Tue, 09 Sep 2025

Package colocboost updated to version 1.0.6 with previous version 1.0.5 dated 2025-09-08

Title: Multi-Context Colocalization Analysis for QTL and GWAS Studies
Description: A multi-task learning approach to variable selection regression with highly correlated predictors and sparse effects, based on frequentist statistical inference. It provides statistical evidence to identify which subsets of predictors have non-zero effects on which subsets of response variables, motivated and designed for colocalization analysis across genome-wide association studies (GWAS) and quantitative trait loci (QTL) studies. The ColocBoost model is described in Cao et. al. (2025) <doi:10.1101/2025.04.17.25326042>.
Author: Xuewei Cao [cre, aut, cph], Haochen Sun [aut, cph], Ru Feng [aut, cph], Daniel Nachun [aut, cph], Kushal Dey [aut, cph], Gao Wang [aut, cph]
Maintainer: Xuewei Cao <xc2270@cumc.columbia.edu>

Diff between colocboost versions 1.0.5 dated 2025-09-08 and 1.0.6 dated 2025-09-09

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Package czso readmission to version 0.4.3 with previous version 0.4.2 dated 2025-06-21

Title: Use Open Data from the Czech Statistical Office in R
Description: Get programmatic access to the open data provided by the Czech Statistical Office (CZSO, <https://csu.gov.cz>).
Author: Petr Bouchal [aut, cre] , Jindra Lacko [ctb]
Maintainer: Petr Bouchal <pbouchal@gmail.com>

This is a re-admission after prior archival of version 0.4.2 dated 2025-06-21

Diff between czso versions 0.4.2 dated 2025-06-21 and 0.4.3 dated 2025-09-09

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Package IPEDSuploadables updated to version 2.11.0 with previous version 2.10.0 dated 2024-12-08

Title: Transforms Institutional Data into Text Files for IPEDS Automated Import/Upload
Description: Starting from user-supplied institutional data, these scripts transform, aggregate, and reshape the information to produce key-value pair data files that are able to be uploaded to IPEDS (Integrated Postsecondary Education Data System) through their submission portal <https://surveys.nces.ed.gov/ipeds/>. Starting data specifications can be found in the vignettes. Final files are saved locally to a location of the user's choice. User-friendly readable files can also be produced for purposes of data review and validation.
Author: Alison Lanski [aut, cre], Shiloh Fling [aut]
Maintainer: Alison Lanski <alanski@nd.edu>

Diff between IPEDSuploadables versions 2.10.0 dated 2024-12-08 and 2.11.0 dated 2025-09-09

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Package fslr updated to version 2.27.0 with previous version 2.25.3 dated 2024-05-10

Title: Wrapper Functions for 'FSL' ('FMRIB' Software Library) from Functional MRI of the Brain ('FMRIB')
Description: Wrapper functions that interface with 'FSL' <http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/>, a powerful and commonly-used 'neuroimaging' software, using system commands. The goal is to be able to interface with 'FSL' completely in R, where you pass R objects of class 'nifti', implemented by package 'oro.nifti', and the function executes an 'FSL' command and returns an R object of class 'nifti' if desired.
Author: John Muschelli [aut, cre]
Maintainer: John Muschelli <muschellij2@gmail.com>

Diff between fslr versions 2.25.3 dated 2024-05-10 and 2.27.0 dated 2025-09-09

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Package flippant updated to version 1.5.7 with previous version 1.5.5 dated 2024-04-09

Title: Dithionite Scramblase Assay Analysis
Description: The lipid scrambling activity of protein extracts and purified scramblases is often determined using a fluorescence-based assay involving many manual steps. flippant offers an integrated solution for the analysis and publication-grade graphical presentation of dithionite scramblase assays, as well as a platform for review, dissemination and extension of the strategies it employs. The package's name derives from a play on the fact that lipid scrambling is also sometimes referred to as 'flipping'. The package is originally published as Cotton, R.J., Ploier, B., Goren, M.A., Menon, A.K., and Graumann, J. (2017). "flippant–An R package for the automated analysis of fluorescence-based scramblase assays." BMC Bioinformatics 18, 146. <DOI:10.1186/s12859-017-1542-y>.
Author: Johannes Graumann [cre, aut], Richard Cotton [aut]
Maintainer: Johannes Graumann <johannes.graumann@uni-marburg.de>

Diff between flippant versions 1.5.5 dated 2024-04-09 and 1.5.7 dated 2025-09-09

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Package bbknnR updated to version 2.0.2 with previous version 2.0.1 dated 2025-06-05

Title: Perform Batch Balanced KNN in R
Description: A fast and intuitive batch effect removal tool for single-cell data. BBKNN is originally used in the 'scanpy' python package, and now can be used with 'Seurat' seamlessly.
Author: Yuchen Li [aut, cre]
Maintainer: Yuchen Li <ycli1995@outlook.com>

Diff between bbknnR versions 2.0.1 dated 2025-06-05 and 2.0.2 dated 2025-09-09

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New package STCYP with initial version 1.0.0
Package: STCYP
Title: Spatio-Temporal Crop Yield Prediction
Version: 1.0.0
Description: Provides crop yield and meteorological data for Ontario, Canada. Includes functions for fitting and predicting data using spatio-temporal models, as well as tools for visualizing the results. The package builds upon existing R packages, including 'copula' (Hofert et al., 2025) <doi:10.32614/CRAN.package.copula>, and 'bsts' (Scott, 2024) <doi:10.32614/CRAN.package.bsts>.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: bsts, copula, ggplot2, grDevices, rootSolve, stats
Depends: R (>= 4.0.0)
LazyData: true
LazyDataCompression: xz
Suggests: knitr, rmarkdown, testthat (>= 3.0.0),
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2025-09-04 20:18:48 UTC; liyongkun
Author: Marie Michaelides [aut], Melina Mailhot [aut], Yongkun Li [aut, cre]
Maintainer: Yongkun Li <yongkun.li@concordia.ca>
Repository: CRAN
Date/Publication: 2025-09-09 14:40:23 UTC

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New package sparsesurv with initial version 0.1.1
Package: sparsesurv
Title: Forecasting and Early Outbreak Detection for Sparse Count Data
Version: 0.1.1
Description: Functions for fitting, forecasting, and early detection of outbreaks in sparse surveillance count time series. Supports negative binomial (NB), self-exciting NB, generalise autoregressive moving average (GARMA) NB , zero-inflated NB (ZINB), self-exciting ZINB, generalise autoregressive moving average ZINB, and hurdle formulations. Climatic and environmental covariates can be included in the regression component and/or the zero-modified components. Includes outbreak-detection algorithms for NB, ZINB, and hurdle models, with utilities for prediction and diagnostics.
License: GPL (>= 3)
Encoding: UTF-8
Depends: R (>= 4.1)
Imports: R2jags, coda, stats
Suggests: testthat (>= 3.0.0), knitr, rjags, rmarkdown, ggplot2, reshape2
SystemRequirements: JAGS (>= 4.x)
URL: https://github.com/alexangelakis-ang/sparsesurv
BugReports: https://github.com/alexangelakis-ang/sparsesurv/issues
NeedsCompilation: no
Packaged: 2025-09-04 08:36:20 UTC; angeal
Author: Alexandros Angelakis [aut, cre], Bryan Nyawanda [aut], Penelope Vounatsou [aut]
Maintainer: Alexandros Angelakis <alexandros.angelakis@swisstph.ch>
Repository: CRAN
Date/Publication: 2025-09-09 14:10:02 UTC

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New package RobustAdaptiveDecomposition with initial version 0.1.0
Package: RobustAdaptiveDecomposition
Title: Decomposes a Univariate Time Series into Subcomponents
Version: 0.1.0
Description: Provides a method to decompose a univariate time series into meaningful subcomponents for analysis and denoising.
License: GPL-3
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2025-09-04 08:58:38 UTC; Dubai Computers
Author: Laiba Sultan Dar [aut, cre], Muhammad Aamir [aut], Muhammad Hamraz [aut]
Maintainer: Laiba Sultan Dar <laibasultan@awkum.edu.pk>
Repository: CRAN
Date/Publication: 2025-09-09 14:10:12 UTC

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New package rjuliabugs with initial version 0.1.0
Package: rjuliabugs
Title: Interface to 'JuliaBUGS.jl' from R
Version: 0.1.0
Description: Provides an R interface to the 'JuliaBUGS.jl' package (<https://github.com/TuringLang/JuliaBUGS.jl>) for Bayesian inference using the BUGS modeling language. Allows R users to run models in Julia and return results as familiar R objects. Visualization and posterior analysis are supported via the 'bayesplot' and 'posterior' packages.
License: MIT + file LICENSE
Encoding: UTF-8
SystemRequirements: Julia (>= 1.10.8) with the following packages installed: 'JuliaBUGS.jl', 'LogDensityProblemsAD.jl', 'ReverseDiff.jl', 'AdvancedHMC.jl', 'AbstractMCMC.jl', 'LogDensityProblems.jl', 'MCMCChains.jl', 'RCall.jl', 'Suppressor.jl'.
Imports: coda, JuliaCall, posterior
Suggests: bayesplot, knitr, rmarkdown, gridExtra, rstan, nimble
URL: https://mateusmaiads.github.io/rjuliabugs/
BugReports: https://github.com/MateusMaiaDS/rjuliabugs/issues
NeedsCompilation: no
Packaged: 2025-09-04 17:17:07 UTC; mateusmaia
Author: Mateus Maia [aut, cre], Xianda Sun [aut], Robert Goudie [aut]
Maintainer: Mateus Maia <mateus.maiamarques@glasgow.ac.uk>
Repository: CRAN
Date/Publication: 2025-09-09 14:40:02 UTC

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New package ppwdeming with initial version 1.0.6
Package: ppwdeming
Version: 1.0.6
Date: 2025-09-03
Title: Precision Profile Weighted Deming Regression
Author: Douglas M. Hawkins [aut], Jessica J. Kraker [aut, cre]
Maintainer: Jessica J. Kraker <krakerjj@uwec.edu>
Depends: R (>= 3.6.0)
Suggests: testthat (>= 3.0.0)
Imports: stats
Description: Weighted Deming regression, also known as "errors-in-variable" regression, is applied with suitable weights. Weights are modeled via a precision profile; functions are provided for implementing it in both known and unknown precision profile situations. The package provides tools for precision profile weighted Deming (PWD) regression. It covers two settings – one where the precision profiles are known either from external studies or from adequate replication of the X and Y readings, and one in which there is a plausible functional form for the precision profiles but the exact function must be estimated from the (generally singlicate) readings. The function set includes tools for: estimated standard errors (via jackknifing); standardized-residual analysis function with regression diagnostic tools for normality, linearity and constant variance; and an outlier analysis identifying significant outliers for closer investigation. Further information on mathematical derivations and application [...truncated...]
License: GPL (>= 3)
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2025-09-04 11:36:08 UTC; jjkra
Repository: CRAN
Date/Publication: 2025-09-09 14:20:02 UTC

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New package mogiw with initial version 0.1.0
Package: mogiw
Title: The Marshal–Olkin Generalized Inverse Weibull Distribution
Version: 0.1.0
Maintainer: Atchanut Rattanalertnusorn <atchanut_r@rmutt.ac.th>
Description: Density, distribution function, quantile function, and random generation function based on Salem, H. M. (2019)<doi:10.5539/mas.v13n2p54>. In addition, a numerical method for maximum likelihood estimation is provided.
License: GPL-3
Language: en-US
Encoding: UTF-8
Imports: stats
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2025-09-04 08:02:00 UTC; User
Author: Atchanut Rattanalertnusorn [aut, cre]
Repository: CRAN
Date/Publication: 2025-09-09 14:10:07 UTC

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New package memshare with initial version 1.0.1
Package: memshare
Title: Shared Memory Multithreading
Version: 1.0.1
Date: 2025-08-28
Description: This project extends 'R' with a mechanism for efficient parallel data access by utilizing 'C++' shared memory. Large data objects can be accessed and manipulated directly from 'R' without redundant copying, providing both speed and memory efficiency.
Maintainer: Michael Thrun <m.thrun@gmx.net>
LazyLoad: yes
LinkingTo: Rcpp
Imports: Rcpp (>= 1.0.14), parallel
Suggests: ScatterDensity (>= 0.1.1), DataVisualizations (>= 1.1.5), mpmi
SystemRequirements: C++17, GNU make
Depends: R (>= 4.3.0)
NeedsCompilation: yes
License: GPL-3
URL: https://www.iap-gmbh.de
Encoding: UTF-8
Packaged: 2025-09-04 17:12:44 UTC; MCT
Author: Julian Maerte [aut, ctr] , Romain Francois [ctb], Michael Thrun [aut, ths, rev, cph, cre]
Repository: CRAN
Date/Publication: 2025-09-09 14:30:02 UTC

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New package IndonesiAPIs with initial version 0.1.0
Package: IndonesiAPIs
Title: Access Indonesian Data via Public APIs and Curated Datasets
Version: 0.1.0
Maintainer: Renzo Caceres Rossi <arenzocaceresrossi@gmail.com>
Description: Provides functions to access data from public RESTful APIs including 'Nager.Date', 'World Bank API', and 'REST Countries API', retrieving real-time or historical data related to Indonesia, such as holidays, economic indicators, and international demographic and geopolitical indicators. The package also includes a curated collection of open datasets focused on Indonesia, covering topics such as consumer prices, poverty probability, food prices by region, tourism destinations, and minimum wage statistics. The package supports reproducible research and teaching by integrating reliable international APIs and structured datasets from public, academic, and government sources. For more information on the APIs, see: 'Nager.Date' <https://date.nager.at/Api>, 'World Bank API' <https://datahelpdesk.worldbank.org/knowledgebase/articles/889392>, and 'REST Countries API' <https://restcountries.com/>.
License: MIT + file LICENSE
Language: en
URL: https://github.com/lightbluetitan/indonesiapis, https://lightbluetitan.github.io/indonesiapis/
BugReports: https://github.com/lightbluetitan/indonesiapis/issues
Encoding: UTF-8
LazyData: true
Depends: R (>= 4.1.0)
Imports: utils, httr, jsonlite, dplyr, scales, tibble
Suggests: ggplot2, testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2025-09-04 14:25:27 UTC; Renzo
Author: Renzo Caceres Rossi [aut, cre]
Repository: CRAN
Date/Publication: 2025-09-09 14:20:07 UTC

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New package clockplot with initial version 0.7.2
Package: clockplot
Title: Plot Event Times on a 24-Hour Clock
Version: 0.7.2
Description: Provides a novel visualization technique for plotting timestamped events on a 24-hour circular clock face. This is particularly useful for analyzing daily patterns, event clustering, and gaps in temporal data. The package also generalizes this approach to create cyclic charts for other periods, including weekly and monthly cycles, enabling effective event planning and pattern analysis across multiple time frames.
License: MIT + file LICENSE
Imports: dplyr, tidyr, tibble, ggplot2, hms
Encoding: UTF-8
LazyData: true
Depends: R (>= 2.10)
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
URL: https://github.com/mahmudstat/clockplot/
BugReports: https://github.com/mahmudstat/clockplot/issues
Language: en-US
NeedsCompilation: no
Packaged: 2025-09-04 18:10:16 UTC; mahmud
Author: Abdullah Al Mahmud [aut, cre, cph]
Maintainer: Abdullah Al Mahmud <almahmud.sbi@gmail.com>
Repository: CRAN
Date/Publication: 2025-09-09 14:40:07 UTC

More information about clockplot at CRAN
Permanent link

Package cfbfastR readmission to version 2.0.0 with previous version 1.9.0 dated 2022-06-13

Title: Access College Football Play by Play Data
Description: A utility to quickly obtain clean and tidy college football data. Serves as a wrapper around the <https://collegefootballdata.com/> API and provides functions to access live play by play and box score data from ESPN <https://www.espn.com> when available. It provides users the capability to access a plethora of endpoints, and supplement that data with additional information (Expected Points Added/Win Probability added).
Author: Saiem Gilani [cre, aut], Akshay Easwaran [aut], Jared Lee [aut], Eric Hess [aut], Michael Egle [ctb], Nate Manzo [ctb], Jason DeLoach [ctb], Tej Seth [ctb], Conor McQuiston [ctb], Tan Ho [ctb], Keegan Abdoo [ctb], Matt Spencer [ctb], Sebastian Carl [ [...truncated...]
Maintainer: Saiem Gilani <saiem.gilani@gmail.com>

This is a re-admission after prior archival of version 1.9.0 dated 2022-06-13

Diff between cfbfastR versions 1.9.0 dated 2022-06-13 and 2.0.0 dated 2025-09-09

 cfbfastR-1.9.0/cfbfastR/R/cfb_pbp.R                                             |only
 cfbfastR-1.9.0/cfbfastR/inst                                                    |only
 cfbfastR-2.0.0/cfbfastR/DESCRIPTION                                             |   26 
 cfbfastR-2.0.0/cfbfastR/MD5                                                     |  349 +--
 cfbfastR-2.0.0/cfbfastR/NAMESPACE                                               |   18 
 cfbfastR-2.0.0/cfbfastR/NEWS.md                                                 |  102 
 cfbfastR-2.0.0/cfbfastR/R/cfbd_api_key.R                                        |   79 
 cfbfastR-2.0.0/cfbfastR/R/cfbd_betting.R                                        |  123 -
 cfbfastR-2.0.0/cfbfastR/R/cfbd_coaches.R                                        |   77 
 cfbfastR-2.0.0/cfbfastR/R/cfbd_conferences.R                                    |   23 
 cfbfastR-2.0.0/cfbfastR/R/cfbd_draft.R                                          |  114 
 cfbfastR-2.0.0/cfbfastR/R/cfbd_drives.R                                         |  142 -
 cfbfastR-2.0.0/cfbfastR/R/cfbd_games.R                                          | 1095 +++++----
 cfbfastR-2.0.0/cfbfastR/R/cfbd_metrics.R                                        |  969 +++++---
 cfbfastR-2.0.0/cfbfastR/R/cfbd_pbp_data.R                                       | 1147 +++++-----
 cfbfastR-2.0.0/cfbfastR/R/cfbd_play.R                                           |  808 +++++--
 cfbfastR-2.0.0/cfbfastR/R/cfbd_players.R                                        |  264 --
 cfbfastR-2.0.0/cfbfastR/R/cfbd_ratings.R                                        |  608 ++---
 cfbfastR-2.0.0/cfbfastR/R/cfbd_recruiting.R                                     |  242 --
 cfbfastR-2.0.0/cfbfastR/R/cfbd_stats.R                                          |  517 +---
 cfbfastR-2.0.0/cfbfastR/R/cfbd_teams.R                                          |  351 +--
 cfbfastR-2.0.0/cfbfastR/R/cfbd_venues.R                                         |   25 
 cfbfastR-2.0.0/cfbfastR/R/cfbfastR-package.R                                    |   18 
 cfbfastR-2.0.0/cfbfastR/R/create_epa.R                                          |  219 +
 cfbfastR-2.0.0/cfbfastR/R/create_wpa_naive.R                                    |    2 
 cfbfastR-2.0.0/cfbfastR/R/espn_cfb_pbp.R                                        |   99 
 cfbfastR-2.0.0/cfbfastR/R/espn_cfb_player_stats.R                               |only
 cfbfastR-2.0.0/cfbfastR/R/espn_cfb_team_stats.R                                 |  665 +++--
 cfbfastR-2.0.0/cfbfastR/R/espn_metrics_wp.R                                     |   39 
 cfbfastR-2.0.0/cfbfastR/R/espn_ratings_fpi.R                                    |   78 
 cfbfastR-2.0.0/cfbfastR/R/espn_scoreboard.R                                     |  193 +
 cfbfastR-2.0.0/cfbfastR/R/helper_pbp_add_player_cols.R                          |   40 
 cfbfastR-2.0.0/cfbfastR/R/helper_pbp_add_yardage.R                              |   13 
 cfbfastR-2.0.0/cfbfastR/R/helper_pbp_penalty_detection.R                        |    2 
 cfbfastR-2.0.0/cfbfastR/R/load_cfb.R                                            |   54 
 cfbfastR-2.0.0/cfbfastR/R/load_cfb_pbp.R                                        |only
 cfbfastR-2.0.0/cfbfastR/R/utils.R                                               |  114 
 cfbfastR-2.0.0/cfbfastR/README.md                                               |  179 -
 cfbfastR-2.0.0/cfbfastR/man/cfbd_betting_lines.Rd                               |    9 
 cfbfastR-2.0.0/cfbfastR/man/cfbd_calendar.Rd                                    |   12 
 cfbfastR-2.0.0/cfbfastR/man/cfbd_coaches.Rd                                     |    1 
 cfbfastR-2.0.0/cfbfastR/man/cfbd_conferences.Rd                                 |    1 
 cfbfastR-2.0.0/cfbfastR/man/cfbd_draft.Rd                                       |   76 
 cfbfastR-2.0.0/cfbfastR/man/cfbd_draft_picks.Rd                                 |    7 
 cfbfastR-2.0.0/cfbfastR/man/cfbd_draft_positions.Rd                             |    6 
 cfbfastR-2.0.0/cfbfastR/man/cfbd_draft_teams.Rd                                 |    6 
 cfbfastR-2.0.0/cfbfastR/man/cfbd_drives.Rd                                      |   12 
 cfbfastR-2.0.0/cfbfastR/man/cfbd_game_box_advanced.Rd                           |   12 
 cfbfastR-2.0.0/cfbfastR/man/cfbd_game_info.Rd                                   |   19 
 cfbfastR-2.0.0/cfbfastR/man/cfbd_game_media.Rd                                  |   19 
 cfbfastR-2.0.0/cfbfastR/man/cfbd_game_player_stats.Rd                           |  110 
 cfbfastR-2.0.0/cfbfastR/man/cfbd_game_records.Rd                                |   28 
 cfbfastR-2.0.0/cfbfastR/man/cfbd_game_team_stats.Rd                             |   30 
 cfbfastR-2.0.0/cfbfastR/man/cfbd_game_weather.Rd                                |   14 
 cfbfastR-2.0.0/cfbfastR/man/cfbd_games.Rd                                       |    8 
 cfbfastR-2.0.0/cfbfastR/man/cfbd_live_plays.Rd                                  |only
 cfbfastR-2.0.0/cfbfastR/man/cfbd_live_scoreboard.Rd                             |only
 cfbfastR-2.0.0/cfbfastR/man/cfbd_metrics.Rd                                     |   35 
 cfbfastR-2.0.0/cfbfastR/man/cfbd_metrics_fg_ep.Rd                               |only
 cfbfastR-2.0.0/cfbfastR/man/cfbd_metrics_ppa_games.Rd                           |   19 
 cfbfastR-2.0.0/cfbfastR/man/cfbd_metrics_ppa_players_games.Rd                   |   25 
 cfbfastR-2.0.0/cfbfastR/man/cfbd_metrics_ppa_players_season.Rd                  |   23 
 cfbfastR-2.0.0/cfbfastR/man/cfbd_metrics_ppa_predicted.Rd                       |   15 
 cfbfastR-2.0.0/cfbfastR/man/cfbd_metrics_ppa_teams.Rd                           |   19 
 cfbfastR-2.0.0/cfbfastR/man/cfbd_metrics_wepa_players_kicking.Rd                |only
 cfbfastR-2.0.0/cfbfastR/man/cfbd_metrics_wepa_players_passing.Rd                |only
 cfbfastR-2.0.0/cfbfastR/man/cfbd_metrics_wepa_players_rushing.Rd                |only
 cfbfastR-2.0.0/cfbfastR/man/cfbd_metrics_wepa_team_season.Rd                    |only
 cfbfastR-2.0.0/cfbfastR/man/cfbd_metrics_wp.Rd                                  |   15 
 cfbfastR-2.0.0/cfbfastR/man/cfbd_metrics_wp_pregame.Rd                          |   19 
 cfbfastR-2.0.0/cfbfastR/man/cfbd_pbp_data.Rd                                    |  734 +++---
 cfbfastR-2.0.0/cfbfastR/man/cfbd_play.Rd                                        |  134 -
 cfbfastR-2.0.0/cfbfastR/man/cfbd_play_stats_player.Rd                           |   26 
 cfbfastR-2.0.0/cfbfastR/man/cfbd_play_stats_types.Rd                            |   11 
 cfbfastR-2.0.0/cfbfastR/man/cfbd_play_types.Rd                                  |    9 
 cfbfastR-2.0.0/cfbfastR/man/cfbd_player_info.Rd                                 |    6 
 cfbfastR-2.0.0/cfbfastR/man/cfbd_player_returning.Rd                            |   14 
 cfbfastR-2.0.0/cfbfastR/man/cfbd_player_usage.Rd                                |   10 
 cfbfastR-2.0.0/cfbfastR/man/cfbd_players.Rd                                     |   68 
 cfbfastR-2.0.0/cfbfastR/man/cfbd_plays.Rd                                       |   22 
 cfbfastR-2.0.0/cfbfastR/man/cfbd_rankings.Rd                                    |   35 
 cfbfastR-2.0.0/cfbfastR/man/cfbd_ratings.Rd                                     |   12 
 cfbfastR-2.0.0/cfbfastR/man/cfbd_ratings_elo.Rd                                 |   35 
 cfbfastR-2.0.0/cfbfastR/man/cfbd_ratings_fpi.Rd                                 |only
 cfbfastR-2.0.0/cfbfastR/man/cfbd_ratings_sp.Rd                                  |   75 
 cfbfastR-2.0.0/cfbfastR/man/cfbd_ratings_sp_conference.Rd                       |   10 
 cfbfastR-2.0.0/cfbfastR/man/cfbd_ratings_srs.Rd                                 |   13 
 cfbfastR-2.0.0/cfbfastR/man/cfbd_recruiting.Rd                                  |  128 -
 cfbfastR-2.0.0/cfbfastR/man/cfbd_recruiting_player.Rd                           |   11 
 cfbfastR-2.0.0/cfbfastR/man/cfbd_recruiting_position.Rd                         |    7 
 cfbfastR-2.0.0/cfbfastR/man/cfbd_recruiting_team.Rd                             |   11 
 cfbfastR-2.0.0/cfbfastR/man/cfbd_recruiting_transfer_portal.Rd                  |    7 
 cfbfastR-2.0.0/cfbfastR/man/cfbd_stats.Rd                                       |  118 -
 cfbfastR-2.0.0/cfbfastR/man/cfbd_stats_categories.Rd                            |    8 
 cfbfastR-2.0.0/cfbfastR/man/cfbd_stats_game_advanced.Rd                         |   11 
 cfbfastR-2.0.0/cfbfastR/man/cfbd_stats_season_advanced.Rd                       |   10 
 cfbfastR-2.0.0/cfbfastR/man/cfbd_stats_season_player.Rd                         |   16 
 cfbfastR-2.0.0/cfbfastR/man/cfbd_stats_season_team.Rd                           |   12 
 cfbfastR-2.0.0/cfbfastR/man/cfbd_team_info.Rd                                   |   20 
 cfbfastR-2.0.0/cfbfastR/man/cfbd_team_matchup.Rd                                |    8 
 cfbfastR-2.0.0/cfbfastR/man/cfbd_team_matchup_records.Rd                        |    8 
 cfbfastR-2.0.0/cfbfastR/man/cfbd_team_roster.Rd                                 |    8 
 cfbfastR-2.0.0/cfbfastR/man/cfbd_team_talent.Rd                                 |   10 
 cfbfastR-2.0.0/cfbfastR/man/cfbd_teams.Rd                                       |  140 -
 cfbfastR-2.0.0/cfbfastR/man/cfbd_venues.Rd                                      |    4 
 cfbfastR-2.0.0/cfbfastR/man/cfbfastR-package.Rd                                 |    2 
 cfbfastR-2.0.0/cfbfastR/man/create_epa.Rd                                       |   11 
 cfbfastR-2.0.0/cfbfastR/man/csv_from_url.Rd                                     |   30 
 cfbfastR-2.0.0/cfbfastR/man/data.Rd                                             |   74 
 cfbfastR-2.0.0/cfbfastR/man/espn_cfb_calendar.Rd                                |   72 
 cfbfastR-2.0.0/cfbfastR/man/espn_cfb_pbp.Rd                                     |   57 
 cfbfastR-2.0.0/cfbfastR/man/espn_cfb_player_stats.Rd                            |only
 cfbfastR-2.0.0/cfbfastR/man/espn_cfb_scoreboard.Rd                              |   40 
 cfbfastR-2.0.0/cfbfastR/man/espn_cfb_team_stats.Rd                              |  637 ++---
 cfbfastR-2.0.0/cfbfastR/man/espn_metrics.Rd                                     |    4 
 cfbfastR-2.0.0/cfbfastR/man/espn_ratings_fpi.Rd                                 |   96 
 cfbfastR-2.0.0/cfbfastR/man/helpers_pbp.Rd                                      |   10 
 cfbfastR-2.0.0/cfbfastR/man/load_cfb_pbp.Rd                                     |   20 
 cfbfastR-2.0.0/cfbfastR/man/load_cfb_rosters.Rd                                 |   12 
 cfbfastR-2.0.0/cfbfastR/man/load_cfb_schedules.Rd                               |   12 
 cfbfastR-2.0.0/cfbfastR/man/load_cfb_teams.Rd                                   |    8 
 cfbfastR-2.0.0/cfbfastR/man/rds_from_url.Rd                                     |    5 
 cfbfastR-2.0.0/cfbfastR/man/register_cfbd.Rd                                    |   18 
 cfbfastR-2.0.0/cfbfastR/man/update_cfb_db.Rd                                    |   15 
 cfbfastR-2.0.0/cfbfastR/tests/testthat/test-cfbd_betting_lines.R                |   13 
 cfbfastR-2.0.0/cfbfastR/tests/testthat/test-cfbd_calendar.R                     |    4 
 cfbfastR-2.0.0/cfbfastR/tests/testthat/test-cfbd_coaches.R                      |    2 
 cfbfastR-2.0.0/cfbfastR/tests/testthat/test-cfbd_conferences.R                  |    2 
 cfbfastR-2.0.0/cfbfastR/tests/testthat/test-cfbd_draft_picks.R                  |    6 
 cfbfastR-2.0.0/cfbfastR/tests/testthat/test-cfbd_draft_positions.R              |    2 
 cfbfastR-2.0.0/cfbfastR/tests/testthat/test-cfbd_draft_teams.R                  |    2 
 cfbfastR-2.0.0/cfbfastR/tests/testthat/test-cfbd_drives.R                       |    4 
 cfbfastR-2.0.0/cfbfastR/tests/testthat/test-cfbd_game_box_advanced.R            |    4 
 cfbfastR-2.0.0/cfbfastR/tests/testthat/test-cfbd_game_info.R                    |   41 
 cfbfastR-2.0.0/cfbfastR/tests/testthat/test-cfbd_game_media.R                   |    4 
 cfbfastR-2.0.0/cfbfastR/tests/testthat/test-cfbd_game_player_stats.R            |   70 
 cfbfastR-2.0.0/cfbfastR/tests/testthat/test-cfbd_game_records.R                 |   11 
 cfbfastR-2.0.0/cfbfastR/tests/testthat/test-cfbd_game_team_stats.R              |    6 
 cfbfastR-2.0.0/cfbfastR/tests/testthat/test-cfbd_game_weather.R                 |    4 
 cfbfastR-2.0.0/cfbfastR/tests/testthat/test-cfbd_live_plays.R                   |only
 cfbfastR-2.0.0/cfbfastR/tests/testthat/test-cfbd_live_scoreboard.R              |only
 cfbfastR-2.0.0/cfbfastR/tests/testthat/test-cfbd_metrics_fg_ep.R                |only
 cfbfastR-2.0.0/cfbfastR/tests/testthat/test-cfbd_metrics_ppa_games.R            |    6 
 cfbfastR-2.0.0/cfbfastR/tests/testthat/test-cfbd_metrics_ppa_players_games.R    |    6 
 cfbfastR-2.0.0/cfbfastR/tests/testthat/test-cfbd_metrics_ppa_players_season.R   |    4 
 cfbfastR-2.0.0/cfbfastR/tests/testthat/test-cfbd_metrics_ppa_predicted.R        |    4 
 cfbfastR-2.0.0/cfbfastR/tests/testthat/test-cfbd_metrics_wepa_players_kicking.R |only
 cfbfastR-2.0.0/cfbfastR/tests/testthat/test-cfbd_metrics_wepa_players_passing.R |only
 cfbfastR-2.0.0/cfbfastR/tests/testthat/test-cfbd_metrics_wepa_players_rushing.R |only
 cfbfastR-2.0.0/cfbfastR/tests/testthat/test-cfbd_metrics_wepa_team_season.R     |only
 cfbfastR-2.0.0/cfbfastR/tests/testthat/test-cfbd_metrics_wp.R                   |    4 
 cfbfastR-2.0.0/cfbfastR/tests/testthat/test-cfbd_metrics_wp_pregame.R           |    4 
 cfbfastR-2.0.0/cfbfastR/tests/testthat/test-cfbd_pbp_data.R                     |only
 cfbfastR-2.0.0/cfbfastR/tests/testthat/test-cfbd_play_stats_player.R            |   90 
 cfbfastR-2.0.0/cfbfastR/tests/testthat/test-cfbd_play_stats_types.R             |    4 
 cfbfastR-2.0.0/cfbfastR/tests/testthat/test-cfbd_play_types.R                   |    2 
 cfbfastR-2.0.0/cfbfastR/tests/testthat/test-cfbd_player_info.R                  |    6 
 cfbfastR-2.0.0/cfbfastR/tests/testthat/test-cfbd_player_returning.R             |    2 
 cfbfastR-2.0.0/cfbfastR/tests/testthat/test-cfbd_player_usage.R                 |    2 
 cfbfastR-2.0.0/cfbfastR/tests/testthat/test-cfbd_rankings.R                     |   14 
 cfbfastR-2.0.0/cfbfastR/tests/testthat/test-cfbd_ratings_elo.R                  |    6 
 cfbfastR-2.0.0/cfbfastR/tests/testthat/test-cfbd_ratings_fpi.R                  |only
 cfbfastR-2.0.0/cfbfastR/tests/testthat/test-cfbd_ratings_sp.R                   |    6 
 cfbfastR-2.0.0/cfbfastR/tests/testthat/test-cfbd_ratings_sp_conf.R              |    6 
 cfbfastR-2.0.0/cfbfastR/tests/testthat/test-cfbd_ratings_srs.R                  |    6 
 cfbfastR-2.0.0/cfbfastR/tests/testthat/test-cfbd_recruiting_player.R            |    6 
 cfbfastR-2.0.0/cfbfastR/tests/testthat/test-cfbd_recruiting_position.R          |    8 
 cfbfastR-2.0.0/cfbfastR/tests/testthat/test-cfbd_recruiting_team.R              |    6 
 cfbfastR-2.0.0/cfbfastR/tests/testthat/test-cfbd_recruiting_transfer_portal.R   |    2 
 cfbfastR-2.0.0/cfbfastR/tests/testthat/test-cfbd_stats_categories.R             |    2 
 cfbfastR-2.0.0/cfbfastR/tests/testthat/test-cfbd_stats_game_advanced.R          |    8 
 cfbfastR-2.0.0/cfbfastR/tests/testthat/test-cfbd_stats_season_advanced.R        |    7 
 cfbfastR-2.0.0/cfbfastR/tests/testthat/test-cfbd_stats_season_player.R          |   14 
 cfbfastR-2.0.0/cfbfastR/tests/testthat/test-cfbd_stats_season_team.R            |    6 
 cfbfastR-2.0.0/cfbfastR/tests/testthat/test-cfbd_team_info.R                    |    6 
 cfbfastR-2.0.0/cfbfastR/tests/testthat/test-cfbd_team_matchup.R                 |    4 
 cfbfastR-2.0.0/cfbfastR/tests/testthat/test-cfbd_team_matchup_records.R         |    4 
 cfbfastR-2.0.0/cfbfastR/tests/testthat/test-cfbd_team_roster.R                  |    6 
 cfbfastR-2.0.0/cfbfastR/tests/testthat/test-cfbd_team_talent.R                  |    2 
 cfbfastR-2.0.0/cfbfastR/tests/testthat/test-cfbd_venues.R                       |    7 
 cfbfastR-2.0.0/cfbfastR/tests/testthat/test-espn_cfb_calendar.R                 |    4 
 cfbfastR-2.0.0/cfbfastR/tests/testthat/test-espn_cfb_player_stats.R             |only
 cfbfastR-2.0.0/cfbfastR/tests/testthat/test-espn_cfb_schedule.R                 |   13 
 cfbfastR-2.0.0/cfbfastR/tests/testthat/test-espn_cfb_scoreboard.R               |   16 
 cfbfastR-2.0.0/cfbfastR/tests/testthat/test-espn_cfb_team_stats.R               |   72 
 cfbfastR-2.0.0/cfbfastR/tests/testthat/test-espn_metrics_wp.R                   |    2 
 cfbfastR-2.0.0/cfbfastR/tests/testthat/test-espn_ratings_fpi.R                  |   27 
 187 files changed, 7328 insertions(+), 5449 deletions(-)

More information about cfbfastR at CRAN
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New package spantest with initial version 1.1-3
Package: spantest
Title: Mean-Variance Spanning Tests
Version: 1.1-3
Description: Provides a comprehensive suite of portfolio spanning tests for asset pricing, such as Huberman and Kandel (1987) <doi:10.1111/j.1540-6261.1987.tb03917.x>, Gibbons et al. (1989) <doi:10.2307/1913625>, Kempf and Memmel (2006) <doi:10.1007/BF03396737>, Pesaran and Yamagata (2024) <doi:10.1093/jjfinec/nbad002>, and Gungor and Luger (2016) <doi:10.1080/07350015.2015.1019510>.
License: GPL-3
Encoding: UTF-8
Depends: R (>= 4.1.0)
URL: https://github.com/ArdiaD/spantest
BugReports: https://github.com/ArdiaD/spantest/issues
Suggests: rmarkdown, testthat (>= 3.0.0)
Imports: Rdpack, stats, utils
NeedsCompilation: no
Packaged: 2025-09-03 17:21:59 UTC; dardia
Author: David Ardia [aut, cre] , Benjamin Seguin [aut], Rosnel Sessinou [ctb], Richard Luger [ctb]
Maintainer: David Ardia <david.ardia.ch@gmail.com>
Repository: CRAN
Date/Publication: 2025-09-09 13:40:02 UTC

More information about spantest at CRAN
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New package pmsesampling with initial version 0.1.1
Package: pmsesampling
Title: Sample Size Determination for Accurate Predictive Linear Regression
Version: 0.1.1
Description: Provides analytic and simulation tools to estimate the minimum sample size required for achieving a target prediction mean-squared error (PMSE) or a specified proportional PMSE reduction (pPMSEr) in linear regression models. Functions implement the criteria of Ma (2023) <https://digital.wpi.edu/downloads/0g354j58c>, support covariance-matrix handling, and include helpers for root-finding and diagnostic plotting.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: Matrix, stats, rootSolve
Suggests: rmarkdown, testthat(>= 3.0.0)
BugReports: https://github.com/Chenaters/pmsesampling/issues
URL: https://github.com/Chenaters/pmsesampling
NeedsCompilation: no
Packaged: 2025-09-04 04:29:42 UTC; 12245
Author: Louis Chen [aut, cre], Zheyang Wu [aut, ths]
Maintainer: Louis Chen <chenaters@gmail.com>
Repository: CRAN
Date/Publication: 2025-09-09 14:00:02 UTC

More information about pmsesampling at CRAN
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New package pdfcombiner with initial version 1.9.8
Package: pdfcombiner
Title: Graphical User Interface for Manipulating PDF and Image Files
Version: 1.9.8
Maintainer: Steve Choy <steve.choy@outlook.com>
Description: A 'shiny' app that supports merging of PDF and/or image files with page selection, removal, or rotation options. It is a fast, free, and secure alternative to commercial software or various online websites which require users to sign-up, and it avoids any potential risks associated with uploading files elsewhere.
License: MIT + file LICENSE
URL: https://github.com/stevechoy/pdfcombiner, https://lagom.shinyapps.io/pdfcombiner/
BugReports: https://github.com/stevechoy/pdfcombiner/issues
Encoding: UTF-8
Imports: shiny, pdftools, qpdf,
Suggests: bslib, rJava, staplr, testthat (>= 3.0.0), magick, officer, openxlsx, shinythemes
Depends: R (>= 3.5.0)
NeedsCompilation: no
Packaged: 2025-09-04 05:21:25 UTC; choysiuf
Author: Steve Choy [aut, cre, cph]
Repository: CRAN
Date/Publication: 2025-09-09 14:00:08 UTC

More information about pdfcombiner at CRAN
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New package optconerrf with initial version 1.0.0
Package: optconerrf
Title: Optimal Monotone Conditional Error Functions
Version: 1.0.0
Description: Design and analysis of confirmatory adaptive clinical trials using the optimal conditional error framework according to Brannath and Bauer (2004) <doi:10.1111/j.0006-341X.2004.00221.x>. An extension to the optimal conditional error function using interim estimates as described in Brannath and Dreher (2024) <doi:10.48550/arXiv.2402.00814> and functions to ensure that the resulting conditional error function is non-increasing are also available.
Imports: ggplot2, methods
License: GPL (>= 3)
Encoding: UTF-8
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
URL: https://github.com/morten-dreher/optconerrf
BugReports: https://github.com/morten-dreher/optconerrf/issues
NeedsCompilation: no
Packaged: 2025-09-03 19:51:20 UTC; Morten
Author: Morten Dreher [aut, cre], Werner Brannath [aut, cph] , Cornelia Ursula Kunz [ctb] , Johanna zur Verth [aut]
Maintainer: Morten Dreher <morten.dreher@outlook.de>
Repository: CRAN
Date/Publication: 2025-09-09 13:40:07 UTC

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New package missalpha with initial version 0.1.0
Package: missalpha
Title: Find Range of Cronbach Alpha with a Dataset Including Missing Data
Version: 0.1.0
Maintainer: Biying Zhou <biying.zhou@psu.edu>
Description: Provides functions to calculate the minimum and maximum possible values of Cronbach's alpha when item-level missing data are present. Cronbach's alpha (Cronbach, 1951 <doi:10.1007/BF02310555>) is one of the most widely used measures of internal consistency in the social, behavioral, and medical sciences (Bland & Altman, 1997 <doi:10.1136/bmj.314.7080.572>; Tavakol & Dennick, 2011 <doi:10.5116/ijme.4dfb.8dfd>). However, conventional implementations assume complete data, and listwise deletion is often applied when missingness occurs, which can lead to biased or overly optimistic reliability estimates (Enders, 2003 <doi:10.1037/1082-989X.8.3.322>). This package implements computational strategies including enumeration, Monte Carlo sampling, and optimization algorithms (e.g., Genetic Algorithm, Differential Evolution, Sequential Least Squares Programming) to obtain sharp lower and upper bounds of Cronbach's alpha under arbitrary missing data patterns. The ap [...truncated...]
License: MIT + file LICENSE
Depends: R (>= 3.1.0),
Imports: GA, DEoptim, nloptr, stats,
Encoding: UTF-8
Suggests: testthat (>= 3.0.0)
LazyData: true
NeedsCompilation: no
Packaged: 2025-09-03 21:09:11 UTC; zby15
Author: Feng Ji [aut], Biying Zhou [aut, cre]
Repository: CRAN
Date/Publication: 2025-09-09 13:50:02 UTC

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New package inshiny with initial version 0.1.0
Package: inshiny
Title: Compact Inline Widgets for 'shiny' Apps
Version: 0.1.0
Description: Provides a basic set of compact widgets for 'shiny' apps which occupy less space and can appear inline with surrounding text.
License: MIT + file LICENSE
Encoding: UTF-8
URL: https://github.com/nicholasdavies/inshiny, https://nicholasdavies.github.io/inshiny/
BugReports: https://github.com/nicholasdavies/inshiny/issues
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
Imports: bslib, htmltools, rlang, shiny, stringr
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2025-09-04 00:34:30 UTC; nick
Author: Nick Davies [aut, cre]
Maintainer: Nick Davies <nicholas.davies@lshtm.ac.uk>
Repository: CRAN
Date/Publication: 2025-09-09 14:00:13 UTC

More information about inshiny at CRAN
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New package ETDQualitizer with initial version 0.9.0
Package: ETDQualitizer
Title: Automated Eye Tracking Data Quality Determination for Screen-Based Eye Trackers
Version: 0.9.0
Maintainer: Diederick Niehorster <diederick_c.niehorster@humlab.lu.se>
Description: Compute common data quality metrics for accuracy, precision and data loss for screen-based eye trackers. Supports input data both in pixels on the screen and in degrees, output measures are (where appropriate) expressed as angles in degrees.
License: MIT + file LICENSE
URL: https://github.com/dcnieho/ETDQualitizer
BugReports: https://github.com/dcnieho/ETDQualitizer/issues
Encoding: UTF-8
Imports: R6, stats
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2025-09-03 20:44:39 UTC; huml-dkn
Author: Diederick Niehorster [aut, cre, cph]
Repository: CRAN
Date/Publication: 2025-09-09 13:50:07 UTC

More information about ETDQualitizer at CRAN
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New package autotesteR with initial version 0.1.7
Package: autotesteR
Title: Automated Functions for Basic Statistical Tests
Version: 0.1.7
Description: Provides simple and intuitive functions for basic statistical analyses. Methods include the t-test (Student 1908 <doi:10.1093/biomet/6.1.1>), the Mann-Whitney U test (Mann and Whitney 1947 <doi:10.1214/aoms/1177730491>), Pearson's correlation (Pearson 1895 <doi:10.1098/rspl.1895.0041>), and analysis of variance (Fisher 1925, <doi:10.1007/978-1-4612-4380-9_5>). Functions are compatible with 'ggplot2' and 'dplyr'.
License: MIT + file LICENSE
Depends: R (>= 4.1.0)
Encoding: UTF-8
Imports: car, crayon, dplyr, FSA, ggplot2, multcompView, nortest, stats, utils
NeedsCompilation: no
Packaged: 2025-09-04 01:34:44 UTC; Seu Computador
Author: Luiz Garcia [aut, cre]
Maintainer: Luiz Garcia <luiz.cardoso@ufpr.br>
Repository: CRAN
Date/Publication: 2025-09-09 14:00:17 UTC

More information about autotesteR at CRAN
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Package RSC updated to version 2.0.5 with previous version 2.0.4 dated 2023-04-17

Title: Robust and Sparse Correlation Matrix
Description: Performs robust and sparse correlation matrix estimation. Robustness is achieved based on a simple robust pairwise correlation estimator, while sparsity is obtained based on thresholding. The optimal thresholding is tuned via cross-validation. See Serra, Coretto, Fratello and Tagliaferri (2018) <doi:10.1093/bioinformatics/btx642>.
Author: Luca Coraggio [cre, aut], Pietro Coretto [aut], Angela Serra [aut], Roberto Tagliaferri [ctb]
Maintainer: Luca Coraggio <luca.coraggio@unina.it>

Diff between RSC versions 2.0.4 dated 2023-04-17 and 2.0.5 dated 2025-09-09

 DESCRIPTION |    8 ++++----
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More information about RSC at CRAN
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New package rFDP with initial version 0.1.1
Package: rFDP
Title: Resampling-Based False Discovery Proportion Control
Version: 0.1.1
Date: 2025-09-03
Maintainer: Jesse Hemerik <hemerik@ese.eur.nl>
Description: Methods for Resampling-based False Discovery Proportion control. A function is provided that provides simultaneous, multi-resolution False Discovery Exceedance (FDX) control as described in Hemerik (2025) <doi:10.48550/arXiv.2509.02376>.
License: GNU General Public License
Imports: methods
NeedsCompilation: no
Packaged: 2025-09-03 10:54:40 UTC; jessu
Author: Jesse Hemerik [aut, cre]
Repository: CRAN
Date/Publication: 2025-09-09 13:00:02 UTC

More information about rFDP at CRAN
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Package RcppSMC updated to version 0.2.9 with previous version 0.2.8 dated 2025-05-10

Title: Rcpp Bindings for Sequential Monte Carlo
Description: R access to the Sequential Monte Carlo Template Classes by Johansen <doi:10.18637/jss.v030.i06> is provided. At present, four additional examples have been added, and the first example from the JSS paper has been extended. Further integration and extensions are planned.
Author: Dirk Eddelbuettel [aut, cre] , Adam M. Johansen [aut] , Leah F. South [aut] , Ilya Zarubin [aut]
Maintainer: Dirk Eddelbuettel <edd@debian.org>

Diff between RcppSMC versions 0.2.8 dated 2025-05-10 and 0.2.9 dated 2025-09-09

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Package particle.swarm.optimisation updated to version 1.0.1 with previous version 1.0 dated 2021-05-21

Title: Optimisation with Particle Swarm Optimisation
Description: A toolbox to create a particle swarm optimisation (PSO), the package contains two classes: the Particle and the Particle Swarm, this two class are used to run the PSO with methods to easily print, plot and save the result.
Author: Theo Brunet [aut, cre]
Maintainer: Theo Brunet <brunet.theo83140@gmail.com>

Diff between particle.swarm.optimisation versions 1.0 dated 2021-05-21 and 1.0.1 dated 2025-09-09

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Package nettskjemar updated to version 1.0.4 with previous version 1.0.3 dated 2025-09-04

Title: Connect to the 'nettskjema.no' API of the University of Oslo
Description: Enables users to retrieve data, meta-data, and codebooks from <https://nettskjema.no/>. The data from the API is richer than from the online data portal. This package is not developed by the University of Oslo IT. Mowinckel (2021) <doi:10.5281/zenodo.4745481>.
Author: Athanasia Mo Mowinckel [aut, cre] , Trym Nohr Fjoertoft [ctb]
Maintainer: Athanasia Mo Mowinckel <a.m.mowinckel@psykologi.uio.no>

Diff between nettskjemar versions 1.0.3 dated 2025-09-04 and 1.0.4 dated 2025-09-09

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More information about nettskjemar at CRAN
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Package multiApply updated to version 2.1.5 with previous version 2.1.4 dated 2023-03-28

Title: Apply Functions to Multiple Multidimensional Arrays or Vectors
Description: The base apply function and its variants, as well as the related functions in the 'plyr' package, typically apply user-defined functions to a single argument (or a list of vectorized arguments in the case of mapply). The 'multiApply' package extends this paradigm with its only function, Apply, which efficiently applies functions taking one or a list of multiple unidimensional or multidimensional arrays (or combinations thereof) as input. The input arrays can have different numbers of dimensions as well as different dimension lengths, and the applied function can return one or a list of unidimensional or multidimensional arrays as output. This saves development time by preventing the R user from writing often error-prone and memory-inefficient loops dealing with multiple complex arrays. Also, a remarkable feature of Apply is the transparent use of multi-core through its parameter 'ncores'. In contrast to the base apply function, this package suggests the use of 'target dimensions' as op [...truncated...]
Author: BSC-CNS [aut, cph], Nicolau Manubens [aut], Alasdair Hunter [aut], An-Chi Ho [ctb], Nuria Perez [ctb], Victoria Agudetse [ctb, cre]
Maintainer: Victoria Agudetse <victoria.agudetse@bsc.es>

Diff between multiApply versions 2.1.4 dated 2023-03-28 and 2.1.5 dated 2025-09-09

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More information about multiApply at CRAN
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Package mlsurvlrnrs updated to version 0.0.6 with previous version 0.0.5 dated 2025-03-03

Title: R6-Based ML Survival Learners for 'mlexperiments'
Description: Enhances 'mlexperiments' <https://CRAN.R-project.org/package=mlexperiments> with additional machine learning ('ML') learners for survival analysis. The package provides R6-based survival learners for the following algorithms: 'glmnet' <https://CRAN.R-project.org/package=glmnet>, 'ranger' <https://CRAN.R-project.org/package=ranger>, 'xgboost' <https://CRAN.R-project.org/package=xgboost>, and 'rpart' <https://CRAN.R-project.org/package=rpart>. These can be used directly with the 'mlexperiments' R package.
Author: Lorenz A. Kapsner [cre, aut, cph]
Maintainer: Lorenz A. Kapsner <lorenz.kapsner@gmail.com>

Diff between mlsurvlrnrs versions 0.0.5 dated 2025-03-03 and 0.0.6 dated 2025-09-09

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Package jqbr updated to version 1.0.4 with previous version 1.0.3 dated 2023-08-15

Title: 'jQuery QueryBuilder' Input for 'Shiny'
Description: A highly configurable 'jQuery' plugin offering a simple interface to create complex queries/filters in 'Shiny'. The outputted rules can easily be parsed into a set of 'R' and/or 'SQL' queries and used to filter data. Custom parsing of the rules is also supported. For more information about 'jQuery QueryBuilder' see <https://querybuilder.js.org/>.
Author: Harry Fisher [aut, cre]
Maintainer: Harry Fisher <harryfisher21@gmail.com>

Diff between jqbr versions 1.0.3 dated 2023-08-15 and 1.0.4 dated 2025-09-09

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Package hdbinseg updated to version 1.0.3 with previous version 1.0.2 dated 2023-08-17

Title: Change-Point Analysis of High-Dimensional Time Series via Binary Segmentation
Description: Binary segmentation methods for detecting and estimating multiple change-points in the mean or second-order structure of high-dimensional time series as described in Cho and Fryzlewicz (2014) <doi:10.1111/rssb.12079> and Cho (2016) <doi:10.1214/16-EJS1155>.
Author: Haeran Cho [aut, cre], Piotr Fryzlewicz [aut]
Maintainer: Haeran Cho <haeran.cho@bristol.ac.uk>

Diff between hdbinseg versions 1.0.2 dated 2023-08-17 and 1.0.3 dated 2025-09-09

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New package EQUALCompareImages with initial version 0.1.0
Package: EQUALCompareImages
Title: Comparison of Images for Researchers Without Coding Skills
Version: 0.1.0
Date: 2025-08-29
Author: Kurinchi Gurusamy [aut, cre]
Maintainer: Kurinchi Gurusamy <k.gurusamy@ucl.ac.uk>
Depends: cowplot, ggplot2, magick, knitr, zip
Imports: shinybusy
Description: Support functions for R-based "EQUALCompareImages - Compare similarity between and within images" shiny application which allow researchers without coding skills or expertise in image comparison algorithms to compare images. Gurusamy,K (2025)<doi:10.5281/zenodo.16994047>.
License: GPL (>= 3)
Encoding: UTF-8
URL: https://sites.google.com/view/equal-group/home
NeedsCompilation: no
Packaged: 2025-09-03 09:57:08 UTC; kurin
Repository: CRAN
Date/Publication: 2025-09-09 13:00:11 UTC

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New package eFCM with initial version 1.0
Package: eFCM
Title: Exponential Factor Copula Model
Version: 1.0
Maintainer: Mengran Li <m.li.3@research.gla.ac.uk>
Description: Implements the exponential Factor Copula Model (eFCM) of Castro-Camilo, D. and Huser, R. (2020) for spatial extremes, with tools for dependence estimation, tail inference, and visualization. The package supports likelihood-based inference, Gaussian process modeling via Matérn covariance functions, and bootstrap uncertainty quantification. See Castro-Camilo and Huser (2020) <doi:10.1080/01621459.2019.1647842>.
License: GPL (>= 3)
Encoding: UTF-8
Depends: R (>= 3.5.0)
Imports: Rcpp, nsRFA, ismev, fields, mnormt, numDeriv, pbmcapply, boot, progress
LinkingTo: Rcpp, RcppArmadillo
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: yes
LazyData: false
Packaged: 2025-09-03 11:44:32 UTC; 2592713L
Author: Mengran Li [aut, cre], Daniela Castro-Camilo [aut]
Repository: CRAN
Date/Publication: 2025-09-09 13:00:06 UTC

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Package brms updated to version 2.23.0 with previous version 2.22.0 dated 2024-09-23

Title: Bayesian Regression Models using 'Stan'
Description: Fit Bayesian generalized (non-)linear multivariate multilevel models using 'Stan' for full Bayesian inference. A wide range of distributions and link functions are supported, allowing users to fit -- among others -- linear, robust linear, count data, survival, response times, ordinal, zero-inflated, hurdle, and even self-defined mixture models all in a multilevel context. Further modeling options include both theory-driven and data-driven non-linear terms, auto-correlation structures, censoring and truncation, meta-analytic standard errors, and quite a few more. In addition, all parameters of the response distribution can be predicted in order to perform distributional regression. Prior specifications are flexible and explicitly encourage users to apply prior distributions that actually reflect their prior knowledge. Models can easily be evaluated and compared using several methods assessing posterior or prior predictions. References: Bürkner (2017) <doi:10.18637/jss.v080.i01>; B [...truncated...]
Author: Paul-Christian Buerkner [aut, cre], Jonah Gabry [ctb], Sebastian Weber [ctb], Andrew Johnson [ctb], Martin Modrak [ctb], Hamada S. Badr [ctb], Frank Weber [ctb], Aki Vehtari [ctb], Mattan S. Ben-Shachar [ctb], Hayden Rabel [ctb], Simon C. Mills [ctb], [...truncated...]
Maintainer: Paul-Christian Buerkner <paul.buerkner@gmail.com>

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Package survivoR updated to version 2.3.7 with previous version 2.3.6 dated 2025-06-13

Title: Data from all Seasons of Survivor (US) TV Series in Tidy Format
Description: Datasets detailing the results, castaways, and events of each season of Survivor for the US, Australia, South Africa, New Zealand, and the UK. This includes details on the cast, voting history, immunity and reward challenges, jury votes, boot order, advantage details, and episode ratings. Use this for analysis of trends and statistics of the game.
Author: Daniel Oehm [aut, cre], Carly Levitz [ctb]
Maintainer: Daniel Oehm <danieloehm@gmail.com>

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Package FlexReg updated to version 1.4 with previous version 1.3.1 dated 2025-04-14

Title: Regression Models for Bounded Continuous and Discrete Responses
Description: Functions to fit regression models for bounded continuous and discrete responses. In case of bounded continuous responses (e.g., proportions and rates), available models are the flexible beta (Migliorati, S., Di Brisco, A. M., Ongaro, A. (2018) <doi:10.1214/17-BA1079>), the variance-inflated beta (Di Brisco, A. M., Migliorati, S., Ongaro, A. (2020) <doi:10.1177/1471082X18821213>), the beta (Ferrari, S.L.P., Cribari-Neto, F. (2004) <doi:10.1080/0266476042000214501>), and their augmented versions to handle the presence of zero/one values (Di Brisco, A. M., Migliorati, S. (2020) <doi:10.1002/sim.8406>) are implemented. In case of bounded discrete responses (e.g., bounded counts, such as the number of successes in n trials), available models are the flexible beta-binomial (Ascari, R., Migliorati, S. (2021) <doi:10.1002/sim.9005>), the beta-binomial, and the binomial are implemented. Inference is dealt with a Bayesian approach based on the Hamiltonian Monte C [...truncated...]
Author: Roberto Ascari [aut, cre], Agnese M. Di Brisco [aut], Sonia Migliorati [aut], Andrea Ongaro [aut]
Maintainer: Roberto Ascari <roberto.ascari@unimib.it>

Diff between FlexReg versions 1.3.1 dated 2025-04-14 and 1.4 dated 2025-09-09

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Package zenplots updated to version 1.0.7 with previous version 1.0.6 dated 2023-11-07

Title: Zigzag Expanded Navigation Plots
Description: Graphical tools for visualizing high-dimensional data along a path of alternating one- and two-dimensional plots. Includes optional interactive graphics via 'loon' (which uses 'tcltk' from base R). Support is provided for constructing graph structures and, when available, plotting them with Bioconductor packages (e.g., 'graph', 'Rgraphviz'); these are optional and examples/vignettes are skipped if they are not installed. For algorithms and further details, see <doi:10.18637/jss.v095.i04>.
Author: Marius Hofert [aut], Wayne Oldford [aut, cre]
Maintainer: Wayne Oldford <rwoldford@uwaterloo.ca>

Diff between zenplots versions 1.0.6 dated 2023-11-07 and 1.0.7 dated 2025-09-09

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Package sqlcaser updated to version 0.2.1 with previous version 0.2.0 dated 2023-11-24

Title: 'SQL' Case Statement Generator
Description: Includes built-in methods for generating long 'SQL' CASE statements, and other 'SQL' statements that may otherwise be arduous to construct by hand.The generated statement can easily be concatenated to string literals to form queries to 'SQL'-like databases, such as when using the 'RODBC' package. The current methods include casewhen() for building CASE statements, inlist() for building IN statements, and updatetable() for building UPDATE statements.
Author: Leoson Hoay [aut, cre]
Maintainer: Leoson Hoay <leoson.public@gmail.com>

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Package SKNN updated to version 4.1.1 with previous version 4.1 dated 2024-10-08

Title: A Super K-Nearest Neighbor (SKNN) Classification Algorithm
Description: It's a Super K-Nearest Neighbor(SKNN) classification method with using kernel density to describe weight of the distance between a training observation and the testing sample. Comparison of performance between SKNN and KNN shows that SKNN is significantly superior to KNN.
Author: Yarong Yang [aut, cre], Nader Ebrahimi [ctb], Yoram Rubin [ctb], Jacob Zhang [ctb]
Maintainer: Yarong Yang <Yi.YA_yaya@hotmail.com>

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Package RobinCar2 updated to version 0.2.0 with previous version 0.1.1 dated 2025-04-03

Title: ROBust INference for Covariate Adjustment in Randomized Clinical Trials
Description: Performs robust estimation and inference when using covariate adjustment and/or covariate-adaptive randomization in randomized controlled trials. This package is trimmed to reduce the dependencies and validated to be used across industry. See "FDA's final guidance on covariate adjustment"<https://www.regulations.gov/docket/FDA-2019-D-0934>, Tsiatis (2008) <doi:10.1002/sim.3113>, Bugni et al. (2018) <doi:10.1080/01621459.2017.1375934>, Ye, Shao, Yi, and Zhao (2023)<doi:10.1080/01621459.2022.2049278>, Ye, Shao, and Yi (2022)<doi:10.1093/biomet/asab015>, Rosenblum and van der Laan (2010)<doi:10.2202/1557-4679.1138>, Wang et al. (2021)<doi:10.1080/01621459.2021.1981338>, Ye, Bannick, Yi, and Shao (2023)<doi:10.1080/24754269.2023.2205802>, and Bannick, Shao, Liu, Du, Yi, and Ye (2024)<doi:10.48550/arXiv.2306.10213>.
Author: Liming Li [aut, cre] , Marlena Bannick [aut] , Daniel Sabanes Bove [aut] , Dong Xi [aut], Ting Ye [aut], Yanyao Yi [aut], Gregory Chen [ctb], Gilead Sciences, Inc. [cph, fnd], F. Hoffmann-La Roche AG [cph, fnd], Merck Sharp & Dohme, Inc. [cph, fnd], [...truncated...]
Maintainer: Liming Li <liming.li1@astrazeneca.com>

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Package ohenery updated to version 0.1.4 with previous version 0.1.3 dated 2025-04-20

Title: Modeling of Ordinal Random Variables via Softmax Regression
Description: Supports the modeling of ordinal random variables, like the outcomes of races, via Softmax regression, under the Harville <doi:10.1080/01621459.1973.10482425> and Henery <doi:10.1111/j.2517-6161.1981.tb01153.x> models.
Author: Steven E. Pav [aut, cre]
Maintainer: Steven E. Pav <shabbychef@gmail.com>

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Package MRTAnalysis updated to version 0.3.0 with previous version 0.2.0 dated 2025-08-29

Title: Assessing Proximal, Distal, and Mediated Causal Excursion Effects for Micro-Randomized Trials
Description: Provides methods to analyze micro-randomized trials (MRTs) with binary treatment options. Supports three types of analyses: (1) proximal causal excursion effects, including weighted and centered least squares (WCLS) for continuous proximal outcomes by Boruvka et al. (2018) <doi:10.1080/01621459.2017.1305274> and the estimator for marginal excursion effect (EMEE) for binary proximal outcomes by Qian et al. (2021) <doi:10.1093/biomet/asaa070>; (2) distal causal excursion effects (DCEE) for continuous distal outcomes using a two-stage estimator by Qian (2025) <doi:10.48550/arXiv.2502.13500>; and (3) mediated causal excursion effects (MCEE) for continuous distal outcomes, estimating natural direct and indirect excursion effects in the presence of time-varying mediators by Qian (2025) <doi:10.48550/arXiv.2506.20027>.
Author: Tianchen Qian [aut, cre] , Shaolin Xiang [aut], Zhaoxi Cheng [aut], Audrey Boruvka [ctb]
Maintainer: Tianchen Qian <t.qian@uci.edu>

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Package fmtr updated to version 1.6.9 with previous version 1.6.8 dated 2025-01-27

Title: Easily Apply Formats to Data
Description: Contains a set of functions that can be used to apply formats to data frames or vectors. The package aims to provide functionality similar to that of SAS® formats. Formats are assigned to the format attribute on data frame columns. Then when the fdata() function is called, a new data frame is created with the column data formatted as specified. The package also contains a value() function to create a user-defined format, similar to a SAS® user-defined format.
Author: David Bosak [aut, cre]
Maintainer: David Bosak <dbosak01@gmail.com>

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Package centerline updated to version 0.2.4 with previous version 0.2.2 dated 2025-03-16

Title: Extract Centerline from Closed Polygons
Description: Generates skeletons of closed 2D polygons using Voronoi diagrams. It provides methods for 'sf', 'terra', and 'geos' objects to compute polygon centerlines based on the generated skeletons. Voronoi, G. (1908) <doi:10.1515/crll.1908.134.198>.
Author: Anatoly Tsyplenkov [aut, cre, cph]
Maintainer: Anatoly Tsyplenkov <atsyplenkov@fastmail.com>

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Package BatchExperiments updated to version 1.4.4 with previous version 1.4.3 dated 2022-03-21

Title: Statistical Experiments on Batch Computing Clusters
Description: Extends the BatchJobs package to run statistical experiments on batch computing clusters. For further details see the project web page.
Author: Bernd Bischl [aut], Michel Lang [aut, cre], Olaf Mersmann [aut]
Maintainer: Michel Lang <michellang@gmail.com>

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Package xpose.xtras updated to version 0.1.0 with previous version 0.0.3 dated 2025-08-23

Title: Extra Functionality for the 'xpose' Package
Description: Adding some at-present missing functionality, or functions unlikely to be added to the base 'xpose' package. This includes some diagnostic plots that have been missing in translation from 'xpose4', but also some useful features that truly extend the capabilities of what can be done with 'xpose'. These extensions include the concept of a set of 'xpose' objects, and diagnostics for likelihood-based models.
Author: John Prybylski [aut, cre, cph]
Maintainer: John Prybylski <jprybylski@gmail.com>

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Package SVEMnet updated to version 2.1.3 with previous version 1.5.3 dated 2025-08-22

Title: Self-Validated Ensemble Models with Lasso and Relaxed-Elastic Net Regression
Description: Implements Self-Validated Ensemble Models (SVEM, Lemkus et al. (2021) <doi:10.1016/j.chemolab.2021.104439>) using Elastic Net regression via 'glmnet' (Friedman et al. <doi:10.18637/jss.v033.i01>). SVEM averages predictions from multiple models fitted to fractionally weighted bootstraps of the data, tuned with anti-correlated validation weights. Also implements the randomized permutation whole model test for SVEM (Karl (2024) <doi:10.1016/j.chemolab.2024.105122>). \\Code for the whole model test was taken from the supplementary material of Karl (2024). Development of this package was assisted by 'GPT o1-preview' for code structure and documentation.
Author: Andrew T. Karl [cre, aut]
Maintainer: Andrew T. Karl <akarl@asu.edu>

Diff between SVEMnet versions 1.5.3 dated 2025-08-22 and 2.1.3 dated 2025-09-09

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Package optweight updated to version 1.0.0 with previous version 0.2.5 dated 2019-09-16

Title: Optimization-Based Stable Balancing Weights
Description: Use optimization to estimate weights that balance covariates for binary, multi-category, continuous, and multivariate treatments in the spirit of Zubizarreta (2015) <doi:10.1080/01621459.2015.1023805>. The degree of balance can be specified for each covariate. In addition, sampling weights can be estimated that allow a sample to generalize to a population specified with given target moments of covariates.
Author: Noah Greifer [aut, cre]
Maintainer: Noah Greifer <noah.greifer@gmail.com>

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Package mlexperiments updated to version 0.0.7 with previous version 0.0.6 dated 2025-09-06

Title: Machine Learning Experiments
Description: Provides 'R6' objects to perform parallelized hyperparameter optimization and cross-validation. Hyperparameter optimization can be performed with Bayesian optimization (via 'ParBayesianOptimization' <https://cran.r-project.org/package=ParBayesianOptimization>) and grid search. The optimized hyperparameters can be validated using k-fold cross-validation. Alternatively, hyperparameter optimization and validation can be performed with nested cross-validation. While 'mlexperiments' focuses on core wrappers for machine learning experiments, additional learner algorithms can be supplemented by inheriting from the provided learner base class.
Author: Lorenz A. Kapsner [cre, aut, cph]
Maintainer: Lorenz A. Kapsner <lorenz.kapsner@gmail.com>

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Package icarus updated to version 0.3.3 with previous version 0.3.2 dated 2023-05-27

Title: Calibrates and Reweights Units in Samples
Description: Provides user-friendly tools for calibration in survey sampling. The package is production-oriented, and its interface is inspired by the famous popular macro 'Calmar' for SAS, so that 'Calmar' users can quickly get used to 'icarus'. In addition to calibration (with linear, raking and logit methods), 'icarus' features functions for calibration on tight bounds and penalized calibration.
Author: Antoine Rebecq [aut] , Khaled Larbi [cre], Institut national de la statistique et des etudes economiques [cph]
Maintainer: Khaled Larbi <khaled.larbi@insee.fr>

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Package ggEDA updated to version 0.2.0 with previous version 0.1.0 dated 2025-05-07

Title: Turnkey Visualisations for Exploratory Data Analysis
Description: Provides interactive visualisations for exploratory data analysis of high-dimensional datasets. Includes parallel coordinate plots for exploring large datasets with mostly quantitative features, but also stacked one-dimensional visualisations that more effectively show missingness and complex categorical relationships in smaller datasets.
Author: Sam El-Kamand [aut, cre] , Children's Cancer Institute Australia [cph]
Maintainer: Sam El-Kamand <sam.elkamand@gmail.com>

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Package EstimationTools updated to version 4.3.1 with previous version 4.0.0 dated 2022-12-10

Title: Maximum Likelihood Estimation for Probability Functions from Data Sets
Description: Total Time on Test plot and routines for parameter estimation of any lifetime distribution implemented in R via maximum likelihood (ML) given a data set. It is implemented thinking on parametric survival analysis, but it feasible to use in parameter estimation of probability density or mass functions in any field. The main routines 'maxlogL' and 'maxlogLreg' are wrapper functions specifically developed for ML estimation. There are included optimization procedures such as 'nlminb' and 'optim' from base package, and 'DEoptim' Mullen (2011) <doi:10.18637/jss.v040.i06>. Standard errors are estimated with 'numDeriv' Gilbert (2011) <https://CRAN.R-project.org/package=numDeriv> or the option 'Hessian = TRUE' of 'optim' function.
Author: Jaime Mosquera [aut, cre, cph] , Freddy Hernandez [ctb]
Maintainer: Jaime Mosquera <jmosquerag@unal.edu.co>

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Package ChemoSpec updated to version 6.3.1 with previous version 6.3.0 dated 2025-07-31

Title: Exploratory Chemometrics for Spectroscopy
Description: A collection of functions for top-down exploratory data analysis of spectral data including nuclear magnetic resonance (NMR), infrared (IR), Raman, X-ray fluorescence (XRF) and other similar types of spectroscopy. Includes functions for plotting and inspecting spectra, peak alignment, hierarchical cluster analysis (HCA), principal components analysis (PCA) and model-based clustering. Robust methods appropriate for this type of high-dimensional data are available. ChemoSpec is designed for structured experiments, such as metabolomics investigations, where the samples fall into treatment and control groups. Graphical output is formatted consistently for publication quality plots. ChemoSpec is intended to be very user friendly and to help you get usable results quickly. A vignette covering typical operations is available.
Author: Bryan A. Hanson [aut, cre] , Mike Bostock [cph, ctb] , Matt Keinsley [ctb] , Tejasvi Gupta [ctb]
Maintainer: Bryan A. Hanson <hanson@depauw.edu>

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