I., Sipols, A., de Blas, C. S., Pastor, L., & Bayona, S. (2023) <doi:10.1186/S12938-023-01079-X>. Percival, D. B., & Walden, A. T. (2000,ISBN:0521640687). Maharaj, E. A., & Alonso, A. M. (2014) <doi:10.1016/j.csda.2013.09.006>.
Author: Ivan Velasco [aut, cre, cph]
Maintainer: Ivan Velasco <ivan.velasco@urjc.es>

This is a re-admission after prior archival of version 0.1.3 dated 2024-07-02

Diff between TSEAL versions 0.1.3 dated 2024-07-02 and 0.1.4 dated 2026-03-16

 TSEAL-0.1.3/TSEAL/R/Rdsm.R                                |only
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 TSEAL-0.1.4/TSEAL/tests/testthat/test-Discriminant.R      |  167 +++----
 TSEAL-0.1.4/TSEAL/tests/testthat/test-MultiWaveAnalisys.R |   19 
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 38 files changed, 766 insertions(+), 730 deletions(-)

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Package Rpdb updated to version 2.4.3 with previous version 2.4.1 dated 2025-09-15

Title: Read, Write, Visualize and Manipulate PDB Files
Description: Provides tools to read, write, visualize Protein Data Bank (PDB) files and perform some structural manipulations.
Author: Leonard Mada [cre, ctb], Julien Ide [aut]
Maintainer: Leonard Mada <lmada@umft.ro>

Diff between Rpdb versions 2.4.1 dated 2025-09-15 and 2.4.3 dated 2026-03-16

 DESCRIPTION                |   14 ++--
 MD5                        |   63 ++++++++++-----------
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 33 files changed, 618 insertions(+), 519 deletions(-)

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New package qshap with initial version 1.0
Package: qshap
Title: Fast Calculation of Feature Contributions in Boosting Trees
Version: 1.0
Date: 2026-03-02
Description: Computes feature-specific R-squared (R2) contributions for boosting tree models using a Shapley-value-based decomposition of the total R-squared in polynomial time. Supports models fitted with 'XGBoost' and 'LightGBM', and provides efficient parallel implementations suitable for large-scale problems. Multiple visualization tools are included for interpreting and communicating feature contributions. The methodology is described in Jiang, Zhang, and Zhang (2025) <doi:10.48550/arXiv.2407.03515>.
License: GPL (>= 2)
URL: https://github.com/catstats/Q-SHAP_R
BugReports: https://github.com/catstats/Q-SHAP_R/issues
Imports: Rcpp (>= 1.0.14), xgboost (>= 3.1.3.1), parallel, lightgbm, viridisLite, ggplot2, jsonlite, methods, progress
Suggests: shiny
LinkingTo: Rcpp, RcppEigen
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2026-03-09 19:50:27 UTC; jiangzhongli
Author: Steven He [aut], Zhongli Jiang [aut, cre], Dabao Zhang [aut]
Maintainer: Zhongli Jiang <zhongli.jiang.stats@gmail.com>
Repository: CRAN
Date/Publication: 2026-03-16 16:00:07 UTC

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New package optbinningR with initial version 0.2.1
Package: optbinningR
Title: Optimal Binning Methods for Predictive Modeling and Analytics
Version: 0.2.1
Description: Native R tools for optimal binning workflows in predictive modeling. The package provides APIs for binary, multi-class and continuous targets, with multi-variable binning and scorecard workflows. Methods are informed by Navas-Palencia (2020) <doi:10.48550/arXiv.2001.08025> and Navas-Palencia (2021) <doi:10.48550/arXiv.2104.08619>.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: stats, utils
Suggests: testthat (>= 3.0.0), jsonlite, lintr, covr
URL: https://github.com/s-rani1/optbinningR
BugReports: https://github.com/s-rani1/optbinningR/issues
NeedsCompilation: no
Packaged: 2026-03-09 20:13:36 UTC; sudheerrani
Author: S. Rani [aut, cre]
Maintainer: S. Rani <s.rani@live.com>
Repository: CRAN
Date/Publication: 2026-03-16 16:00:13 UTC

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New package mvardlurt with initial version 1.0.2
Package: mvardlurt
Title: Multivariate ARDL Unit Root Test
Version: 1.0.2
Description: Implements the multivariate autoregressive distributed lag (ARDL) unit root test proposed by Sam, McNown, Goh, and Goh (2024) <doi:10.1080/03796205.2024.2439101>. The test augments the standard ADF regression with lagged levels of a covariate to improve power when cointegration exists. Bootstrap critical values ensure correct size regardless of nuisance parameters. Provides automatic lag selection via AIC/BIC, diagnostic tests, and comprehensive inference tables following the four-case framework.
License: GPL-3
URL: https://github.com/muhammedalkhalaf/mvardlurt
BugReports: https://github.com/muhammedalkhalaf/mvardlurt/issues
Encoding: UTF-8
Depends: R (>= 4.0.0)
Imports: grDevices, graphics, stats, utils
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
NeedsCompilation: no
Packaged: 2026-03-09 17:54:26 UTC; acad_
Author: Muhammad Alkhalaf [aut, cre, cph]
Maintainer: Muhammad Alkhalaf <muhammedalkhalaf@gmail.com>
Repository: CRAN
Date/Publication: 2026-03-16 15:50:10 UTC

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Package inkaR updated to version 0.4.4 with previous version 0.4.3 dated 2026-03-13

Title: Download and Analyze Spatial Development Data from INKAR
Description: A lightweight package to download spatial development indicators from the BBSR INKAR (Indikatoren und Karten zur Raum- und Stadtentwicklung) database. It provides a modern interface using 'httr2', robust caching, concurrent API querying for fast spatial dimension lookups, and native geospatial mapping integration.
Author: Omer Furkan Coban [aut, cre]
Maintainer: Omer Furkan Coban <oemer.furkan.coban@uni-oldenburg.de>

Diff between inkaR versions 0.4.3 dated 2026-03-13 and 0.4.4 dated 2026-03-16

 DESCRIPTION          |    6 +++---
 MD5                  |   14 +++++++-------
 NEWS.md              |    5 +++++
 R/api.R              |   16 +++++++++++++++-
 R/download.R         |    4 ++--
 R/inkaR-package.R    |    8 ++++----
 man/inkaR-package.Rd |    8 ++++----
 man/inkaR.Rd         |    4 ++--
 8 files changed, 42 insertions(+), 23 deletions(-)

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New package jumble with initial version 0.1.0
Package: jumble
Title: A Discrete Colour Palette
Version: 0.1.0
Description: A pretty discrete colour palette that is also relatively colourblind and contrast-safe for a light background.
License: MIT + file LICENSE
URL: https://github.com/davidhodge931/jumble, https://davidhodge931.github.io/jumble/
BugReports: https://github.com/davidhodge931/jumble/issues
Depends: R (>= 4.1.0)
Suggests: scales, testthat (>= 3.0.0)
Encoding: UTF-8
Language: en-GB
NeedsCompilation: no
Packaged: 2026-03-09 18:56:46 UTC; david
Author: David Hodge [aut, cre, cph]
Maintainer: David Hodge <davidhodge931@gmail.com>
Repository: CRAN
Date/Publication: 2026-03-16 15:50:16 UTC

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Package hypothesize updated to version 1.0.0 with previous version 0.11.0 dated 2026-02-28

Title: Consistent API for Hypothesis Testing
Description: Provides a consistent API for hypothesis testing built on principles from 'Structure and Interpretation of Computer Programs': data abstraction, closure (combining tests yields tests), and higher-order functions (transforming tests). Implements z-tests, Wald tests, likelihood ratio tests, Fisher's method for combining p-values, and multiple testing corrections. Designed for use by other packages that want to wrap their hypothesis tests in a consistent interface.
Author: Alexander Towell [aut, cre]
Maintainer: Alexander Towell <lex@metafunctor.com>

Diff between hypothesize versions 0.11.0 dated 2026-02-28 and 1.0.0 dated 2026-03-16

 DESCRIPTION                            |    6 -
 MD5                                    |   34 +++---
 NEWS.md                                |   23 ++++
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 inst/doc/boolean-algebra.html          |    8 -
 inst/doc/introduction.R                |   15 +-
 inst/doc/introduction.Rmd              |   19 +--
 inst/doc/introduction.html             |   43 ++++---
 man/confint.hypothesis_test.Rd         |    1 
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 man/lrt.Rd                             |   39 ++++--
 man/score_test.Rd                      |    6 -
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 tests/testthat/test-hypothesis-tests.R |  166 +++++++++++++++++++++++++++++
 vignettes/introduction.Rmd             |   19 +--
 18 files changed, 459 insertions(+), 194 deletions(-)

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New package hmetad with initial version 0.1.0
Package: hmetad
Title: Fit the Meta-D' Model of Confidence Ratings Using 'brms'
Version: 0.1.0
Description: Implementation of Bayesian regressions over the meta-d' model of psychological data from two alternative forced choice tasks with ordinal confidence ratings. For more information, see Maniscalco & Lau (2012) <doi:10.1016/j.concog.2011.09.021>. The package is a front-end to the 'brms' package, which facilitates a wide range of regression designs, as well as tools for efficiently extracting posterior estimates, plotting, and significance testing.
License: GPL (>= 3)
Depends: R (>= 4.2.0), brms (>= 2.23.0)
Imports: abind (>= 1.4.8), dplyr (>= 1.2.0), glue (>= 1.8.0), posterior (>= 1.6.1), rlang (>= 1.1.7), stats, stringr (>= 1.6.0), tidybayes (>= 3.0.7), tidyr (>= 1.3.2)
Suggests: colorspace, knitr, purrr (>= 1.2.1), rmarkdown, testthat (>= 3.0.0), tidyverse (>= 2.0.0)
VignetteBuilder: knitr
Encoding: UTF-8
URL: https://metacoglab.github.io/hmetad/, https://github.com/metacoglab/hmetad
BugReports: https://github.com/metacoglab/hmetad/issues
LazyData: true
NeedsCompilation: no
Packaged: 2026-03-09 18:52:02 UTC; kevin
Author: Kevin O'Neill [aut, cre, cph] , Stephen Fleming [aut, cph]
Maintainer: Kevin O'Neill <kevin.o'neill@ucl.ac.uk>
Repository: CRAN
Date/Publication: 2026-03-16 16:00:26 UTC

More information about hmetad at CRAN
Permanent link

New package dormancy with initial version 0.1.0
Package: dormancy
Title: Detection and Analysis of Dormant Patterns in Data
Version: 0.1.0
Description: A novel framework for detecting, quantifying, and analyzing dormant patterns in multivariate data. Dormant patterns are statistical relationships that exist in data but remain inactive until specific trigger conditions emerge. This concept, inspired by biological dormancy (seeds, pathogens) and geological phenomena (dormant faults), provides tools to identify latent risks, hidden correlations, and potential phase transitions in complex systems. The package introduces methods for quantifying dormancy depth, trigger sensitivity, and awakening risk - enabling analysts to discover patterns that conventional methods miss because they focus only on currently active relationships.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.0.0)
Imports: stats, utils, grDevices, graphics, Rcpp (>= 1.0.0)
Suggests: testthat (>= 3.0.0), knitr, rmarkdown, ggplot2, covr
LinkingTo: Rcpp
VignetteBuilder: knitr
URL: https://github.com/danymukesha/dormancy/, https://danymukesha.github.io/dormancy/
BugReports: https://github.com/danymukesha/dormancy/issues/
NeedsCompilation: yes
Packaged: 2026-03-09 20:30:00 UTC; dany.mukesha
Author: Dany Mukesha [aut, cre]
Maintainer: Dany Mukesha <danymukesha@gmail.com>
Repository: CRAN
Date/Publication: 2026-03-16 16:00:33 UTC

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New package boundedur with initial version 1.0.1
Package: boundedur
Title: Unit Root Tests for Bounded Time Series
Version: 1.0.1
Description: Implements unit root tests for bounded time series following Cavaliere and Xu (2014) <doi:10.1016/j.jeconom.2013.08.012>. Standard unit root tests (ADF, Phillips-Perron) have non-standard limiting distributions when the time series is bounded. This package provides modified ADF and M-type tests (MZ-alpha, MZ-t, MSB) with p-values computed via Monte Carlo simulation of bounded Brownian motion. Supports one-sided (lower bound only) and two-sided bounds, with automatic lag selection using the MAIC criterion of Ng and Perron (2001) <doi:10.1111/1468-0262.00256>.
License: GPL-3
URL: https://github.com/muhammedalkhalaf/boundedur
BugReports: https://github.com/muhammedalkhalaf/boundedur/issues
Encoding: UTF-8
Depends: R (>= 3.5.0)
Imports: stats
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-03-09 17:14:10 UTC; acad_
Author: Muhammad Alkhalaf [aut, cre, cph] , Giuseppe Cavaliere [ctb] , Fang Xu [ctb]
Maintainer: Muhammad Alkhalaf <muhammedalkhalaf@gmail.com>
Repository: CRAN
Date/Publication: 2026-03-16 15:50:22 UTC

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Package RTMBdist updated to version 1.0.2 with previous version 1.0.1 dated 2026-02-24

Title: Distributions Compatible with Automatic Differentiation by 'RTMB'
Description: Extends the functionality of the 'RTMB' <https://kaskr.r-universe.dev/RTMB> package by providing a collection of non-standard probability distributions compatible with automatic differentiation (AD). While 'RTMB' enables flexible and efficient modelling, including random effects, its built-in support is limited to standard distributions. The package adds additional AD-compatible distributions, broadening the range of models that can be implemented and estimated using 'RTMB'. Automatic differentiation and Laplace approximation are described in Kristensen et al. (2016) <doi:10.18637/jss.v070.i05>.
Author: Jan-Ole Fischer [aut, cre]
Maintainer: Jan-Ole Fischer <jan-ole.fischer@mailbox.org>

Diff between RTMBdist versions 1.0.1 dated 2026-02-24 and 1.0.2 dated 2026-03-16

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Package clinTrialData (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:

2026-03-03 0.1.0

Permanent link
Package mvQuad updated to version 1.0-10 with previous version 1.0-8 dated 2023-09-19

Title: Methods for Multivariate Quadrature
Description: Provides methods to construct multivariate grids, which can be used for multivariate quadrature. This grids can be based on different quadrature rules like Newton-Cotes formulas (trapezoidal-, Simpson's- rule, ...) or Gauss quadrature (Gauss-Hermite, Gauss-Legendre, ...). For the construction of the multidimensional grid the product-rule or the combination- technique can be applied.
Author: Constantin Weiser [aut, cre]
Maintainer: Constantin Weiser <constantin.weiser@gmail.com>

Diff between mvQuad versions 1.0-8 dated 2023-09-19 and 1.0-10 dated 2026-03-16

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Package mlr3tuning updated to version 1.6.0 with previous version 1.5.1 dated 2025-12-14

Title: Hyperparameter Optimization for 'mlr3'
Description: Hyperparameter optimization package of the 'mlr3' ecosystem. It features highly configurable search spaces via the 'paradox' package and finds optimal hyperparameter configurations for any 'mlr3' learner. 'mlr3tuning' works with several optimization algorithms e.g. Random Search, Iterated Racing, Bayesian Optimization (in 'mlr3mbo') and Hyperband (in 'mlr3hyperband'). Moreover, it can automatically optimize learners and estimate the performance of optimized models with nested resampling.
Author: Marc Becker [cre, aut] , Michel Lang [aut] , Jakob Richter [aut] , Bernd Bischl [aut] , Daniel Schalk [aut]
Maintainer: Marc Becker <marcbecker@posteo.de>

Diff between mlr3tuning versions 1.5.1 dated 2025-12-14 and 1.6.0 dated 2026-03-16

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Package libcoin updated to version 1.0-12 with previous version 1.0-11 dated 2026-03-06

Title: Linear Test Statistics for Permutation Inference
Description: Basic infrastructure for linear test statistics and permutation inference in the framework of Strasser and Weber (1999) <https://epub.wu.ac.at/102/>. This package must not be used by end-users. CRAN package 'coin' implements all user interfaces and is ready to be used by anyone.
Author: Torsten Hothorn [aut, cre] , Henric Winell [aut]
Maintainer: Torsten Hothorn <Torsten.Hothorn@R-project.org>

Diff between libcoin versions 1.0-11 dated 2026-03-06 and 1.0-12 dated 2026-03-16

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Package tteICE updated to version 1.1.4 with previous version 1.1.3 dated 2026-03-02

Title: Treatment Effect Estimation for Time-to-Event Data with Intercurrent Events
Description: Analysis of treatment effects in clinical trials with time-to-event outcomes is complicated by intercurrent events. This package implements methods for estimating and inferring the cumulative incidence functions for time-to-event (TTE) outcomes with intercurrent events (ICE) under the five strategies outlined in the ICH E9 (R1) addendum, see Deng (2025) <doi:10.1002/sim.70091>. This package can be used for analyzing data from both randomized controlled trials and observational studies. In general, the data involve a primary outcome event and, potentially, an intercurrent event. Two data structures are allowed: competing risks, where only the time to the first event is recorded, and semicompeting risks, where the times to both the primary outcome event and intercurrent event (or censoring) are recorded. For estimation methods, users can choose nonparametric estimation (which does not use covariates) and semiparametrically efficient estimation.
Author: Yuhao Deng [aut], Yi Zhou [cre]
Maintainer: Yi Zhou <yzhou@pku.edu.cn>

Diff between tteICE versions 1.1.3 dated 2026-03-02 and 1.1.4 dated 2026-03-16

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Package conductor updated to version 0.1.2 with previous version 0.1.1 dated 2022-08-28

Title: Create Tours in 'Shiny' Apps Using 'Shepherd.js'
Description: Enable the use of 'Shepherd.js' to create tours in 'Shiny' applications.
Author: Etienne Bacher [aut, cre]
Maintainer: Etienne Bacher <etienne.bacher@protonmail.com>

Diff between conductor versions 0.1.1 dated 2022-08-28 and 0.1.2 dated 2026-03-16

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Package RcppClassicExamples updated to version 0.1.4 with previous version 0.1.3 dated 2023-11-30

Title: Examples using 'RcppClassic' to Interface R and C++
Description: The 'Rcpp' package contains a C++ library that facilitates the integration of R and C++ in various ways via a rich API. This API was preceded by an earlier version which has been deprecated since 2010 (but is still supported to provide backwards compatibility in the package 'RcppClassic'). This package 'RcppClassicExamples' provides usage examples for the older, deprecated API. There is also a corresponding package 'RcppExamples' with examples for the newer, current API which we strongly recommend as the basis for all new development.
Author: Dirk Eddelbuettel [aut, cre] , Romain Francois [aut] , Dominick Samperi [aut]
Maintainer: Dirk Eddelbuettel <edd@debian.org>

Diff between RcppClassicExamples versions 0.1.3 dated 2023-11-30 and 0.1.4 dated 2026-03-16

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Package gdldata updated to version 0.3 with previous version 0.2 dated 2025-09-01

Title: 'Global Data Lab' R API
Description: Retrieve datasets from the 'Global Data Lab' website <https://globaldatalab.org> directly into R data frames. Functions are provided to reference available options (indicators, levels, countries, regions) as well.
Author: Global Data Lab [cph], Aaron van Geffen [aut, cre]
Maintainer: Aaron van Geffen <aaron.vangeffen@ru.nl>

Diff between gdldata versions 0.2 dated 2025-09-01 and 0.3 dated 2026-03-16

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Package deseats updated to version 1.1.2 with previous version 1.1.1 dated 2025-06-23

Title: Data-Driven Locally Weighted Regression for Trend and Seasonality in TS
Description: Various methods for the identification of trend and seasonal components in time series (TS) are provided. Among them is a data-driven locally weighted regression approach with automatically selected bandwidth for equidistant short-memory time series. The approach is a combination / extension of the algorithms by Feng (2013) <doi:10.1080/02664763.2012.740626> and Feng, Y., Gries, T., and Fritz, M. (2020) <doi:10.1080/10485252.2020.1759598> and a brief description of this new method is provided in the package documentation. Furthermore, the package allows its users to apply the base model of the Berlin procedure, version 4.1, as described in Speth (2004) <https://www.destatis.de/DE/Methoden/Saisonbereinigung/BV41-methodenbericht-Heft3_2004.pdf?__blob=publicationFile>. Permission to include this procedure was kindly provided by the Federal Statistical Office of Germany.
Author: Yuanhua Feng [aut] , Dominik Schulz [aut, cre]
Maintainer: Dominik Schulz <dominik.schulz@uni-paderborn.de>

Diff between deseats versions 1.1.1 dated 2025-06-23 and 1.1.2 dated 2026-03-16

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Package BayesPower updated to version 1.0.3 with previous version 1.0.2 dated 2026-02-12

Title: Sample Size and Power Calculation for Bayesian Testing with Bayes Factor
Description: The goal of 'BayesPower' is to provide tools for Bayesian sample size determination and power analysis across a range of common hypothesis testing scenarios using Bayes factors. The main function, BayesPower_BayesFactor(), launches an interactive 'shiny' application for performing these analyses. The application also provides command-line code for reproducibility. Details of the methods are described in the tutorial by Wong, Pawel, and Tendeiro (2025) <doi:10.31234/osf.io/pgdac_v3>.
Author: Tsz Keung Wong [aut, cre], Samuel Pawel [aut], Jorge Tendeiro [aut]
Maintainer: Tsz Keung Wong <t.k.wong3004@gmail.com>

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Package ronfig updated to version 0.0.9 with previous version 0.0.8 dated 2026-01-12

Title: Load Configuration Values
Description: A simple approach to configuring R projects with different parameter values. Configurations are specified using a reduced subset of base R and parsed accordingly.
Author: Tim Taylor [aut, cre, cph]
Maintainer: Tim Taylor <tim.taylor@hiddenelephants.co.uk>

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Package ritalic updated to version 0.12.0 with previous version 0.11.0 dated 2025-03-30

Title: Interface to the ITALIC Database of Lichen Biodiversity
Description: A programmatic interface to the Web Service methods provided by ITALIC (<https://italic.units.it>). ITALIC is a database of lichen data in Italy and bordering European countries. 'ritalic' includes functions for retrieving information about lichen scientific names, geographic distribution, ecological data, morpho-functional traits and identification keys. More information about the data is available at <https://italic.units.it/?procedure=base&t=59&c=60>. The API documentation is available at <https://italic.units.it/?procedure=api>.
Author: Matteo Conti [aut, cre] , Luana Francesconi [aut], Alice Musina [aut], Luca Di Nuzzo [aut], Gabriele Gheza [aut], Chiara Pistocchi [aut], Juri Nascimbene [aut], Pier Luigi Nimis [aut], Stefano Martellos [aut]
Maintainer: Matteo Conti <matt.ciao@gmail.com>

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Package REPS updated to version 1.1.0 with previous version 1.0.0 dated 2025-07-30

Title: Hedonic and Multilateral Index Methods for Real Estate Price Statistics
Description: Compute price indices using various Hedonic and multilateral methods, including Laspeyres, Paasche, Fisher, and HMTS (Hedonic Multilateral Time series re-estimation with splicing). The central function calculate_hedonic_index() offers a unified interface for running these methods on structured datasets. This package is designed to support index construction workflows across a wide range of domains — including but not limited to real estate — where quality-adjusted price comparisons over time are essential. The development of this package was funded by Eurostat and Statistics Netherlands (CBS), and carried out by Statistics Netherlands. The HMTS method implemented here is described in Ishaak, Ouwehand and Remøy (2024) <doi:10.1177/0282423X241246617>. For broader methodological context, see Eurostat (2013, ISBN:978-92-79-25984-5, <doi:10.2785/34007>).
Author: Farley Ishaak [aut], Pim Ouwehand [aut], David Pietersz [aut], Liu Nuo Su [aut], Cynthia Cao [aut], Mohammed Kardal [aut], Odens van der Zwan [aut], Vivek Gajadhar [aut, cre]
Maintainer: Vivek Gajadhar <v.gajadhar@cbs.nl>

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Package PublicationBiasBenchmark updated to version 0.2.0 with previous version 0.1.3 dated 2025-12-05

Title: Benchmark for Publication Bias Correction Methods
Description: Implements a unified interface for benchmarking meta-analytic publication bias correction methods through simulation studies (see Bartoš et al., 2025, <doi:10.48550/arXiv.2510.19489>). It provides 1) predefined data-generating mechanisms from the literature, 2) functions for running meta-analytic methods on simulated data, 3) pre-simulated datasets and pre-computed results for reproducible benchmarks, 4) tools for visualizing and comparing method performance.
Author: Frantisek Bartos [aut, cre] , Samuel Pawel [aut] , Bjoern S. Siepe [aut] , Petr Čala [aut]
Maintainer: Frantisek Bartos <f.bartos96@gmail.com>

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Package wikiTools updated to version 1.2.21 with previous version 1.2.15 dated 2025-10-18

Title: Tools for Wikidata and Wikipedia
Description: A set of wrappers intended to check, read and download information from the Wikimedia sources. It is specifically created to work with names of celebrities, in which case their information and statistics can be downloaded. Additionally, it also builds links and snippets to use in combination with the function gallery() in netCoin package.
Author: Modesto Escobar [aut, cph, cre] , Angel Zazo [aut], Carlos Prieto [aut] , David Barrios [aut], Cristina Calvo [aut]
Maintainer: Modesto Escobar <modesto@usal.es>

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Package tvReg updated to version 0.5.11 with previous version 0.5.10 dated 2026-03-12

Title: Time-Varying Coefficient for Single and Multi-Equation Regressions
Description: Fitting time-varying coefficient models for single and multi-equation regressions, using kernel smoothing techniques.
Author: Isabel Casas [aut, cre], Ruben Fernandez-Casal [aut]
Maintainer: Isabel Casas <casasis@gmail.com>

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Package standardlastprofile updated to version 1.1.0 with previous version 1.0.0 dated 2023-12-11

Title: BDEW Standard Load Profiles for Electricity
Description: Provides representative standard load profiles (SLPs) for electricity published by the German Association of Energy and Water Industries (BDEW Bundesverband der Energie- und Wasserwirtschaft e.V.) in a tidy format. Covers the 1999 profiles — households (H0), commerce (G0–G6), and agriculture (L0–L2) — and the updated 2025 profiles (H25, G25, L25, P25, S25), which additionally represent households with photovoltaic systems and battery storage. Also provides an interface for generating a standard load profile over a user-defined date range. The 1999 data and methodology are described in VDEW (1999), "Repräsentative VDEW-Lastprofile", <https://www.bdew.de/media/documents/1999_Repraesentative-VDEW-Lastprofile.pdf>. The generation algorithm is described in VDEW (2000), "Anwendung der Repräsentativen VDEW-Lastprofile step-by-step", <https://www.bdew.de/media/documents/2000131_Anwendung-repraesentativen_Lastprofile-Step-by-step.pdf>. The 2025 profiles are described in BDEW (2025), [...truncated...]
Author: Markus Doering [aut, cre, cph]
Maintainer: Markus Doering <m4rkus.doering@gmail.com>

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Package seqHMM updated to version 2.2.0 with previous version 2.1.0 dated 2025-09-25

Title: Mixture Hidden Markov Models for Social Sequence Data and Other Multivariate, Multichannel Categorical Time Series
Description: Designed for estimating variants of hidden (latent) Markov models (HMMs), mixture HMMs, and non-homogeneous HMMs (NHMMs) for social sequence data and other categorical time series. Special cases include feedback-augmented NHMMs, Markov models without latent layer, mixture Markov models, and latent class models. The package supports models for one or multiple subjects with one or multiple parallel sequences (channels). External covariates can be added to explain cluster membership in mixture models as well as initial, transition and emission probabilities in NHMMs. The package provides functions for evaluating and comparing models, as well as functions for visualizing of multichannel sequence data and HMMs. For NHMMs, methods for computing average causal effects and marginal state and emission probabilities are available. Models are estimated using maximum likelihood via the EM algorithm or direct numerical maximization with analytical gradients. Documentation is available via several v [...truncated...]
Author: Jouni Helske [aut, cre] , Satu Helske [aut]
Maintainer: Jouni Helske <jouni.helske@iki.fi>

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Package pdxTrees readmission to version 0.5.1 with previous version 0.5.0 dated 2026-01-16

Title: Data Package of Portland, Oregon Trees
Description: An engaging collection of datasets from Portland Parks and Recreation. The city of Portland inventoried every tree in over 170 parks and along the streets in 96 neighborhoods.
Author: Kelly McConville [aut, cre], Isabelle Caldwell [aut], OR City of Portland [cph], Nicholas Horton [ctb]
Maintainer: Kelly McConville <k.mcconville@bucknell.edu>

This is a re-admission after prior archival of version 0.5.0 dated 2026-01-16

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Package pannotator readmission to version 1.0.1 with previous version 1.0.0.4 dated 2024-11-11

Title: Visualisation and Annotation of 360 Degree Imagery
Description: Provides a customisable R 'shiny' app for immersively visualising, mapping and annotating panospheric (360 degree) imagery. The flexible interface allows annotation of any geocoded images using up to 4 user specified drop-down menus. The app uses 'leaflet' to render maps that display the geo-locations of images and Panellum <https://pannellum.org/>, a lightweight panorama viewer for the web, to render images in virtual 360 degree viewing mode. Key functions include the ability to draw on & export parts of 360 images for downstream applications. Users can also draw polygons and points on map imagery related to the panoramic images and export them for further analysis. Downstream applications include using annotations to train Artificial Intelligence/Machine Learning (AI/ML) models and geospatial modelling and analysis of camera based survey data.
Author: Nunzio Knerr [aut, cre] , Robert Godfree [aut] , Matthew Petroff [ctb], CSIRO [cph]
Maintainer: Nunzio Knerr <Nunzio.Knerr@csiro.au>

This is a re-admission after prior archival of version 1.0.0.4 dated 2024-11-11

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Package ggpedigree updated to version 1.1.1.1 with previous version 1.1.1.0.0 dated 2026-03-13

Title: Visualizing Pedigrees with 'ggplot2' and 'plotly'
Description: Provides plotting functions for visualizing pedigrees and family trees. The package complements a behavior genetics package 'BGmisc' [Garrison et al. (2024) <doi:10.21105/joss.06203>] by rendering pedigrees using the 'ggplot2' framework. Features include support for duplicated individuals, complex mating structures, integration with simulated pedigrees, and layout customization. Due to the impending deprecation of kinship2, version 1.0 incorporates the layout helper functions from kinship2. The pedigree alignment algorithms are adapted from 'kinship2' [Sinnwell et al. (2014) <doi:10.1159/000363105>]. We gratefully acknowledge the original authors: Jason Sinnwell, Terry Therneau, Daniel Schaid, and Elizabeth Atkinson for their foundational work.
Author: S. Mason Garrison [aut, cre, cph]
Maintainer: S. Mason Garrison <garrissm@wfu.edu>

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Package clusterability updated to version 0.2.3.0 with previous version 0.2.2.0 dated 2026-01-12

Title: Performs Tests for Cluster Tendency of a Data Set
Description: Test for cluster tendency (clusterability) of a data set. The methods implemented - reducing the data set to a single dimension using principal component analysis or computing pairwise distances, and performing a multimodality test like the Dip Test or Silverman's Critical Bandwidth Test - are described in Adolfsson, Ackerman, and Brownstein (2019) <doi:10.1016/j.patcog.2018.10.026> and Laborde et al. (2023) <doi: 10.1186/s12859-023-05210-6>. Such methods can inform whether clustering algorithms are appropriate for a data set.
Author: Zachariah Neville [aut, cre], Naomi Brownstein [aut], Maya Ackerman [aut], Andreas Adolfsson [aut]
Maintainer: Zachariah Neville <zachariahneville@outlook.com>

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Package vbracket updated to version 1.3.0 with previous version 1.1.0 dated 2026-01-23

Title: Custom Legends with Statistical Comparison Brackets
Description: Add publication-quality custom legends with vertical brackets. Designed for displaying statistical comparisons between groups, commonly used in scientific publications for showing significance levels. Features include adaptive positioning, automatic bracket spacing for overlapping comparisons, font family inheritance, and support for asterisks, p-values, or custom labels. Compatible with 'ggplot2' graphics.
Author: Yoshiaki Sato [aut, cre]
Maintainer: Yoshiaki Sato <lascia333@gmail.com>

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Package tidylearn updated to version 0.2.0 with previous version 0.1.1 dated 2026-03-13

Title: A Unified Tidy Interface to R's Machine Learning Ecosystem
Description: Provides a unified tidyverse-compatible interface to R's machine learning packages. Wraps established implementations from 'glmnet', 'randomForest', 'xgboost', 'e1071', 'rpart', 'gbm', 'nnet', 'cluster', 'dbscan', and others - providing consistent function signatures, tidy tibble output, unified 'ggplot2'-based visualization, and optional formatted 'gt' tables via the tl_table() family of functions. The underlying algorithms are unchanged; 'tidylearn' simply makes them easier to use together. Access raw model objects via the $fit slot for package-specific functionality. Methods include random forests Breiman (2001) <doi:10.1023/A:1010933404324>, LASSO regression Tibshirani (1996) <doi:10.1111/j.2517-6161.1996.tb02080.x>, elastic net Zou and Hastie (2005) <doi:10.1111/j.1467-9868.2005.00503.x>, support vector machines Cortes and Vapnik (1995) <doi:10.1007/BF00994018>, and gradient boosting Friedman (2001) <doi:10.1214/aos/1013203451>.
Author: Cesaire Tobias [aut, cre]
Maintainer: Cesaire Tobias <cesaire@sheetsolved.com>

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Package etwfe updated to version 0.6.1 with previous version 0.6.0 dated 2025-09-03

Title: Extended Two-Way Fixed Effects
Description: Convenience functions for implementing extended two-way fixed effect regressions a la Wooldridge (2023, 2025) <doi:10.1093/ectj/utad016>, <doi:10.1007/s00181-025-02807-z>.
Author: Grant McDermott [aut, cre] , Frederic Kluser [ctb], Ulrich Morawetz [ctb]
Maintainer: Grant McDermott <contact@grantmcdermott.com>

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Package CLRtools updated to version 0.1.1 with previous version 0.1.0 dated 2026-01-29

Title: Diagnostic Tools for Logistic and Conditional Logistic Regression
Description: Provides tools for fitting, assessing, and comparing logistic and conditional logistic regression models. Includes residual diagnostics and goodness of fit measures for model development and evaluation in matched case control studies.
Author: Brenda Contla Hernandez [aut, cre], Matthieu Vignes [ctb] , Chris Compton [ctb]
Maintainer: Brenda Contla Hernandez <B.Hernandez@massey.ac.nz>

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Package animalEKF (with last version 1.3) was removed from CRAN

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

2025-08-20 1.3
2023-09-29 1.2
2020-10-05 1.1

Permanent link
Package dartR.popgen updated to version 1.2.2 with previous version 1.0.0 dated 2024-06-27

Title: Analysing 'SNP' and 'Silicodart' Data Generated by Genome-Wide Restriction Fragment Analysis
Description: Facilitates the analysis of SNP (single nucleotide polymorphism) and silicodart (presence/absence) data. 'dartR.popgen' provides a suit of functions to analyse such data in a population genetics context. It provides several functions to calculate population genetic metrics and to study population structure. Quite a few functions need additional software to be able to run (gl.run.structure(), gl.blast(), gl.LDNe()). You find detailed description in the help pages how to download and link the packages so the function can run the software. 'dartR.popgen' is part of the the 'dartRverse' suit of packages. Gruber et al. (2018) <doi:10.1111/1755-0998.12745>. Mijangos et al. (2022) <doi:10.1111/2041-210X.13918>.
Author: Bernd Gruber [aut, cre], Arthur Georges [aut], Jose L. Mijangos [aut], Carlo Pacioni [aut], Diana Robledo-Ruiz [aut], Peter J. Unmack [ctb], Oliver Berry [ctb], Lindsay V. Clark [ctb], Floriaan Devloo-Delva [ctb], Eric Archer [ctb], Ching Ching Lau [ [...truncated...]
Maintainer: Bernd Gruber <bernd.gruber@canberra.edu.au>

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Package dartR.spatial updated to version 1.2.2 with previous version 1.0.3 dated 2025-08-21

Title: Applying Landscape Genomic Methods on 'SNP' and 'Silicodart' Data
Description: Provides landscape genomic functions to analyse 'SNP' (single nuclear polymorphism) data, such as least cost path analysis and isolation by distance. Therefore each sample needs to have coordinate data attached (lat/lon) to be able to run most of the functions. 'dartR.spatial' is a package that belongs to the 'dartRverse' suit of packages and depends on 'dartR.base' and 'dartR.data'.
Author: Bernd Gruber [aut, cre], Arthur Georges [aut], Jose L. Mijangos [aut], Carlo Pacioni [aut], Peter J. Unmack [ctb], Oliver Berry [ctb]
Maintainer: Bernd Gruber <bernd.gruber@canberra.edu.au>

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