Wed, 10 Jun 2026

Package dream updated to version 2.1.3 with previous version 2.1.2 dated 2026-06-03

Title: Dynamic Relational Event Analysis and Modeling
Description: A set of tools for relational and event analysis, including two- and one-mode network brokerage and structural measures, and helper functions optimized for relational event analysis with large datasets, including creating relational risk sets, computing network statistics, estimating relational event models, and simulating relational event sequences. For more information on relational event models, see Butts (2008) <doi:10.1111/j.1467-9531.2008.00203.x>, Lerner and Lomi (2020) <doi:10.1017/nws.2019.57>, Bianchi et al. (2024) <doi:10.1146/annurev-statistics-040722-060248>, and Butts et al. (2023) <doi:10.1017/nws.2023.9>. In terms of the structural measures in this package, see Leal (2025) <doi:10.1177/00491241251322517>, Burchard and Cornwell (2018) <doi:10.1016/j.socnet.2018.04.001>, and Fujimoto et al. (2018) <doi:10.1017/nws.2018.11>. This package was developed with support from the National Science Foundation’s (NSF) Human Networks and Data [...truncated...]
Author: Kevin A. Carson [aut, cre] , Diego F. Leal [aut]
Maintainer: Kevin A. Carson <kacarson@arizona.edu>

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Package OPI updated to version 3.1.1 with previous version 3.1.0 dated 2026-03-03

Title: Open Perimetry Interface
Description: Implementation of the Open Perimetry Interface (OPI) for simulating and controlling visual field machines using R. The OPI is a standard for interfacing with visual field testing machines (perimeters) first started as an open source project with support of Haag-Streit in 2010. It specifies basic functions that allow many visual field tests to be constructed. As of February 2022 it is fully implemented on the Haag-Streit Octopus 900 and 'CrewT ImoVifa' ('Topcon Tempo') with partial implementations on the Centervue Compass, Kowa AP 7000 and Android phones. It also has a cousin: the R package 'visualFields', which has tools for analysing and manipulating visual field data.
Author: Andrew Turpin [cre, aut, cph] , David Lawson [ctb, cph], Ivan Marin-Franch [ctb, cph], Matthias Muller [ctb], Jonathan Denniss [ctb, cph], Astrid Zeman [ctb], Giovanni Montesano [ctb]
Maintainer: Andrew Turpin <andrew.turpin@lei.org.au>

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Package LBI updated to version 0.2.5 with previous version 0.2.4 dated 2026-05-22

Title: Likelihood Based Inference
Description: Maximum likelihood estimation and likelihood ratio test are essential for modern statistics. This package supports in calculating likelihood based inference. Reference: Pawitan Y. (2001, ISBN:0-19-850765-8).
Author: Kyun-Seop Bae [aut, cre, cph]
Maintainer: Kyun-Seop Bae <k@acr.kr>

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Package jrt updated to version 1.2.0 with previous version 1.1.3 dated 2025-07-31

Title: Item Response Theory Modeling and Scoring for Judgment Data
Description: Psychometric analysis and scoring of judgment data using polytomous Item-Response Theory (IRT) models, as described in Myszkowski and Storme (2019) <doi:10.1037/aca0000225> and Myszkowski (2021) <doi:10.1037/aca0000287>. A function is used to automatically compare and select models, as well as to present a variety of model-based statistics. Plotting functions are used to present category curves, as well as information, reliability and standard error functions.
Author: Nils Myszkowski [aut, cre]
Maintainer: Nils Myszkowski <nilsmyszkowskiscience@gmail.com>

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Package fitPS updated to version 1.0.6 with previous version 1.0.1 dated 2024-03-19

Title: Fit Zeta Distributions to Forensic Data
Description: Fits Zeta distributions (discrete power laws) to data that arises from forensic surveys of clothing on the presence of glass and paint in various populations. The general method is described to some extent in Coulson, S.A., Buckleton, J.S., Gummer, A.B., and Triggs, C.M. (2001) <doi:10.1016/S1355-0306(01)71847-3>, although the implementation differs.
Author: James Curran [aut, cre]
Maintainer: James Curran <j.curran@auckland.ac.nz>

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Package DFA.CANCOR updated to version 0.4.3 with previous version 0.3.9 dated 2025-09-08

Title: Linear Discriminant Function and Canonical Correlation Analysis
Description: Produces SPSS- and SAS-like output for linear discriminant function analysis and canonical correlation analysis. The methods are described in Manly & Alberto (2017, ISBN:9781498728966), Rencher (2002, ISBN:0-471-41889-7), and Tabachnik & Fidell (2019, ISBN:9780134790541).
Author: Brian P. O'Connor [aut, cre]
Maintainer: Brian P. O'Connor <brian.oconnor@ubc.ca>

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Package shrinkem updated to version 0.3.0 with previous version 0.2.0 dated 2024-10-05

Title: Approximate Bayesian Regularization for Parsimonious Estimates
Description: Approximate Bayesian regularization using Gaussian approximations. The input is a vector of estimates and a Gaussian error covariance matrix of the key parameters. Bayesian shrinkage is then applied to obtain parsimonious solutions. The method is described on Karimova, van Erp, Leenders, and Mulder (2025) <DOI:10.1016/j.jmp.2025.102925>. Gibbs samplers are used for model fitting. The shrinkage priors that are supported are Gaussian (ridge) priors, Laplace (lasso) priors (Park and Casella, 2008 <DOI:10.1198/016214508000000337>), and horseshoe priors (Carvalho, et al., 2010; <DOI:10.1093/biomet/asq017>). These priors include an option for grouped regularization of different subsets of parameters (Meier et al., 2008; <DOI:10.1111/j.1467-9868.2007.00627.x>). F priors are used for the penalty parameters lambda^2 (Mulder and Pericchi, 2018 <DOI:10.1214/17-BA1092>). This correspond to half-Cauchy priors on lambda (Carvalho, Polson, Scott, 2010 <DOI:10.1093/bio [...truncated...]
Author: Joris Mulder [aut, cre], Diana Karimova [aut, ctb], Sara van Erp [ctb], Roger Leenders [ctb]
Maintainer: Joris Mulder <j.mulder3@tilburguniversity.edu>

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Package tbm updated to version 0.3-11 with previous version 0.3-10 dated 2025-12-02

Title: Transformation Boosting Machines
Description: Boosting the likelihood of conditional and shift transformation models as introduced in <DOI:10.1007/s11222-019-09870-4>.
Author: Torsten Hothorn [aut, cre]
Maintainer: Torsten Hothorn <Torsten.Hothorn@R-project.org>

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Package mx.api updated to version 0.3.0 with previous version 0.2.0 dated 2026-05-13

Title: Minimal Matrix Client-Server API
Description: A minimal-dependency client for the 'Matrix' Client-Server HTTP API <https://spec.matrix.org/>, suitable for talking to a 'Synapse' <https://element-hq.github.io/synapse/> or 'Conduit' <https://conduit.rs/> homeserver. Covers login, room management, message send and history, media upload or download, and the transport endpoints needed to coordinate end-to-end encryption (device-key and one-time-key publication, key query and claim, to-device events). Encryption itself is out of scope; pair with a separate crypto package.
Author: Troy Hernandez [aut, cre] , cornball.ai [cph]
Maintainer: Troy Hernandez <troy@cornball.ai>

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Package joinpointR updated to version 1.0.0 with previous version 0.6.2 dated 2026-05-28

Title: Tidy Tools for Joinpoint Regression Models
Description: Provides tools to fit joinpoint regression models with a log-linear specification by levels of a categorical variable. The package acts as a wrapper around the 'segmented' package, facilitating model fitting, selection, and interpretation. It includes functions to estimate the Annual Percent Change (APC) and the Average Annual Percent Change (AAPC), along with their 95% confidence intervals, and to generate formatted summary tables and plots of results.
Author: Tamara Ricardo [aut, cre]
Maintainer: Tamara Ricardo <tamararicardo83@gmail.com>

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Package wizaRdry updated to version 0.6.16 with previous version 0.6.8 dated 2026-05-12

Title: A Magical Framework for Collaborative & Reproducible Data Analysis
Description: A comprehensive data analysis framework for NIH-funded research that streamlines workflows for both data cleaning and preparing NIH Data Archive ('NDA') submission templates. Provides unified access to multiple data sources ('REDCap', 'MongoDB', 'Qualtrics', 'SQL', 'ORACLE') through interfaces to their APIs, with specialized functions for data cleaning, filtering, merging, and parsing. Features automatic validation, field harmonization, and memory-aware processing to enhance reproducibility in multi-site collaborative research as described in Mittal et al. (2021) <doi:10.20900/jpbs.20210011>.
Author: Joshua G. Kenney [aut, cre], Trevor F. Williams [aut], Minerva K. Pappu [aut], Michael J. Spilka [aut], Danielle N. Pratt [ctb], Victor J. Pokorny [ctb], Santiago Castiello de Obeso [ctb], Praveen Suthaharan [ctb], Christian R. Horgan [ctb]
Maintainer: Joshua G. Kenney <joshua.kenney@yale.edu>

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Package vennDiagramLab updated to version 2.4.2 with previous version 2.0.5 dated 2026-05-18

Title: Headless Venn Diagram Analysis and Rendering
Description: Headless companion to the 'Venn Diagram Lab' web tool (<https://www.venndiagramlab.org/>). Build, render, and statistically analyze Venn / 'UpSet' diagrams from 'CSV' / 'TSV' / 'GMT' / 'GMX' inputs. Provides the same 44 SVG models, intersection / 'Jaccard' / hypergeometric statistics, and PDF report layout as the web tool, with byte-equivalent 'TSV' exports (parity-tested against the published Python package). Integrates with 'ggplot2', 'tidygraph', and 'broom'.
Author: Zoltan Dul [aut, cre] , Marton Oelbei [aut] , N. Shaun B. Thomas [aut], Azeddine Si Ammour [aut] , Attila Csikasz-Nagy [aut]
Maintainer: Zoltan Dul <zoltan.dul@gmail.com>

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Package nuggets updated to version 2.2.1 with previous version 2.2.0 dated 2026-03-11

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 scaledescr updated to version 0.2.7 with previous version 0.2.6 dated 2026-04-25

Title: Descriptive, Reliability, and Inferential Tables for Psychometric Scales and Demographic Data
Description: Provides functions to format and summarise already computed outputs from commonly used statistical and psychometric functions into compact, single-row tables and simple graphs, with utilities to export results to CSV, Word, and Excel formats. The package does not implement new statistical methods or estimation procedures; instead, it organises and presents results obtained from existing packages such as 'psych', 'stats', 'gtsummary', and 'lavaan' to streamline reporting workflows in clinical and psychological research.
Author: Darshankumar Dharaiya [aut, cre]
Maintainer: Darshankumar Dharaiya <dharaiya.darshan@gmail.com>

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Package opticskxi updated to version 1.2.2 with previous version 1.2.1 dated 2025-03-09

Title: OPTICS K-Xi Density-Based Clustering
Description: Density-based clustering methods are well adapted to the clustering of high-dimensional data and enable the discovery of core groups of various shapes despite large amounts of noise. This package provides a novel density-based cluster extraction method, OPTICS k-Xi, and a framework to compare k-Xi models using distance-based metrics to investigate datasets with unknown number of clusters. The vignette first introduces density-based algorithms with simulated datasets, then presents and evaluates the k-Xi cluster extraction method. Finally, the models comparison framework is described and experimented on 2 genetic datasets to identify groups and their discriminating features. The k-Xi algorithm is a novel OPTICS cluster extraction method that specifies directly the number of clusters and does not require fine-tuning of the steepness parameter as the OPTICS Xi method. Combined with a framework that compares models with varying parameters, the OPTICS k-Xi method can identify groups in nois [...truncated...]
Author: Thomas Charlon [aut, cre]
Maintainer: Thomas Charlon <charlon@protonmail.com>

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Package CohortSymmetry updated to version 0.3.0 with previous version 0.2.4 dated 2025-03-24

Title: Sequence Symmetry Analysis Using the Observational Medical Outcomes Partnership Common Data Model
Description: Calculating crude sequence ratio, adjusted sequence ratio and confidence intervals using data mapped to the Observational Medical Outcomes Partnership Common Data Model.
Author: Danielle Newby [aut, cre] , Xihang Chen [aut] , Tyman Stanford [aut] , Berta Raventos [aut] , Nicole Pratt [aut] , Ed Burn [aut] , Marti Catala [aut] , Nuria Mercade-Besora [aut] , Mike Du [aut] , Yuchen Guo [aut] , Kim Lopez [aut] , Marta Alcalde-He [...truncated...]
Maintainer: Danielle Newby <danielle.newby@ndorms.ox.ac.uk>

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Package zip updated to version 3.0.0 with previous version 2.3.3 dated 2025-05-13

Title: Cross-Platform 'zip' Compression
Description: Cross-Platform 'zip' Compression Library. A replacement for the 'zip' function, that does not require any additional external tools on any platform.
Author: Gabor Csardi [aut, cre], Kuba Podgorski [ctb], Rich Geldreich [ctb], Arm Limited [ctb, cph] ), Posit Software, PBC [cph, fnd]
Maintainer: Gabor Csardi <csardi.gabor@gmail.com>

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Package TreeDist updated to version 2.14.1 with previous version 2.14.0 dated 2026-05-09

Title: Calculate and Map Distances Between Phylogenetic Trees
Description: Implements measures of tree similarity, including information-based generalized Robinson-Foulds distances (Phylogenetic Information Distance, Clustering Information Distance, Matching Split Information Distance; Smith 2020) <doi:10.1093/bioinformatics/btaa614>; Jaccard-Robinson-Foulds distances (Bocker et al. 2013) <doi:10.1007/978-3-642-40453-5_13>, including the Nye et al. (2006) metric <doi:10.1093/bioinformatics/bti720>; the Matching Split Distance (Bogdanowicz & Giaro 2012) <doi:10.1109/TCBB.2011.48>; the Hierarchical Mutual Information (Perotti et al. 2015) <doi:10.1103/PhysRevE.92.062825>; Maximum Agreement Subtree distances; the Kendall-Colijn (2016) distance <doi:10.1093/molbev/msw124>, and the Nearest Neighbour Interchange (NNI) distance, approximated per Li et al. (1996) <doi:10.1007/3-540-61332-3_168>. Includes tools for visualizing mappings of tree space (Smith 2022) <doi:10.1093/sysbio/syab100>, for identifying islands o [...truncated...]
Author: Martin R. Smith [aut, cre, cph, prg] , Roy Jonker [prg, cph] , Yong Yang [ctb, cph] , Yi Cao [ctb, cph] , Neil Kaye [cph]
Maintainer: Martin R. Smith <martin.smith@durham.ac.uk>

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Package rhino updated to version 1.12.0 with previous version 1.11.0 dated 2025-04-02

Title: A Framework for Enterprise Shiny Applications
Description: A framework that supports creating and extending enterprise Shiny applications using best practices.
Author: Jakub Nowicki [aut, cre], Kamil Zyla [aut], Leszek Sieminski [aut], Marek Rogala [aut], Recle Vibal [aut], Tymoteusz Makowski [aut], Rodrigo Basa [aut], Eduardo Almeida [ctb], Appsilon Sp. z o.o. [cph]
Maintainer: Jakub Nowicki <opensource+kuba@appsilon.com>

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Package NeutroRCDsAnalysis updated to version 0.1.1 with previous version 0.1.0 dated 2026-06-08

Title: Neutrosophic Analysis of Row Column Designs
Description: Description: Provides methods for Neutrosophic Analysis of Variance (NANOVA) and Neutrosophic Analysis of Covariance (NANCOVA) for row-column designs, including Latin square designs and Youden square designs, using interval-valued observations. The package computes neutrosophic sums of squares, mean squares, interval-valued F-statistics, significance tests, and multiple comparisons using Least Significant Difference (LSD) procedures. For crisp data, users may enter identical lower and upper values of responses to obtain classical Analysis of Variance (ANOVA) results. Similarly, users may enter identical lower and upper values for both responses and covariates to obtain classical Analysis of Covariance (ANCOVA) results.
Author: Neethu R.S. [aut, ctb], Boyina Devi Priyanka [aut, ctb], Cini Varghese [aut, ctb], Mohd Harun [aut, ctb], Anindita Datta [aut, ctb], Vinaykumar L.N. [aut, cre]
Maintainer: Vinaykumar L.N. <vinaymandya123@gmail.com>

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Package metamorphr updated to version 0.4.1 with previous version 0.4.0 dated 2026-06-09

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

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Package LFM readmission to version 0.3.4 with previous version 0.3.3 dated 2025-12-06

Title: Laplace Factor Model Analysis and Evaluation
Description: Enables the generation of Laplace factor models across diverse Laplace distributions and facilitates the application of Sparse Online Principal Component (SOPC), Incremental Principal Component (IPC), Perturbation Principal Component (PPC), Stochastic Approximation Principal Component (SAPC), Sparse Principal Component (SPC) and other PC methods and Farm Test methods to these models. Evaluates the efficacy of these methods within the context of Laplace factor models by scrutinizing parameter estimation accuracy, mean square error, and the degree of sparsity.
Author: Guangbao Guo [aut, cre], Siqi Liu [aut]
Maintainer: Guangbao Guo <ggb11111111@163.com>

This is a re-admission after prior archival of version 0.3.3 dated 2025-12-06

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Package gmwmx2 updated to version 0.0.5 with previous version 0.0.4 dated 2026-01-07

Title: Estimate Functional and Stochastic Parameters of Linear Models with Correlated Residuals and Missing Data
Description: Implements the Generalized Method of Wavelet Moments with Exogenous Inputs estimator (GMWMX) presented in Voirol, L., Xu, H., Zhang, Y., Insolia, L., Molinari, R. and Guerrier, S. (2024) <doi:10.48550/arXiv.2409.05160>. The GMWMX estimator allows to estimate functional and stochastic parameters of linear models with correlated residuals in presence of missing data. The 'gmwmx2' package provides functions to load and plot Global Navigation Satellite System (GNSS) data from the Nevada Geodetic Laboratory and functions to estimate linear model model with correlated residuals in presence of missing data.
Author: Lionel Voirol [aut, cre] , Haotian Xu [aut] , Yuming Zhang [aut] , Luca Insolia [aut] , Roberto Molinari [aut] , Stephane Guerrier [aut]
Maintainer: Lionel Voirol <lionelvoirol@hotmail.com>

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Package test.assessr updated to version 2.1.2 with previous version 2.1.0 dated 2026-04-30

Title: Assessing Package Test Reliability and Quality
Description: A reliable and validated tool that calculates unit test coverage for R packages with standard testing frameworks and non-standard testing frameworks.
Author: Edward Gillian [cre, aut] , Hugo Bottois [aut] , Paulin Charliquart [aut], Andre Couturier [aut], Sanofi [cph, fnd]
Maintainer: Edward Gillian <edward.gillian-ext@sanofi.com>

Diff between test.assessr versions 2.1.0 dated 2026-04-30 and 2.1.2 dated 2026-06-10

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Package scpi updated to version 4.0.1 with previous version 4.0.0 dated 2026-06-03

Title: Synthetic Control Methods
Description: Implementation of prediction and inference procedures for Synthetic Control methods using least square, lasso, ridge, or simplex-type constraints. Uncertainty is quantified with prediction intervals as developed in Cattaneo, Feng, and Titiunik (2021) <doi:10.1080/01621459.2021.1979561> for a single treated unit and in Cattaneo, Feng, Palomba, and Titiunik (2027) <doi:10.1162/rest_a_01588> for multiple treated units and staggered adoption. More details about the software implementation can be found in Cattaneo, Feng, Palomba, and Titiunik (2025) <doi:10.18637/jss.v113.i01>.
Author: Matias D. Cattaneo [aut, cre], Yingjie Feng [aut], Filippo Palomba [aut], Rocio Titiunik [aut]
Maintainer: Matias D. Cattaneo <matias.d.cattaneo@gmail.com>

Diff between scpi versions 4.0.0 dated 2026-06-03 and 4.0.1 dated 2026-06-10

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Package admiraldev updated to version 1.5.0 with previous version 1.4.1 dated 2026-05-27

Title: Utility Functions and Development Tools for the Admiral Package Family
Description: Utility functions to check data, variables and conditions for functions used in 'admiral' and 'admiral' extension packages. Additional utility helper functions to assist developers with maintaining documentation, testing and general upkeep of 'admiral' and 'admiral' extension packages.
Author: Edoardo Mancini [aut, cre] , Stefan Bundfuss [aut] , Arianna Cascone [aut] , Kristin Dahnert [aut], Jeffrey Dickinson [aut], Ross Farrugia [aut], Fanny Gautier [aut] , Liam Hobby [aut], Gordon Miller [aut], Lina Patil [aut], Ben Straub [aut], F. Hoff [...truncated...]
Maintainer: Edoardo Mancini <edoardo.mancini@roche.com>

Diff between admiraldev versions 1.4.1 dated 2026-05-27 and 1.5.0 dated 2026-06-10

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Package rYWAASB updated to version 0.4 with previous version 0.3 dated 2025-05-23

Title: Simultaneous Selection by Trait and WAASB Index
Description: This tool proposes a new ranking algorithm that utilizes a "Y*WAASB" biplot generated by the 'metan'. The aim of the current package is to effectively distinguish the top-ranked genotypes in MET (Multi-Environmental Trials). For a detailed explanation of the process of obtaining "WAASB", "WAASBY" indices, and a "Y*WAASB" biplot, refer to the manual included in this package as well as the study by Olivoto & Lúcio (2020) <doi:10.1111/2041-210X.13384>. In this context, "WAASB" refers to the "Weighted Average of Absolute Scores" provided by Olivoto et al. (2019) <doi:10.2134/agronj2019.03.0220>, which quantifies the stability of genotypes across different environments using linear mixed-effect models. To run the package, you need to extract the "WAASB" and "WAASBY" coefficients using the 'metan' and apply them. This tool utilizes PCA (Principal Component Analysis) and differentiates the entries which may be genotypes, hybrids, varieties, etc using "WAASB", "WAASBY", and a c [...truncated...]
Author: Ali Arminian [aut, cre, cph]
Maintainer: Ali Arminian <abeyran@gmail.com>

Diff between rYWAASB versions 0.3 dated 2025-05-23 and 0.4 dated 2026-06-10

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Package rtdists updated to version 0.11-6 with previous version 0.11-5 dated 2022-01-07

Title: Response Time Distributions
Description: Provides response time distributions (density/PDF, distribution function/CDF, quantile function, and random generation): (a) Ratcliff diffusion model (Ratcliff & McKoon, 2008, <doi:10.1162/neco.2008.12-06-420>) based on C code by Andreas and Jochen Voss and (b) linear ballistic accumulator (LBA; Brown & Heathcote, 2008, <doi:10.1016/j.cogpsych.2007.12.002>) with different distributions underlying the drift rate.
Author: Henrik Singmann [aut, cre] , Scott Brown [aut], Matthew Gretton [aut], Andrew Heathcote [aut], Andreas Voss [ctb], Jochen Voss [ctb], Andrew Terry [ctb]
Maintainer: Henrik Singmann <singmann@gmail.com>

Diff between rtdists versions 0.11-5 dated 2022-01-07 and 0.11-6 dated 2026-06-10

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Package outstandR updated to version 2.0.0 with previous version 1.0.0 dated 2026-01-21

Title: Model-Based Standardisation for Indirect Treatment Comparison with Limited Subject-Level Data
Description: For the problem of indirect treatment comparison with limited subject-level data, this package provides tools for model-based standardisation with several different computation approaches. See Remiro‐Azócar A, Heath A, Baio G (2022) ``Parametric G‐computation for compatible indirect treatment comparisons with limited individual patient data'', Res. Synth. Methods, 1–31. ISSN 1759-2879, <doi:10.1002/jrsm.1565>.
Author: Nathan Green [aut, cre, cph] , Chengyang Gao [aut], Antonio Remiro-Azocar [aut]
Maintainer: Nathan Green <n.green@ucl.ac.uk>

Diff between outstandR versions 1.0.0 dated 2026-01-21 and 2.0.0 dated 2026-06-10

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 56 files changed, 1719 insertions(+), 855 deletions(-)

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New package mums2 with initial version 0.1.0
Package: mums2
Title: Microbial Ecology by Tandem Mass Spectrometry
Version: 0.1.0
Description: Tools that researchers can use to analyze untargeted metabolomics data generated using tandem mass spectroscopy from microbial communities. The overall approach taken to analyze metabolomics data parallels that used to analyze microbial communities using 16S rRNA gene sequencing data. Thus, we have a number of methods a user is able to use to generate data. Firstly, users can import Mass Spectrometry 1(MS1) data and filter it. Users are then able to match Mass Spectrometry 2(MS2) data to the filtered (or unfiltered) MS1 data. With the matched data users are able to cluster it, annotate it, predict de novo chemical formulas and calculate alpha and beta diversity. For chemical formula predictions, this was the method used; "Towards de novo identification of metabolites by analyzing tandem mass spectra" (Sebastian Böcker, Florian Rasche (2008) <doi:10.1093/bioinformatics/btn270>). The similarity/dissimilarity calculations we used to cluster our data together was: "Spectral entropy o [...truncated...]
License: GPL (>= 3)
Encoding: UTF-8
URL: https://github.com/mums2/mums2, https://www.mums2.org/mums2/
BugReports: https://github.com/mums2/mums2/issues
LinkingTo: sitmo, Rcpp, RcppThread, testthat, RcppProgress
Imports: clustur, Rcpp, data.table, mpactr, utils, stats, parallel, xml2,
Suggests: knitr, rmarkdown, testthat (>= 3.0.0), tidyverse, networkD3, mzR
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2026-06-04 21:26:57 UTC; grejoh
Author: Allison Mason [aut] , Gregory Johnson [aut] , Patrick Schloss [aut, cre] , Anton Pervukhin [ctb, cph], Florian Rasche [ctb, cph], Henner Sudek [ctb, cph], Marcel Martin [ctb, cph], Yuanyue Li [ctb, cph]
Maintainer: Patrick Schloss <pschloss@umich.edu>
Depends: R (>= 4.1.0)
Repository: CRAN
Date/Publication: 2026-06-10 08:10:02 UTC

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New package fluffy with initial version 1.0.0
Package: fluffy
Title: Schema-Based Validation of 'R' Objects with User-Defined Rules
Version: 1.0.0
Description: A schema-based validation framework for 'R' objects using user-defined rules. Provides three 'S7' classes 'Registry', 'Schema', and 'Validator' to manage rules, define list-based schemas, and validate data in a flexible and extensible manner.
License: MIT + file LICENSE
Encoding: UTF-8
Suggests: jsonlite, kableExtra, knitr, lobstr, readr, rmarkdown, stats, testthat (>= 3.0.0), yaml
Imports: methods, S7, utils
URL: https://lj-jenkins.github.io/fluffy/, https://github.com/LJ-Jenkins/fluffy
VignetteBuilder: knitr
BugReports: https://github.com/LJ-Jenkins/fluffy/issues
NeedsCompilation: no
Packaged: 2026-06-05 14:49:04 UTC; lukej
Author: Luke Jenkins [aut, cre, cph]
Maintainer: Luke Jenkins <luke-jenkins-dev@outlook.com>
Repository: CRAN
Date/Publication: 2026-06-10 08:10:09 UTC

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New package exeval with initial version 0.0.1
Package: exeval
Language: en-US
Title: External Evaluation of Population Pharmacokinetic-Pharmacodynamic (popPKPD) Models
Version: 0.0.1
Description: Provides tools to automate external pharmacokinetic model evaluation workflows, including Bayesian forecasting, predictive performance metrics, diagnostic plotting, and automated reporting.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Depends: R (>= 4.1)
Imports: mapbayr, dplyr, ggplot2, ggpubr, mrgsolve (>= 1.0.8), scales, stats, methods, rlang
Suggests: knitr, rmarkdown,
URL: https://github.com/Martin-Umpierrez/exeval
BugReports: https://github.com/Martin-Umpierrez/exeval/issues
NeedsCompilation: no
Packaged: 2026-06-05 15:03:33 UTC; ialvarez
Author: Manuel Ibarra [aut], Martin Umpierrez [aut, cre], Ignacio Alvarez Castro [aut] , Nicolas Schmidt [aut]
Maintainer: Martin Umpierrez <mumpierrez@fq.edu.uy>
Repository: CRAN
Date/Publication: 2026-06-10 08:10:14 UTC

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New package deepImp with initial version 1.1.0
Package: deepImp
Title: Imputation with Deep Learning Methods
Version: 1.1.0
Description: Imputation of mixed-type and compositional data with neural networks. The architecture (number and size of hidden layers, dropout, activation, optimiser) is user-configurable. See Templ (2021) <doi:10.1007/978-3-030-71175-7>.
License: GPL-2
Encoding: UTF-8
LazyData: TRUE
ByteCompile: TRUE
Depends: R (>= 4.1)
Imports: torch, luz, VIM, robCompositions, stats, utils, graphics
Suggests: keras3, knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-06-05 12:07:20 UTC; matthias
Author: Matthias Templ [aut, cre]
Maintainer: Matthias Templ <matthias.templ@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-10 08:10:20 UTC

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New package CircularRegression with initial version 0.5.1
Package: CircularRegression
Title: Circular Regression Models
Version: 0.5.1
Description: Implements regression models for circular response data, including homogeneous angular regression, consensus angular regression, a two-step workflow, selected special-case model wrappers, and a random-intercept extension for clustered circular outcomes. The main methodology follows Rivest et al. (2016) "A General Angular Regression Model for the Analysis of Data on Animal Movement in Ecology" <doi:10.1111/rssc.12124>.
License: GPL-3
Encoding: UTF-8
Language: en-US
LazyData: true
Imports: circular, graphics, stats, utils
Depends: R (>= 3.5.0)
Suggests: ggplot2, gridExtra, knitr, pkgdown, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
URL: https://github.com/AurelienNicosiaULaval/CircularRegression
BugReports: https://github.com/AurelienNicosiaULaval/CircularRegression/issues
NeedsCompilation: no
Packaged: 2026-06-05 15:27:48 UTC; aureliennicosia
Author: Aurelien Nicosia [aut, cre]
Maintainer: Aurelien Nicosia <aurelien.nicosia@mat.ulaval.ca>
Repository: CRAN
Date/Publication: 2026-06-10 08:20:02 UTC

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New package pkgmatch with initial version 0.5.4
Package: pkgmatch
Title: Find R Packages Matching Either Descriptions or Other R Packages
Version: 0.5.4
Description: Find R packages from CRAN, 'rOpenSci', or Bioconductor corpora. Packages can be matched to general text descriptions, to names of installed packages, or to local paths to entire source repositories. The package is used to list the most similar packages for each new submission to the 'rOpenSci' software peer-review program ('rOpenSci' authors, 2026; <doi:10.5281/zenodo.18885936>).
License: MIT + file LICENSE
URL: https://docs.ropensci.org/pkgmatch/, https://github.com/ropensci-review-tools/pkgmatch
BugReports: https://github.com/ropensci-review-tools/pkgmatch/issues
Depends: R (>= 4.1.0)
Imports: brio, checkmate, cli, curl (>= 6.0.0), dplyr, fs, httr2, memoise, piggyback, Rcpp, rvest, tibble, tidyr, tokenizers, treesitter, treesitter.r, vctrs
Suggests: gert, hms, httptest2, jsonlite, pkgbuild, rappdirs, roxygen2, testthat (>= 3.0.0), withr, knitr, rmarkdown
LinkingTo: Rcpp
NeedsCompilation: yes
Encoding: UTF-8
Language: en-GB
VignetteBuilder: knitr
Packaged: 2026-06-05 11:46:25 UTC; smexus
Author: Mark Padgham [aut, cre] , Davis Vaughan [ctb]
Maintainer: Mark Padgham <mark.padgham@email.com>
Repository: CRAN
Date/Publication: 2026-06-10 07:40:02 UTC

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New package hcinfer with initial version 0.1.0
Package: hcinfer
Title: Heteroskedasticity-Consistent Inference for Linear Models
Version: 0.1.0
Description: Computes heteroskedasticity-consistent covariance matrix estimators for ordinary least squares regression models. The published HC0 through HC5m estimators implemented in the package follow White (1980) <doi:10.2307/1912934>, Hinkley (1977) <doi:10.1080/00401706.1977.10489550>, Horn et al. (1975) <doi:10.1080/01621459.1975.10479877>, MacKinnon and White (1985) <doi:10.1016/0304-4076(85)90158-7>, Cribari-Neto (2004) <doi:10.1016/S0167-9473(02)00366-3>, Cribari-Neto and da Silva (2011) <doi:10.1007/s10182-010-0141-2>, Cribari-Neto et al. (2007) <doi:10.1080/03610920601126589>, and Li et al. (2016) <doi:10.1080/00949655.2016.1198906>. The package also includes HCbeta, a new estimator proposed by the package authors. It provides normal Wald tests, confidence intervals, diagnostics, and S3 output for applied inference.
URL: https://prdm0.github.io/hcinfer/, https://github.com/prdm0/hcinfer
BugReports: https://github.com/prdm0/hcinfer/issues
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: cli, ggplot2, purrr, rlang, tibble
Suggests: dplyr, knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
LazyData: true
NeedsCompilation: no
Packaged: 2026-06-05 12:46:39 UTC; prdm0
Author: Pedro Rafael D. Marinho [aut, cre] , Francisco Cribari-Neto [aut] , Marina Oliveira Cunha [aut]
Maintainer: Pedro Rafael D. Marinho <pedro.rafael.marinho@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-10 08:00:02 UTC

More information about hcinfer at CRAN
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Package factorana updated to version 1.7.1 with previous version 1.3.4 dated 2026-05-12

Title: Factor Model Estimation with Latent Variables
Description: A flexible framework for estimating factor models with multiple latent variables. Supports linear, probit, ordered probit, and multinomial logit model components. Features include multi-stage estimation, automatic parameter initialization, analytical gradients and Hessians, and parallel estimation. Methods are described in Heckman, Humphries, and Veramendi (2016) <doi:10.1016/j.jeconom.2015.12.001>, Heckman, Humphries, and Veramendi (2018) <doi:10.1086/698760>, and Humphries, Joensen, and Veramendi (2024) <doi:10.1257/pandp.20241026>.
Author: Greg Veramendi [aut, cre], Jess Xiong [aut]
Maintainer: Greg Veramendi <greg.veramendi@gmail.com>

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New package dcorBSS with initial version 1.0-0
Package: dcorBSS
Title: Distance-Correlation Based Methods for Blind Source Separation and Dependence Analysis
Version: 1.0-0
Description: Independent component analysis based on distance correlation, including a robust variant using the bowl transformation. The package provides user-facing implementations of distance covariance and distance correlation, including memory-efficient blockwise computations for large data sets. It includes a sequential ICA estimator based on minimizing distance correlation, as well as tools for analyzing serial dependence via distance autocorrelation, dependograms, and permutation-based tests. In addition, it provides functions for testing serial dependence based on distance correlation and the Hilbert–Schmidt independence criterion. The methodology is related to Matteson and Tsay (2017) <doi:10.1080/01621459.2016.1150851> and to the robust framework of Leyder et al. (2026) <doi:10.1007/s11634-026-00674-9>.
License: GPL (>= 3)
Encoding: UTF-8
LinkingTo: Rcpp
Depends: R (>= 4.1.0)
Imports: dccpp, dHSIC, minqa, nloptr, stats, utils, Rcpp
Suggests: energy, JADE, robustbase, knitr, rmarkdown
NeedsCompilation: yes
Author: Sarah Leyder [aut] , Klaus Nordhausen [aut, cre]
Maintainer: Klaus Nordhausen <klausnordhausenR@gmail.com>
VignetteBuilder: knitr
Packaged: 2026-06-04 18:45:44 UTC; nordklau
Repository: CRAN
Date/Publication: 2026-06-10 07:30:09 UTC

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New package clusterindices with initial version 1.0
Package: clusterindices
Title: Cluster Validity Indices
Version: 1.0
Date: 2026-06-05
Author: Michail Tsagris [aut, cre], Nikolaos Kontemeniotis [aut]
Maintainer: Michail Tsagris <mtsagris@uoc.gr>
Depends: R (>= 4.0)
Imports: factoextra, graphics, lowmemtkmeans, Rfast, Rfast2, stats
Description: Numerous indices to choose the optimal number of clusters when performing k-means. Relevant papers include: Tsagris M. and Kontemeniotis N. (2025). Lobachevskii Journal of Mathematics <doi:10.1134/S1995080225613700>. Garcia-Escudero Luis A., Gordaliza Alfonso, Matran Carlos, Mayo-Iscar Agustin. (2008) <doi:10.1214/07-AOS515>.
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2026-06-05 09:13:20 UTC; mtsag
Repository: CRAN
Date/Publication: 2026-06-10 07:40:08 UTC

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Package NeutroCODsAnalysis updated to version 0.1.0 with previous version 0.0.1 dated 2026-06-09

Title: Neutrosophic Analysis Crossover Designs
Description: Provides methods for Neutrosophic Analysis of Variance (NANOVA) for crossover designs and multi-session designs with direct and residual effects using interval-valued observations. The package computes neutrosophic sums of squares, mean squares, interval-valued F-statistics, significance tests, and multiple comparisons using Least Significant Difference (LSD) procedures. For crisp data, users may enter identical lower and upper response values to obtain classical Analysis of Variance (ANOVA) results. The basic idea of neutrosophic statistics is obtained from Smarandache (2014) <https://fs.unm.edu/NeutrosophicStatistics.pdf>, while the analysis procedures implemented in this package are newly developed.
Author: Boyina Devi Priyanka [aut, ctb], Neethu R.S [aut, ctb], Cini Varghese [aut, ctb], Mohd Harun [aut, ctb], Anindita Datta [aut, ctb], Vinaykumar L.N. [aut, cre]
Maintainer: Vinaykumar L.N. <vinaymandya123@gmail.com>

Diff between NeutroCODsAnalysis versions 0.0.1 dated 2026-06-09 and 0.1.0 dated 2026-06-10

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Package goldilocks updated to version 0.5.0 with previous version 0.4.0 dated 2025-01-08

Title: Goldilocks Adaptive Trial Designs for Time-to-Event Endpoints
Description: Implements the Goldilocks adaptive trial design for a time to event outcome using a piecewise exponential model and conjugate Gamma prior distributions. The method closely follows the article by Broglio and colleagues <doi:10.1080/10543406.2014.888569>, which allows users to explore the operating characteristics of different trial designs.
Author: Graeme L. Hickey [aut, cre] , Ying Wan [aut], Thevaa Chandereng [aut] , Becton, Dickinson and Company [cph], Tim Kacprowski [ctb]
Maintainer: Graeme L. Hickey <graemeleehickey@gmail.com>

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Package AIUQ updated to version 0.5.5 with previous version 0.5.4 dated 2026-05-25

Title: Ab Initio Uncertainty Quantification
Description: Uncertainty quantification and inverse estimation by probabilistic generative models from the beginning of the data analysis. An example is a Fourier basis method for inverse estimation in scattering analysis of microscopy videos. It does not require specifying a certain range of Fourier bases and it substantially reduces computational cost via the generalized Schur algorithm. See the reference: Mengyang Gu, Yue He, Xubo Liu and Yimin Luo (2023), <doi:10.48550/arXiv.2309.02468>, and Tong Lin, Jinseok Lee, Matt Helgeson, Megan T Valentine, Yimin Luo, Mengyang Gu (2026), <doi:10.48550/arXiv.2605.29424>.
Author: Yue He [aut], Xubo Liu [aut], Tong Lin [aut], Mengyang Gu [aut, cre]
Maintainer: Mengyang Gu <mengyang@pstat.ucsb.edu>

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Package SuperSurv (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:

2026-05-04 0.1.2
2026-03-26 0.1.1

Permanent link
Package nestedcv (with last version 0.8.2) was removed from CRAN

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

2026-04-10 0.8.2
2025-03-10 0.8.0
2024-11-27 0.7.12
2024-08-16 0.7.10
2024-07-04 0.7.9
2024-03-13 0.7.8
2024-01-30 0.7.4
2023-12-04 0.7.3
2023-10-26 0.7.0
2023-08-22 0.6.9
2023-07-02 0.6.7
2023-06-07 0.6.6
2023-05-30 0.6.4
2023-05-15 0.6.2
2023-04-16 0.6.1
2022-12-05 0.4.4
2022-10-23 0.4.0
2022-09-10 0.3.0
2022-07-07 0.2.3

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Package spmodel updated to version 0.13.0 with previous version 0.12.0 dated 2026-01-24

Title: Spatial Statistical Modeling and Prediction
Description: Fit, summarize, and predict for a variety of spatial statistical models applied to point-referenced and areal (lattice) data. Parameters are estimated using various methods. Additional modeling features include anisotropy, non-spatial random effects, partition factors, big data approaches, and more. Model-fit statistics are used to summarize, visualize, and compare models. Predictions at unobserved locations are readily obtainable. For additional details, see Dumelle et al. (2023) <doi:10.1371/journal.pone.0282524>.
Author: Michael Dumelle [aut, cre] , Matt Higham [aut] , Ryan A. Hill [ctb] , Michael Mahon [ctb] , Jay M. Ver Hoef [aut]
Maintainer: Michael Dumelle <Dumelle.Michael@epa.gov>

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Package r2rtf updated to version 1.3.1 with previous version 1.3.0 dated 2026-01-09

Title: Easily Create Production-Ready Rich Text Format (RTF) Tables and Figures
Description: Create production-ready Rich Text Format (RTF) tables and figures with flexible format.
Author: Yilong Zhang [aut], Siruo Wang [aut], Simiao Ye [aut], Fansen Kong [aut], Brian Lang [aut], Benjamin Wang [aut], Nan Xiao [ctb], Madhusudhan Ginnaram [ctb], Ruchitbhai Patel [aut, cre], Huei-Ling Chen [ctb], Peikun Wu [ctb], Uday Preetham Palukuru [c [...truncated...]
Maintainer: Ruchitbhai Patel <ruchitbhai.patel@merck.com>

Diff between r2rtf versions 1.3.0 dated 2026-01-09 and 1.3.1 dated 2026-06-10

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Package plotthis updated to version 0.12.1 with previous version 0.12.0 dated 2026-04-28

Title: High-Level Plotting Built Upon 'ggplot2' and Other Plotting Packages
Description: Provides high-level API and a wide range of options to create stunning, publication-quality plots effortlessly. It is built upon 'ggplot2' and other plotting packages, and is designed to be easy to use and to work seamlessly with 'ggplot2' objects. It is particularly useful for creating complex plots with multiple layers, facets, and annotations. It also provides a set of functions to create plots for specific types of data, such as Venn diagrams, alluvial diagrams, and phylogenetic trees. The package is designed to be flexible and customizable, and to work well with the 'ggplot2' ecosystem. The API can be found at <https://pwwang.github.io/plotthis/reference/index.html>.
Author: Panwen Wang [aut, cre]
Maintainer: Panwen Wang <pwwang@pwwang.com>

Diff between plotthis versions 0.12.0 dated 2026-04-28 and 0.12.1 dated 2026-06-10

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Package netmeta updated to version 3.6-0 with previous version 3.5-0 dated 2026-05-28

Title: Network Meta-Analysis using Frequentist Methods
Description: A comprehensive set of functions providing frequentist methods for network meta-analysis (Balduzzi et al., 2023) <doi:10.18637/jss.v106.i02> and supporting Schwarzer et al. (2015) <doi:10.1007/978-3-319-21416-0>, Chapter 8 "Network Meta-Analysis": - frequentist network meta-analysis following Rücker (2012) <doi:10.1002/jrsm.1058>; - additive network meta-analysis for combinations of treatments (Rücker et al., 2020) <doi:10.1002/bimj.201800167>; - network meta-analysis of binary data using the Mantel-Haenszel or non-central hypergeometric distribution method (Efthimiou et al., 2019) <doi:10.1002/sim.8158>, or penalised logistic regression (Evrenoglou et al., 2022) <doi:10.1002/sim.9562>; - rankograms and ranking of treatments by the Surface under the cumulative ranking curve (SUCRA) (Salanti et al., 2013) <doi:10.1016/j.jclinepi.2010.03.016>; - ranking of treatments using P-scores (frequentist analogue of SUCRAs without resampling) according to [...truncated...]
Author: Gerta Ruecker [aut] , Ulrike Krahn [aut], Jochem Koenig [aut] , Orestis Efthimiou [aut] , Annabel Davies [aut] , Theodoros Papakonstantinou [aut] , Theodoros Evrenoglou [ctb] , Krzysztof Ciomek [ctb] , Nana-adjoa Kwarteng [ctb] , Guido Schwarzer [aut, [...truncated...]
Maintainer: Guido Schwarzer <guido.schwarzer@uniklinik-freiburg.de>

Diff between netmeta versions 3.5-0 dated 2026-05-28 and 3.6-0 dated 2026-06-10

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Package mlr3misc updated to version 0.22.0 with previous version 0.21.0 dated 2026-02-26

Title: Helper Functions for 'mlr3'
Description: Frequently used helper functions and assertions used in 'mlr3' and its companion packages. Comes with helper functions for functional programming, for printing, to work with 'data.table', as well as some generally useful 'R6' classes. This package also supersedes the package 'BBmisc'.
Author: Marc Becker [cre, aut] , Michel Lang [aut] , Patrick Schratz [aut]
Maintainer: Marc Becker <marcbecker@posteo.de>

Diff between mlr3misc versions 0.21.0 dated 2026-02-26 and 0.22.0 dated 2026-06-10

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More information about mlr3misc at CRAN
Permanent link

Package mlr3 updated to version 1.7.0 with previous version 1.6.0 dated 2026-04-02

Title: Machine Learning in R - Next Generation
Description: Efficient, object-oriented programming on the building blocks of machine learning. Provides 'R6' objects for tasks, learners, resamplings, and measures. The package is geared towards scalability and larger datasets by supporting parallelization and out-of-memory data-backends like databases. While 'mlr3' focuses on the core computational operations, add-on packages provide additional functionality.
Author: Michel Lang [aut] , Bernd Bischl [aut] , Jakob Richter [aut] , Patrick Schratz [aut] , Giuseppe Casalicchio [ctb] , Stefan Coors [ctb] , Quay Au [ctb] , Martin Binder [aut], Florian Pfisterer [aut] , Raphael Sonabend [aut] , Lennart Schneider [ctb] , [...truncated...]
Maintainer: Marc Becker <marcbecker@posteo.de>

Diff between mlr3 versions 1.6.0 dated 2026-04-02 and 1.7.0 dated 2026-06-10

 DESCRIPTION                                |   14 
 MD5                                        |  357 ++++-----
 NEWS.md                                    |   24 
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Package epsiwal updated to version 0.2.0 with previous version 0.1.0 dated 2019-07-02

Title: Exact Post Selection Inference with Applications to the Lasso
Description: Implements the conditional estimation procedure of Lee, Sun, Sun and Taylor (2016) <doi:10.1214/15-AOS1371>. This procedure allows hypothesis testing on the mean of a normal random vector subject to linear constraints. Also supports computation of the MLE of the mean subject to the same constraints.
Author: Steven E. Pav [aut, cre]
Maintainer: Steven E. Pav <shabbychef@gmail.com>

Diff between epsiwal versions 0.1.0 dated 2019-07-02 and 0.2.0 dated 2026-06-10

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Package DRDID updated to version 1.3.0 with previous version 1.2.3 dated 2025-12-04

Title: Doubly Robust Difference-in-Differences Estimators
Description: Implements the locally efficient doubly robust difference-in-differences (DiD) estimators for the average treatment effect proposed by Sant'Anna and Zhao (2020) <doi:10.1016/j.jeconom.2020.06.003>. The estimator combines inverse probability weighting and outcome regression estimators (also implemented in the package) to form estimators with more attractive statistical properties. Two different estimation methods can be used to estimate the nuisance functions.
Author: Pedro H. C. Sant'Anna [aut, cre, cph], Jun Zhao [aut]
Maintainer: Pedro H. C. Sant'Anna <pedrohcgs@gmail.com>

Diff between DRDID versions 1.2.3 dated 2025-12-04 and 1.3.0 dated 2026-06-10

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Package autoFC updated to version 1.0.0.1001 with previous version 1.0.0.1000 dated 2026-05-27

Title: Automatic Toolkit for Construction, Optimization, Scoring and Simulation of Forced-Choice Tests
Description: Forced-choice (FC) response has gained increasing popularity and interest for its resistance to faking when well-designed (Cao & Drasgow, 2019 <doi:10.1037/apl0000414>). To established well-designed FC scales, typically each item within a block should measure different trait and have similar level of social desirability (Zhang et al., 2020 <doi:10.1177/1094428119836486>). Recent study also suggests the importance of high inter-item agreement of social desirability between items within a block (Pavlov et al., 2021 <doi:10.31234/osf.io/hmnrc>). In addition to this, FC developers may also need to maximize factor loading differences (Brown & Maydeu-Olivares, 2011 <doi:10.1177/0013164410375112>) or minimize item location differences (Cao & Drasgow, 2019 <doi:10.1037/apl0000414>) depending on scoring models. Decision of which items should be assigned to the same block, also called as item pairing, is thus critical to the quality of an FC test. Becau [...truncated...]
Author: Mengtong Li [cre, aut] , Tianjun Sun [aut] , Bo Zhang [aut]
Maintainer: Mengtong Li <mt_li@fudan.edu.cn>

Diff between autoFC versions 1.0.0.1000 dated 2026-05-27 and 1.0.0.1001 dated 2026-06-10

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