Wed, 05 Nov 2025

Package Lifertable updated to version 1.0.1 with previous version 0.1.0 dated 2025-02-05

Title: Life and Fertility Tables Specially for Insects
Description: Life and Fertility Tables are appropriate to study the dynamics of arthropods populations. This package provides utilities for constructing Life Tables and Fertility Tables, related demographic parameters, and some simple graphs of interest. It also offers functions to transform the obtained data into a known format for better manipulation. In addition, two methods for obtaining the confidence interval are included.
Author: Carlos Abimael Sarmiento Sanchez [aut, cre], Lauro Soto Rojas [ctb], Alejandro Corona Ambriz [ctb], Gabriel Arcangel Rodriguez Yam [ctb], Yolanda Franco Islas [ctb], Noe Ramirez Negrete [ctb], Adriana Acevedo Alcala [ctb], Esteban Rodriguez Leyva [ct [...truncated...]
Maintainer: Carlos Abimael Sarmiento Sanchez <cass9918@hotmail.com>

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Package ggtangle updated to version 0.0.8 with previous version 0.0.7 dated 2025-06-30

Title: Draw Network with Data
Description: Extends the 'ggplot2' plotting system to support network visualization. Inspired by the 'Method 1' in 'ggtree' (G Yu (2018) <doi:10.1093/molbev/msy194>), 'ggtangle' is designed to work with network associated data.
Author: Guangchuang Yu [aut, cre]
Maintainer: Guangchuang Yu <guangchuangyu@gmail.com>

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Package BFF updated to version 4.5.0 with previous version 4.4.2 dated 2025-05-20

Title: Bayes Factor Functions
Description: Bayes factors represent the ratio of probabilities assigned to data by competing scientific hypotheses. However, one drawback of Bayes factors is their dependence on prior specifications that define null and alternative hypotheses. Additionally, there are challenges in their computation. To address these issues, we define Bayes factor functions (BFFs) directly from common test statistics. BFFs express Bayes factors as a function of the prior densities used to define the alternative hypotheses. These prior densities are centered on standardized effects, which serve as indices for the BFF. Therefore, BFFs offer a summary of evidence in favor of alternative hypotheses that correspond to a range of scientifically interesting effect sizes. Such summaries remove the need for arbitrary thresholds to determine "statistical significance." BFFs are available in closed form and can be easily computed from z, t, chi-squared, and F statistics. They depend on hyperparameters "r" and "tau^2", which d [...truncated...]
Author: Rachael Shudde [aut, cre], Frantisek Bartos [aut], Saptati Datta [aut], Riana Guha [aut], Sandy Pramanik [aut], Valen Johnson [aut]
Maintainer: Rachael Shudde <rachael.shudde@gmail.com>

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Package summarytabl updated to version 0.2.0 with previous version 0.1.0 dated 2025-10-06

Title: Generate Summary Tables for Categorical, Ordinal, and Continuous Data
Description: Provides functions for tabulating and summarizing categorical, multiple response, ordinal, and continuous variables in R data frames. Makes it easy to create clear, structured summary tables, so you spend less time wrangling data and more time interpreting it.
Author: Ama Nyame-Mensah [aut, cre]
Maintainer: Ama Nyame-Mensah <ama@anyamemensah.com>

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Package rAccess updated to version 0.1.1.3 with previous version 0.1.1.2 dated 2025-11-03

Title: Access Control Module for 'shiny' Applications
Description: Provides a flexible framework for implementing hierarchical access control in 'shiny' applications. Features include user permission management through a two-tier system of access panels and units, pluggable 'shiny' module for administrative interfaces, and support for multiple storage backends (local, 'AWS S3', 'Posit Connect'). The system enables fine-grained control over application features, with built-in audit trails and user management capabilities. Integrates seamlessly with 'Posit Connect's authentication system.
Author: Peyman Eshghi [aut, cre] , Nandu Krishnan [aut], Nadia Abraham [aut], Harika Adapala [ctb], Johnson & Johnson Innovative Medicine [cph, fnd]
Maintainer: Peyman Eshghi <peymaan.es@gmail.com>

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Package gfoRmulaICE readmission to version 0.1.1 with previous version 0.1.0 dated 2024-12-02

Title: Parametric Iterative Conditional Expectation G-Formula
Description: Implements iterative conditional expectation (ICE) estimators of the plug-in g-formula (Wen, Young, Robins, and Hernán (2020) <doi:10.1111/biom.13321>). Both singly robust and doubly robust ICE estimators based on parametric models are available. The package can be used to estimate survival curves under sustained treatment strategies (interventions) using longitudinal data with time-varying treatments, time-varying confounders, censoring, and competing events. The interventions can be static or dynamic, and deterministic or stochastic (including threshold interventions). Both prespecified and user-defined interventions are available.
Author: Zhaoxi Cheng [aut], Jing Li [aut, cre], Sophia Rein [aut], Ryan O'Dea [aut], Sean McGrath [aut], Lan Wen [aut], Miguel A. Hernan [aut], 2024 The President and Fellows of Harvard College [cph]
Maintainer: Jing Li <jing_li@hsph.harvard.edu>

This is a re-admission after prior archival of version 0.1.0 dated 2024-12-02

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Package geospatialsuite updated to version 0.1.1 with previous version 0.1.0 dated 2025-09-16

Title: Comprehensive Geospatiotemporal Analysis and Multimodal Integration Toolkit
Description: A comprehensive toolkit for geospatiotemporal analysis featuring 60+ vegetation indices, advanced raster visualization, universal spatial mapping, water quality analysis, CDL crop analysis, spatial interpolation, temporal analysis, and terrain analysis. Designed for agricultural research, environmental monitoring, remote sensing applications, and publication-quality mapping with support for any geographic region and robust error handling. Methods include vegetation indices calculations (Rouse et al. 1974), NDVI and enhanced vegetation indices (Huete et al. 1997) <doi:10.1016/S0034-4257(97)00104-1>, (Akanbi et al. 2024) <doi:10.1007/s41651-023-00164-y>, spatial interpolation techniques (Cressie 1993, ISBN:9780471002556), water quality indices (McFeeters 1996) <doi:10.1080/01431169608948714>, and crop data layer analysis (USDA NASS 2024) <https://www.nass.usda.gov/Research_and_Science/Cropland/>. Funding: This material is based upon financial support by the Natio [...truncated...]
Author: Olatunde D. Akanbi [aut, cre, cph] , Vibha Mandayam [aut] , Yinghui Wu [aut] , Jeffrey Yarus [aut] , Erika I. Barcelos [aut, cph] , Roger H. French [aut, cph]
Maintainer: Olatunde D. Akanbi <olatunde.akanbi@case.edu>

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Package epikit updated to version 0.2.0 with previous version 0.1.6 dated 2024-01-23

Title: Miscellaneous Helper Tools for Epidemiologists
Description: Contains tools for formatting inline code, renaming redundant columns, aggregating age categories, adding survey weights, finding the earliest date of an event, plotting z-curves, generating population counts and formatting proportions with confidence intervals. This is part of the 'R4Epis' project <https://r4epi.github.io/sitrep/>.
Author: Alexander Spina [aut, cre] , Zhian N. Kamvar [aut] , Dirk Schumacher [aut], Kate Doyle [ctb], Applied Epi Incorporated [cph], Medecins Sans Frontieres Operational Centre Amsterdam [fnd]
Maintainer: Alexander Spina <aspina@appliedepi.org>

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Package ds4psy updated to version 1.2.0 with previous version 1.1.0 dated 2025-09-12

Title: Data Science for Psychologists
Description: All datasets and functions required for the examples and exercises of the book "Data Science for Psychologists" (by Hansjoerg Neth, Konstanz University, 2025, <doi:10.5281/zenodo.7229812>), freely available at <https://bookdown.org/hneth/ds4psy/>. The book and corresponding courses introduce principles and methods of data science to students of psychology and other biological or social sciences. The 'ds4psy' package primarily provides datasets, but also functions for data generation and manipulation (e.g., of text and time data) and graphics that are used in the book and its exercises. All functions included in 'ds4psy' are designed to be explicit and instructive, rather than efficient or elegant.
Author: Hansjoerg Neth [aut, cre]
Maintainer: Hansjoerg Neth <h.neth@uni.kn>

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Package cvdprevent readmission to version 0.2.3 with previous version 0.2.2 dated 2025-05-25

Title: Access and Analyse Data from the 'CVD Prevent' API
Description: Provides an R interface to the 'CVD Prevent' application programming interface (API), allowing users to retrieve and analyse cardiovascular disease prevention data from primary care records across England. The Cardiovascular Disease Prevention Audit (CVDPREVENT) automatically extracts routinely held GP health data to support national reporting and improvement initiatives. See the API documentation for details: <https://bmchealthdocs.atlassian.net/wiki/spaces/CP/pages/317882369/CVDPREVENT+API+Documentation>.
Author: Craig Parylo [aut, cre, cph] , Cardiovascular Disease Prevention Audit [ant]
Maintainer: Craig Parylo <craig.parylo2@nhs.net>

This is a re-admission after prior archival of version 0.2.2 dated 2025-05-25

Diff between cvdprevent versions 0.2.2 dated 2025-05-25 and 0.2.3 dated 2025-11-05

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Package cancensus readmission to version 0.5.10 with previous version 0.5.7 dated 2024-02-09

Title: Access, Retrieve, and Work with Canadian Census Data and Geography
Description: Integrated, convenient, and uniform access to Canadian Census data and geography retrieved using the 'CensusMapper' API. This package produces analysis-ready tidy data frames and spatial data in multiple formats, as well as convenience functions for working with Census variables, variable hierarchies, and region selection. API keys are freely available with free registration at <https://censusmapper.ca/api>. Census data and boundary geometries are reproduced and distributed on an "as is" basis with the permission of Statistics Canada (Statistics Canada 1996; 2001; 2006; 2011; 2016; 2021).
Author: Jens von Bergmann [aut] , Dmitry Shkolnik [aut, cre] , Aaron Jacobs [aut]
Maintainer: Dmitry Shkolnik <shkolnikd@gmail.com>

This is a re-admission after prior archival of version 0.5.7 dated 2024-02-09

Diff between cancensus versions 0.5.7 dated 2024-02-09 and 0.5.10 dated 2025-11-05

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Package WayFindR updated to version 0.5.0 with previous version 0.4.1 dated 2025-09-20

Title: Computing Graph Structures on WikiPathways
Description: Converts pathways from 'WikiPathways' GPML format or 'KEGG' KGML format into 'igraph' objects. Includes tools to find all cycles in the resulting graphs and determine which ones involve negative feedback (inhibition).
Author: Kevin R. Coombes [aut, cre], Polina Bombina [aut]
Maintainer: Kevin R. Coombes <krc@silicovore.com>

Diff between WayFindR versions 0.4.1 dated 2025-09-20 and 0.5.0 dated 2025-11-05

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Package sate updated to version 3.1.0 with previous version 2.4.0 dated 2025-03-04

Title: Scientific Analysis of Trial Errors (SATE)
Description: Bundles functions used to analyze the harmfulness of trial errors in criminal trials. Functions in the Scientific Analysis of Trial Errors ('sate') package help users estimate the probability that a jury will find a defendant guilty given jurors' preferences for a guilty verdict and the uncertainty of that estimate. Users can also compare actual and hypothetical trial conditions to conduct harmful error analysis. The conceptual framework is discussed by Barry Edwards, A Scientific Framework for Analyzing the Harmfulness of Trial Errors, UCLA Criminal Justice Law Review (2024) <doi:10.5070/CJ88164341> and Barry Edwards, If The Jury Only Knew: The Effect Of Omitted Mitigation Evidence On The Probability Of A Death Sentence, Virginia Journal of Social Policy & the Law (2025) <https://vasocialpolicy.org/wp-content/uploads/2025/05/Edwards-If-The-Jury-Only-Knew.pdf>. The relationship between individual jurors' verdict preferences and the probability that a jury returns a guil [...truncated...]
Author: Barry Edwards [aut, cre]
Maintainer: Barry Edwards <bce@uga.edu>

Diff between sate versions 2.4.0 dated 2025-03-04 and 3.1.0 dated 2025-11-05

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New package odbc.resourcer with initial version 1.0.0
Package: odbc.resourcer
Title: Open Database Connectivity Resource Resolver
Version: 1.0.0
Description: A database resource that is accessible through the Open Database Connectivity ('ODBC') API. This package uses the Resource model, with URL "resolver" and "client", to dynamically discover and make accessible tables stored in a 'MS SQL Server' database. For more details see Marcon (2021) <doi:10.1371/journal.pcbi.1008880>.
License: LGPL (>= 2.1)
Depends: R6, httr, resourcer, odbc, DBI
Suggests: testthat, knitr, rmarkdown
BugReports: https://github.com/obiba/odbc.resourcer/issues
VignetteBuilder: knitr
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2025-11-02 19:42:58 UTC; yannick
Author: Yannick Marcon [aut, cre] , OBiBa group [cph]
Maintainer: Yannick Marcon <yannick.marcon@obiba.org>
Repository: CRAN
Date/Publication: 2025-11-05 20:20:02 UTC

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Package MLmorph updated to version 0.1.1 with previous version 0.1.0 dated 2025-09-02

Title: Integrating Morphological Modeling and Machine Learning for Decision Support
Description: Integrating morphological modeling with machine learning to support structured decision-making (e.g., in management and consulting). The package enumerates a morphospace of feasible configurations and uses random forests to estimate class probabilities over that space, bridging deductive model exploration with empirical validation. It includes utilities for factorizing inputs, model training, morphospace construction, and an interactive 'shiny' app for scenario exploration.
Author: Oskar Kosch [aut, cre, cph]
Maintainer: Oskar Kosch <contact@oskarkosch.com>

Diff between MLmorph versions 0.1.0 dated 2025-09-02 and 0.1.1 dated 2025-11-05

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New package insulin.secretion with initial version 0.0.1
Package: insulin.secretion
Title: Insulin Secretion Rate Deconvolution
Version: 0.0.1
Description: Calculates insulin secretion rates from C-peptide values based on the methods described in Van Cauter et al. (1992) <doi:10.2337/diab.41.3.368>. Includes functions to calculate estimated insulin secretion rates using linear or cubic spline interpolation of c-peptide values (see Eaton et al., 1980 <doi:10.1210/jcem-51-3-520> and Polonsky et al., 1986 <doi:10.1172/JCI112308>) and to calculate estimates of input coefficients (volume of distribution, short half life, long half life, and fraction attributed to short half life) as described by Van Cauter. Although the generated coefficients are specific to insulin secretion, the two-compartment secretion model used here is useful for certain applications beyond insulin.
License: GPL (>= 3)
Imports: glue, lifecycle, npreg, rlang
Encoding: UTF-8
URL: https://github.com/kstier/isr.deconv
BugReports: https://github.com/kstier/isr.deconv/issues
NeedsCompilation: no
Packaged: 2025-11-02 18:59:35 UTC; kenstier
Author: Ken Stier [aut, cre, cph]
Maintainer: Ken Stier <kennethstier99@gmail.com>
Repository: CRAN
Date/Publication: 2025-11-05 20:20:06 UTC

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New package EpidigiR with initial version 0.1.2
Package: EpidigiR
Title: Digital Epidemiological Analysis and Visualization Tools
Version: 0.1.2
Description: Integrates methods for epidemiological analysis, modeling, and visualization, including functions for summary statistics, SIR (Susceptible-Infectious-Recovered) modeling, DALY (Disability-Adjusted Life Years) estimation, age standardization, diagnostic test evaluation, NLP (Natural Language Processing) keyword extraction, clinical trial power analysis, survival analysis, SNP (Single Nucleotide Polymorphism) association, and machine learning methods such as logistic regression, k-means clustering, Random Forest, and Support Vector Machine (SVM). Includes datasets for prevalence estimation, SIR modeling, genomic analysis, clinical trials, DALY, diagnostic tests, and survival analysis. Methods are based on Gelman et al. (2013) <doi:10.1201/b16018> and Wickham et al. (2019, ISBN:9781492052040>.
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-US
LazyData: true
Depends: R (>= 4.0.0)
Imports: deSolve, sp, tm, glmnet, caret, survival
Suggests: kernlab, randomForest, stats, knitr, rmarkdown, quarto, usethis, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Author: Esther Atsabina Wanjala [aut, cre]
Maintainer: Esther Atsabina Wanjala <digitalepidemiologist23@gmail.com>
Packaged: 2025-11-03 07:06:11 UTC; atsab
Repository: CRAN
Date/Publication: 2025-11-05 20:30:13 UTC

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Package cocktailApp updated to version 0.2.4 with previous version 0.2.3 dated 2023-07-19

Title: 'shiny' App to Discover Cocktails
Description: A 'shiny' app to discover cocktails. The app allows one to search for cocktails by ingredient, filter on rating, and number of ingredients. The package also contains data with the ingredients of nearly 26 thousand cocktails scraped from the web.
Author: Steven E. Pav [aut, cre]
Maintainer: Steven E. Pav <shabbychef@gmail.com>

Diff between cocktailApp versions 0.2.3 dated 2023-07-19 and 0.2.4 dated 2025-11-05

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New package cgmguru with initial version 0.1.0
Package: cgmguru
Title: Advanced Continuous Glucose Monitoring Analysis with High-Performance C++ Backend
Version: 0.1.0
Maintainer: Sang Ho Park <shstat1729@gmail.com>
Description: Tools for advanced analysis of continuous glucose monitoring (CGM) time-series, implementing GRID (Glucose Rate Increase Detector) and GRID-based algorithms for postprandial peak detection, and detection of hypoglycemic and hyperglycemic episodes (Levels 1/2/Extended) aligned with international consensus CGM metrics. Core algorithms are implemented in optimized C++ using 'Rcpp' to provide accurate and fast analysis on large datasets.
License: MIT + file LICENSE
Encoding: UTF-8
LinkingTo: Rcpp
Imports: Rcpp
Suggests: testthat (>= 3.0.0), knitr, rmarkdown, iglu, dplyr, covr, ggplot2, microbenchmark
VignetteBuilder: knitr
URL: https://github.com/shstat1729/cgmguru
BugReports: https://github.com/shstat1729/cgmguru/issues
NeedsCompilation: yes
Packaged: 2025-11-03 08:00:18 UTC; bagsangho
Author: Sang Ho Park [aut, cre], Rosa Oh [aut, ctb], Sang-Man Jin [aut, ctb]
Repository: CRAN
Date/Publication: 2025-11-05 20:30:07 UTC

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New package aclhs with initial version 1.0.1
Package: aclhs
Title: Autocorrelated Conditioned Latin Hypercube Sampling
Version: 1.0.1
Description: Implementation of the autocorrelated conditioned Latin Hypercube Sampling (acLHS) algorithm for 1D (time-series) and 2D (spatial) data. The acLHS algorithm is an extension of the conditioned Latin Hypercube Sampling (cLHS) algorithm that allows sampled data to have similar correlative and statistical features of the original data. Only a properly formatted dataframe needs to be provided to yield subsample indices from the primary function. For more details about the cLHS algorithm, see Minasny and McBratney (2006), <doi:10.1016/j.cageo.2005.12.009>. For acLHS, see Le and Vargas (2024) <doi:10.1016/j.cageo.2024.105539>.
License: MIT + file LICENSE
URL: https://github.com/vargaslab/acLHS
BugReports: https://github.com/vargaslab/acLHS/issues
Depends: R (>= 3.5)
Imports: DEoptim (>= 2.2.8), geoR (>= 1.9.6), graphics (>= 4.5.1), stats (>= 4.5.1), utils (>= 4.5.1)
Suggests: testthat (>= 3.0.0)
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2025-11-01 01:20:15 UTC; Gabe
Author: Van Huong Le [aut, ctb] , Rodrigo Vargas [aut] , Gabriel Laboy [ctb, cre]
Maintainer: Gabriel Laboy <glaboy1@asu.edu>
Repository: CRAN
Date/Publication: 2025-11-05 20:10:02 UTC

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New package PublicationBiasBenchmark with initial version 0.1.0
Package: PublicationBiasBenchmark
Title: Benchmark for Publication Bias Correction Methods
Version: 0.1.0
Maintainer: Frantisek Bartos <f.bartos96@gmail.com>
Description: Implements a unified interface for benchmarking meta-analytic publication bias correction methods through simulation studies (see Bartoš et al., 2022, <doi:10.48550/arXiv.2510.19489>). It provides 1) predefined data-generating mechanisms from the literature, 2) functions for running meta-analytic methods on simulated data, 3) pre-simulated datasets and pre-computed results for reproducible benchmarks, 4) tools for visualizing and comparing method performance.
License: GPL-3
Encoding: UTF-8
Depends: R (>= 3.5.0)
Imports: stats, metafor, osfr, MASS, numDeriv, pwr, sandwich, clubSandwich, lmtest, puniform, Rdpack
Suggests: RoBMA, testthat (>= 3.0.0), rmarkdown, knitr, kableExtra, DT, ggplot2, scales, ggdist, rprojroot, desc
URL: https://github.com/FBartos/PublicationBiasBenchmark, https://fbartos.github.io/PublicationBiasBenchmark/
BugReports: https://github.com/FBartos/PublicationBiasBenchmark/issues
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2025-11-01 14:51:06 UTC; fbart
Author: Frantisek Bartos [aut, cre] , Samuel Pawel [aut] , Bjoern S. Siepe [aut]
Repository: CRAN
Date/Publication: 2025-11-05 20:00:02 UTC

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Package MRTAnalysis updated to version 0.3.1 with previous version 0.3.0 dated 2025-09-09

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>

Diff between MRTAnalysis versions 0.3.0 dated 2025-09-09 and 0.3.1 dated 2025-11-05

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Package DSOpal updated to version 1.5.0 with previous version 1.4.1 dated 2025-07-25

Title: 'DataSHIELD' Implementation for 'Opal'
Description: 'DataSHIELD' is an infrastructure and series of R packages that enables the remote and 'non-disclosive' analysis of sensitive research data. This package is the 'DataSHIELD' interface implementation for 'Opal', which is the data integration application for biobanks by 'OBiBa'. Participant data, once collected from any data source, must be integrated and stored in a central data repository under a uniform model. 'Opal' is such a central repository. It can import, process, validate, query, analyze, report, and export data. 'Opal' is the reference implementation of the 'DataSHIELD' infrastructure.
Author: Yannick Marcon [aut, cre] , Becca Wilson [ctb] , OBiBa group [cph]
Maintainer: Yannick Marcon <yannick.marcon@obiba.org>

Diff between DSOpal versions 1.4.1 dated 2025-07-25 and 1.5.0 dated 2025-11-05

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Package phsopendata updated to version 1.0.1 with previous version 1.0.0 dated 2025-09-01

Title: Extract from the Scottish Health and Social Care Open Data Platform
Description: Extract and interact with data from the Scottish Health and Social Care Open Data platform <https://www.opendata.nhs.scot>.
Author: Public Health Scotland [cph], Csilla Scharle [aut, cre], James Hayes [aut] , David Aikman [aut], Ross Hull [aut]
Maintainer: Csilla Scharle <csilla.scharle2@phs.scot>

Diff between phsopendata versions 1.0.0 dated 2025-09-01 and 1.0.1 dated 2025-11-05

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Package randomForestSRC updated to version 3.4.4 with previous version 3.4.3 dated 2025-10-10

Title: Fast Unified Random Forests for Survival, Regression, and Classification (RF-SRC)
Description: Fast OpenMP parallel computing of Breiman's random forests for univariate, multivariate, unsupervised, survival, competing risks, class imbalanced classification and quantile regression. New Mahalanobis splitting for correlated outcomes. Extreme random forests and randomized splitting. Suite of imputation methods for missing data. Fast random forests using subsampling. Confidence regions and standard errors for variable importance. New improved holdout importance. Case-specific importance. Minimal depth variable importance. Visualize trees on your Safari or Google Chrome browser. Anonymous random forests for data privacy.
Author: Hemant Ishwaran [aut], Udaya B. Kogalur [aut, cre]
Maintainer: Udaya B. Kogalur <ubk@kogalur.com>

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Package PubChemR updated to version 2.1.7 with previous version 2.1.6 dated 2025-10-30

Title: Interface to the 'PubChem' Database for Chemical Data Retrieval
Description: Provides an interface to the 'PubChem' database via the PUG REST <https://pubchem.ncbi.nlm.nih.gov/docs/pug-rest> and PUG View <https://pubchem.ncbi.nlm.nih.gov/docs/pug-view> services. This package allows users to automatically access chemical and biological data from 'PubChem', including compounds, substances, assays, and various other data types. Functions are available to retrieve data in different formats, perform searches, and access detailed annotations.
Author: Selcuk Korkmaz [aut, cre] , Bilge Eren Yamasan [aut] , Dincer Goksuluk [aut]
Maintainer: Selcuk Korkmaz <selcukorkmaz@gmail.com>

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Package opalr updated to version 3.5.0 with previous version 3.4.2 dated 2024-09-18

Title: 'Opal' Data Repository Client and 'DataSHIELD' Utils
Description: Data integration Web application for biobanks by 'OBiBa'. 'Opal' is the core database application for biobanks. Participant data, once collected from any data source, must be integrated and stored in a central data repository under a uniform model. 'Opal' is such a central repository. It can import, process, validate, query, analyze, report, and export data. 'Opal' is typically used in a research center to analyze the data acquired at assessment centres. Its ultimate purpose is to achieve seamless data-sharing among biobanks. This 'Opal' client allows to interact with 'Opal' web services and to perform operations on the R server side. 'DataSHIELD' administration tools are also provided.
Author: Yannick Marcon [aut, cre] , Amadou Gaye [ctb] , OBiBa group [cph]
Maintainer: Yannick Marcon <yannick.marcon@obiba.org>

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Package mirai updated to version 2.5.2 with previous version 2.5.1 dated 2025-10-06

Title: Minimalist Async Evaluation Framework for R
Description: Designed for simplicity, a 'mirai' evaluates an R expression asynchronously, locally or distributed over the network. Built on 'nanonext' and 'NNG' for modern networking and concurrency, scales efficiently to millions of tasks over thousands of persistent parallel processes. Provides optimal scheduling over fast 'IPC', TCP, and TLS connections, integrating with SSH or cluster managers. Implements event-driven promises for reactive programming, and supports custom serialization for cross-language data types.
Author: Charlie Gao [aut, cre] , Joe Cheng [ctb], Posit Software, PBC [cph, fnd] , Hibiki AI Limited [cph]
Maintainer: Charlie Gao <charlie.gao@posit.co>

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Package dataverse updated to version 0.3.16 with previous version 0.3.15 dated 2025-05-20

Title: Client for Dataverse 4+ Repositories
Description: Provides access to Dataverse APIs <https://dataverse.org/> (versions 4-5), enabling data search, retrieval, and deposit. For Dataverse versions <= 3.0, use the archived 'dvn' package <https://cran.r-project.org/package=dvn>.
Author: Shiro Kuriwaki [aut, cre] , Will Beasley [aut] , Thomas J. Leeper [aut] , Philip Durbin [aut] , Sebastian Karcher [aut] , Jan Kanis [ctb], Edward Jee [ctb], Johannes Gruber [ctb] , Martin Morgan [ctb] , Konrad Oberwimmer [ctb]
Maintainer: Shiro Kuriwaki <shirokuriwaki@gmail.com>

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Package candisc updated to version 1.0.0 with previous version 0.9.0 dated 2024-05-06

Title: Visualizing Generalized Canonical Discriminant and Canonical Correlation Analysis
Description: Functions for computing and visualizing generalized canonical discriminant analyses and canonical correlation analysis for a multivariate linear model. Traditional canonical discriminant analysis is restricted to a one-way 'MANOVA' design and is equivalent to canonical correlation analysis between a set of quantitative response variables and a set of dummy variables coded from the factor variable. The 'candisc' package generalizes this to higher-way 'MANOVA' designs for all factors in a multivariate linear model, computing canonical scores and vectors for each term. The graphic functions provide low-rank (1D, 2D, 3D) visualizations of terms in an 'mlm' via the 'plot.candisc' and 'heplot.candisc' methods. Related plots are now provided for canonical correlation analysis when all predictors are quantitative. Methods for linear discriminant analysis are now included.
Author: Michael Friendly [aut, cre] , John Fox [aut]
Maintainer: Michael Friendly <friendly@yorku.ca>

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Package GHRexplore updated to version 0.2.1 with previous version 0.2.0 dated 2025-09-05

Title: Exploratory Analysis of Temporal and Spatio-Temporal Health Data
Description: A collection of commonly used visualizations of temporal and spatio-temporal health data including case counts, incidence rates, and covariates. The available plot types include time series, heatmaps, seasonality plots, maps and more. The package supports standard data transformations such as temporal and spatial aggregations, while offering extensive customization options for the resulting figures.
Author: Carles Mila [aut, cre] , Giovenale Moirano [aut] , Anna B. Kawiecki [aut] , Rachel Lowe [aut, cph]
Maintainer: Carles Mila <carles.milagarcia@bsc.es>

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Package bWGR updated to version 2.2.15 with previous version 2.2.14 dated 2025-10-29

Title: Bayesian Whole-Genome Regression
Description: Whole-genome regression methods on Bayesian framework fitted via EM or Gibbs sampling, single step (<doi:10.1534/g3.119.400728>), univariate and multivariate (<doi:10.1186/s12711-022-00730-w>, <doi:10.1093/genetics/iyae179>), with optional kernel term and sampling techniques (<doi:10.1186/s12859-017-1582-3>).
Author: Alencar Xavier [aut, cre] , William Muir [aut], David Habier [aut], Kyle Kocak [aut], Shizhong Xu [aut], Katy Rainey [aut]
Maintainer: Alencar Xavier <alenxav@gmail.com>

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Package terra updated to version 1.8-80 with previous version 1.8-70 dated 2025-09-26

Title: Spatial Data Analysis
Description: Methods for spatial data analysis with vector (points, lines, polygons) and raster (grid) data. Methods for vector data include geometric operations such as intersect and buffer. Raster methods include local, focal, global, zonal and geometric operations. The predict and interpolate methods facilitate the use of regression type (interpolation, machine learning) models for spatial prediction, including with satellite remote sensing data. Processing of very large files is supported. See the manual and tutorials on <https://rspatial.org/> to get started. 'terra' replaces the 'raster' package ('terra' can do more, and it is faster and easier to use).
Author: Robert J. Hijmans [cre, aut] , Marcia Barbosa [ctb] , Roger Bivand [ctb] , Andrew Brown [ctb] , Michael Chirico [ctb] , Emanuele Cordano [ctb] , Krzysztof Dyba [ctb] , Edzer Pebesma [ctb] , Barry Rowlingson [ctb] , Michael D. Sumner [ctb]
Maintainer: Robert J. Hijmans <r.hijmans@gmail.com>

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More information about terra at CRAN
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Package odeGUTS updated to version 1.1.0 with previous version 1.0.3 dated 2024-10-04

Title: Solve ODE for GUTS-RED-SD and GUTS-RED-IT Using Compiled Code
Description: Allows performing forwards prediction for the General Unified Threshold model of Survival using compiled ode code. This package was created to avoid dependency with the 'morse' package that requires the installation of 'JAGS'. This package is based on functions from the 'morse' package v3.3.1: Virgile Baudrot, Sandrine Charles, Marie Laure Delignette-Muller, Wandrille Duchemin, Benoit Goussen, Nils Kehrein, Guillaume Kon-Kam-King, Christelle Lopes, Philippe Ruiz, Alexander Singer and Philippe Veber (2021) <https://CRAN.R-project.org/package=morse>.
Author: Benoit Goussen [aut] , Carlo Romoli [cre]
Maintainer: Carlo Romoli <carlo.romoli@ibacon.com>

Diff between odeGUTS versions 1.0.3 dated 2024-10-04 and 1.1.0 dated 2025-11-05

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Package mwcsr updated to version 0.1.10 with previous version 0.1.9 dated 2024-09-09

Title: Solvers for Maximum Weight Connected Subgraph Problem and Its Variants
Description: Algorithms for solving various Maximum Weight Connected Subgraph Problems, including variants with budget constraints, cardinality constraints, weighted edges and signals. The package represents an R interface to high-efficient solvers based on relax-and-cut approach (Álvarez-Miranda E., Sinnl M. (2017) <doi:10.1016/j.cor.2017.05.015>) mixed-integer programming (Loboda A., Artyomov M., and Sergushichev A. (2016) <doi:10.1007/978-3-319-43681-4_17>) and simulated annealing.
Author: Alexander Loboda [aut, cre], Nikolay Poperechnyi [aut], Eduardo Alvarez-Miranda [aut], Markus Sinnl [aut], Alexey Sergushichev [aut], Paul Hosler Jr. [cph] , www.hamcrest.org [cph] , Barak Naveh and Contributors [cph] , The Apache Software Foundation [...truncated...]
Maintainer: Alexander Loboda <aleks.loboda@gmail.com>

Diff between mwcsr versions 0.1.9 dated 2024-09-09 and 0.1.10 dated 2025-11-05

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Package MultiATSM updated to version 1.5.1 with previous version 1.5.0 dated 2025-10-23

Title: Multicountry Term Structure of Interest Rates Models
Description: Package for estimating, analyzing, and forecasting multi-country macro-finance affine term structure models (ATSMs). All setups build on the single-country unspanned macroeconomic risk framework from Joslin, Priebsch, and Singleton (2014, JF) <doi:10.1111/jofi.12131>. Multicountry extensions by Jotikasthira, Le, and Lundblad (2015, JFE) <doi:10.1016/j.jfineco.2014.09.004>, Candelon and Moura (2023, EM) <doi:10.1016/j.econmod.2023.106453>, and Candelon and Moura (2024, JFEC) <doi:10.1093/jjfinec/nbae008> are also available. The package also provides tools for bias correction as in Bauer Rudebusch and Wu (2012, JBES) <doi:10.1080/07350015.2012.693855>, bootstrap analysis, and several graphical/numerical outputs.
Author: Rubens Moura [aut, cre]
Maintainer: Rubens Moura <rubens.gtmoura@gmail.com>

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Package mas updated to version 0.4 with previous version 0.3 dated 2024-04-08

Title: Multi-Population Association Studies
Description: Mixed model-based genome-wide association analysis that accommodate population membership information, variance adjustment, and correlated responses.
Author: Alencar Xavier [aut, cre] , Shizhong Xu [aut, ctb]
Maintainer: Alencar Xavier <alenxav@gmail.com>

Diff between mas versions 0.3 dated 2024-04-08 and 0.4 dated 2025-11-05

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Package nuggets updated to version 2.1.0 with previous version 2.0.2 dated 2025-10-30

Title: Extensible Framework for Data Pattern Exploration
Description: A framework for systematic exploration of association rules (Agrawal et al., 1994, <https://www.vldb.org/conf/1994/P487.PDF>), contrast patterns (Chen, 2022, <doi:10.48550/arXiv.2209.13556>), emerging patterns (Dong et al., 1999, <doi:10.1145/312129.312191>), subgroup discovery (Atzmueller, 2015, <doi:10.1002/widm.1144>), and conditional correlations (Hájek, 1978, <doi:10.1007/978-3-642-66943-9>). User-defined functions may also be supplied to guide custom pattern searches. Supports both crisp (Boolean) and fuzzy data. Generates candidate conditions expressed as elementary conjunctions, evaluates them on a dataset, and inspects the induced sub-data for statistical, logical, or structural properties such as associations, correlations, or contrasts. Includes methods for visualization of logical structures and supports interactive exploration through integrated Shiny applications.
Author: Michal Burda [aut, cre]
Maintainer: Michal Burda <michal.burda@osu.cz>

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Package hmmTMB updated to version 1.1.2 with previous version 1.1.1 dated 2025-09-11

Title: Fit Hidden Markov Models using Template Model Builder
Description: Fitting hidden Markov models using automatic differentiation and Laplace approximation, allowing for fast inference and flexible covariate effects (including random effects and smoothing splines) on model parameters. The package is described by Michelot (2025) <doi:10.18637/jss.v114.i05>.
Author: Theo Michelot [aut, cre], Richard Glennie [aut, ctb]
Maintainer: Theo Michelot <theo.michelot@dal.ca>

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Package DER updated to version 1.2 with previous version 1.1 dated 2025-05-28

Title: Income Polarization Index
Description: The DER (or PaF) income polarization index as proposed by Duclos J. Y., Esteban, J. and Ray D. (2004). "Polarization: concepts, measurement, estimation". Econometrica, 72(6): 1737--1772. <doi:10.1111/j.1468-0262.2004.00552.x>. The index may be computed for a single or for a range of values of the alpha-parameter. Bootstrapping is also available.
Author: Michail Tsagris [aut, cre], Christos Adam [aut]
Maintainer: Michail Tsagris <mtsagris@uoc.gr>

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Package MLwrap updated to version 0.2.2 with previous version 0.2.1 dated 2025-10-21

Title: Machine Learning Modelling for Everyone
Description: A minimal library specifically designed to make the estimation of Machine Learning (ML) techniques as easy and accessible as possible, particularly within the framework of the Knowledge Discovery in Databases (KDD) process in data mining. The package provides essential tools to structure and execute each stage of a predictive or classification modeling workflow, aligning closely with the fundamental steps of the KDD methodology, from data selection and preparation, through model building and tuning, to the interpretation and evaluation of results using Sensitivity Analysis. The 'MLwrap' workflow is organized into four core steps; preprocessing(), build_model(), fine_tuning(), and sensitivity_analysis(). These steps correspond, respectively, to data preparation and transformation, model construction, hyperparameter optimization, and sensitivity analysis. The user can access comprehensive model evaluation results including fit assessment metrics, plots, predictions, and performance diagn [...truncated...]
Author: Javier Martinez Garcia [aut] , Juan Jose Montano Moreno [ctb] , Albert Sese [cre, ctb]
Maintainer: Albert Sese <albert.sese@uib.es>

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Package comets updated to version 0.2-2 with previous version 0.2-1 dated 2025-09-10

Title: Covariance Measure Tests for Conditional Independence
Description: Covariance measure tests for conditional independence testing against conditional covariance and nonlinear conditional mean alternatives. The package implements versions of the generalised covariance measure test (Shah and Peters, 2020, <doi:10.1214/19-aos1857>) and projected covariance measure test (Lundborg et al., 2023, <doi:10.1214/24-AOS2447>). The tram-GCM test, for censored responses, is implemented including the Cox model and survival forests (Kook et al., 2024, <doi:10.1080/01621459.2024.2395588>). Application examples to variable significance testing and modality selection can be found in Kook and Lundborg (2024, <doi:10.1093/bib/bbae475>).
Author: Lucas Kook [aut, cre] , Anton Rask Lundborg [ctb]
Maintainer: Lucas Kook <lucasheinrich.kook@gmail.com>

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Package bgev updated to version 0.2 with previous version 0.1 dated 2024-03-14

Title: Bimodal GEV Distribution with Location Parameter
Description: Density, distribution function, quantile function random generation and estimation of bimodal GEV distribution given in Otiniano et al. (2023) <doi:10.1007/s10651-023-00566-7>. This new generalization of the well-known GEV (Generalized Extreme Value) distribution is useful for modeling heterogeneous bimodal data from different areas.
Author: Cira Otiniano Author [aut], Yasmin Lirio Author [aut], Thiago Sousa Developer [cre]
Maintainer: Thiago Sousa Developer <thiagoestatistico@gmail.com>

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Package tempdisagg updated to version 1.2.0 with previous version 1.1.1 dated 2023-08-08

Title: Methods for Temporal Disaggregation and Interpolation of Time Series
Description: Temporal disaggregation methods are used to disaggregate and interpolate a low frequency time series to a higher frequency series, where either the sum, the mean, the first or the last value of the resulting high frequency series is consistent with the low frequency series. Temporal disaggregation can be performed with or without one or more high frequency indicator series. Contains the methods of Chow-Lin, Santos-Silva-Cardoso, Fernandez, Litterman, Denton and Denton-Cholette, summarized in Sax and Steiner (2013) <doi:10.32614/RJ-2013-028>. Supports most R time series classes.
Author: Christoph Sax [aut, cre] , Peter Steiner [aut], Tommaso Di Fonzo [ctb], Nelson Stevens [ctb], Tobias Schieferdecker [ctb]
Maintainer: Christoph Sax <christoph.sax@gmail.com>

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Package FARS updated to version 0.7.1 with previous version 0.7.0 dated 2025-10-26

Title: Factor-Augmented Regression Scenarios
Description: Provides a comprehensive framework in R for modeling and forecasting economic scenarios based on multi-level dynamic factor model. The package enables users to: (i) extract global and group-specific factors using a flexible multi-level factor structure; (ii) compute asymptotically valid confidence regions for the estimated factors, accounting for uncertainty in the factor loadings; (iii) obtain estimates of the parameters of the factor-augmented quantile regressions together with their standard deviations; (iv) recover full predictive conditional densities from estimated quantiles; (v) obtain risk measures based on extreme quantiles of the conditional densities; (vi) estimate the conditional density and the corresponding extreme quantiles when the factors are stressed.
Author: Gian Pietro Bellocca [aut, cre], Ignacio Garron [aut], Vladimir Rodriguez-Caballero [aut], Esther Ruiz [aut]
Maintainer: Gian Pietro Bellocca <gbellocc@est-econ.uc3m.es>

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Package BayesChange updated to version 2.1.2 with previous version 2.1.1 dated 2025-10-17

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

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