Mon, 28 Apr 2025

Package splithalfr updated to version 3.0.0 with previous version 2.2.2 dated 2023-09-14

Title: Estimate Split-Half Reliabilities
Description: Estimates split-half reliabilities for scoring algorithms of cognitive tasks and questionnaires. The 'splithalfr' supports researcher-provided scoring algorithms, with six vignettes illustrating how on included datasets. The package provides four splitting methods (first-second, odd-even, permutated, Monte Carlo), the option to stratify splits by task design, a number of reliability coefficients, the option to sub-sample data, and bootstrapped confidence intervals.
Author: Thomas Pronk [aut, cre]
Maintainer: Thomas Pronk <pronkthomas@gmail.com>

Diff between splithalfr versions 2.2.2 dated 2023-09-14 and 3.0.0 dated 2025-04-28

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Package datamedios updated to version 1.2.0 with previous version 1.1.0 dated 2025-02-18

Title: Scraping Chilean Media
Description: A system for extracting news from Chilean media, specifically through Web Scapping from Chilean media. The package allows for news searches using search phrases and date filters, and returns the results in a structured format, ready for analysis. Additionally, it includes functions to clean the extracted data, visualize it, and store it in databases. All of this can be done automatically, facilitating the collection and analysis of relevant information from Chilean media.
Author: Exequiel Trujillo [aut, cre, cph, fnd], Ismael Aguayo [aut, fnd], Klaus Lehmann [aut, fnd]
Maintainer: Exequiel Trujillo <exequiel.trujillo@ug.uchile.cl>

Diff between datamedios versions 1.1.0 dated 2025-02-18 and 1.2.0 dated 2025-04-28

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Package SAMtool updated to version 1.8.1 with previous version 1.8.0 dated 2024-11-07

Title: Stock Assessment Methods Toolkit
Description: Simulation tools for closed-loop simulation are provided for the 'MSEtool' operating model to inform data-rich fisheries. 'SAMtool' provides a conditioning model, assessment models of varying complexity with standardized reporting, model-based management procedures, and diagnostic tools for evaluating assessments inside closed-loop simulation.
Author: Quang Huynh [aut, cre], Tom Carruthers [aut], Adrian Hordyk [aut]
Maintainer: Quang Huynh <quang@bluematterscience.com>

Diff between SAMtool versions 1.8.0 dated 2024-11-07 and 1.8.1 dated 2025-04-28

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Package rlandfire updated to version 2.0.0 with previous version 1.0.0 dated 2024-03-15

Title: Interface to 'LANDFIRE Product Service' API
Description: Provides access to a suite of geospatial data layers for wildfire management, fuel modeling, ecology, natural resource management, climate, conservation, etc., via the 'LANDFIRE' (<https://www.landfire.gov/>) Product Service ('LFPS') API.
Author: Mark Buckner [aut, cre, cph]
Maintainer: Mark Buckner <mab677@cornell.edu>

Diff between rlandfire versions 1.0.0 dated 2024-03-15 and 2.0.0 dated 2025-04-28

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Package zen4R updated to version 0.10.1 with previous version 0.10 dated 2024-06-05

Title: Interface to 'Zenodo' REST API
Description: Provides an Interface to 'Zenodo' (<https://zenodo.org>) REST API, including management of depositions, attribution of DOIs by 'Zenodo' and upload and download of files.
Author: Emmanuel Blondel [aut, cre] , Julien Barde [ctb] , Stephen Eglen [ctb] , Hans Van Calster [ctb] , Floris Vanderhaeghe [ctb] , Jemma Stachelek [ctb]
Maintainer: Emmanuel Blondel <emmanuel.blondel1@gmail.com>

Diff between zen4R versions 0.10 dated 2024-06-05 and 0.10.1 dated 2025-04-28

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Package tabr updated to version 0.5.2 with previous version 0.5.1 dated 2024-09-11

Title: Music Notation Syntax, Manipulation, Analysis and Transcription in R
Description: Provides a music notation syntax and a collection of music programming functions for generating, manipulating, organizing, and analyzing musical information in R. Music syntax can be entered directly in character strings, for example to quickly transcribe short pieces of music. The package contains functions for directly performing various mathematical, logical and organizational operations and musical transformations on special object classes that facilitate working with music data and notation. The same music data can be organized in tidy data frames for a familiar and powerful approach to the analysis of large amounts of structured music data. Functions are available for mapping seamlessly between these formats and their representations of musical information. The package also provides an API to 'LilyPond' (<https://lilypond.org/>) for transcribing musical representations in R into tablature ("tabs") and sheet music. 'LilyPond' is open source music engraving software for gener [...truncated...]
Author: Matthew Leonawicz [aut, cre]
Maintainer: Matthew Leonawicz <rpkgs@pm.me>

Diff between tabr versions 0.5.1 dated 2024-09-11 and 0.5.2 dated 2025-04-28

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New package tsissm with initial version 1.0.1
Package: tsissm
Title: Linear Innovations State Space Unobserved Components Model
Version: 1.0.1
Maintainer: Alexios Galanos <alexios@4dscape.com>
Description: Unobserved components time series model using the linear innovations state space representation (single source of error) with choice of error distributions and option for dynamic variance. Methods for estimation using automatic differentiation, automatic model selection and ensembling, prediction, filtering, simulation and backtesting. Based on the model described in Hyndman et al (2012) <doi:10.1198/jasa.2011.tm09771>.
Depends: R (>= 4.1.0), Rcpp (>= 0.12.9), tsmethods (>= 1.0.0)
LinkingTo: Rcpp (>= 0.12.9), TMB, RcppEigen
Imports: TMB (>= 1.7.20), methods, tsaux, tsdistributions, zoo, xts, copula, flextable, data.table, sandwich, nloptr, RTMB, viridisLite, future, future.apply, progressr
Suggests: rmarkdown, tstests, knitr, testthat (>= 3.0.0)
License: GPL-2
Encoding: UTF-8
VignetteBuilder: knitr
LazyData: true
URL: https://github.com/tsmodels/tsissm, https://www.nopredict.com/packages/tsissm
NeedsCompilation: yes
Packaged: 2025-04-26 16:51:09 UTC; alexios
Author: Alexios Galanos [aut, cre]
Repository: CRAN
Date/Publication: 2025-04-28 18:30:02 UTC

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New package robustGarch with initial version 0.4.2
Package: robustGarch
Title: Robust Garch(1,1) Model
Version: 0.4.2
Description: A method for modeling robust generalized autoregressive conditional heteroskedasticity (Garch) (1,1) processes, providing robustness toward additive outliers instead of innovation outliers. This work is based on the methodology described by Muler and Yohai (2008) <doi:10.1016/j.jspi.2007.11.003>.
License: MIT + file LICENSE
Encoding: UTF-8
URL: https://github.com/EchoRLiu/robustGarch
BugReports: https://github.com/EchoRLiu/robustGarch/issues
Suggests: rmarkdown, testthat, PCRA
Imports: Rsolnp, nloptr, rugarch, zoo, xts
Depends: R (>= 4.3.0)
NeedsCompilation: no
Packaged: 2025-04-27 18:12:42 UTC; yuhongliu
Author: Echo Liu [aut, cre], Daniel Xia [aut], R. Douglas Martin [aut]
Maintainer: Echo Liu <yuhong.echo.liu@gmail.com>
Repository: CRAN
Date/Publication: 2025-04-28 18:50:02 UTC

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New package refitgaps with initial version 0.1.1
Package: refitgaps
Title: Reduce the Number of Holes in the School Timetable
Version: 0.1.1
Description: If a teacher was assigned, say, hours 1, 2, 4, 6 for his lessons on the current day, then he got two "gaps" (or "holes"), in hours 3 and 5. If the total number of holes in the existing daily schedule is too large (exceeding, say, 6% of the total lessons), then the problem arises of reallocating the respective lessons by hours (respecting the constraints induced by the existence of coupled lessons) so that the total number of holes is as small as possible.
License: MIT + file LICENSE
Encoding: UTF-8
Language: ro
Imports: dplyr, magrittr, purrr, rlang, stats, tibble
Depends: R (>= 3.5.0)
LazyData: true
Suggests: knitr, rmarkdown, stringr, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2025-04-27 07:23:37 UTC; vb
Author: Vlad Bazon [aut, cre]
Maintainer: Vlad Bazon <vlad.bazon@gmail.com>
Repository: CRAN
Date/Publication: 2025-04-28 18:40:02 UTC

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New package RADanalysis with initial version 1.0.1
Package: RADanalysis
Title: Normalization and Analysis of Rank Abundance Distributions
Version: 1.0.1
Date: 2025-04-26
Description: Implementation of the MaxRank normalization method, which enables standardization of Rank Abundance Distributions (RADs) to a specified number of ranks. Rank abundance distributions are widely used in biology and ecology to describe species abundances, and are mathematically equivalent to complementary cumulative distribution functions (CCDFs) used in physics, linguistics, sociology, and other fields. The method is described in Saeedghalati et al. (2017) <doi:10.1371/journal.pcbi.1005362>.
License: GPL-3
LazyData: TRUE
Encoding: UTF-8
Depends: R (>= 2.10)
Imports: sfsmisc, scales, stats, graphics
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2025-04-26 07:00:27 UTC; ffarn
Author: Mohmmadkarim Saeedghalati [aut, cre], Farnoush Farahpour [aut], Daniel Hoffmann [aut]
Maintainer: Mohmmadkarim Saeedghalati <arsham@gmail.com>
Repository: CRAN
Date/Publication: 2025-04-28 18:40:12 UTC

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Package prodlim updated to version 2025.04.28 with previous version 2024.06.25 dated 2024-06-24

Title: Product-Limit Estimation for Censored Event History Analysis
Description: Fast and user friendly implementation of nonparametric estimators for censored event history (survival) analysis. Kaplan-Meier and Aalen-Johansen method.
Author: Thomas A. Gerds [aut, cre]
Maintainer: Thomas A. Gerds <tag@biostat.ku.dk>

Diff between prodlim versions 2024.06.25 dated 2024-06-24 and 2025.04.28 dated 2025-04-28

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Package metasnf updated to version 2.1.2 with previous version 2.1.1 dated 2025-04-25

Title: Meta Clustering with Similarity Network Fusion
Description: Framework to facilitate patient subtyping with similarity network fusion and meta clustering. The similarity network fusion (SNF) algorithm was introduced by Wang et al. (2014) in <doi:10.1038/nmeth.2810>. SNF is a data integration approach that can transform high-dimensional and diverse data types into a single similarity network suitable for clustering with minimal loss of information from each initial data source. The meta clustering approach was introduced by Caruana et al. (2006) in <doi:10.1109/ICDM.2006.103>. Meta clustering involves generating a wide range of cluster solutions by adjusting clustering hyperparameters, then clustering the solutions themselves into a manageable number of qualitatively similar solutions, and finally characterizing representative solutions to find ones that are best for the user's specific context. This package provides a framework to easily transform multi-modal data into a wide range of similarity network fusion-derived cluster solutio [...truncated...]
Author: Prashanth S Velayudhan [aut, cre], Xiaoqiao Xu [aut], Prajkta Kallurkar [aut], Ana Patricia Balbon [aut], Maria T Secara [aut], Adam Taback [aut], Denise Sabac [aut], Nicholas Chan [aut], Shihao Ma [aut], Bo Wang [aut], Daniel Felsky [aut], Stephanie [...truncated...]
Maintainer: Prashanth S Velayudhan <psvelayu@gmail.com>

Diff between metasnf versions 2.1.1 dated 2025-04-25 and 2.1.2 dated 2025-04-28

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New package LLMAgentR with initial version 0.2.0
Package: LLMAgentR
Title: Language Model Agents in R for AI Workflows and Research
Version: 0.2.0
Maintainer: Kwadwo Daddy Nyame Owusu Boakye <kwadwo.owusuboakye@outlook.com>
Description: Provides modular, graph-based agents powered by large language models (LLMs) for intelligent task execution in R. Supports structured workflows for tasks such as forecasting, data visualization, feature engineering, data wrangling, data cleaning, SQL, code generation, weather reporting, and research-driven question answering. Each agent performs iterative reasoning: recommending steps, generating R code, executing, debugging, and explaining results. Includes built-in support for packages such as 'tidymodels', 'modeltime', 'plotly', 'ggplot2', and 'prophet'. Designed for analysts, developers, and teams building intelligent, reproducible AI workflows in R. Compatible with LLM providers such as 'OpenAI', 'Anthropic', 'Groq', and 'Ollama'. Inspired by the Python package 'langagent'.
License: MIT + file LICENSE
Encoding: UTF-8
URL: https://github.com/knowusuboaky/LLMAgentR
BugReports: https://github.com/knowusuboaky/LLMAgentR/issues
Depends: R (>= 4.1.0)
Imports: plotly, stats, utils, DBI, RSQLite, dplyr, glue, httr, officer, purrr, timetk, pdftools, parsnip, recipes, workflows, rsample, modeltime.ensemble, modeltime, xml2
Suggests: testthat (>= 3.0.0), roxygen2, jsonlite, magrittr, rlang, tidyr, ggplot2, usethis, prophet, forcats, kernlab, xgboost, xfun, modeltime.resample, tidymodels, tibble, lubridate, methods, stringr, tesseract, rvest, fastDummies
NeedsCompilation: no
Packaged: 2025-04-27 10:20:30 UTC; kwadw
Author: Kwadwo Daddy Nyame Owusu Boakye [aut, cre]
Repository: CRAN
Date/Publication: 2025-04-28 18:40:15 UTC

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Package heimdall updated to version 1.0.737 with previous version 1.0.717 dated 2024-06-30

Title: Drift Adaptable Models
Description: In streaming data analysis, it is crucial to detect significant shifts in the data distribution or the accuracy of predictive models over time, a phenomenon known as **concept drift**. The **heimdall** package aims to identify when concept drift occurs and provide methodologies for adapting models in non-stationary environments. It offers a range of state-of-the-art techniques for detecting concept drift and maintaining model performance. Additionally, **heimdall** provides tools for adapting models in response to these changes, ensuring continuous and accurate predictions in dynamic contexts. Methods for concept drift detection are described in Tavares (2022) <doi:10.1007/s12530-021-09415-z>.
Author: Lucas Tavares [aut], Leonardo Carvalho [aut], Diego Carvalho [aut], Esther Pacitti [aut], Fabio Porto [aut], Eduardo Ogasawara [aut, ths, cre] , Federal Center for Technological Education of Rio de Janeiro [cph]
Maintainer: Eduardo Ogasawara <eogasawara@ieee.org>

Diff between heimdall versions 1.0.717 dated 2024-06-30 and 1.0.737 dated 2025-04-28

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New package ggsegmentedtotalbar with initial version 0.1.0
Package: ggsegmentedtotalbar
Title: Create a Segmented Total Bar Plot with Custom Annotations and Labels
Version: 0.1.0
Description: It provides a better alternative for stacked bar plot by creating a segmented total bar plot with custom annotations and labels. It is useful for visualizing the total of a variable and its segments in a single bar, making it easier to compare the segments and their contributions to the total.
License: MIT + file LICENSE
URL: https://github.com/ozancanozdemir/ggsegmentedtotalbar
BugReports: https://github.com/ozancanozdemir/ggsegmentedtotalbar/issues
Depends: R (>= 4.0)
Imports: ggplot2, grid, forcats
Suggests: testthat (>= 3.0.0), devtools, remotes, roxygen2, usethis, knitr, rmarkdown
Encoding: UTF-8
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2025-04-27 14:18:29 UTC; ozancanozdemir
Author: Ozancan Ozdemir [aut, cre]
Maintainer: Ozancan Ozdemir <ozancanozdemir@gmail.com>
Repository: CRAN
Date/Publication: 2025-04-28 18:40:09 UTC

More information about ggsegmentedtotalbar at CRAN
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Package CrossVA (with last version 1.0.0) was removed from CRAN

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

2021-08-10 1.0.0
2020-04-22 0.10.0
2019-07-03 0.9.9
2019-05-17 0.9.8
2019-04-21 0.9.7
2019-04-18 0.9.6
2019-01-19 0.9.5
2018-12-11 0.9.4
2018-10-24 0.9.3
2018-08-24 0.9.2
2017-09-04 0.9.1
2016-11-10 0.9.0

Permanent link
New package ZEP with initial version 0.1.3
Package: ZEP
Title: Procedures Related to the Zadeh's Extension Principle for Fuzzy Data
Version: 0.1.3
Description: Procedures for calculation, plotting, and approximation of the outputs for fuzzy numbers (see A.I. Ban, L. Coroianu, P. Grzegorzewski "Fuzzy Numbers: Approximations, Ranking and Applications" (2015)) based on the Zadeh's Extension Principle (see de Barros, L.C., Bassanezi, R.C., Lodwick, W.A. (2017) <doi:10.1007/978-3-662-53324-6_2>).
License: GPL-3
NeedsCompilation: yes
Imports: FuzzyNumbers, methods
Encoding: UTF-8
Depends: R (>= 3.5.0)
Suggests: testthat (>= 3.0.0)
Packaged: 2025-04-26 04:02:56 UTC; mroman
Author: Maciej Romaniuk [cre, aut] ), Abbas Parchami [aut] ), Przemyslaw Grzegorzewski [ctb] )
Maintainer: Maciej Romaniuk <mroman@ibspan.waw.pl>
Repository: CRAN
Date/Publication: 2025-04-28 17:30:02 UTC

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Package astrochron updated to version 1.5 with previous version 1.4 dated 2024-09-17

Title: A Computational Tool for Astrochronology
Description: Routines for astrochronologic testing, astronomical time scale construction, and time series analysis <doi:10.1016/j.earscirev.2018.11.015>. Also included are a range of statistical analysis and modeling routines that are relevant to time scale development and paleoclimate analysis.
Author: Stephen Meyers [aut, cre], Alberto Malinverno [ctb], Linda Hinnov [ctb], Christian Zeeden [ctb], Huaran Liu [ctb], Vincent Moron [ctb], Michel Crucifix [ctb]
Maintainer: Stephen Meyers <smeyers@geology.wisc.edu>

Diff between astrochron versions 1.4 dated 2024-09-17 and 1.5 dated 2025-04-28

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New package bartXViz with initial version 1.0.3
Package: bartXViz
Title: Visualization of BART and BARP using SHAP
Version: 1.0.3
Date: 2025-04-29
Description: The contribution of variables in Bayesian Additive Regression Trees (BART) and Bayesian Additive Regression Trees with Post-Stratification (BARP) models is computed using permutation-based Shapley values. The computed SHAP values are then utilized to visualize the contribution of each variable through various plots. The computation of SHAP values for most models follows the methodology proposed by Strumbel and Kononenko (2014) <doi:10.1007/s10115-013-0679-x>, while for XGBoost, the approach introduced by Lundberg et al. (2020) <doi:10.1038/s42256-019-0138-9> was also considered. The BART model was referenced based on the works of Chipman, George, and McCulloch (2010) <doi:10.1214/09-AOAS285> and Kapelner and Bleich (2013) <doi:10.18637/jss.v070.i04>, while the methodology for the BARP model was based on Bisbee (2019) <doi:10.1017/S0003055419000480>.
License: GPL (>= 2)
Depends: R (>= 3.5.0), SuperLearner
Imports: bartMachine, BART, ggplot2, ggforce, data.table, ggfittext, ggpubr, foreach, gggenes, Rcpp, dplyr, tidyr, stringr,abind,data.table, utils,grid,dbarts, forcats, gridExtra,reshape2, missForest
LinkingTo: Rcpp, RcppArmadillo
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2025-04-26 06:04:19 UTC; ddong
Author: Dong-eun Lee [aut, cre], Eun-Kyung Lee [aut]
Maintainer: Dong-eun Lee <ldongeun.leel@gmail.com>
Repository: CRAN
Date/Publication: 2025-04-28 17:40:02 UTC

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Package lme4breeding updated to version 1.0.60 with previous version 1.0.50 dated 2025-01-17

Title: Relationship-Based Mixed-Effects Models
Description: Fit relationship-based and customized mixed-effects models with complex variance-covariance structures using the 'lme4' machinery. The core computational algorithms are implemented using the 'Eigen' 'C++' library for numerical linear algebra and 'RcppEigen' 'glue'.
Author: Giovanny Covarrubias-Pazaran [aut, cre]
Maintainer: Giovanny Covarrubias-Pazaran <cova_ruber@live.com.mx>

Diff between lme4breeding versions 1.0.50 dated 2025-01-17 and 1.0.60 dated 2025-04-28

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Package fastbeta updated to version 0.4.0 with previous version 0.3.2 dated 2025-03-24

Title: Fast Approximation of Time-Varying Infectious Disease Transmission Rates
Description: A fast method for approximating time-varying infectious disease transmission rates from disease incidence time series and other data, based on a discrete time approximation of an SEIR model, as analyzed in Jagan et al. (2020) <doi:10.1371/journal.pcbi.1008124>.
Author: Mikael Jagan [aut, cre]
Maintainer: Mikael Jagan <jaganmn@mcmaster.ca>

Diff between fastbeta versions 0.3.2 dated 2025-03-24 and 0.4.0 dated 2025-04-28

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Package r2glmm updated to version 0.1.3 with previous version 0.1.2 dated 2017-08-05

Title: Computes R Squared for Mixed (Multilevel) Models
Description: The model R squared and semi-partial R squared for the linear and generalized linear mixed model (LMM and GLMM) are computed with confidence limits. The R squared measure from Edwards et.al (2008) <DOI:10.1002/sim.3429> is extended to the GLMM using penalized quasi-likelihood (PQL) estimation (see Jaeger et al. 2016 <DOI:10.1080/02664763.2016.1193725>). Three methods of computation are provided and described as follows. First, The Kenward-Roger approach. Due to some inconsistency between the 'pbkrtest' package and the 'glmmPQL' function, the Kenward-Roger approach in the 'r2glmm' package is limited to the LMM. Second, The method introduced by Nakagawa and Schielzeth (2013) <DOI:10.1111/j.2041-210x.2012.00261.x> and later extended by Johnson (2014) <DOI:10.1111/2041-210X.12225>. The 'r2glmm' package only computes marginal R squared for the LMM and does not generalize the statistic to the GLMM; however, confidence limits and semi-partial R squared for fixed effect [...truncated...]
Author: Byron Jaeger [aut, cre]
Maintainer: Byron Jaeger <byron.jaeger@gmail.com>

Diff between r2glmm versions 0.1.2 dated 2017-08-05 and 0.1.3 dated 2025-04-28

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Package NNS updated to version 11.3 with previous version 11.2 dated 2025-03-25

Title: Nonlinear Nonparametric Statistics
Description: Nonlinear nonparametric statistics using partial moments. Partial moments are the elements of variance and asymptotically approximate the area of f(x). These robust statistics provide the basis for nonlinear analysis while retaining linear equivalences. NNS offers: Numerical integration, Numerical differentiation, Clustering, Correlation, Dependence, Causal analysis, ANOVA, Regression, Classification, Seasonality, Autoregressive modeling, Normalization, Stochastic dominance and Advanced Monte Carlo sampling. All routines based on: Viole, F. and Nawrocki, D. (2013), Nonlinear Nonparametric Statistics: Using Partial Moments (ISBN: 1490523995).
Author: Fred Viole [aut, cre], Roberto Spadim [ctb]
Maintainer: Fred Viole <ovvo.financial.systems@gmail.com>

Diff between NNS versions 11.2 dated 2025-03-25 and 11.3 dated 2025-04-28

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Package MDSMap updated to version 1.3 with previous version 1.1 dated 2018-08-09

Title: High Density Genetic Linkage Mapping using Multidimensional Scaling
Description: Estimate genetic linkage maps for markers on a single chromosome (or in a single linkage group) from pairwise recombination fractions or intermarker distances using weighted metric multidimensional scaling. The methods are suitable for autotetraploid as well as diploid populations. Options for assessing the fit to a known map are also provided. Methods are discussed in detail in Preedy and Hackett (2016) <doi:10.1007/s00122-016-2761-8>.
Author: Katharine F. Preedy [aut], Christine A. Hackett [aut], Bram Boskamp [cre]
Maintainer: Bram Boskamp <bram.boskamp@bioss.ac.uk>

Diff between MDSMap versions 1.1 dated 2018-08-09 and 1.3 dated 2025-04-28

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Package ARDECO updated to version 2.2.2 with previous version 2.2.1 dated 2025-04-18

Title: Annual Regional Database of the European Commission (ARDECO)
Description: A set of functions to access the 'ARDECO' (Annual Regional Database of the European Commission) data directly from the official ARDECO public repository through the exploitation of the 'ARDECO' APIs. The APIs are completely transparent to the user and the provided functions provide a direct access to the 'ARDECO' data. The 'ARDECO' database is a collection of variables related to demography, employment, labour market, domestic product, capital formation. Each variable can be exposed in one or more units of measure as well as refers to total values plus additional dimensions like economic sectors, gender, age classes. Data can be also aggregated at country level according to the tercet classes as defined by EUROSTAT. The description of the 'ARDECO' database can be found at the following URL <https://urban.jrc.ec.europa.eu/ardeco>.
Author: Carmelo Attardo [cre], Giuseppe Bucciarelli [aut], European Commission, JRC [cph]
Maintainer: Carmelo Attardo <carmelo.attardo@ec.europa.eu>

Diff between ARDECO versions 2.2.1 dated 2025-04-18 and 2.2.2 dated 2025-04-28

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New package xactonomial with initial version 1.0.3
Package: xactonomial
Title: Inference for Functions of Multinomial Parameters
Version: 1.0.3
Date: 2025-04-20
URL: https://sachsmc.github.io/xactonomial/
BugReports: https://github.com/sachsmc/xactonomial/issues/
Description: We consider the problem where we observe k vectors (possibly of different lengths), each representing an independent multinomial random vector. For a given function that takes in the concatenated vector of multinomial probabilities and outputs a real number, this is a Monte Carlo estimation procedure of an exact p-value and confidence interval. The resulting inference is valid even in small samples, when the parameter is on the boundary, and when the function is not differentiable at the parameter value, all situations where asymptotic methods and the bootstrap would fail. For more details see Sachs, Fay, and Gabriel (2025) <doi:10.48550/arXiv.2406.19141>.
License: MIT + file LICENSE
Encoding: UTF-8
SystemRequirements: Cargo (Rust's package manager), rustc >= 1.70
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
Depends: R (>= 4.2)
NeedsCompilation: yes
Packaged: 2025-04-20 11:59:55 UTC; micsac
Author: Michael C Sachs [aut, cre], Michael P Fay [aut], Erin E Gabriel [aut], David B Dahl [ctb] )
Maintainer: Michael C Sachs <sachsmc@gmail.com>
Repository: CRAN
Date/Publication: 2025-04-28 13:50:02 UTC

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Package tesselle updated to version 1.6.0 with previous version 1.5.0 dated 2024-12-10

Title: Easily Install and Load 'tesselle' Packages
Description: Easy install and load key packages from the 'tesselle' suite in a single step. The 'tesselle' suite is a collection of packages for research and teaching in archaeology. These packages focus on quantitative analysis methods developed for archaeology. The 'tesselle' packages are designed to work seamlessly together and to complement general-purpose and other specialized statistical packages. These packages can be used to explore and analyze common data types in archaeology: count data, compositional data and chronological data. Learn more about 'tesselle' at <https://www.tesselle.org>.
Author: Nicolas Frerebeau [aut, cre] , Brice Lebrun [art] , Universite Bordeaux Montaigne [fnd] , CNRS [fnd]
Maintainer: Nicolas Frerebeau <nicolas.frerebeau@u-bordeaux-montaigne.fr>

Diff between tesselle versions 1.5.0 dated 2024-12-10 and 1.6.0 dated 2025-04-28

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Package surveytable updated to version 0.9.7 with previous version 0.9.6 dated 2025-03-13

Title: Formatted Survey Estimates
Description: Short and understandable commands that generate tabulated, formatted, and rounded survey estimates. Mostly a wrapper for the 'survey' package (Lumley (2004) <doi:10.18637/jss.v009.i08> <https://CRAN.R-project.org/package=survey>) that identifies low-precision estimates using the National Center for Health Statistics (NCHS) presentation standards (Parker et al. (2017) <https://www.cdc.gov/nchs/data/series/sr_02/sr02_175.pdf>, Parker et al. (2023) <doi:10.15620/cdc:124368>).
Author: Alex Strashny [aut, cre]
Maintainer: Alex Strashny <alex.strashny@gmail.com>

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 R/total.R                                                                           |    4 
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 R/var_not.R                                                                         |   52 -
 R/z_utils.R                                                                         |   98 +--
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New package orbweaver with initial version 0.18.2
Package: orbweaver
Title: Fast and Efficient Graph Data Structures
Version: 0.18.2
Description: Seamlessly build and manipulate graph structures, leveraging its high-performance methods for filtering, joining, and mutating data. Ensures that mutations and changes to the graph are performed in place, streamlining your workflow for optimal productivity.
License: MIT + file LICENSE
URL: https://github.com/ixpantia/orbweaver-r
BugReports: https://github.com/ixpantia/orbweaver-r/issues
Depends: R (>= 4.2.0)
Imports: glue, methods, rlang
Suggests: testthat (>= 3.0.0)
Encoding: UTF-8
SystemRequirements: Cargo (Rust's package manager) >= 1.70, rustc >= 1.70
NeedsCompilation: yes
Packaged: 2025-04-21 15:21:23 UTC; andres
Author: ixpantia, SRL [cph], Andres Quintero [aut, cre], The authors of the dependency Rust crates [ctb]
Maintainer: Andres Quintero <andres@ixpantia.com>
Repository: CRAN
Date/Publication: 2025-04-28 13:50:07 UTC

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Package ebvcube updated to version 0.5.0 with previous version 0.4.0 dated 2025-03-05

Title: Working with netCDF for Essential Biodiversity Variables
Description: The concept of Essential Biodiversity Variables (EBV, <https://geobon.org/ebvs/what-are-ebvs/>) comes with a data structure based on the Network Common Data Form (netCDF). The 'ebvcube' 'R' package provides functionality to easily create, access and visualise this data. The EBV netCDFs can be downloaded from the EBV Data Portal: Christian Langer/ iDiv (2020) <https://portal.geobon.org/>.
Author: Luise Quoss [aut, cre] , Nestor Fernandez [aut] , Christian Langer [aut] , Jose Valdez [aut] , Henrique Miguel Pereira [aut]
Maintainer: Luise Quoss <luise.quoss@idiv.de>

Diff between ebvcube versions 0.4.0 dated 2025-03-05 and 0.5.0 dated 2025-04-28

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Package dexter updated to version 1.6.1 with previous version 1.6.0 dated 2025-04-07

Title: Data Management and Analysis of Tests
Description: A system for the management, assessment, and psychometric analysis of data from educational and psychological tests.
Author: Gunter Maris [aut], Timo Bechger [aut], Jesse Koops [aut, cre], Ivailo Partchev [aut]
Maintainer: Jesse Koops <jesse.koops@cito.nl>

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Package daltoolbox updated to version 1.1.747 with previous version 1.1.737 dated 2025-04-21

Title: Leveraging Experiment Lines to Data Analytics
Description: The natural increase in the complexity of current research experiments and data demands better tools to enhance productivity in Data Analytics. The package is a framework designed to address the modern challenges in data analytics workflows. The package is inspired by Experiment Line concepts. It aims to provide seamless support for users in developing their data mining workflows by offering a uniform data model and method API. It enables the integration of various data mining activities, including data preprocessing, classification, regression, clustering, and time series prediction. It also offers options for hyper-parameter tuning and supports integration with existing libraries and languages. Overall, the package provides researchers with a comprehensive set of functionalities for data science, promoting ease of use, extensibility, and integration with various tools and libraries. Information on Experiment Line is based on Ogasawara et al. (2009) <doi:10.1007/978-3-642-02279-1_2 [...truncated...]
Author: Eduardo Ogasawara [aut, ths, cre] , Antonio Castro [aut, ctb], Diego Salles [aut, ths], Janio Lima [aut, ths], Lucas Tavares [aut, ths], Diego Carvalho [aut, ths], Eduardo Bezerra [aut, ths], Rafaelli Coutinho [aut, ths], Federal Center for Technolog [...truncated...]
Maintainer: Eduardo Ogasawara <eogasawara@ieee.org>

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Package shapr updated to version 1.0.4 with previous version 1.0.3 dated 2025-04-01

Title: Prediction Explanation with Dependence-Aware Shapley Values
Description: Complex machine learning models are often hard to interpret. However, in many situations it is crucial to understand and explain why a model made a specific prediction. Shapley values is the only method for such prediction explanation framework with a solid theoretical foundation. Previously known methods for estimating the Shapley values do, however, assume feature independence. This package implements methods which accounts for any feature dependence, and thereby produces more accurate estimates of the true Shapley values. An accompanying 'Python' wrapper ('shaprpy') is available through the GitHub repository.
Author: Martin Jullum [cre, aut] , Lars Henry Berge Olsen [aut] , Annabelle Redelmeier [aut], Jon Lachmann [aut] , Nikolai Sellereite [aut] , Anders Loeland [ctb], Jens Christian Wahl [ctb], Camilla Lingjaerde [ctb], Norsk Regnesentral [cph, fnd]
Maintainer: Martin Jullum <Martin.Jullum@nr.no>

Diff between shapr versions 1.0.3 dated 2025-04-01 and 1.0.4 dated 2025-04-28

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Package mapme.biodiversity updated to version 0.9.4 with previous version 0.9.3 dated 2024-10-21

Title: Efficient Monitoring of Global Biodiversity Portfolios
Description: Biodiversity areas, especially primary forest, serve a multitude of functions for local economy, regional functionality of the ecosystems as well as the global health of our planet. Recently, adverse changes in human land use practices and climatic responses to increased greenhouse gas emissions, put these biodiversity areas under a variety of different threats. The present package helps to analyse a number of biodiversity indicators based on freely available geographical datasets. It supports computational efficient routines that allow the analysis of potentially global biodiversity portfolios. The primary use case of the package is to support evidence based reporting of an organization's effort to protect biodiversity areas under threat and to identify regions were intervention is most duly needed.
Author: Darius A. Goergen [aut] , Om Prakash Bhandari [aut], Andreas Petutschnig [ctb] , Sven Bergtold [ctb, cre], Zivan Karaman [ctb] , MAPME-Initiative [cph, fnd]
Maintainer: Sven Bergtold <sven.bergtold@gmail.com>

Diff between mapme.biodiversity versions 0.9.3 dated 2024-10-21 and 0.9.4 dated 2025-04-28

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 mapme.biodiversity-0.9.4/mapme.biodiversity/NEWS.md                                                 |  722 ++---
 mapme.biodiversity-0.9.4/mapme.biodiversity/R/calc_ecoregion.R                                      |    2 
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 mapme.biodiversity-0.9.4/mapme.biodiversity/R/calc_gsw_occurrence.R                                 |    2 
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 mapme.biodiversity-0.9.4/mapme.biodiversity/R/calc_ipbes_biomes.R                                   |    4 
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 mapme.biodiversity-0.9.4/mapme.biodiversity/R/calc_traveltime_2000.R                                |    2 
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 mapme.biodiversity-0.9.4/mapme.biodiversity/R/get_fritz_et_al.R                                     |    2 
 mapme.biodiversity-0.9.4/mapme.biodiversity/R/get_gfw_lossyear.R                                    |    2 
 mapme.biodiversity-0.9.4/mapme.biodiversity/R/get_gmw.R                                             |    2 
 mapme.biodiversity-0.9.4/mapme.biodiversity/R/get_gsw.R                                             |    2 
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 mapme.biodiversity-0.9.4/mapme.biodiversity/R/get_iucn.R                                            |    3 
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 mapme.biodiversity-0.9.4/mapme.biodiversity/R/get_ucdp_ged.R                                        |    2 
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More information about mapme.biodiversity at CRAN
Permanent link

New package licoread with initial version 0.1.1
Package: licoread
Title: Reads Raw Files from Li-COR Gas Analyzers
Version: 0.1.1
Date: 2025-04-23
Description: Reads raw files from Li-COR gas analyzers and produces a dataframe that can directly be used with 'fluxible' <https://cran.r-project.org/package=fluxible>.
License: GPL (>= 3)
Encoding: UTF-8
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
Imports: dplyr, jsonlite, lubridate, purrr, readr, rlang, stringr, tibble, tidyr, yaml
URL: https://jogaudard.github.io/licoread/
BugReports: https://github.com/jogaudard/licoread/issues
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2025-04-25 16:31:20 UTC; jga051
Author: Joseph Gaudard [aut, cre]
Maintainer: Joseph Gaudard <joseph.gaudard@pm.me>
Depends: R (>= 4.1.0)
Repository: CRAN
Date/Publication: 2025-04-28 12:30:02 UTC

More information about licoread at CRAN
Permanent link

New package joker with initial version 0.14.2
Package: joker
Title: Probability Distributions and Parameter Estimation
Version: 0.14.2
Description: Implements an S4 distribution system and estimation methods for parameters of common distribution families. The common d, p, q, r function family for each distribution is enriched with the ll, e, and v counterparts, computing the log-likelihood, performing estimation, and calculating the asymptotic variance - covariance matrix, respectively. Parameter estimation is performed analytically whenever possible.
License: GPL (>= 3)
URL: https://thechibo.github.io/joker/
BugReports: https://github.com/thechibo/joker/issues/
Depends: R (>= 4.0.0)
Imports: ggh4x, ggplot2, grDevices, Matrix, methods, stats, utils
Suggests: covr, knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
Encoding: UTF-8
Language: en-US
NeedsCompilation: no
Packaged: 2025-04-25 16:36:53 UTC; John
Author: Ioannis Oikonomidis [aut, cre] , Samis Trevezas [aut, ths]
Maintainer: Ioannis Oikonomidis <goikon@math.uoa.gr>
Repository: CRAN
Date/Publication: 2025-04-28 12:40:01 UTC

More information about joker at CRAN
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Package grates updated to version 1.5.0 with previous version 1.4.3 dated 2025-03-10

Title: Grouped Date Classes
Description: Provides a coherent interface and implementation for creating grouped date classes.
Author: Tim Taylor [aut, cre]
Maintainer: Tim Taylor <tim.taylor@hiddenelephants.co.uk>

Diff between grates versions 1.4.3 dated 2025-03-10 and 1.5.0 dated 2025-04-28

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More information about grates at CRAN
Permanent link

New package forensicpopdata with initial version 1.0.2
Package: forensicpopdata
Title: Allele Frequency Data for Human Genetic Markers
Version: 1.0.2
Description: Provides allele frequency data for Short Tandem Repeat human genetic markers commonly used in forensic genetics for human identification and kinship analysis. Includes published population frequency data from the US National Institute of Standards and Technology and the UK government.
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.5)
Imports: xml2
NeedsCompilation: no
Packaged: 2025-04-25 14:33:20 UTC; maart
Author: Maarten Kruijver [aut, cre]
Maintainer: Maarten Kruijver <maarten.kruijver@esr.cri.nz>
Repository: CRAN
Date/Publication: 2025-04-28 12:30:06 UTC

More information about forensicpopdata at CRAN
Permanent link

Package bulkreadr updated to version 1.2.0 with previous version 1.1.1 dated 2024-05-26

Title: The Ultimate Tool for Reading Data in Bulk
Description: Designed to simplify and streamline the process of reading and processing large volumes of data in R, this package offers a collection of functions tailored for bulk data operations. It enables users to efficiently read multiple sheets from Microsoft Excel and Google Sheets workbooks, as well as various CSV files from a directory. The data is returned as organized data frames, facilitating further analysis and manipulation. Ideal for handling extensive data sets or batch processing tasks, bulkreadr empowers users to manage data in bulk effortlessly, saving time and effort in data preparation workflows. Additionally, the package seamlessly works with labelled data from SPSS and Stata.
Author: Ezekiel Ogundepo [aut, cre] , Ernest Fokoue [ctb] , Golibe Ezeechesi [ctb], Fatimo Adebanjo [ctb], Isaac Ajao [ctb]
Maintainer: Ezekiel Ogundepo <gbganalyst@gmail.com>

Diff between bulkreadr versions 1.1.1 dated 2024-05-26 and 1.2.0 dated 2025-04-28

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More information about bulkreadr at CRAN
Permanent link

Package bayestestR updated to version 0.15.3 with previous version 0.15.2 dated 2025-02-07

Title: Understand and Describe Bayesian Models and Posterior Distributions
Description: Provides utilities to describe posterior distributions and Bayesian models. It includes point-estimates such as Maximum A Posteriori (MAP), measures of dispersion (Highest Density Interval - HDI; Kruschke, 2015 <doi:10.1016/C2012-0-00477-2>) and indices used for null-hypothesis testing (such as ROPE percentage, pd and Bayes factors). References: Makowski et al. (2021) <doi:10.21105/joss.01541>.
Author: Dominique Makowski [aut, cre] , Daniel Luedecke [aut] , Mattan S. Ben-Shachar [aut] , Indrajeet Patil [aut] , Micah K. Wilson [aut] , Brenton M. Wiernik [aut] , Paul-Christian Buerkner [rev], Tristan Mahr [rev] , Henrik Singmann [ctb] , Quentin F. Gron [...truncated...]
Maintainer: Dominique Makowski <officialeasystats@gmail.com>

Diff between bayestestR versions 0.15.2 dated 2025-02-07 and 0.15.3 dated 2025-04-28

 DESCRIPTION                              |   16 +-
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 R/bci.R                                  |   35 +---
 R/check_prior.R                          |    9 -
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 R/print.equivalence_test.R               |    2 
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Package tidytuesdayR updated to version 1.2.0 with previous version 1.1.2 dated 2024-09-09

Title: Access the Weekly 'TidyTuesday' Project Dataset
Description: 'TidyTuesday' is a project by the 'Data Science Learning Community' in which they post a weekly dataset in a public data repository (<https://github.com/rfordatascience/tidytuesday>) for people to analyze and visualize. This package provides the tools to easily download this data and the description of the source.
Author: Jon Harmon [aut, cre] , Ellis Hughes [aut], Thomas Mock [ctb], Data Science Learning Community [dtc]
Maintainer: Jon Harmon <jonthegeek@gmail.com>

Diff between tidytuesdayR versions 1.1.2 dated 2024-09-09 and 1.2.0 dated 2025-04-28

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Permanent link

Package ATNr updated to version 1.1.1 with previous version 1.1.0 dated 2023-09-04

Title: Run Allometric Trophic Networks Models
Description: Implements the differential equations associated to different versions of Allometric Trophic Models (ATN) to estimate the temporal dynamics of species biomasses in food webs. It offers several features to generate synthetic food webs and to parametrise models as well as a wrapper to the ODE solver deSolve.
Author: Benoit Gauzens [cre, aut], Emilio Berti [aut]
Maintainer: Benoit Gauzens <benoit.gauzens@gmail.com>

Diff between ATNr versions 1.1.0 dated 2023-09-04 and 1.1.1 dated 2025-04-28

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Package BayesChange updated to version 2.1.0 with previous version 2.0.0 dated 2025-03-12

Title: Bayesian Methods for Change Points Analysis
Description: Perform change points detection on univariate and multivariate time series according to the methods presented by Asael Fabian Martínez and Ramsés H. Mena (2014) <doi:10.1214/14-BA878> and Corradin, Danese and Ongaro (2022) <doi:10.1016/j.ijar.2021.12.019>. It also clusters different types of time dependent data with common change points, see "Model-based clustering of time-dependent observations with common structural changes" (Corradin,Danese,KhudaBukhsh and Ongaro, 2024) <doi:10.48550/arXiv.2410.09552> for details.
Author: Luca Danese [aut, cre, cph] , Riccardo Corradin [aut], Andrea Ongaro [aut]
Maintainer: Luca Danese <l.danese1@campus.unimib.it>

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More information about BayesChange at CRAN
Permanent link

Package stops updated to version 1.9-1 with previous version 1.8-2 dated 2024-09-22

Title: Structure Optimized Proximity Scaling
Description: Methods that use flexible variants of multidimensional scaling (MDS) which incorporate parametric nonlinear distance transformations and trade-off the goodness-of-fit fit with structure considerations to find optimal hyperparameters, also known as structure optimized proximity scaling (STOPS) (Rusch, Mair & Hornik, 2023,<doi:10.1007/s11222-022-10197-w>). The package contains various functions, wrappers, methods and classes for fitting, plotting and displaying different 1-way MDS models with ratio, interval, ordinal optimal scaling in a STOPS framework. These cover essentially the functionality of the package smacofx, including Torgerson (classical) scaling with power transformations of dissimilarities, SMACOF MDS with powers of dissimilarities, Sammon mapping with powers of dissimilarities, elastic scaling with powers of dissimilarities, spherical SMACOF with powers of dissimilarities, (ALSCAL) s-stress MDS with powers of dissimilarities, r-stress MDS, MDS with powers of diss [...truncated...]
Author: Thomas Rusch [aut, cre] , Patrick Mair [aut] , Kurt Hornik [ctb]
Maintainer: Thomas Rusch <thomas.rusch@wu.ac.at>

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Package rplum updated to version 0.5.2 with previous version 0.5.1 dated 2024-09-29

Title: Bayesian Age-Depth Modelling of Cores Dated by Pb-210
Description: An approach to age-depth modelling that uses Bayesian statistics to reconstruct accumulation histories for 210Pb-dated deposits using prior information. It can combine 210Pb, radiocarbon, and other dates in the chronologies. See Aquino et al. (2018) <doi:10.1007/s13253-018-0328-7>. Note that parts of the code underlying 'rplum' are derived from the 'rbacon' package by the same authors, and there remains a degree of overlap between the two packages.
Author: Maarten Blaauw [aut, cre] , J. Andres Christen [aut, ctb, cph] , Marco A. Aquino Lopez [aut] , Judith Esquivel Vazquez [ctb], Oscar M. Gonzalez V. [ctb], Ted Belding [cph], James Theiler [cph], Brian Gough [cph], Charles Karney [cph]
Maintainer: Maarten Blaauw <maarten.blaauw@qub.ac.uk>

Diff between rplum versions 0.5.1 dated 2024-09-29 and 0.5.2 dated 2025-04-28

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Permanent link

Package pkgdown updated to version 2.1.2 with previous version 2.1.1 dated 2024-09-17

Title: Make Static HTML Documentation for a Package
Description: Generate an attractive and useful website from a source package. 'pkgdown' converts your documentation, vignettes, 'README', and more to 'HTML' making it easy to share information about your package online.
Author: Hadley Wickham [aut, cre] , Jay Hesselberth [aut] , Maelle Salmon [aut] , Olivier Roy [aut], Salim Brueggemann [aut] , Posit Software, PBC [cph, fnd]
Maintainer: Hadley Wickham <hadley@posit.co>

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Permanent link

Package pbkrtest updated to version 0.5.4 with previous version 0.5.3 dated 2024-06-26

Title: Parametric Bootstrap, Kenward-Roger and Satterthwaite Based Methods for Test in Mixed Models
Description: Computes p-values based on (a) Satterthwaite or Kenward-Rogers degree of freedom methods and (b) parametric bootstrap for mixed effects models as implemented in the 'lme4' package. Implements parametric bootstrap test for generalized linear mixed models as implemented in 'lme4' and generalized linear models. The package is documented in the paper by Halekoh and Højsgaard, (2012, <doi:10.18637/jss.v059.i09>). Please see 'citation("pbkrtest")' for citation details.
Author: Ulrich Halekoh [aut, cph], Soeren Hoejsgaard [aut, cre, cph]
Maintainer: Soeren Hoejsgaard <sorenh@math.aau.dk>

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Package msme updated to version 0.5.4 with previous version 0.5.3 dated 2018-03-18

Title: Functions and Datasets for "Methods of Statistical Model Estimation"
Description: Functions and datasets from Hilbe, J.M., and Robinson, A.P. 2013. Methods of Statistical Model Estimation. Chapman & Hall / CRC.
Author: Joseph Hilbe [aut], Andrew Robinson [aut, cre]
Maintainer: Andrew Robinson <apro@unimelb.edu.au>

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Package mlogit updated to version 1.1-2 with previous version 1.1-1 dated 2020-10-02

Title: Multinomial Logit Models
Description: Maximum likelihood estimation of random utility discrete choice models. The software is described in Croissant (2020) <doi:10.18637/jss.v095.i11> and the underlying methods in Train (2009) <doi:10.1017/CBO9780511805271>.
Author: Yves Croissant [aut, cre]
Maintainer: Yves Croissant <yves.croissant@univ-reunion.fr>

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Package hubeau updated to version 0.5.2 with previous version 0.5.1 dated 2025-01-13

Title: Get Data from the French National Database on Water 'Hub'Eau'
Description: Collection of functions to help retrieving data from 'Hub'Eau' the free and public French National APIs on water <https://hubeau.eaufrance.fr/>.
Author: David Dorchies [aut, cre] , Pascal Irz [ctb] , Sebastien Grall [ctb], Philippe Amiotte Suchet [ctb]
Maintainer: David Dorchies <david.dorchies@inrae.fr>

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Package COUNT updated to version 1.3.5 with previous version 1.3.4 dated 2016-10-19

Title: Functions, Data and Code for Count Data
Description: Functions, data and code for Hilbe, J.M. 2011. Negative Binomial Regression, 2nd Edition (Cambridge University Press) and Hilbe, J.M. 2014. Modeling Count Data (Cambridge University Press).
Author: Joseph M Hilbe [aut], Andrew Robinson [cre]
Maintainer: Andrew Robinson <apro@unimelb.edu.au>

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Package cgam updated to version 1.26 with previous version 1.25 dated 2025-04-23

Title: Constrained Generalized Additive Model
Description: A constrained generalized additive model is fitted by the cgam routine. Given a set of predictors, each of which may have a shape or order restrictions, the maximum likelihood estimator for the constrained generalized additive model is found using an iteratively re-weighted cone projection algorithm. The ShapeSelect routine chooses a subset of predictor variables and describes the component relationships with the response. For each predictor, the user needs only specify a set of possible shape or order restrictions. A model selection method chooses the shapes and orderings of the relationships as well as the variables. The cone information criterion (CIC) is used to select the best combination of variables and shapes. A genetic algorithm may be used when the set of possible models is large. In addition, the cgam routine implements a two-dimensional isotonic regression using warped-plane splines without additivity assumptions. It can also fit a convex or concave regression surface with [...truncated...]
Author: Mary Meyer [aut], Xiyue Liao [aut, cre]
Maintainer: Xiyue Liao <xliao@sdsu.edu>

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Package RcmdrPlugin.BWS2 updated to version 0.3-0 with previous version 0.2-2 dated 2024-05-21

Title: R Commander Plug-in for Case 2 Best-Worst Scaling
Description: Adds menu items for case 2 (profile case) best-worst scaling (BWS2) to the R Commander. BWS2 is a question-based survey method that constructs profiles (combinations of attribute levels) using an orthogonal array, asks respondents to select the best and worst levels in each profile, and measures preferences for attribute levels by analyzing the responses. For details, see Aizaki and Fogarty (2019) <doi:10.1016/j.jocm.2019.100171>.
Author: Hideo Aizaki [aut, cre]
Maintainer: Hideo Aizaki <azk-r@spa.nifty.com>

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Package EDOIF updated to version 0.1.4 with previous version 0.1.3 dated 2021-03-28

Title: Empirical Distribution Ordering Inference Framework (EDOIF)
Description: A non-parametric framework based on estimation statistics principle. Its main purpose is to infer orders of empirical distributions from different categories based on a probability of finding a value in one distribution that is greater than an expectation of another distribution. Given a set of ordered-pair of real-category values the framework is capable of 1) inferring orders of domination of categories and representing orders in the form of a graph; 2) estimating magnitude of difference between a pair of categories in forms of mean-difference confidence intervals; and 3) visualizing domination orders and magnitudes of difference of categories. The publication of this package is at Chainarong Amornbunchornvej, Navaporn Surasvadi, Anon Plangprasopchok, and Suttipong Thajchayapong (2020) <doi:10.1016/j.heliyon.2020.e05435>.
Author: Chainarong Amornbunchornvej [aut, cre]
Maintainer: Chainarong Amornbunchornvej <grandca@gmail.com>

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Package rusquant (with last version 1.1.4) was removed from CRAN

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

2024-09-16 1.1.4

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Package trelloR (with last version 0.8.0) was removed from CRAN

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

2023-08-27 0.8.0
2021-04-21 0.7.1
2021-01-28 0.7.0
2016-09-22 0.1.0

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