Thu, 09 Oct 2025

Package bennu updated to version 0.3.2 with previous version 0.3.1 dated 2025-07-25

Title: Bayesian Estimation of Naloxone Kit Number Under-Reporting
Description: Bayesian model and associated tools for generating estimates of total naloxone kit numbers distributed and used from naloxone kit orders data. Provides functions for generating simulated data of naloxone kit use and functions for generating samples from the posterior.
Author: Mike Irvine [aut, cre, cph] , Samantha Bardwell [ctb], Andrew Johnson [ctb]
Maintainer: Mike Irvine <mike.irvine@bccdc.ca>

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Package TriDimRegression updated to version 1.0.3 with previous version 1.0.2 dated 2023-09-13

Title: Bayesian Statistics for 2D/3D Transformations
Description: Fits 2D and 3D geometric transformations via 'Stan' probabilistic programming engine ( Stan Development Team (2021) <https://mc-stan.org>). Returns posterior distribution for individual parameters of the fitted distribution. Allows for computation of LOO and WAIC information criteria (Vehtari A, Gelman A, Gabry J (2017) <doi:10.1007/s11222-016-9696-4>) as well as Bayesian R-squared (Gelman A, Goodrich B, Gabry J, and Vehtari A (2018) <doi:10.1080/00031305.2018.1549100>).
Author: Alexander Pastukhov [aut, cre] , Claus-Christian Carbon [aut]
Maintainer: Alexander (Sasha) Pastukhov <pastukhov.alexander@gmail.com>

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Package RiskMap updated to version 1.0.0 with previous version 0.1.0 dated 2024-06-25

Title: Geostatistical Modeling of Spatially Referenced Data
Description: Geostatistical analysis of continuous and count data. Implements stationary Gaussian processes with Matérn correlation for spatial prediction, as described in Diggle and Giorgi (2019, ISBN: 978-1-138-06102-7).
Author: Emanuele Giorgi [aut, cre] , Claudio Fronterre [ctb]
Maintainer: Emanuele Giorgi <e.giorgi@bham.ac.uk>

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Package redquack updated to version 0.3.0 with previous version 0.2.0 dated 2025-05-14

Title: Transfer 'REDCap' Data to Database
Description: Transfer 'REDCap' (Research Electronic Data Capture) data to a database, specifically optimized for 'DuckDB'. Processes data in chunks to handle large datasets without exceeding available memory. Features include data labeling, coded value conversion, and hearing a "quack" sound on success.
Author: Dylan Pieper [aut, cre]
Maintainer: Dylan Pieper <dylanpieper@gmail.com>

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Package ExtremeRisks updated to version 0.0.5 with previous version 0.0.4-1 dated 2025-04-26

Title: Extreme Risk Measures
Description: A set of procedures for estimating risks related to extreme events via risk measures such as Expectile, Value-at-Risk, etc. is provided. Estimation methods for univariate independent observations and temporal dependent observations are available. The methodology is extended to the case of independent multidimensional observations. The statistical inference is performed through parametric and non-parametric estimators. Inferential procedures such as confidence intervals, confidence regions and hypothesis testing are obtained by exploiting the asymptotic theory. Adapts the methodologies derived in Padoan and Stupfler (2022) <doi:10.3150/21-BEJ1375>, Davison et al. (2023) <doi:10.1080/07350015.2022.2078332>, Daouia et al. (2018) <doi:10.1111/rssb.12254>, Drees (2000) <doi:10.1214/aoap/1019487617>, Drees (2003) <doi:10.3150/bj/1066223272>, de Haan and Ferreira (2006) <doi:10.1007/0-387-34471-3>, de Haan et al. (2016) <doi:10.1007/s00780-015-0287-6> [...truncated...]
Author: Simone Padoan [cre, aut], Gilles Stupfler [aut], Carlotta Pacifici [aut]
Maintainer: Simone Padoan <simone.padoan@unibocconi.it>

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Package RKorAPClient updated to version 1.2.1 with previous version 1.2.0 dated 2025-09-10

Title: 'KorAP' Web Service Client Package
Description: A client package that makes the 'KorAP' web service API accessible from R. The corpus analysis platform 'KorAP' has been developed as a scientific tool to make potentially large, stratified and multiply annotated corpora, such as the 'German Reference Corpus DeReKo' or the 'Corpus of the Contemporary Romanian Language CoRoLa', accessible for linguists to let them verify hypotheses and to find interesting patterns in real language use. The 'RKorAPClient' package provides access to 'KorAP' and the corpora behind it for user-created R code, as a programmatic alternative to the 'KorAP' web user-interface. You can learn more about 'KorAP' and use it directly on 'DeReKo' at <https://korap.ids-mannheim.de/>.
Author: Marc Kupietz [aut, cre], Nils Diewald [ctb], Leibniz Institute for the German Language [cph, fnd]
Maintainer: Marc Kupietz <kupietz@ids-mannheim.de>

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Package rversions updated to version 3.0.0 with previous version 2.1.2 dated 2022-08-31

Title: Query 'R' Versions, Including 'r-release' and 'r-oldrel'
Description: Query the main 'R' 'SVN' repository to find the versions 'r-release' and 'r-oldrel' refer to, and also all previous 'R' versions and their release dates.
Author: Gabor Csardi [aut, cre], Jeroen Ooms [ctb], R Consortium [fnd], Posit Software, PBC [cph, fnd]
Maintainer: Gabor Csardi <csardi.gabor@gmail.com>

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Package oysteR updated to version 0.1.4 with previous version 0.1.1 dated 2021-01-10

Title: Scans R Projects for Vulnerable Third Party Dependencies
Description: Collects a list of your third party R packages, and scans them with the 'OSS' Index provided by 'Sonatype', reporting back on any vulnerabilities that are found in the third party packages you use.
Author: Jeffry Hesse [aut], Brittany Belle [aut], Colin Gillespie [aut, cre] , Dan Rollo [aut], Josiah Parry [aut] , Sonatype [cph]
Maintainer: Colin Gillespie <csgillespie@gmail.com>

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Package glmmTMB updated to version 1.1.13 with previous version 1.1.12 dated 2025-08-18

Title: Generalized Linear Mixed Models using Template Model Builder
Description: Fit linear and generalized linear mixed models with various extensions, including zero-inflation. The models are fitted using maximum likelihood estimation via 'TMB' (Template Model Builder). Random effects are assumed to be Gaussian on the scale of the linear predictor and are integrated out using the Laplace approximation. Gradients are calculated using automatic differentiation.
Author: Mollie Brooks [aut, cre] , Ben Bolker [aut] , Kasper Kristensen [aut], Martin Maechler [aut] , Arni Magnusson [aut] , Maeve McGillycuddy [ctb], Hans Skaug [aut] , Anders Nielsen [aut] , Casper Berg [aut] , Koen van Bentham [aut], Nafis Sadat [ctb] , [...truncated...]
Maintainer: Mollie Brooks <mollieebrooks@gmail.com>

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Package rsofun updated to version 5.1.0 with previous version 5.0.0 dated 2024-11-28

Title: The P-Model and BiomeE Modelling Framework
Description: Implements the Simulating Optimal FUNctioning framework for site-scale simulations of ecosystem processes, including model calibration. It contains 'Fortran 90' modules for the P-model (Stocker et al. (2020) <doi:10.5194/gmd-13-1545-2020>), SPLASH (Davis et al. (2017) <doi:10.5194/gmd-10-689-2017>) and BiomeE (Weng et al. (2015) <doi:10.5194/bg-12-2655-2015>).
Author: Benjamin Stocker [aut, cre] , Koen Hufkens [aut] , Josefa Aran Paredes [aut] , Laura Marques [ctb] , Mayeul Marcadella [ctb] , Ensheng Weng [ctb] , Fabian Bernhard [aut] , Geocomputation and Earth Observation, University of Bern [cph, fnd]
Maintainer: Benjamin Stocker <benjamin.stocker@gmail.com>

Diff between rsofun versions 5.0.0 dated 2024-11-28 and 5.1.0 dated 2025-10-09

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More information about rsofun at CRAN
Permanent link

Package lulab.utils updated to version 1.0.0 with previous version 0.0.4 dated 2024-10-07

Title: Supporting Functions Maintained by Zhen Lu
Description: Miscellaneous functions commonly used by LuLab. This package aims to help more researchers on epidemiology to perform data management and visualization more efficiently.
Author: Zhen Lu [aut, cre]
Maintainer: Zhen Lu <luzh29@mail2.sysu.edu.cn>

Diff between lulab.utils versions 0.0.4 dated 2024-10-07 and 1.0.0 dated 2025-10-09

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Package visOmopResults updated to version 1.3.1 with previous version 1.3.0 dated 2025-10-05

Title: Graphs and Tables for OMOP Results
Description: Provides methods to transform omop_result objects into formatted tables and figures, facilitating the visualisation of study results working with the Observational Medical Outcomes Partnership (OMOP) Common Data Model.
Author: Marti Catala [aut] , Nuria Mercade-Besora [aut, cre] , Yuchen Guo [ctb] , Elin Rowlands [ctb] , Marta Alcalde-Herraiz [ctb] , Edward Burn [ctb]
Maintainer: Nuria Mercade-Besora <nuria.mercadebesora@ndorms.ox.ac.uk>

Diff between visOmopResults versions 1.3.0 dated 2025-10-05 and 1.3.1 dated 2025-10-09

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Permanent link

New package tseffects with initial version 0.1.4
Package: tseffects
Title: Dynamic (Causal) Inferences from Time Series (with Interactions)
Version: 0.1.4
Maintainer: Soren Jordan <sorenjordanpols@gmail.com>
Description: Autoregressive distributed lag (A[R]DL) models (and their reparameterized equivalent, the Generalized Error-Correction Model [GECM]) (see De Boef and Keele 2008 <doi:10.1111/j.1540-5907.2007.00307.x>) are the workhorse models in uncovering dynamic inferences. ADL models are simple to estimate; this is what makes them attractive. Once these models are estimated, what is less clear is how to uncover a rich set of dynamic inferences from these models. We provide tools for recovering those inferences in three forms: causal inferences from ADL models, traditional time series quantities of interest (short- and long-run effects), and dynamic conditional relationships.
URL: https://sorenjordan.github.io/tseffects/, https://github.com/sorenjordan/tseffects
BugReports: https://github.com/sorenjordan/tseffects/issues
Imports: mpoly, car, ggplot2, sandwich, stats, utils
Suggests: knitr, rmarkdown, vdiffr, testthat (>= 3.0.0)
Depends: R (>= 3.5.0)
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
BuildManual: yes
NeedsCompilation: no
Packaged: 2025-10-06 14:16:05 UTC; sorenjordan
Author: Soren Jordan [aut, cre, cph] , Garrett N. Vande Kamp [aut], Reshi Rajan [aut]
Repository: CRAN
Date/Publication: 2025-10-09 12:10:02 UTC

More information about tseffects at CRAN
Permanent link

Package treedata.table readmission to version 0.1.1 with previous version 0.1.0 dated 2020-09-30

Title: Manipulation of Matched Phylogenies and Data using 'data.table'
Description: An implementation that combines trait data and a phylogenetic tree (or trees) into a single object of class 'treedata.table'. The resulting object can be easily manipulated to simultaneously change the trait- and tree-level sampling. Currently implemented functions allow users to use a 'data.table' syntax when performing operations on the trait dataset within the 'treedata.table' object. For more details see Roman-Palacios et al. (2021) <doi:10.7717/peerj.12450>.
Author: Josef Uyeda [aut] , Cristian Roman-Palacios [aut, cre] , April Wright [aut] , Luke Harmon [ctb], Hugo Gruson [rev], Kari Norman [rev]
Maintainer: Cristian Roman-Palacios <cromanpa@arizona.edu>

This is a re-admission after prior archival of version 0.1.0 dated 2020-09-30

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New package shinymrp with initial version 0.9.0
Package: shinymrp
Title: Interface for Multilevel Regression and Poststratification
Version: 0.9.0
Author: Toan Tran [cre, aut, cph], Jonah Gabry [aut, cph], Yajuan Si [aut, cph]
Maintainer: Toan Tran <trannttoan97@gmail.com>
Description: Dual interfaces, graphical and programmatic, designed for intuitive applications of Multilevel Regression and Poststratification (MRP). Users can apply the method to a variety of datasets, from electronic health records to sample survey data, through an end-to-end Bayesian data analysis workflow. The package provides robust tools for data cleaning, exploratory analysis, flexible model building, and insightful result visualization. For more details, see Si et al. (2020) <https://www150.statcan.gc.ca/n1/en/pub/12-001-x/2020002/article/00003-eng.pdf?st=iF1_Fbrh> and Si (2025) <doi:10.1214/24-STS932>.
License: MIT + file LICENSE
URL: https://mrp-interface.github.io/shinymrp/
BugReports: https://github.com/mrp-interface/shinymrp/issues
Depends: R (>= 3.6.0)
Imports: bsicons, bslib, checkmate, config (>= 0.3.2), dplyr, DT, ggplot2, golem (>= 0.4.1), highcharter, htmlwidgets, httr2, loo, lubridate, magrittr, patchwork, posterior, purrr, qs, R6, RColorBrewer, readr, rlang, scales, shiny (>= 1.8.0), shinyjs, shinyWidgets, stringr, tidyr, waiter
Suggests: cmdstanr, knitr, rmarkdown, spelling, testthat (>= 3.0.0)
Additional_repositories: https://stan-dev.r-universe.dev/
Encoding: UTF-8
Language: en-US
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2025-10-06 19:09:16 UTC; tntoan
Repository: CRAN
Date/Publication: 2025-10-09 12:20:09 UTC

More information about shinymrp at CRAN
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New package kardl with initial version 0.1.1
Package: kardl
Title: Make Symmetric and Asymmetric ARDL Estimations
Version: 0.1.1
Maintainer: Huseyin Karamelikli <hakperest@gmail.com>
Description: Implements estimation procedures for Autoregressive Distributed Lag (ARDL) and Nonlinear ARDL (NARDL) models, which allow researchers to investigate both short- and long-run relationships in time series data under mixed orders of integration. The package supports simultaneous modeling of symmetric and asymmetric regressors, flexible treatment of short-run and long-run asymmetries, and automated equation handling. It includes several cointegration testing approaches such as the Pesaran-Shin-Smith F and t bounds tests, the Banerjee error correction test, and the restricted ECM test, together with diagnostic tools including Wald tests for asymmetry, ARCH tests, and stability procedures (CUSUM and CUSUMQ). Methodological foundations are provided in Pesaran, Shin, and Smith (2001) <doi:10.1016/S0304-4076(01)00049-5> and Shin, Yu, and Greenwood-Nimmo (2014, ISBN:9780123855079).
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: stats, msm, lmtest, nlWaldTest, car, utils
Suggests: knitr, rmarkdown, officer, flextable, equatags, magrittr, rlang, ggplot2, tidyr, dplyr, testthat (>= 3.0.0)
NeedsCompilation: no
VignetteBuilder: knitr
Packaged: 2025-10-06 12:27:43 UTC; huseyin
Author: Huseyin Karamelikli [aut, cre] , Huseyin Utku Demir [aut]
Depends: R (>= 3.5.0)
Repository: CRAN
Date/Publication: 2025-10-09 12:10:11 UTC

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New package ItemRest with initial version 0.2.3
Package: ItemRest
Title: Automated Item Removal Strategies for Exploratory Factor Analysis
Version: 0.2.3
Description: Automates the identification and comparative evaluation of item-removal strategies in exploratory factor analysis, producing transparent summaries (explained variance, loading ranges, reliability) to support comfortable, reproducible decisions. The criteria are based on best practices and established heuristics (e.g., Costello & Osborne (2005) <doi:10.7275/jyj1-4868>, Howard (2016) <doi:10.1080/10447318.2015.1087664>).
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1)
Imports: gtools, psych, qgraph, stats, utils
URL: https://github.com/ahmetcaliskan1987/ItemRest
BugReports: https://github.com/ahmetcaliskan1987/ItemRest/issues
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2025-10-06 14:02:37 UTC; ahmetcaliskan
Author: Ahmet Caliskan [aut, cre], Abdullah Faruk Kilic [aut]
Maintainer: Ahmet Caliskan <ahmetcaliskan1987@gmail.com>
Repository: CRAN
Date/Publication: 2025-10-09 12:10:17 UTC

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Package immundata updated to version 0.0.5 with previous version 0.0.3 dated 2025-09-04

Title: A Unified Data Layer for Large-Scale Single-Cell, Spatial and Bulk Immunomics
Description: Provides a unified data layer for single-cell, spatial and bulk T-cell and B-cell immune receptor repertoire data. Think AnnData or SeuratObject, but for AIRR data, a.k.a. Adaptive Immune Receptor Repertoire, VDJ-seq, RepSeq, or VDJ sequencing data.
Author: Vadim I. Nazarov [aut, cre]
Maintainer: Vadim I. Nazarov <support@immunomind.com>

Diff between immundata versions 0.0.3 dated 2025-09-04 and 0.0.5 dated 2025-10-09

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New package BioMonTools with initial version 1.2.4
Package: BioMonTools
Title: Biomonitoring and Bioassessment Calculations
Version: 1.2.4
Maintainer: Erik W. Leppo <Erik.Leppo@tetratech.com>
Description: An aid for manipulating data associated with biomonitoring and bioassessment. Calculations include metric calculation, marking of excluded taxa, subsampling, and multimetric index calculation. Targeted communities are benthic macroinvertebrates, fish, periphyton, and coral. As described in the Revised Rapid Bioassessment Protocols (Barbour et al. 1999) <https://archive.epa.gov/water/archive/web/html/index-14.html>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.5)
Imports: dplyr, maps, rlang, stats, tidyselect, tidyr
Suggests: DataExplorer, DT, ggplot2, knitr, lazyeval, readxl, reshape2, rmarkdown, testthat, shiny, shinydashboard, shinydashboardPlus, shinyjs, shinyWidgets, utils, writexl, shinyalert
URL: https://github.com/leppott/BioMonTools
BugReports: https://github.com/leppott/BioMonTools/issues
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2025-10-06 18:17:29 UTC; Erik.Leppo
Author: Erik W. Leppo [aut, cre] , Jen Stamp [ctb], John van Sickles [ctb], Ben Block [ctb]
Repository: CRAN
Date/Publication: 2025-10-09 12:40:02 UTC

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Package semTests readmission to version 0.7.1 with previous version 0.5.0 dated 2024-01-18

Title: Goodness-of-Fit Testing for Structural Equation Models
Description: Supports eigenvalue block-averaging p-values (Foldnes, Grønneberg, 2018) <doi:10.1080/10705511.2017.1373021>, penalized eigenvalue block-averaging p-values (Foldnes, Moss, Grønneberg, 2024) <doi:10.1080/10705511.2024.2372028>, penalized regression p-values (Foldnes, Moss, Grønneberg, 2024) <doi:10.1080/10705511.2024.2372028>, as well as traditional p-values such as Satorra-Bentler. All p-values can be calculated using unbiased or biased gamma estimates (Du, Bentler, 2022) <doi:10.1080/10705511.2022.2063870> and two choices of chi square statistics.
Author: Jonas Moss [aut, cre] , Njal Foldnes [ctb] , Steffen Groenneberg [ctb]
Maintainer: Jonas Moss <jonas.moss.statistics@gmail.com>

This is a re-admission after prior archival of version 0.5.0 dated 2024-01-18

Diff between semTests versions 0.5.0 dated 2024-01-18 and 0.7.1 dated 2025-10-09

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Package rvif updated to version 3.2 with previous version 3.1 dated 2025-09-05

Title: Collinearity Detection using Redefined Variance Inflation Factor and Graphical Methods
Description: The detection of troubling approximate collinearity in a multiple linear regression model is a classical problem in Econometrics. This package is focused on determining whether or not the degree of approximate multicollinearity in a multiple linear regression model is of concern, meaning that it affects the statistical analysis (i.e. individual significance tests) of the model. This objective is achieved by using the variance inflation factor redefined and the scatterplot between the variance inflation factor and the coefficient of variation. For more details see SalmerĂłn R., GarcĂ­a C.B. and GarcĂ­a J. (2018) <doi:10.1080/00949655.2018.1463376>, SalmerĂłn, R., RodrĂ­guez, A. and GarcĂ­a C. (2020) <doi:10.1007/s00180-019-00922-x>, SalmerĂłn, R., GarcĂ­a, C.B, RodrĂ­guez, A. and GarcĂ­a, C. (2022) <doi:10.32614/RJ-2023-010>, SalmerĂłn, R., GarcĂ­a, C.B. and GarcĂ­a, J. (2025) <doi:10.1007/s10614-024-10575-8> and SalmerĂłn, R., GarcĂ­a, C.B, GarcĂ­a J. (2023, working paper) < [...truncated...]
Author: R. Salmeron [aut, cre], C.B. Garcia [aut]
Maintainer: R. Salmeron <romansg@ugr.es>

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 rvif-3.2/rvif/man/SLM2.Rd                                                                  |    2 
 rvif-3.2/rvif/man/Wissel.Rd                                                                |    2 
 rvif-3.2/rvif/man/cv_vif.Rd                                                                |    8 
 rvif-3.2/rvif/man/employees.Rd                                                             |    4 
 rvif-3.2/rvif/man/euribor.Rd                                                               |    4 
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New package psme with initial version 1.0.0
Package: psme
Version: 1.0.0
Date: 2025-10-06
Title: Penalized Splines Mixed-Effects Models
Maintainer: Zheyuan Li <zheyuan.li@bath.edu>
Depends: R (>= 4.0.0)
Imports: stats, Matrix, methods, mgcv, lme4
Description: Fit penalized splines mixed-effects models (a special case of additive models) for large longitudinal datasets. The package includes a psme() function that (1) relies on package 'mgcv' for constructing population and subject smooth functions as penalized splines, (2) transforms the constructed additive model to a linear mixed-effects model, (3) exploits package 'lme4' for model estimation and (4) backtransforms the estimated linear mixed-effects model to the additive model for interpretation and visualization. See Pedersen et al. (2019) <doi:10.7717/peerj.6876> and Bates et al. (2015) <doi:10.18637/jss.v067.i01> for an introduction. Unlike the gamm() function in 'mgcv', the psme() function is fast and memory-efficient, able to handle datasets with millions of observations.
License: GPL-3
NeedsCompilation: no
URL: https://github.com/ZheyuanLi/psme
Packaged: 2025-10-06 11:38:57 UTC; lzy
Author: Zheyuan Li [aut, cre]
Repository: CRAN
Date/Publication: 2025-10-09 12:00:06 UTC

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Package Keng updated to version 2025.10.8 with previous version 2025.9.1 dated 2025-08-31

Title: Knock Errors Off Nice Guesses
Description: Miscellaneous functions and data used in psychological research and teaching. Keng currently has a built-in dataset depress, and could (1) scale a vector; (2) compute the cut-off values of Pearson's r with known sample size; (3) test the significance and compute the post-hoc power for Pearson's r with known sample size; (4) conduct a priori power analysis and plan the sample size for Pearson's r; (5) compare lm()'s fitted outputs using R-squared, f_squared, post-hoc power, and PRE (Proportional Reduction in Error, also called partial R-squared or partial Eta-squared); (6) calculate PRE from partial correlation, Cohen's f, or f_squared; (7) conduct a priori power analysis and plan the sample size for one or a set of predictors in regression analysis; (8) conduct post-hoc power analysis for one or a set of predictors in regression analysis with known sample size; (9) randomly pick numbers for Chinese Super Lotto and Double Color Balls; (10) assess course objective achievement in Outcome- [...truncated...]
Author: Qingyao Zhang [aut, cre]
Maintainer: Qingyao Zhang <qingyaozhang@outlook.com>

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New package CaMeA with initial version 0.1.0
Package: CaMeA
Title: Causal Meta-Analysis for Aggregated Data
Version: 0.1.0
Maintainer: Clement Berenfeld <clement.berenfeld@inria.fr>
Description: A tool for causal meta-analysis. This package implements the aggregation formulas and inference methods proposed in Berenfeld et al. (2025) <doi:10.48550/arXiv.2505.20168>. Users can input aggregated data across multiple studies and compute causally meaningful aggregated effects of their choice (risk difference, risk ratio, odds ratio, etc) under user-specified population weighting. The built-in function camea() allows to obtain precise variance estimates for these effects and to compare the latter to a classical meta-analysis aggregate, the random effect model, as implemented in the 'metafor' package <https://CRAN.R-project.org/package=metafor>.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: purrr, metafor, tibble, dplyr
Suggests: knitr, rmarkdown, kableExtra
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2025-10-06 11:50:30 UTC; berenfeld
Author: Clement Berenfeld [ctb, cre], Ahmed Boughdiri [ctb], Charif El Gataa [aut], Julie Josse [ctb]
Repository: CRAN
Date/Publication: 2025-10-09 12:00:10 UTC

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Package units updated to version 1.0-0 with previous version 0.8-7 dated 2025-03-11

Title: Measurement Units for R Vectors
Description: Support for measurement units in R vectors, matrices and arrays: automatic propagation, conversion, derivation and simplification of units; raising errors in case of unit incompatibility. Compatible with the POSIXct, Date and difftime classes. Uses the UNIDATA udunits library and unit database for unit compatibility checking and conversion. Documentation about 'units' is provided in the paper by Pebesma, Mailund & Hiebert (2016, <doi:10.32614/RJ-2016-061>), included in this package as a vignette; see 'citation("units")' for details.
Author: Edzer Pebesma [aut, cre] , Thomas Mailund [aut], Tomasz Kalinowski [aut], James Hiebert [ctb], Inaki Ucar [aut] , Thomas Lin Pedersen [ctb]
Maintainer: Edzer Pebesma <edzer.pebesma@uni-muenster.de>

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Package minic updated to version 1.0.3 with previous version 1.0.2 dated 2025-06-05

Title: Minimization Methods for Ill-Conditioned Problems
Description: Implementation of methods for minimizing ill-conditioned problems. Currently only includes regularized (quasi-)newton optimization (Kanzow and Steck et al. (2023), <doi:10.1007/s12532-023-00238-4>).
Author: Bert van der Veen [aut, cre]
Maintainer: Bert van der Veen <bert_van_der_veen@hotmail.com>

Diff between minic versions 1.0.2 dated 2025-06-05 and 1.0.3 dated 2025-10-09

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Package metamorphr updated to version 0.2.0 with previous version 0.1.1 dated 2025-09-01

Title: Tidy and Streamlined Metabolomics Data Workflows
Description: Facilitate tasks typically encountered during metabolomics data analysis including data import, filtering, missing value imputation (Stacklies et al. (2007) <doi:10.1093/bioinformatics/btm069>, Stekhoven et al. (2012) <doi:10.1093/bioinformatics/btr597>, Tibshirani et al. (2017) <doi:10.18129/B9.BIOC.IMPUTE>, Troyanskaya et al. (2001) <doi:10.1093/bioinformatics/17.6.520>), normalization (Bolstad et al. (2003) <doi:10.1093/bioinformatics/19.2.185>, Dieterle et al. (2006) <doi:10.1021/ac051632c>, Zhao et al. (2020) <doi:10.1038/s41598-020-72664-6>) transformation, centering and scaling (Van Den Berg et al. (2006) <doi:10.1186/1471-2164-7-142>) as well as statistical tests and plotting. 'metamorphr' introduces a tidy (Wickham et al. (2019) <doi:10.21105/joss.01686>) format for metabolomics data and is designed to make it easier to build elaborate analysis workflows and to integrate them with 'tidyverse' packages including 'dplyr' and [...truncated...]
Author: Yannik Schermer [aut, cre, cph]
Maintainer: Yannik Schermer <yannik.schermer@chem.rptu.de>

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Package matlib updated to version 1.0.1 with previous version 1.0.0 dated 2024-10-02

Title: Matrix Functions for Teaching and Learning Linear Algebra and Multivariate Statistics
Description: A collection of matrix functions for teaching and learning matrix linear algebra as used in multivariate statistical methods. Many of these functions are designed for tutorial purposes in learning matrix algebra ideas using R. In some cases, functions are provided for concepts available elsewhere in R, but where the function call or name is not obvious. In other cases, functions are provided to show or demonstrate an algorithm. In addition, a collection of functions are provided for drawing vector diagrams in 2D and 3D and for rendering matrix expressions and equations in LaTeX.
Author: Michael Friendly [aut, cre] , John Fox [aut] , Phil Chalmers [aut] , Georges Monette [ctb] , Gaston Sanchez [ctb]
Maintainer: Michael Friendly <friendly@yorku.ca>

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Package laminr updated to version 1.2.0 with previous version 1.1.1 dated 2025-05-15

Title: Client for 'LaminDB'
Description: Interact with 'LaminDB'. 'LaminDB' is an open-source data framework for biology. This package allows you to query and download data from 'LaminDB' instances.
Author: Robrecht Cannoodt [aut, cre] , Luke Zappia [aut] , Data Intuitive [aut], Lamin Labs [aut, cph]
Maintainer: Robrecht Cannoodt <robrecht@lamin.ai>

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Package colorblindcheck updated to version 1.0.4 with previous version 1.0.2 dated 2023-05-13

Title: Check Color Palettes for Problems with Color Vision Deficiency
Description: Compare color palettes with simulations of color vision deficiencies - deuteranopia, protanopia, and tritanopia. It includes calculation of distances between colors, and creating summaries of differences between a color palette and simulations of color vision deficiencies. This work was inspired by the blog post at <https://www.datawrapper.de/blog/colorblind-check>.
Author: Jakub Nowosad [aut, cre]
Maintainer: Jakub Nowosad <nowosad.jakub@gmail.com>

Diff between colorblindcheck versions 1.0.2 dated 2023-05-13 and 1.0.4 dated 2025-10-09

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Package StreamCatTools updated to version 0.8.0 with previous version 0.7.0 dated 2025-09-15

Title: 'StreamCatTools'
Description: Tools for using the 'StreamCat' and 'LakeCat' API and interacting with the 'StreamCat' and 'LakeCat' database. Convenience functions in the package wrap the API for 'StreamCat' on <https://api.epa.gov/StreamCat/streams/metrics>.
Author: Marc Weber [aut, cre], Ryan Hill [ctb], Travis Hudson [ctb], Allen Brookes [ctb], David Rebhuhn [ctb], Michael Dumelle [ctb], Zachary Smith [ctb]
Maintainer: Marc Weber <weber.marc@epa.gov>

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Package stats19 updated to version 3.4.0 with previous version 3.3.1 dated 2025-01-15

Title: Work with Open Road Traffic Casualty Data from Great Britain
Description: Work with and download road traffic casualty data from Great Britain. Enables access to the UK's official road safety statistics, 'STATS19'. Enables users to specify a download directory for the data, which can be set permanently by adding `STATS19_DOWNLOAD_DIRECTORY=/path/to/a/dir` to your `.Renviron` file, which can be opened with `usethis::edit_r_environ()`. The data is provided as a series of `.csv` files. This package downloads, reads-in and formats the data, making it suitable for analysis. See the stats19 vignette for details. Data available from 1979 to 2024. See the official data series at <https://www.data.gov.uk/dataset/cb7ae6f0-4be6-4935-9277-47e5ce24a11f/road-accidents-safety-data>. The package is described in a paper in the Journal of Open Source Software (Lovelace et al. 2019) <doi:10.21105/joss.01181>. See Gilardi et al. (2022) <doi:10.1111/rssa.12823>, Vidal-Tortosa et al. (2021) <doi:10.1016/j.jth.2021.101291>, Tait et al. (2023) <doi:10.101 [...truncated...]
Author: Robin Lovelace [aut, cre] , Malcolm Morgan [aut] , Layik Hama [aut] , Mark Padgham [aut] , David Ranzolin [rev], Adam Sparks [rev, ctb] , Ivo Wengraf [ctb], RAC Foundation [fnd], Blaise Kelly [aut]
Maintainer: Robin Lovelace <rob00x@gmail.com>

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Package statmod updated to version 1.5.1 with previous version 1.5.0 dated 2023-01-06

Title: Statistical Modeling
Description: A collection of algorithms and functions to aid statistical modeling. Includes limiting dilution analysis (aka ELDA), growth curve comparisons, mixed linear models, heteroscedastic regression, inverse-Gaussian probability calculations, Gauss quadrature and a secure convergence algorithm for nonlinear models. Also includes advanced generalized linear model functions including Tweedie and Digamma distributional families, secure convergence and exact distributional calculations for unit deviances.
Author: Gordon Smyth [cre, aut], Lizhong Chen [aut], Yifang Hu [ctb], Peter Dunn [ctb], Belinda Phipson [ctb], Yunshun Chen [ctb]
Maintainer: Gordon Smyth <smyth@wehi.edu.au>

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Package quadrupen updated to version 0.2-13 with previous version 0.2-12 dated 2024-06-25

Title: Sparsity by Worst-Case Quadratic Penalties
Description: Fits classical sparse regression models with efficient active set algorithms by solving quadratic problems as described by Grandvalet, Chiquet and Ambroise (2017) <doi:10.48550/arXiv.1210.2077>. Also provides a few methods for model selection purpose (cross-validation, stability selection).
Author: Julien Chiquet [aut, cre]
Maintainer: Julien Chiquet <julien.chiquet@inrae.fr>

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New package PERSUADE with initial version 0.1.2
Package: PERSUADE
Title: Parametric Survival Model Selection for Decision-Analytic Models
Version: 0.1.2
Description: Provides a standardized framework to support the selection and evaluation of parametric survival models for time-to-event data. Includes tools for visualizing survival data, checking proportional hazards assumptions (Grambsch and Therneau, 1994, <doi:10.1093/biomet/81.3.515>), comparing parametric (Ishak and colleagues, 2013, <doi:10.1007/s40273-013-0064-3>), spline (Royston and Parmar, 2002, <doi:10.1002/sim.1203>) and cure models, examining hazard functions, and evaluating model extrapolation. Methods are consistent with recommendations in the NICE Decision Support Unit Technical Support Documents (14 and 21 <https://sheffield.ac.uk/nice-dsu/tsds/survival-analysis>). Results are structured to facilitate integration into decision-analytic models, and reports can be generated with 'rmarkdown'. The package builds on existing tools including 'flexsurv' (Jackson, 2016, <doi:10.18637/jss.v070.i08>)) and 'flexsurvcure' for estimating cure models.
License: GPL (>= 3)
URL: https://github.com/Bram-R/PERSUADE
BugReports: https://github.com/Bram-R/PERSUADE/issues
Depends: R (>= 4.1.0)
Imports: data.table, flexsurv, flexsurvcure, ggplot2, muhaz, rmarkdown, rms, sft, stats, survival, survminer
Suggests: kableExtra, knitr, testthat (>= 3.1.2), utils
VignetteBuilder: knitr
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2025-10-06 09:47:00 UTC; G10028783
Author: Bram Ramaekers [aut, cre, ths] , Xavier Pouwels [ctb] , Sabine Grimm [ths] , Manuela Joore [ths]
Maintainer: Bram Ramaekers <bram.ramaekers@mumc.nl>
Repository: CRAN
Date/Publication: 2025-10-09 08:10:03 UTC

More information about PERSUADE at CRAN
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Package orderly updated to version 2.0.0 with previous version 1.4.3 dated 2021-09-22

Title: Lightweight Reproducible Reporting
Description: Distributed reproducible computing framework, adopting ideas from git, docker and other software. By defining a lightweight interface around the inputs and outputs of an analysis, a lot of the repetitive work for reproducible research can be automated. We define a simple format for organising and describing work that facilitates collaborative reproducible research and acknowledges that all analyses are run multiple times over their lifespans.
Author: Rich FitzJohn [aut, cre], Robert Ashton [aut], Martin Eden [aut], Alex Hill [aut], Wes Hinsley [aut], Mantra Kusumgar [aut], Paul Lietar [aut], James Thompson [aut], Katy Gaythorpe [aut], Imperial College of Science, Technology and Medicine [cph]
Maintainer: Rich FitzJohn <rich.fitzjohn@gmail.com>

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New package geoflow with initial version 1.0.0
Package: geoflow
Version: 1.0.0
Date: 2025-10-08
Title: Orchestrate Geospatial (Meta)Data Management Workflows and Manage FAIR Services
Description: An engine to facilitate the orchestration and execution of metadata-driven data management workflows, in compliance with 'FAIR' (Findable, Accessible, Interoperable and Reusable) data management principles. By means of a pivot metadata model, relying on the 'DublinCore' standard (<https://dublincore.org/>), a unique source of metadata can be used to operate multiple and inter-connected data management actions. Users can also customise their own workflows by creating specific actions but the library comes with a set of native actions targeting common geographic information and data management, in particular actions oriented to the publication on the web of metadata and data resources to provide standard discovery and access services. At first, default actions of the library were meant to focus on providing turn-key actions for geospatial (meta)data: 1) by creating manage geospatial (meta)data complying with 'ISO/TC211' (<https://committee.iso.org/home/tc211>) and 'OGC' (< [...truncated...]
Maintainer: Emmanuel Blondel <emmanuel.blondel1@gmail.com>
Depends: R (>= 3.3)
Imports: R6, methods, dotenv, benchmarkme, httr, mime, jsonlite, yaml, XML, xml2, rdflib, curl, whisker, mime, digest, dplyr, readr, arrow, zip, png, uuid, sf, sfarrow, terra, geometa (>= 0.9), geosapi, geonapi, geonode4R, ows4R
Suggests: testthat, readxl, gsheet, googledrive, DBI, rapiclient, RMariaDB, RPostgres, RPostgreSQL, RSQLite, ncdf4, thredds, EML, emld, datapack, dataone, rgbif, ocs4R, zen4R, atom4R, d4storagehub4R, rmarkdown, dataverse, blastula, waldo
License: MIT + file LICENSE
URL: https://github.com/r-geoflow/geoflow
BugReports: https://github.com/r-geoflow/geoflow/issues
LazyLoad: yes
NeedsCompilation: no
Packaged: 2025-10-08 20:09:51 UTC; emman
Author: Emmanuel Blondel [aut, cre, cph] , Julien, Barde [aut] , Wilfried Heintz [aut] , Alexandre Bennici [ctb], Sylvain Poulain [ctb], Bastien Grasset [ctb], Mathias Rouan [ctb], Emilie Lerigoleur [ctb], Yvan Le Bras [ctb], Jeroen Ooms [ctb]
Repository: CRAN
Date/Publication: 2025-10-09 08:50:09 UTC

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Package diemr updated to version 1.5.1 with previous version 1.5 dated 2025-09-11

Title: Genome Polarization via Diagnostic Index Expectation Maximization
Description: Implements a likelihood-based method for genome polarization, identifying which alleles of SNV markers belong to either side of a barrier to gene flow. The approach co-estimates individual assignment, barrier strength, and divergence between sides, with direct application to studies of hybridization. Includes VCF-to-diem conversion and input checks, support for mixed ploidy and parallelization, and tools for visualization and diagnostic outputs. Based on diagnostic index expectation maximization as described in Baird et al. (2023) <doi:10.1111/2041-210X.14010>.
Author: Natalia Martinkova [aut, cre] , Stuart Baird [aut]
Maintainer: Natalia Martinkova <martinkova@ivb.cz>

Diff between diemr versions 1.5 dated 2025-09-11 and 1.5.1 dated 2025-10-09

 DESCRIPTION                                                       |   24 +-
 MD5                                                               |   50 +++--
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 NEWS.md                                                           |   10 +
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Package bootStateSpace updated to version 1.0.3 with previous version 1.0.2 dated 2025-02-14

Title: Bootstrap for State Space Models
Description: Provides a streamlined and user-friendly framework for bootstrapping in state space models, particularly when the number of subjects/units (n) exceeds one, a scenario commonly encountered in social and behavioral sciences. The parametric bootstrap implemented here was developed and applied in Pesigan, Russell, and Chow (2025) <doi:10.1037/met0000779>.
Author: Ivan Jacob Agaloos Pesigan [aut, cre, cph] , Michael A. Russell [ctb] , Sy-Miin Chow [ctb]
Maintainer: Ivan Jacob Agaloos Pesigan <r.jeksterslab@gmail.com>

Diff between bootStateSpace versions 1.0.2 dated 2025-02-14 and 1.0.3 dated 2025-10-09

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More information about bootStateSpace at CRAN
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New package PKPDindex with initial version 0.2.0
Package: PKPDindex
Title: Optimal PK/PD Index Finder
Version: 0.2.0
Description: Fits Emax models to pharmacokinetic/pharmacodynamic (PK/PD) data, estimate key parameters, and visualise model fits for multiple PK/PD indices. Methods are described in Macdougall J (2006) <doi:10.1007/0-387-33706-7_9>, Spiess AN, Neumeyer N (2010) <doi:10.1186/1471-2210-10-6>, and Burnham KP, Anderson DR (2004) <doi:10.1177/0049124104268644>.
License: GPL (>= 3)
Encoding: UTF-8
Depends: R (>= 3.5)
LazyData: true
NeedsCompilation: no
Packaged: 2025-10-06 00:31:58 UTC; najla
Author: Najla Alabdulkarim [aut, cre], Joseph F Standing [aut]
Maintainer: Najla Alabdulkarim <naaalabdulkarim@hotmail.com>
Repository: CRAN
Date/Publication: 2025-10-09 07:40:07 UTC

More information about PKPDindex at CRAN
Permanent link

New package logolink with initial version 0.1.0
Package: logolink
Title: An Interface for Running 'NetLogo' Simulations
Version: 0.1.0
Description: An interface for 'NetLogo' <https://www.netlogo.org> that enables programmatic setup and execution of simulations. Designed to facilitate integrating 'NetLogo' models into reproducible workflows by creating and running 'BehaviorSpace' experiments and retrieving their results.
License: GPL (>= 3)
URL: https://danielvartan.github.io/logolink/, https://github.com/danielvartan/logolink/
BugReports: https://github.com/danielvartan/logolink/issues/
Depends: R (>= 4.4)
Imports: checkmate (>= 2.3.3), cli (>= 3.6.5), dplyr (>= 1.1.4), fs (>= 1.6.6), glue (>= 1.8.0), janitor (>= 2.2.1), magrittr (>= 2.0.4), purrr (>= 1.1.0), readr (>= 2.1.5), stringr (>= 1.5.2), xml2 (>= 1.4.0)
Suggests: bslib (>= 0.9.0), covr (>= 3.6.4), knitr (>= 1.50), spelling (>= 2.3.2), testthat (>= 3.2.3), tibble (>= 3.3.0),
Encoding: UTF-8
Language: en-US
NeedsCompilation: no
Packaged: 2025-10-06 07:35:27 UTC; danielvartan
Author: Daniel Vartanian [aut, cre, ccp, cph]
Maintainer: Daniel Vartanian <danielvartan@proton.me>
Repository: CRAN
Date/Publication: 2025-10-09 08:00:02 UTC

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New package graphonmix with initial version 0.0.1.0
Package: graphonmix
Title: Generates Mixture Graphs from Dense and Sparse Graphons
Version: 0.0.1.0
Maintainer: Sevvandi Kandanaarachchi <sevvandik@gmail.com>
Description: Generates (U,W) mixture graphs where U is a line graph graphon and W is a dense graphon. Graphons are graph limits and graphon U can be written as sequence of positive numbers adding to 1. Graphs are sampled from U and W and joined randomly to obtain the mixture graph. Given a mixture graph, U can be inferred. Kandanaarachchi and Ong (2025) <doi:10.48550/arXiv.2505.13864>.
License: GPL (>= 3)
Encoding: UTF-8
Imports: ggplot2, igraph, imager, stats
Suggests: gridExtra, knitr, rmarkdown
VignetteBuilder: knitr
URL: https://sevvandi.github.io/graphonmix/
NeedsCompilation: no
Packaged: 2025-10-05 22:38:34 UTC; kan092
Author: Sevvandi Kandanaarachchi [aut, cre]
Repository: CRAN
Date/Publication: 2025-10-09 07:40:02 UTC

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New package CopernicusClimate with initial version 0.0.2
Package: CopernicusClimate
Title: Search Download and Handle Data from Copernicus Climate Data Service
Version: 0.0.2
Description: Subset and download data from EU Copernicus Climate Data Service: <https://cds.climate.copernicus.eu/>. Import information about the Earth's past, present and future climate from Copernicus into R without the need of external software.
Depends: R (>= 4.1.0)
Imports: dplyr, httr2, jsonlite, methods, purrr, rlang, stringr, tibble, tidyr
Suggests: ggplot2, knitr, RefManageR, rmarkdown, stars, testthat (>= 3.0.0)
License: GPL (>= 3)
Encoding: UTF-8
URL: https://pepijn-devries.github.io/CopernicusClimate/, https://github.com/pepijn-devries/CopernicusClimate/
BugReports: https://github.com/pepijn-devries/CopernicusMarine/issues
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2025-10-05 15:45:23 UTC; vries171
Author: Pepijn de Vries [aut, cre]
Maintainer: Pepijn de Vries <pepijn.devries@outlook.com>
Repository: CRAN
Date/Publication: 2025-10-09 07:40:12 UTC

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New package choicedata with initial version 0.1.0
Package: choicedata
Title: Working with Choice Data
Version: 0.1.0
Description: Offers a set of objects tailored to simplify working with choice data. It enables the computation of choice probabilities and the likelihood of various types of choice models based on given data.
License: GPL (>= 3)
Encoding: UTF-8
URL: https://github.com/loelschlaeger/choicedata, http://loelschlaeger.de/choicedata/
BugReports: https://github.com/loelschlaeger/choicedata/issues
Suggests: mlogit, rmarkdown, testthat (>= 3.0.0)
Imports: checkmate, cli, dplyr, Formula, ggplot2, Matrix, mvtnorm, optimizeR, oeli (>= 0.7.5), patchwork, Rdpack, rlang, tibble, tidyr, utils
LazyData: true
LazyDataCompression: xz
Depends: R (>= 4.1.0)
NeedsCompilation: no
Packaged: 2025-10-06 08:08:22 UTC; Lennart Oelschläger
Author: Lennart Oelschlaeger [aut, cre]
Maintainer: Lennart Oelschlaeger <oelschlaeger.lennart@gmail.com>
Repository: CRAN
Date/Publication: 2025-10-09 08:00:08 UTC

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Package WeibullR updated to version 1.2.4 with previous version 1.2.1 dated 2022-06-25

Title: Weibull Analysis for Reliability Engineering
Description: Life data analysis in the graphical tradition of Waloddi Weibull. Methods derived from Robert B. Abernethy (2008, ISBN 0-965306-3-2), Wayne Nelson (1982, ISBN: 9780471094586), William Q. Meeker and Lois A. Escobar (1998, ISBN: 1-471-14328-6), John I. McCool, (2012, ISBN: 9781118217986).
Author: David Silkworth [aut], Jurgen Symynck [aut], Jacob Ormerod [cre], OpenReliability.org [cph]
Maintainer: Jacob Ormerod <jake@openreliability.org>

Diff between WeibullR versions 1.2.1 dated 2022-06-25 and 1.2.4 dated 2025-10-09

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Package RcppCGAL updated to version 6.1 with previous version 6.0.1 dated 2025-01-08

Title: 'Rcpp' Integration for 'CGAL'
Description: Creates a header only package to link to the 'CGAL' (Computational Geometry Algorithms Library) header files in 'Rcpp'. There are a variety of potential uses for the software such as Hilbert sorting, K-D Tree nearest neighbors, and convex hull algorithms. For more information about how to use the header files, see the 'CGAL' documentation at <https://www.cgal.org>. Currently downloads version 6.1 of the 'CGAL' header files.
Author: Eric Dunipace [aut, cre] , Tyler Morgan-Wall [ctb], The CGAL Project [cph]
Maintainer: Eric Dunipace <edunipace@mail.harvard.edu>

Diff between RcppCGAL versions 6.0.1 dated 2025-01-08 and 6.1 dated 2025-10-09

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Package nlmixr2est updated to version 4.1.1 with previous version 4.1.0 dated 2025-08-29

Title: Nonlinear Mixed Effects Models in Population PK/PD, Estimation Routines
Description: Fit and compare nonlinear mixed-effects models in differential equations with flexible dosing information commonly seen in pharmacokinetics and pharmacodynamics (Almquist, Leander, and Jirstrand 2015 <doi:10.1007/s10928-015-9409-1>). Differential equation solving is by compiled C code provided in the 'rxode2' package (Wang, Hallow, and James 2015 <doi:10.1002/psp4.12052>).
Author: Matthew Fidler [aut, cre] , Yuan Xiong [aut], Rik Schoemaker [aut] , Justin Wilkins [aut] , Wenping Wang [aut], Robert Leary [ctb], Mason McComb [ctb] , Vipul Mann [aut], Mirjam Trame [ctb], Mahmoud Abdelwahab [ctb], Teun Post [ctb], Richard Hooijmai [...truncated...]
Maintainer: Matthew Fidler <matthew.fidler@gmail.com>

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Package midasml updated to version 0.1.11 with previous version 0.1.10 dated 2022-04-29

Title: Estimation and Prediction Methods for High-Dimensional Mixed Frequency Time Series Data
Description: The 'midasml' package implements estimation and prediction methods for high-dimensional mixed-frequency (MIDAS) time-series and panel data regression models. The regularized MIDAS models are estimated using orthogonal (e.g. Legendre) polynomials and sparse-group LASSO (sg-LASSO) estimator. For more information on the 'midasml' approach see Babii, Ghysels, and Striaukas (2021, JBES forthcoming) <doi:10.1080/07350015.2021.1899933>. The package is equipped with the fast implementation of the sg-LASSO estimator by means of proximal block coordinate descent. High-dimensional mixed frequency time-series data can also be easily manipulated with functions provided in the package.
Author: Jonas Striaukas [cre, aut], Andrii Babii [aut], Jad Beyhum [aut], Eric Ghysels [aut], Alex Kostrov [ctb]
Maintainer: Jonas Striaukas <jonas.striaukas@gmail.com>

Diff between midasml versions 0.1.10 dated 2022-04-29 and 0.1.11 dated 2025-10-09

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Package grf updated to version 2.5.0 with previous version 2.4.0 dated 2024-11-15

Title: Generalized Random Forests
Description: Forest-based statistical estimation and inference. GRF provides non-parametric methods for heterogeneous treatment effects estimation (optionally using right-censored outcomes, multiple treatment arms or outcomes, or instrumental variables), as well as least-squares regression, quantile regression, and survival regression, all with support for missing covariates.
Author: Julie Tibshirani [aut], Susan Athey [aut], Rina Friedberg [ctb], Vitor Hadad [ctb], David Hirshberg [ctb], Luke Miner [ctb], Erik Sverdrup [aut, cre], Stefan Wager [aut], Marvin Wright [ctb]
Maintainer: Erik Sverdrup <erik.sverdrup@monash.edu>

Diff between grf versions 2.4.0 dated 2024-11-15 and 2.5.0 dated 2025-10-09

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Package FSSF updated to version 0.1.2 with previous version 0.1.1 dated 2020-02-05

Title: Generate Fully-Sequential Space-Filling Designs Inside a Unit Hypercube
Description: Provides three methods to generate fully-sequential space-filling designs inside a unit hypercube. A 'fully-sequential space-filling design' means a sequence of nested designs (as the design size varies from one point up to some maximum number of points) with the design points added one at a time and such that the design at each size has good space-filling properties. Two methods target the minimum pairwise distance criterion and generate maximin designs, among which one method is more efficient when design size is large. One method targets the maximum hole size criterion and uses a heuristic to generate what is closer to a minimax design.
Author: Boyang Shang [aut, cre], Daniel W. Apley [aut]
Maintainer: Boyang Shang <boyangshang2015@u.northwestern.edu>

Diff between FSSF versions 0.1.1 dated 2020-02-05 and 0.1.2 dated 2025-10-09

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Package DAAG updated to version 1.25.7 with previous version 1.25.6 dated 2024-05-26

Title: Data Analysis and Graphics Data and Functions
Description: Functions and data sets used in examples and exercises in the text Maindonald, J.H. and Braun, W.J. (2003, 2007, 2010) "Data Analysis and Graphics Using R", and in an upcoming Maindonald, Braun, and Andrews text that builds on this earlier text.
Author: John H Maindonald [aut], W. John Braun [aut, cre]
Maintainer: W. John Braun <john.braun@ubc.ca>

Diff between DAAG versions 1.25.6 dated 2024-05-26 and 1.25.7 dated 2025-10-09

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Package caviarpd updated to version 0.3.21 with previous version 0.3.20 dated 2025-06-02

Title: Cluster Analysis via Random Partition Distributions
Description: Cluster analysis is performed using pairwise distance information and a random partition distribution. The method is implemented for two random partition distributions. It draws samples and then obtains and plots clustering estimates. An implementation of a selection algorithm is provided for the mass parameter of the partition distribution. Since pairwise distances are the principal input to this procedure, it is most comparable to the hierarchical and k-medoids clustering methods. The method is Dahl, Andros, Carter (2022+) <doi:10.1002/sam.11602>.
Author: David B. Dahl [aut, cre] , R. Jacob Andros [aut] , J. Brandon Carter [aut] , Alex Crichton [ctb] , Brendan Zabarauskas [ctb] , David B. Dahl [ctb] , David Tolnay [ctb] , Jim Turner [ctb] , Jorge Aparicio [ctb] , Josh Stone [ctb] , Mikhail Vorotilov [ [...truncated...]
Maintainer: David B. Dahl <dahl@stat.byu.edu>

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