Tue, 08 Jul 2025

Package OmopViewer updated to version 0.4.0 with previous version 0.3.0 dated 2025-04-15

Title: Visualise OMOP Results using 'shiny' Applications
Description: Visualise results obtained from analysing data mapped to the Observational Medical Outcomes Partnership (OMOP) common data model using 'shiny' applications.
Author: Marti Catala [aut, cre] , Yuchen Guo [aut] , Edward Burn [ctb] , Nuria Mercade-Besora [ctb] , Elin Rowlands [ctb] , Cecilia Campanile [ctb]
Maintainer: Marti Catala <marti.catalasabate@ndorms.ox.ac.uk>

Diff between OmopViewer versions 0.3.0 dated 2025-04-15 and 0.4.0 dated 2025-07-08

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Package mixedBayes updated to version 0.1.10 with previous version 0.1.9 dated 2025-06-27

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

Diff between mixedBayes versions 0.1.9 dated 2025-06-27 and 0.1.10 dated 2025-07-08

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Package stopp updated to version 1.0.0 with previous version 0.2.4 dated 2024-06-04

Title: Spatio-Temporal Point Pattern Methods, Model Fitting, Diagnostics, Simulation, Local Tests
Description: Toolbox for different kinds of spatio-temporal analyses to be performed on observed point patterns, following the growing stream of literature on point process theory. This R package implements functions to perform different kinds of analyses on point processes, proposed in the papers (Siino, Adelfio, and Mateu 2018<doi:10.1007/s00477-018-1579-0>; Siino et al. 2018<doi:10.1002/env.2463>; Adelfio et al. 2020<doi:10.1007/s00477-019-01748-1>; D’Angelo, Adelfio, and Mateu 2021<doi:10.1016/j.spasta.2021.100534>; D’Angelo, Adelfio, and Mateu 2022<doi:10.1007/s00362-022-01338-4>; D’Angelo, Adelfio, and Mateu 2023<doi:10.1016/j.csda.2022.107679>). The main topics include modeling, statistical inference, and simulation issues on spatio-temporal point processes on Euclidean space and linear networks. Version 1.0.0 has been updated for accompanying the journal publication D Angelo and Adelfio 2025 <doi:10.18637/jss.v113.i10>.
Author: Nicoletta D'Angelo [aut, cre] , Giada Adelfio [aut]
Maintainer: Nicoletta D'Angelo <nicoletta.dangelo@unipa.it>

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Package rts2 updated to version 0.8.3 with previous version 0.8.0 dated 2025-06-10

Title: Real-Time Disease Surveillance
Description: Supports modelling real-time case data to facilitate the real-time surveillance of infectious diseases and other point phenomena. The package provides automated computational grid generation over an area of interest with methods to map covariates between geographies, model fitting including spatially aggregated case counts, and predictions and visualisation. Both Bayesian and maximum likelihood methods are provided. Log-Gaussian Cox Processes are described by Diggle et al. (2013) <doi:10.1214/13-STS441> and we provide both the low-rank approximation for Gaussian processes described by Solin and Särkkä (2020) <doi:10.1007/s11222-019-09886-w> and Riutort-Mayol et al (2023) <doi:10.1007/s11222-022-10167-2> and the nearest neighbour Gaussian process described by Datta et al (2016) <doi:10.1080/01621459.2015.1044091>. 'cmdstanr' can be downloaded at <https://mc-stan.org/cmdstanr/>.
Author: Sam Watson [aut, cre]
Maintainer: Sam Watson <s.i.watson@bham.ac.uk>

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Package projpred updated to version 2.9.0 with previous version 2.8.0 dated 2023-12-14

Title: Projection Predictive Feature Selection
Description: Performs projection predictive feature selection for generalized linear models (Piironen, Paasiniemi, and Vehtari, 2020, <doi:10.1214/20-EJS1711>) with or without multilevel or additive terms (Catalina, Bürkner, and Vehtari, 2022, <https://proceedings.mlr.press/v151/catalina22a.html>), for some ordinal and nominal regression models (Weber, Glass, and Vehtari, 2025, <doi:10.1007/s00180-024-01506-0>), and for many other regression models (using the latent projection by Catalina, Bürkner, and Vehtari, 2021, <doi:10.48550/arXiv.2109.04702>, which can also be applied to most of the former models). The package is compatible with the 'rstanarm' and 'brms' packages, but other reference models can also be used. See the vignettes and the documentation for more information and examples.
Author: Juho Piironen [aut], Markus Paasiniemi [aut], Alejandro Catalina [aut], Frank Weber [aut], Osvaldo Martin [cre, aut], Aki Vehtari [aut], Jonah Gabry [ctb], Marco Colombo [ctb], Paul-Christian Buerkner [ctb], Hamada S. Badr [ctb], Brian Sullivan [ctb], [...truncated...]
Maintainer: Osvaldo Martin <aloctavodia@gmail.com>

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Package kernelshap updated to version 0.8.0 with previous version 0.7.0 dated 2024-08-17

Title: Kernel SHAP
Description: Efficient implementation of Kernel SHAP (Lundberg and Lee, 2017, <doi:10.48550/arXiv.1705.07874>) permutation SHAP, and additive SHAP for model interpretability. For Kernel SHAP and permutation SHAP, if the number of features is too large for exact calculations, the algorithms iterate until the SHAP values are sufficiently precise in terms of their standard errors. The package integrates smoothly with meta-learning packages such as 'tidymodels', 'caret' or 'mlr3'. It supports multi-output models, case weights, and parallel computations. Visualizations can be done using the R package 'shapviz'.
Author: Michael Mayer [aut, cre] , David Watson [aut] , Przemyslaw Biecek [ctb]
Maintainer: Michael Mayer <mayermichael79@gmail.com>

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Package hakaiApi updated to version 1.0.4 with previous version 1.0.3 dated 2025-05-27

Title: Authenticated HTTP Request Client for the 'Hakai' API
Description: Initializes a class that obtains API credentials and provides a method to use those credentials to make GET requests to the 'Hakai' API server. Usage instructions are documented at <https://hakaiinstitute.github.io/hakai-api/>.
Author: Sam Albers [aut, cre], Taylor Denouden [aut], Brett Johnson [aut], Nate Rosenstock [ctb], Chris Davis [ctb], Hakai Institute [cph]
Maintainer: Sam Albers <sam.albers@hakai.org>

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Package L1pack updated to version 0.60 with previous version 0.52 dated 2025-03-18

Title: Routines for L1 Estimation
Description: L1 estimation for linear regression using Barrodale and Roberts' method <doi:10.1145/355616.361024> and the EM algorithm <doi:10.1023/A:1020759012226>. Estimation of mean and covariance matrix using the multivariate Laplace distribution, density, distribution function, quantile function and random number generation for univariate and multivariate Laplace distribution <doi:10.1080/03610929808832115>. Implementation of Naik and Plungpongpun <doi:10.1007/0-8176-4487-3_7> for the Generalized spatial median estimator is included.
Author: Felipe Osorio [aut, cre] , Tymoteusz Wolodzko [aut]
Maintainer: Felipe Osorio <faosorios.stat@gmail.com>

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Package ggpmisc updated to version 0.6.2 with previous version 0.6.1 dated 2024-11-14

Title: Miscellaneous Extensions to 'ggplot2'
Description: Extensions to 'ggplot2' respecting the grammar of graphics paradigm. Statistics: locate and tag peaks and valleys; label plot with the equation of a fitted polynomial or other types of models including major axis, quantile and robust and resistant regression. Labels for P-value, R^2 or adjusted R^2 or information criteria for fitted models; parametric and non-parametric correlation; label with ANOVA table for fitted models; label with summary table for fitted models; annotations for multiple comparisons with adjusted P-values. Model fit classes for which suitable methods are provided by package 'broom' and 'broom.mixed' are supported as well as user-defined wrappers on model fit functions. Scales and stats to build volcano and quadrant plots based on outcomes, fold changes, p-values and false discovery rates.
Author: Pedro J. Aphalo [aut, cre] , Kamil Slowikowski [ctb] , Samer Mouksassi [ctb]
Maintainer: Pedro J. Aphalo <pedro.aphalo@helsinki.fi>

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Package fwb updated to version 0.5.0 with previous version 0.4.0 dated 2025-06-11

Title: Fractional Weighted Bootstrap
Description: An implementation of the fractional weighted bootstrap to be used as a drop-in for functions in the 'boot' package. The fractional weighted bootstrap (also known as the Bayesian bootstrap) involves drawing weights randomly that are applied to the data rather than resampling units from the data. See Xu et al. (2020) <doi:10.1080/00031305.2020.1731599> for details.
Author: Noah Greifer [aut, cre]
Maintainer: Noah Greifer <noah.greifer@gmail.com>

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Package glmmrBase updated to version 1.0.1 with previous version 1.0.0 dated 2025-04-01

Title: Generalised Linear Mixed Models in R
Description: Specification, analysis, simulation, and fitting of generalised linear mixed models. Includes Markov Chain Monte Carlo Maximum likelihood and Laplace approximation model fitting for a range of models, non-linear fixed effect specifications, a wide range of flexible covariance functions that can be combined arbitrarily, robust and bias-corrected standard error estimation, power calculation, data simulation, and more. See <https://samuel-watson.github.io/glmmr-web/> for a detailed manual.
Author: Sam Watson [aut, cre]
Maintainer: Sam Watson <S.I.Watson@bham.ac.uk>

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Package teal.logger updated to version 0.4.0 with previous version 0.3.2 dated 2025-02-14

Title: Logging Setup for the 'teal' Family of Packages
Description: Utilizing the 'logger' framework to record events within a package, specific to 'teal' family of packages. Supports logging namespaces, hierarchical logging, various log destinations, vectorization, and more.
Author: Dawid Kaledkowski [aut, cre], Konrad Pagacz [aut], F. Hoffmann-La Roche AG [cph, fnd]
Maintainer: Dawid Kaledkowski <dawid.kaledkowski@roche.com>

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Package lamW updated to version 2.2.5 with previous version 2.2.4 dated 2024-06-17

Title: Lambert-W Function
Description: Implements both real-valued branches of the Lambert-W function (Corless et al, 1996) <doi:10.1007/BF02124750> without the need for installing the entire GSL.
Author: Avraham Adler [aut, cph, cre]
Maintainer: Avraham Adler <Avraham.Adler@gmail.com>

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Package actuar updated to version 3.3-6 with previous version 3.3-5 dated 2025-01-09

Title: Actuarial Functions and Heavy Tailed Distributions
Description: Functions and data sets for actuarial science: modeling of loss distributions; risk theory and ruin theory; simulation of compound models, discrete mixtures and compound hierarchical models; credibility theory. Support for many additional probability distributions to model insurance loss size and frequency: 23 continuous heavy tailed distributions; the Poisson-inverse Gaussian discrete distribution; zero-truncated and zero-modified extensions of the standard discrete distributions. Support for phase-type distributions commonly used to compute ruin probabilities. Main reference: <doi:10.18637/jss.v025.i07>. Implementation of the Feller-Pareto family of distributions: <doi:10.18637/jss.v103.i06>.
Author: Vincent Goulet [cre, aut] , Sebastien Auclair [ctb], Christophe Dutang [aut] , Walter Garcia-Fontes [ctb], Nicholas Langevin [ctb], Xavier Milhaud [ctb], Tommy Ouellet [ctb], Alexandre Parent [ctb], Mathieu Pigeon [aut], Louis-Philippe Pouliot [ctb], [...truncated...]
Maintainer: Vincent Goulet <vincent.goulet@act.ulaval.ca>

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Package OpenRepGrid updated to version 0.1.18 with previous version 0.1.17 dated 2025-03-02

Title: Tools to Analyze Repertory Grid Data
Description: Analyze repertory grids, a qualitative-quantitative data collection technique devised by George A. Kelly in the 1950s. Today, grids are used across various domains ranging from clinical psychology to marketing. The package contains functions to quantitatively analyze and visualize repertory grid data (e.g. 'Fransella', 'Bell', & 'Bannister', 2004, ISBN: 978-0-470-09080-0). The package is part of the The package is part of the <https://openrepgrid.org/> project.
Author: Mark Heckmann [aut, cre, cph] , Alejandro Garcia Gutierrez [ctb], Diego Vitali [ctb]
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Package froggeR updated to version 0.5.0 with previous version 0.4.0 dated 2025-03-16

Title: Enhance 'Quarto' Project Workflows and Standards
Description: Streamlines 'Quarto' workflows by providing tools for consistent project setup and documentation. Enables portability through reusable metadata, automated project structure creation, and standardized templates. Features include enhanced project initialization, pre-formatted 'Quarto' documents, inclusion of 'Quarto' brand functionality, comprehensive data protection settings, custom styling, and structured documentation generation. Designed to improve efficiency and collaboration in R data science projects by reducing repetitive setup tasks while maintaining consistent formatting across multiple documents.
Author: Kyle Grealis [aut, cre]
Maintainer: Kyle Grealis <kyleGrealis@icloud.com>

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Package correlation updated to version 0.8.8 with previous version 0.8.7 dated 2025-03-03

Title: Methods for Correlation Analysis
Description: Lightweight package for computing different kinds of correlations, such as partial correlations, Bayesian correlations, multilevel correlations, polychoric correlations, biweight correlations, distance correlations and more. Part of the 'easystats' ecosystem. References: Makowski et al. (2020) <doi:10.21105/joss.02306>.
Author: Dominique Makowski [aut, inv] , Brenton M. Wiernik [aut, cre] , Indrajeet Patil [aut] , Daniel Luedecke [aut] , Mattan S. Ben-Shachar [aut] , Remi Theriault [aut] , Mark White [rev], Maximilian M. Rabe [rev]
Maintainer: Brenton M. Wiernik <brenton@wiernik.org>

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Package manydist updated to version 0.4.7 with previous version 0.4.5 dated 2025-07-02

Title: Unbiased Distances for Mixed-Type Data
Description: A comprehensive framework for calculating unbiased distances in datasets containing mixed-type variables (numerical and categorical). The package implements a general formulation that ensures multivariate additivity and commensurability, meaning that variables contribute equally to the overall distance regardless of their type, scale, or distribution. Supports multiple distance measures including Gower's distance, Euclidean distance, Manhattan distance, and various categorical variable distances such as simple matching, Eskin, occurrence frequency, and association-based distances. Provides tools for variable scaling (standard deviation, range, robust range, and principal component scaling), and handles both independent and association-based category dissimilarities. Implements methods to correct for biases that typically arise from different variable types, distributions, and number of categories. Particularly useful for cluster analysis, data visualization, and other distance-based me [...truncated...]
Author: Alfonso Iodice D'Enza [aut], Angelos Markos [aut, cre], Michel van de Velden [aut], Carlo Cavicchia [aut]
Maintainer: Angelos Markos <amarkos@gmail.com>

Diff between manydist versions 0.4.5 dated 2025-07-02 and 0.4.7 dated 2025-07-08

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Package EHRmuse updated to version 0.0.2.2 with previous version 0.0.2.1 dated 2025-01-28

Title: Multi-Cohort Selection Bias Correction using IPW and AIPW Methods
Description: Comprehensive toolkit for addressing selection bias in binary disease models across diverse non-probability samples, each with unique selection mechanisms. It utilizes Inverse Probability Weighting (IPW) and Augmented Inverse Probability Weighting (AIPW) methods to reduce selection bias effectively in multiple non-probability cohorts by integrating data from either individual-level or summary-level external sources. The package also provides a variety of variance estimation techniques. Please refer to Kundu et al. <doi:10.48550/arXiv.2412.00228>.
Author: Ritoban Kundu [aut], Michael Kleinsasser [cre]
Maintainer: Michael Kleinsasser <biostat-cran-manager@umich.edu>

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Package DPQ updated to version 0.6-0 with previous version 0.5-9 dated 2024-08-23

Title: Density, Probability, Quantile ('DPQ') Computations
Description: Computations for approximations and alternatives for the 'DPQ' (Density (pdf), Probability (cdf) and Quantile) functions for probability distributions in R. Primary focus is on (central and non-central) beta, gamma and related distributions such as the chi-squared, F, and t. -- For several distribution functions, provide functions implementing formulas from Johnson, Kotz, and Kemp (1992) <doi:10.1002/bimj.4710360207> and Johnson, Kotz, and Balakrishnan (1995) for discrete or continuous distributions respectively. This is for the use of researchers in these numerical approximation implementations, notably for my own use in order to improve standard R pbeta(), qgamma(), ..., etc: {'"dpq"'-functions}.
Author: Martin Maechler [aut, cre] , Morten Welinder [ctb] ), Wolfgang Viechtbauer [ctb] , 2002), Ross Ihaka [ctb] , Marius Hofert [ctb] , lssum), R-core [ctb] , R Foundation [cph]
Maintainer: Martin Maechler <maechler@stat.math.ethz.ch>

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Package dfidx updated to version 0.2-0 with previous version 0.1-2 dated 2025-06-08

Title: Indexed Data Frames
Description: Provides extended data frames, with a special data frame column which contains two indexes, with potentially a nesting structure.
Author: Yves Croissant [aut, cre]
Maintainer: Yves Croissant <yves.croissant@univ-reunion.fr>

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Package binaryRL updated to version 0.9.0 with previous version 0.8.9 dated 2025-06-15

Title: Reinforcement Learning Tools for Two-Alternative Forced Choice Tasks
Description: Tools for building reinforcement learning (RL) models specifically tailored for Two-Alternative Forced Choice (TAFC) tasks, commonly employed in psychological research. These models build upon the foundational principles of model-free reinforcement learning detailed in Sutton and Barto (2018) <ISBN:9780262039246>. The package allows for the intuitive definition of RL models using simple if-else statements. Our approach to constructing and evaluating these computational models is informed by the guidelines proposed in Wilson & Collins (2019) <doi:10.7554/eLife.49547>. Example datasets included with the package are sourced from the work of Mason et al. (2024) <doi:10.3758/s13423-023-02415-x>.
Author: YuKi [aut, cre]
Maintainer: YuKi <hmz1969a@gmail.com>

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Package whirl updated to version 0.3.0 with previous version 0.2.0 dated 2025-04-15

Title: Log Execution of Scripts
Description: Logging of scripts suitable for clinical trials using 'Quarto' to create nice human readable logs. 'whirl' enables execution of scripts in batch, while simultaneously creating logs for the execution of each script, and providing an overview summary log of the entire batch execution.
Author: Aksel Thomsen [aut, cre], Lovemore Gakava [aut], Cervan Girard [aut], Kristian Troejelsgaard [aut], Steffen Falgreen Larsen [aut], Vladimir Obucina [aut], Michael Svingel [aut], Skander Mulder [aut], Novo Nordisk A/S [cph]
Maintainer: Aksel Thomsen <oath@novonordisk.com>

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Package vecmatch updated to version 1.2.0 with previous version 1.1.0 dated 2025-04-24

Title: Generalized Propensity Score Estimation and Matching for Multiple Groups
Description: Implements the Vector Matching algorithm to match multiple treatment groups based on previously estimated generalized propensity scores. The package includes tools for visualizing initial confounder imbalances, estimating treatment assignment probabilities using various methods, defining the common support region, performing matching across multiple groups, and evaluating matching quality. For more details, see Lopez and Gutman (2017) <doi:10.1214/17-STS612>.
Author: Mateusz Kolek [aut, cre, cph]
Maintainer: Mateusz Kolek <mati.kolek13@gmail.com>

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Package Epi updated to version 2.60 with previous version 2.59 dated 2025-01-13

Title: Statistical Analysis in Epidemiology
Description: Functions for demographic and epidemiological analysis in the Lexis diagram, i.e. register and cohort follow-up data. In particular representation, manipulation, rate estimation and simulation for multistate data - the Lexis suite of functions, which includes interfaces to 'mstate', 'etm' and 'cmprsk' packages. Contains functions for Age-Period-Cohort and Lee-Carter modeling and a function for interval censored data and some useful functions for tabulation and plotting, as well as a number of epidemiological data sets.
Author: Bendix Carstensen [aut, cre], Martyn Plummer [aut], Esa Laara [ctb], Michael Hills [ctb]
Maintainer: Bendix Carstensen <b@bxc.dk>

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Package eks updated to version 1.1.1 with previous version 1.1.0 dated 2025-05-18

Title: Tidy and Geospatial Kernel Smoothing
Description: Extensions of the kernel smoothing functions from the 'ks' package for compatibility with the tidyverse and geospatial ecosystems <doi:10.1007/s00180-024-01543-9>.
Author: Tarn Duong [aut, cre]
Maintainer: Tarn Duong <tarn.duong@gmail.com>

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Package ageutils updated to version 0.1.0 with previous version 0.0.9 dated 2025-07-01

Title: Collection of Functions for Working with Age Intervals
Description: Provides a collection of efficient functions for working with individual ages and corresponding intervals. These include functions for conversion from an age to an interval, aggregation of ages with associated counts in to intervals and the splitting of interval counts based on specified age distributions.
Author: Tim Taylor [aut, cre, cph] , Edwin van Leeuwen [aut]
Maintainer: Tim Taylor <tim.taylor@hiddenelephants.co.uk>

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Package redist updated to version 4.3.0 with previous version 4.2.0 dated 2024-01-13

Title: Simulation Methods for Legislative Redistricting
Description: Enables researchers to sample redistricting plans from a pre-specified target distribution using Sequential Monte Carlo and Markov Chain Monte Carlo algorithms. The package allows for the implementation of various constraints in the redistricting process such as geographic compactness and population parity requirements. Tools for analysis such as computation of various summary statistics and plotting functionality are also included. The package implements the SMC algorithm of McCartan and Imai (2023) <doi:10.1214/23-AOAS1763>, the enumeration algorithm of Fifield, Imai, Kawahara, and Kenny (2020) <doi:10.1080/2330443X.2020.1791773>, the Flip MCMC algorithm of Fifield, Higgins, Imai and Tarr (2020) <doi:10.1080/10618600.2020.1739532>, the Merge-split/Recombination algorithms of Carter et al. (2019) <doi:10.48550/arXiv.1911.01503> and DeFord et al. (2021) <doi:10.1162/99608f92.eb30390f>, and the Short-burst optimization algorithm of Cannon et al. (2020) < [...truncated...]
Author: Christopher T. Kenny [aut, cre] , Cory McCartan [aut] , Ben Fifield [aut] , Kosuke Imai [aut] , Jun Kawahara [ctb], Alexander Tarr [ctb], Michael Higgins [ctb]
Maintainer: Christopher T. Kenny <christopherkenny@fas.harvard.edu>

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Package NNS updated to version 11.4 with previous version 11.3 dated 2025-04-28

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

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Package gemtc updated to version 1.1-0 with previous version 1.0-2 dated 2023-06-21

Title: Network Meta-Analysis Using Bayesian Methods
Description: Network meta-analyses (mixed treatment comparisons) in the Bayesian framework using JAGS. Includes methods to assess heterogeneity and inconsistency, and a number of standard visualizations. van Valkenhoef et al. (2012) <doi:10.1002/jrsm.1054>; van Valkenhoef et al. (2015) <doi:10.1002/jrsm.1167>.
Author: Gert van Valkenhoef [aut, cre], Joel Kuiper [aut]
Maintainer: Gert van Valkenhoef <gert@gertvv.nl>

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Package dmm updated to version 3.2-1 with previous version 3.1-1 dated 2025-02-25

Title: Dyadic Mixed Model for Pedigree Data
Description: Mixed model analysis for quantitative genetics with multi-trait responses and pedigree-based partitioning of individual variation into a range of environmental and genetic variance components for individual and maternal effects. Method documented in dmmOverview.pdf; dmm is an implementation of dispersion mean model described by Searle et al. (1992) "Variance Components", Wiley, NY. 'DMM' can do 'MINQUE', 'bias-corrected-ML', and 'REML' variance and covariance component estimates.
Author: Neville Jackson [aut, cre]
Maintainer: Neville Jackson <nanddjackson@bigpond.com>

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Package utsf updated to version 1.3.0 with previous version 1.2.0 dated 2025-05-19

Title: Univariate Time Series Forecasting
Description: An engine for univariate time series forecasting using different regression models in an autoregressive way. The engine provides an uniform interface for applying the different models. Furthermore, it is extensible so that users can easily apply their own regression models to univariate time series forecasting and benefit from all the features of the engine, such as preprocessings or estimation of forecast accuracy.
Author: Maria Pilar Frias-Bustamante [aut] , Francisco Martinez [aut, cre, cph]
Maintainer: Francisco Martinez <fmartin@ujaen.es>

Diff between utsf versions 1.2.0 dated 2025-05-19 and 1.3.0 dated 2025-07-08

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New package Transition with initial version 1.0.0
Package: Transition
Title: Characterise Transitions in Test Result Status in Longitudinal Studies
Version: 1.0.0
Date: 2025-07-04
Description: Analyse data from longitudinal studies to characterise changes in values of semi-quantitative outcome variables within individual subjects, using high performance C++ code to enable rapid processing of large datasets. A flexible methodology is available for codifying these state transitions.
License: MIT + file LICENSE
Imports: Rcpp (>= 1.0.14)
LinkingTo: Rcpp
Encoding: UTF-8
Depends: R (>= 4.1.0)
LazyData: true
URL: https://mark-eis.github.io/Transition/
NeedsCompilation: yes
Packaged: 2025-07-04 21:11:08 UTC; runner
Author: Mark Eisler [aut, cre, cph] , Ana Rabaza [aut]
Maintainer: Mark Eisler <mark.eisler@bristol.ac.uk>
Repository: CRAN
Date/Publication: 2025-07-08 10:00:02 UTC

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New package smsets with initial version 1.2.3
Package: smsets
Date: 2025-07-03
Title: Simple Multivariate Statistical Estimation and Tests
Version: 1.2.3
Description: A collection of simple parameter estimation and tests for the comparison of multivariate means and variation, to accompany Chapters 4 and 5 of the book Multivariate Statistical Methods. A Primer (5th edition), by Manly BFJ, Navarro Alberto JA & Gerow K (2024) <doi:10.1201/9781003453482>.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 3.6)
LazyData: true
Imports: stringr, data.table, Hotelling, biotools
Suggests: car, knitr, rmarkdown, testthat (>= 3.0.0),
VignetteBuilder: knitr
URL: https://github.com/ganava4/smsets
BugReports: https://github.com/ganava4/smsets/issues
NeedsCompilation: no
Packaged: 2025-07-04 17:58:55 UTC; jorgen
Author: Jorge Navarro Alberto [aut, cre, cph]
Maintainer: Jorge Navarro Alberto <ganava4@gmail.com>
Repository: CRAN
Date/Publication: 2025-07-08 09:50:05 UTC

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New package intervalpsych with initial version 0.1.0
Package: intervalpsych
Title: Analyzing Interval Data in Psychometrics
Version: 0.1.0
Maintainer: Matthias Kloft <kloft.dev+intervalpsych@gmail.com>
Description: Implements the Interval Consensus Model (ICM) for analyzing continuous bounded interval-valued responses in psychometrics using 'Stan' for 'Bayesian' estimation. Provides functions for transforming interval data to simplex representations, fitting item response theory (IRT) models with isometric log-ratio (ILR) and sum log-ratio (SLR) link functions, and visualizing results. The package enables aggregation and analysis of interval-valued response data commonly found in psychological measurement and related disciplines. Based on Kloft et al. (2024) <doi:10.31234/osf.io/dzvw2>.
License: GPL (>= 3)
Encoding: UTF-8
URL: https://matthiaskloft.github.io/intervalpsych/, https://github.com/matthiaskloft/intervalpsych
BugReports: https://github.com/matthiaskloft/intervalpsych/issues
Biarch: true
Depends: R (>= 4.1)
Imports: dplyr, ggdist, ggokabeito, ggplot2, methods, posterior, purrr, Rcpp (>= 0.12.0), RcppParallel (>= 5.0.1), rstan (>= 2.18.1), rstantools (>= 2.4)
LinkingTo: BH (>= 1.66.0), Rcpp (>= 0.12.0), RcppEigen (>= 0.3.3.3.0), RcppParallel (>= 5.0.1), rstan (>= 2.18.1), StanHeaders (>= 2.18.0)
SystemRequirements: GNU make
LazyData: true
Suggests: testthat (>= 3.0.0)
NeedsCompilation: yes
Packaged: 2025-07-04 00:13:43 UTC; Matze
Author: Matthias Kloft [aut, cre, cph] , Bjoern S. Siepe [aut]
Repository: CRAN
Date/Publication: 2025-07-08 09:20:02 UTC

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Package imageRy updated to version 0.2.0 with previous version 0.1.1 dated 2025-06-25

Title: Modify and Share Images
Description: Tools for manipulating, visualizing, and exporting raster images in R. Designed as an educational resource for students learning the basics of remote sensing, the package provides user-friendly functions to apply color ramps, export RGB composites, and create multi-frame visualizations. Built on top of the 'terra' and 'ggplot2' packages. See <https://github.com/ducciorocchini/imageRy> for more details and examples.
Author: Duccio Rocchini [aut], Ludovico Chieffallo [aut, cre], Giovanni Andrea Nocera [ctb], Giacomo Panza [ctb], Michele Torresani [aut], Elisa Thouverai [aut]
Maintainer: Ludovico Chieffallo <ludovico.chieffallo2@unibo.it>

Diff between imageRy versions 0.1.1 dated 2025-06-25 and 0.2.0 dated 2025-07-08

 DESCRIPTION        |    6 ++--
 MD5                |   14 ++++-----
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 R/im.import.R      |   73 +++++++++++++++++++++++++++-----------------------
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New package HighFive with initial version 3.0.0
Package: HighFive
Title: The 'HighFive' 'C++' Interface to 'HDF5'
Description: A modern idiomatic header-only C++ interface for 'libhdf5'. Original software can be found at <https://github.com/highfive-devs/highfive/>.
Version: 3.0.0
Date: 2025-07-02
URL: https://github.com/theAeon/HighFive
BugReports: https://github.com/theAeon/HighFive/issues
License: BSL-1.0
Copyright: file inst/COPYRIGHTS
SystemRequirements: C++14, hdf5
NeedsCompilation: no
Packaged: 2025-07-02 16:45:11 UTC; andrew
Author: Andrew Robbins [aut, cre] , Blue Brain Project/EPFL [aut]
Maintainer: Andrew Robbins <robbiand@umich.edu>
Repository: CRAN
Date/Publication: 2025-07-08 09:10:02 UTC

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New package ArgentinAPI with initial version 0.1.0
Package: ArgentinAPI
Title: Access Argentine Economic, Social, and Geopolitical Data via RESTful APIs and Curated Datasets
Version: 0.1.0
Maintainer: Renzo Caceres Rossi <arenzocaceresrossi@gmail.com>
Description: Provides functions to access data from the 'ArgentinaDatos API' and the 'REST Countries API' related to Argentina's exchange rates, inflation, political figures, holidays, and general country-level indicators. Additionally, the package includes curated datasets related to Argentina, covering topics such as economic indicators, biodiversity, agriculture, human rights, genetic data, and consumer prices. The package supports research and analysis focused on Argentina by integrating open APIs with high-quality datasets from various domains. For more details on the 'ArgentinaDatos API', see <https://argentinadatos.com/> and for 'REST Countries', see <https://restcountries.com/>.
License: GPL-3
URL: https://github.com/lightbluetitan/argentinapi, https://lightbluetitan.github.io/argentinapi/
BugReports: https://github.com/lightbluetitan/argentinapi/issues
Encoding: UTF-8
LazyData: true
Depends: R (>= 4.1.0)
Imports: utils, httr, jsonlite, dplyr, lubridate
Suggests: ggplot2, testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2025-07-04 07:13:55 UTC; renzorossiv
Author: Renzo Caceres Rossi [aut, cre]
Repository: CRAN
Date/Publication: 2025-07-08 09:30:01 UTC

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Package dsmmR updated to version 1.0.7 with previous version 1.0.5 dated 2024-07-27

Title: Estimation and Simulation of Drifting Semi-Markov Models
Description: Performs parametric and non-parametric estimation and simulation of drifting semi-Markov processes. The definition of parametric and non-parametric model specifications is also possible. Furthermore, three different types of drifting semi-Markov models are considered. These models differ in the number of transition matrices and sojourn time distributions used for the computation of a number of semi-Markov kernels, which in turn characterize the drifting semi-Markov kernel. For the parametric model estimation and specification, several discrete distributions are considered for the sojourn times: Uniform, Poisson, Geometric, Discrete Weibull and Negative Binomial. The non-parametric model specification makes no assumptions about the shape of the sojourn time distributions. Semi-Markov models are described in: Barbu, V.S., Limnios, N. (2008) <doi:10.1007/978-0-387-73173-5>. Drifting Markov models are described in: Vergne, N. (2008) <doi:10.2202/1544-6115.1326>. Reliability ind [...truncated...]
Author: Vlad Stefan Barbu [aut] , Ioannis Mavrogiannis [aut, cre] , Nicolas Vergne [aut]
Maintainer: Ioannis Mavrogiannis <mavrogiannis.ioa@gmail.com>

Diff between dsmmR versions 1.0.5 dated 2024-07-27 and 1.0.7 dated 2025-07-08

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Package door updated to version 0.0.2 with previous version 0.0.1 dated 2025-06-28

Title: Analysis of Clinical Trials with the Desirability of Outcome Ranking Methodology
Description: Statistical methods and related graphical representations for the Desirability of Outcome Ranking (DOOR) methodology. The DOOR is a paradigm for the design, analysis, interpretation of clinical trials and other research studies based on the patient centric benefit risk evaluation. The package provides functions for generating summary statistics from individual level/summary level datasets, conduct DOOR probability-based inference, and visualization of the results. For more details of DOOR methodology, see Hamasaki and Evans (2025) <doi:10.1201/9781003390855>. For more explanation of the statistical methods and the graphics, see the technical document and user manual of the DOOR 'Shiny' apps at <https://methods.bsc.gwu.edu>.
Author: Yijie He [aut, cre], Qihang Wu [ctb], Toshimitsu Hamasaki [ctb]
Maintainer: Yijie He <yih148@gwu.edu>

Diff between door versions 0.0.1 dated 2025-06-28 and 0.0.2 dated 2025-07-08

 DESCRIPTION |   10 +++++-----
 MD5         |    2 +-
 2 files changed, 6 insertions(+), 6 deletions(-)

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Package SelfControlledCaseSeries (with last version 6.0.0) was removed from CRAN

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

2025-06-23 6.0.0

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Package DistributionIV (with last version 0.1.2) was removed from CRAN

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

2025-06-27 0.1.2
2025-02-27 0.1.0

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Package EMTscore (with last version 0.1.1) was removed from CRAN

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

2025-04-17 0.1.1

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