Fri, 27 Jun 2025

Package rprev updated to version 1.0.6 with previous version 1.0.5 dated 2021-05-04

Title: Estimating Disease Prevalence from Registry Data
Description: Estimates disease prevalence for a given index date using existing registry data extended with Monte Carlo simulations following the method of Crouch et al (2014) <doi: 10.1016/j.canep.2014.02.005>.
Author: Stuart Lacy [cre, aut], Simon Crouch [aut], Stephanie Lax [aut]
Maintainer: Stuart Lacy <stuart.lacy@york.ac.uk>

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Package Analitica updated to version 1.8.5 with previous version 1.8.1 dated 2025-06-14

Title: Exploratory Data Analysis, Group Comparison Tools, and Other Procedures
Description: Provides a comprehensive set of tools for descriptive statistics, graphical data exploration, outlier detection, homoscedasticity testing, and multiple comparison procedures. Includes manual implementations of Levene's test, Bartlett's test, and the Fligner-Killeen test, as well as post hoc comparison methods such as Tukey, Scheffé, Games-Howell, Brunner-Munzel, and others. This version introduces two new procedures: the Jonckheere-Terpstra trend test and the Jarque-Bera test with Glinskiy's (2024) correction. Designed for use in teaching, applied statistical analysis, and reproducible research.
Author: Carlos Jimenez-Gallardo [aut, cre]
Maintainer: Carlos Jimenez-Gallardo <carlos.jimenez@ufrontera.cl>

Diff between Analitica versions 1.8.1 dated 2025-06-14 and 1.8.5 dated 2025-06-27

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Package gsDesign2 updated to version 1.1.5 with previous version 1.1.4 dated 2025-06-06

Title: Group Sequential Design with Non-Constant Effect
Description: The goal of 'gsDesign2' is to enable fixed or group sequential design under non-proportional hazards. To enable highly flexible enrollment, time-to-event and time-to-dropout assumptions, 'gsDesign2' offers piecewise constant enrollment, failure rates, and dropout rates for a stratified population. This package includes three methods for designs: average hazard ratio, weighted logrank tests in Yung and Liu (2019) <doi:10.1111/biom.13196>, and MaxCombo tests. Substantial flexibility on top of what is in the 'gsDesign' package is intended for selecting boundaries.
Author: Keaven Anderson [aut], Yujie Zhao [aut, cre], Yilong Zhang [aut], John Blischak [aut], Yihui Xie [aut], Nan Xiao [aut], Jianxiao Yang [aut], Amin Shirazi [ctb], Ruixue Wang [ctb], Yi Cui [ctb], Ping Yang [ctb], Xin Tong Li [ctb], Chenxiang Li [ctb], [...truncated...]
Maintainer: Yujie Zhao <yujie.zhao@merck.com>

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Package copBasic updated to version 2.2.8 with previous version 2.2.7 dated 2025-01-25

Title: General Bivariate Copula Theory and Many Utility Functions
Description: Extensive functions for bivariate copula (bicopula) computations and related operations for bicopula theory. The lower, upper, product, and select other bicopula are implemented along with operations including the diagonal, survival copula, dual of a copula, co-copula, and numerical bicopula density. Level sets, horizontal and vertical sections are supported. Numerical derivatives and inverses of a bicopula are provided through which simulation is implemented. Bicopula composition, convex combination, asymmetry extension, and products also are provided. Support extends to the Kendall Function as well as the Lmoments thereof. Kendall Tau, Spearman Rho and Footrule, Gini Gamma, Blomqvist Beta, Hoeffding Phi, Schweizer- Wolff Sigma, tail dependency, tail order, skewness, and bivariate Lmoments are implemented, and positive/negative quadrant dependency, left (right) increasing (decreasing) are available. Other features include Kullback-Leibler Divergence, Vuong Procedure, spectral measure, [...truncated...]
Author: William Asquith [aut, cre]
Maintainer: William Asquith <william.asquith@ttu.edu>

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Package rbiom updated to version 2.2.1 with previous version 2.2.0 dated 2025-04-04

Title: Read/Write, Analyze, and Visualize 'BIOM' Data
Description: A toolkit for working with Biological Observation Matrix ('BIOM') files. Read/write all 'BIOM' formats. Compute rarefaction, alpha diversity, and beta diversity (including 'UniFrac'). Summarize counts by taxonomic level. Subset based on metadata. Generate visualizations and statistical analyses. CPU intensive operations are coded in C for speed.
Author: Daniel P. Smith [aut, cre] , Alkek Center for Metagenomics and Microbiome Research [cph, fnd]
Maintainer: Daniel P. Smith <dansmith01@gmail.com>

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Package mixedBayes updated to version 0.1.9 with previous version 0.1.8 dated 2025-05-15

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>

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Package groupedHyperframe updated to version 0.2.4 with previous version 0.2.3 dated 2025-06-05

Title: Grouped Hyper Data Frame: An Extension of Hyper Data Frame
Description: An S3 class 'groupedHyperframe' that inherits from hyper data frame. Batch processes on point-pattern hyper column. Aggregation of function-value-table hyper column(s) and numeric hyper column(s) over a nested grouping structure.
Author: Tingting Zhan [aut, cre] , Inna Chervoneva [aut]
Maintainer: Tingting Zhan <tingtingzhan@gmail.com>

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Package ForLion updated to version 0.3.0 with previous version 0.2.0 dated 2025-06-10

Title: 'ForLion' Algorithm to Find D-Optimal Designs for Experiments
Description: Designing experimental plans that involve both discrete and continuous factors with general parametric statistical models using the 'ForLion' algorithm and 'EW ForLion' algorithm. The algorithms will search for locally optimal designs and EW optimal designs under the D-criterion. Reference: Huang, Y., Li, K., Mandal, A., & Yang, J., (2024)<doi:10.1007/s11222-024-10465-x>.
Author: Yifei Huang [aut], Siting Lin [aut, cre], Jie Yang [aut]
Maintainer: Siting Lin <slin95@uic.edu>

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Package ripserr updated to version 1.0.0 with previous version 0.3.0 dated 2025-04-06

Title: Calculate Persistent Homology with Ripser-Based Engines
Description: Ports the Ripser <doi:10.48550/arXiv.1908.02518> and Cubical Ripser <doi:10.48550/arXiv.2005.12692> persistent homology calculation engines from C++. Can be used as a rapid calculation tool in topological data analysis pipelines.
Author: Raoul R. Wadhwa [aut] , Matt Piekenbrock [aut], Jason Cory Brunson [aut, cre] , Xinyi Zhang [aut], Alice Zhang [aut] , Kent Phipps [aut], Sean Hershkowitz [aut], Emily Noble [ctb], Aymeric Stamm [ctb] , Aidan Bryant [ctb], James Golabek [ctb], Jacob [...truncated...]
Maintainer: Jason Cory Brunson <cornelioid@gmail.com>

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Package httptest2 updated to version 1.2.0 with previous version 1.1.0 dated 2024-04-26

Title: Test Helpers for 'httr2'
Description: Testing and documenting code that communicates with remote servers can be painful. This package helps with writing tests for packages that use 'httr2'. It enables testing all of the logic on the R sides of the API without requiring access to the remote service, and it also allows recording real API responses to use as test fixtures. The ability to save responses and load them offline also enables writing vignettes and other dynamic documents that can be distributed without access to a live server.
Author: Neal Richardson [aut, cre] , Jonathan Keane [ctb], Maelle Salmon [ctb]
Maintainer: Neal Richardson <neal.p.richardson@gmail.com>

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Package eratosthenes updated to version 0.0.9 with previous version 0.0.2 dated 2024-09-20

Title: Archaeological Synchronism
Description: Estimation of unknown historical or archaeological dates subject to relationships with other relative dates and absolute constraints, derived as marginal densities from the full joint conditional, using a two-stage Gibbs sampler with consistent batch means to assess convergence. Features reporting on Monte Carlo standard errors, as well as tools for rule-based estimation of dates of production and use of artifact types, aligning and checking relative sequences, and evaluating the impact of the omission of relative/absolute events upon one another.
Author: Stephen A. Collins-Elliott [aut, cre]
Maintainer: Stephen A. Collins-Elliott <sce@utk.edu>

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Package restfulr updated to version 0.0.16 with previous version 0.0.15 dated 2022-06-16

Title: R Interface to RESTful Web Services
Description: Models a RESTful service as if it were a nested R list.
Author: Michael Lawrence [aut, cre]
Maintainer: Michael Lawrence <michafla@gene.com>

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Package jarbes updated to version 2.3.0 with previous version 2.2.5 dated 2025-03-28

Title: Just a Rather Bayesian Evidence Synthesis
Description: Provides a new class of Bayesian meta-analysis models that incorporates a model for internal and external validity bias. In this way, it is possible to combine studies of diverse quality and different types. For example, we can combine the results of randomized control trials (RCTs) with the results of observational studies (OS).
Author: Pablo Emilio Verde [aut, cre]
Maintainer: Pablo Emilio Verde <pabloemilio.verde@hhu.de>

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Package sleev updated to version 1.1.4 with previous version 1.1.3 dated 2025-06-12

Title: Semiparametric Likelihood Estimation with Errors in Variables
Description: Efficient regression analysis under general two-phase sampling, where Phase I includes error-prone data and Phase II contains validated data on a subset.
Author: Sarah Lotspeich [aut], Ran Tao [aut, cre], Joey Sherrill [prg], Jiangmei Xiong [ctb]
Maintainer: Ran Tao <r.tao@vanderbilt.edu>

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Package oeli updated to version 0.7.4 with previous version 0.7.3 dated 2025-05-19

Title: Some Utilities for Developing Data Science Software
Description: A collection of general-purpose helper functions that I (and maybe others) find useful when developing data science software. Includes tools for simulation, data transformation, input validation, and more.
Author: Lennart Oelschlaeger [aut, cre]
Maintainer: Lennart Oelschlaeger <oelschlaeger.lennart@gmail.com>

Diff between oeli versions 0.7.3 dated 2025-05-19 and 0.7.4 dated 2025-06-27

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Package nlsic updated to version 1.1.1 with previous version 1.1.0 dated 2025-05-16

Title: Non Linear Least Squares with Inequality Constraints
Description: We solve non linear least squares problems with optional equality and/or inequality constraints. Non linear iterations are globalized with back-tracking method. Linear problems are solved by dense QR decomposition from 'LAPACK' which can limit the size of treated problems. On the other side, we avoid condition number degradation which happens in classical quadratic programming approach. Inequality constraints treatment on each non linear iteration is based on 'NNLS' method (by Lawson and Hanson). We provide an original function 'lsi_ln' for solving linear least squares problem with inequality constraints in least norm sens. Thus if Jacobian of the problem is rank deficient a solution still can be provided. However, truncation errors are probable in this case. Equality constraints are treated by using a basis of Null-space. User defined function calculating residuals must return a list having residual vector (not their squared sum) and Jacobian. If Jacobian is not in the returned list, [...truncated...]
Author: Serguei Sokol [aut, cre]
Maintainer: Serguei Sokol <sokol@insa-toulouse.fr>

Diff between nlsic versions 1.1.0 dated 2025-05-16 and 1.1.1 dated 2025-06-27

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Package hyper.gam updated to version 0.1.2 with previous version 0.1.1 dated 2025-05-27

Title: Generalized Additive Models with Hyper Column
Description: Generalized additive models with a numeric hyper column tabulated on a common grid. Sign-adjustment based on the correlation of model prediction and a selected slice of the hyper column. Visualization of the integrand surface over the hyper column.
Author: Tingting Zhan [aut, cre] , Inna Chervoneva [aut] , Erjia Cui [ctb]
Maintainer: Tingting Zhan <tingtingzhan@gmail.com>

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Package ggpubr updated to version 0.6.1 with previous version 0.6.0 dated 2023-02-10

Title: 'ggplot2' Based Publication Ready Plots
Description: The 'ggplot2' package is excellent and flexible for elegant data visualization in R. However the default generated plots requires some formatting before we can send them for publication. Furthermore, to customize a 'ggplot', the syntax is opaque and this raises the level of difficulty for researchers with no advanced R programming skills. 'ggpubr' provides some easy-to-use functions for creating and customizing 'ggplot2'- based publication ready plots.
Author: Alboukadel Kassambara [aut, cre]
Maintainer: Alboukadel Kassambara <alboukadel.kassambara@gmail.com>

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Package dataRetrieval updated to version 2.7.19 with previous version 2.7.18 dated 2025-02-27

Title: Retrieval Functions for USGS and EPA Hydrology and Water Quality Data
Description: Collection of functions to help retrieve U.S. Geological Survey and U.S. Environmental Protection Agency water quality and hydrology data from web services.
Author: Laura DeCicco [aut, cre] , Robert Hirsch [aut] , David Lorenz [aut], Jordan Read [ctb], Jordan Walker [ctb], Lindsay Platt [ctb], David Watkins [aut] , David Blodgett [aut] , Mike Johnson [aut] , Aliesha Krall [ctb] , Lee Stanish [ctb] , Joeseph Zemm [...truncated...]
Maintainer: Laura DeCicco <ldecicco@usgs.gov>

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Package arima2 updated to version 3.4.0 with previous version 3.3.0 dated 2024-08-19

Title: Likelihood Based Inference for ARIMA Modeling
Description: Estimating and analyzing auto regressive integrated moving average (ARIMA) models. The primary function in this package is arima(), which fits an ARIMA model to univariate time series data using a random restart algorithm. This approach frequently leads to models that have model likelihood greater than or equal to that of the likelihood obtained by fitting the same model using the arima() function from the 'stats' package. This package enables proper optimization of model likelihoods, which is a necessary condition for performing likelihood ratio tests. This package relies heavily on the source code of the arima() function of the 'stats' package. For more information, please see Jesse Wheeler and Edward L. Ionides (2023) <doi:10.48550/arXiv.2310.01198>.
Author: Jesse Wheeler [aut, cre, cph], Noel McAllister [aut], Dhajanae Sylvertooth [aut], Edward Ionides [ctb], Brian Ripley [ctb] , R Core Team [cph]
Maintainer: Jesse Wheeler <jeswheel@umich.edu>

Diff between arima2 versions 3.3.0 dated 2024-08-19 and 3.4.0 dated 2025-06-27

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Package upset.hp updated to version 0.0.2 with previous version 0.0.1 dated 2025-06-04

Title: Generate UpSet Plots of VP and HP Based on the ASV Concept
Description: Using matrix layout to visualize the unique, common, or individual contribution of each predictor (or matrix of predictors) towards explained variation on different models. These contributions were derived from variation partitioning (VP) and hierarchical partitioning (HP), applying the algorithm of "Lai et al. (2022) Generalizing hierarchical and variation partitioning in multiple regression and canonical analyses using the rdacca.hp R package.Methods in Ecology and Evolution, 13: 782-788 <doi:10.1111/2041-210X.13800>".
Author: Jiangshan Lai [aut, cre] , Yao Liu [aut], Bangken Ying [aut]
Maintainer: Jiangshan Lai <lai@njfu.edu.cn>

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Package TVMVP updated to version 1.0.5 with previous version 1.0.4 dated 2025-05-29

Title: Time-Varying Minimum Variance Portfolio
Description: Provides the estimation of a time-dependent covariance matrix of returns with the intended use for portfolio optimization. The package offers methods for determining the optimal number of factors to be used in the covariance estimation, a hypothesis test of time-varying covariance, and user-friendly functions for portfolio optimization and rolling window evaluation. The local PCA method, method for determining the number of factors, and associated hypothesis test are based on Su and Wang (2017) <doi:10.1016/j.jeconom.2016.12.004>. The approach to time-varying portfolio optimization follows Fan et al. (2024) <doi:10.1016/j.jeconom.2022.08.007>. The regularisation applied to the residual covariance matrix adopts the technique introduced by Chen et al. (2019) <doi:10.1016/j.jeconom.2019.04.025>.
Author: Erik Lillrank [aut, cre] , Yukai Yang [aut]
Maintainer: Erik Lillrank <erik.lillrank@gmail.com>

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Package mapi updated to version 1.1.3 with previous version 1.0.5 dated 2022-01-19

Title: Mapping Averaged Pairwise Information
Description: Mapping Averaged Pairwise Information (MAPI) is an exploratory method providing graphical representations summarizing the spatial variation of pairwise metrics (eg. distance, similarity coefficient, ...) computed between georeferenced samples.
Author: Sylvain Piry [aut, cre] , Thomas Campolunghi [aut], Florent Cestier [aut], Karine Berthier [aut]
Maintainer: Sylvain Piry <sylvain.piry@inrae.fr>

Diff between mapi versions 1.0.5 dated 2022-01-19 and 1.1.3 dated 2025-06-27

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Package glorenz updated to version 0.1.1 with previous version 0.1.0 dated 2025-06-04

Title: Transformed and Relative Lorenz Curves for Survey Weighted Data
Description: Functions for constructing Transformed and Relative Lorenz curves with survey sampling weights. Given a variable of interest measured in two groups with scaled survey weights so that their hypothetical populations are of equal size, tlorenz() computes the proportion of members of the group with smaller values (ordered from smallest to largest) needed for their sum to match the sum of the top qth percentile of the group with higher values. rlorenz() shows the fraction of the total value of the group with larger values held by the pth percentile of those in the group with smaller values. Fd() is a survey weighted cumulative distribution function and Eps() is a survey weighted inverse cdf used in rlorenz(). Ramos, Graubard, and Gastwirth (2025) <doi:10.1093/jrsssa/qnaf044>.
Author: Mark Ramos [aut, cre, cph]
Maintainer: Mark Ramos <mlr6219@psu.edu>

Diff between glorenz versions 0.1.0 dated 2025-06-04 and 0.1.1 dated 2025-06-27

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Package coat updated to version 0.2.1 with previous version 0.2.0 dated 2023-07-11

Title: Conditional Method Agreement Trees (COAT)
Description: Agreement of continuously scaled measurements made by two techniques, devices or methods is usually evaluated by the well-established Bland-Altman analysis or plot. Conditional method agreement trees (COAT), proposed by Karapetyan, Zeileis, Henriksen, and Hapfelmeier (2023) <doi:10.48550/arXiv.2306.04456>, embed the Bland-Altman analysis in the framework of recursive partitioning to explore heterogeneous method agreement in dependence of covariates. COAT can also be used to perform a Bland-Altman test for differences in method agreement.
Author: Alexander Hapfelmeier [aut, cre] , Siranush Karapetyan [aut] , Achim Zeileis [aut]
Maintainer: Alexander Hapfelmeier <Alexander.Hapfelmeier@mri.tum.de>

Diff between coat versions 0.2.0 dated 2023-07-11 and 0.2.1 dated 2025-06-27

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Package xpose.nlmixr2 updated to version 0.4.1 with previous version 0.4.0 dated 2022-06-08

Title: Graphical Diagnostics for Pharmacometric Models: Extension to 'nlmixr2'
Description: Extension to 'xpose' to support 'nlmixr2'. Provides functions to import 'nlmixr2' fit data into an 'xpose' data object, allowing the use of 'xpose' for 'nlmixr2' model diagnostics.
Author: Justin Wilkins [aut, cre, cph], Matthew Fidler [aut, cph], Benjamin Guiastrennec [aut], Andrew C. Hooker [aut], Anna Olofsson [aut, cph], Sebastian Ueckert [aut], Ron Keizer [aut], Kajsa Harling [ctb], Mike K. Smith [ctb], Elodie Plan [ctb], Mats O. [...truncated...]
Maintainer: Justin Wilkins <justin.wilkins@occams.com>

Diff between xpose.nlmixr2 versions 0.4.0 dated 2022-06-08 and 0.4.1 dated 2025-06-27

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Package bigassertr updated to version 0.1.7 with previous version 0.1.6 dated 2023-01-10

Title: Assertion and Message Functions
Description: Enhanced message functions (cat() / message() / warning() / error()) using wrappers around sprintf(). Also, multiple assertion functions (e.g. to check class, length, values, files, arguments, etc.).
Author: Florian Prive [aut, cre]
Maintainer: Florian Prive <florian.prive.21@gmail.com>

Diff between bigassertr versions 0.1.6 dated 2023-01-10 and 0.1.7 dated 2025-06-27

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New package smvr with initial version 0.1.0
Package: smvr
Title: Simple Implementation of Semantic Versioning
Version: 0.1.0
Description: Simple implementation of Semantic Versioning 2.0.0 on the 'vctrs' package. This package provides a simple way to create, compare, and manipulate semantic versions in R. It is designed to be lightweight and easy to use.
License: MIT + file LICENSE
URL: https://eitsupi.github.io/smvr/, https://github.com/eitsupi/smvr
BugReports: https://github.com/eitsupi/smvr/issues
Depends: R (>= 4.1)
Imports: cli (>= 3.4.0), rlang (>= 1.1.0), vctrs
Suggests: dplyr, testthat (>= 3.0.0), tibble
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2025-06-24 12:31:56 UTC; rstudio
Author: Tatsuya Shima [aut, cre]
Maintainer: Tatsuya Shima <ts1s1andn@gmail.com>
Repository: CRAN
Date/Publication: 2025-06-27 13:40:02 UTC

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New package gemR with initial version 1.2.1
Encoding: UTF-8
Package: gemR
Title: General Effect Modelling
Version: 1.2.1
Date: 2025-06-23
Description: Two-step modeling with separation of sources of variation through analysis of variance and subsequent multivariate modeling through a range of unsupervised and supervised statistical methods. Separation can focus on removal of interfering effects or isolation of effects of interest. EF Mosleth et al. (2021) <doi:10.1038/s41598-021-82388-w> and EF Mosleth et al. (2020) <doi:10.1016/B978-0-12-409547-2.14882-6>.
Depends: R (>= 3.5.0)
Imports: ggplot2, scales, gridExtra, glmnet, pls, plsVarSel, mixlm, HDANOVA, lme4, pracma, neuralnet
License: GPL
LazyData: TRUE
NeedsCompilation: no
Packaged: 2025-06-24 09:18:35 UTC; kristian
Author: Kristian Hovde Liland [aut, cre], Ellen Faergestad Mosleth [ctb]
Maintainer: Kristian Hovde Liland <kristian.liland@nmbu.no>
Repository: CRAN
Date/Publication: 2025-06-27 13:10:02 UTC

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Package fdasrvf updated to version 2.4.0 with previous version 2.3.6 dated 2025-02-17

Title: Elastic Functional Data Analysis
Description: Performs alignment, PCA, and modeling of multidimensional and unidimensional functions using the square-root velocity framework (Srivastava et al., 2011 <doi:10.48550/arXiv.1103.3817> and Tucker et al., 2014 <DOI:10.1016/j.csda.2012.12.001>). This framework allows for elastic analysis of functional data through phase and amplitude separation.
Author: J. Derek Tucker [aut, cre] , Aymeric Stamm [ctb]
Maintainer: J. Derek Tucker <jdtuck@sandia.gov>

Diff between fdasrvf versions 2.3.6 dated 2025-02-17 and 2.4.0 dated 2025-06-27

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Package DistributionIV updated to version 0.1.2 with previous version 0.1.0 dated 2025-02-27

Title: Distributional Instrumental Variable (DIV) Model
Description: Distributional instrumental variable (DIV) model for estimation of the interventional distribution of the outcome Y under a do-intervention on the treatment X. Instruments, predictors and targets can be univariate or multivariate. Functionality includes estimation of the (conditional) interventional mean and quantiles, as well as sampling from the fitted (conditional) interventional distribution.
Author: Anastasiia Holovchak [aut, cre, ctb], Sorawit Saengkyongam [aut, ctb], Nicolai Meinshausen [aut, ctb], Xinwei Shen [aut, ctb]
Maintainer: Anastasiia Holovchak <anastasiia.holovchak@stat.math.ethz.ch>

Diff between DistributionIV versions 0.1.0 dated 2025-02-27 and 0.1.2 dated 2025-06-27

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New package ClimaRep with initial version 0.6
Package: ClimaRep
Title: Estimating Climate Representativeness
Version: 0.6
Description: Offers tools to estimate the climate representativeness of defined areas and quantifies and analyzes its transformation under future climate change scenarios. Approaches described in Mingarro and Lobo (2018) <doi:10.32800/abc.2018.41.0333> and Mingarro and Lobo (2022) <doi:10.1017/S037689292100014X>.
License: MIT + file LICENSE
Encoding: UTF-8
Suggests: testthat (>= 3.0.0)
Imports: ggplot2, terra, utils, stats, sf, tidyterra
NeedsCompilation: no
Packaged: 2025-06-24 11:38:33 UTC; mario
Author: Mario Mingarro Lopez [aut, cre]
Maintainer: Mario Mingarro Lopez <mario_mingarro@mncn.csic.es>
Repository: CRAN
Date/Publication: 2025-06-27 13:30:13 UTC

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New package clampSeg with initial version 1.2-0
Package: clampSeg
Title: Idealisation of Patch Clamp Recordings
Version: 1.2-0
Depends: R (>= 3.3.0)
Imports: stepR (>= 2.1.0), lowpassFilter, stats, methods
Suggests: testthat, R.cache (>= 0.10.0), R.rsp
Description: Implements the model-free multiscale idealisation approaches: Jump-Segmentation by MUltiResolution Filter (JSMURF), Hotz et al. (2013) <doi:10.1109/TNB.2013.2284063>, JUmp Local dEconvolution Segmentation filter (JULES), Pein et al. (2018) <doi:10.1109/TNB.2018.2845126>, and Heterogeneous Idealization by Local testing and DEconvolution (HILDE), Pein et al. (2021) <doi:10.1109/TNB.2020.3031202>. Further details on how to use them are given in the accompanying vignette.
VignetteBuilder: R.rsp
License: GPL-3
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2025-06-24 09:28:44 UTC; pein
Author: Pein Florian [aut, cre], Timo Aspelmeier [ctb]
Maintainer: Pein Florian <f.pein@lancaster.ac.uk>
Repository: CRAN
Date/Publication: 2025-06-27 13:30:08 UTC

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New package BayesRegDTR with initial version 1.0.1
Package: BayesRegDTR
Title: Bayesian Regression for Dynamic Treatment Regimes
Version: 1.0.1
Description: Methods to estimate optimal dynamic treatment regimes using Bayesian likelihood-based regression approach as described in Yu, W., & Bondell, H. D. (2023) <doi:10.1093/jrsssb/qkad016> Uses backward induction and dynamic programming theory for computing expected values. Offers options for future parallel computing.
License: GPL (>= 3)
Imports: Rcpp (>= 1.0.13-1), mvtnorm, foreach, progressr, stats, future
Depends: doRNG
Suggests: cli, testthat (>= 3.0.0), doFuture
LinkingTo: Rcpp, RcppArmadillo
Encoding: UTF-8
URL: https://github.com/jlimrasc/BayesRegDTR
BugReports: https://github.com/jlimrasc/BayesRegDTR/issues
NeedsCompilation: yes
Packaged: 2025-06-24 10:16:44 UTC; jerem
Author: Jeremy Lim [aut, cre], Weichang Yu [aut]
Maintainer: Jeremy Lim <jeremylim23@gmail.com>
Repository: CRAN
Date/Publication: 2025-06-27 13:20:02 UTC

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New package avseqmc with initial version 1.0.1
Package: avseqmc
Title: Anytime-Valid Sequential Estimation of Monte-Carlo p-Values
Version: 1.0.1
Description: Anytime-valid sequential estimation of the p-value of a test calibrated by Monte-Carlo simulation, as described in Stoepker & Castro (2024) <doi:10.48550/arXiv.2409.18908>.
License: GPL-3
Encoding: UTF-8
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
Author: Ivo V. Stoepker [aut, cre], Rui M. Castro [aut]
Maintainer: Ivo V. Stoepker <i.v.stoepker@tue.nl>
NeedsCompilation: no
Packaged: 2025-06-24 12:42:48 UTC; s136539
Repository: CRAN
Date/Publication: 2025-06-27 13:40:05 UTC

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Package unhcrthemes updated to version 0.7.0 with previous version 0.6.3 dated 2025-01-16

Title: UNHCR 'ggplot2' Theme and Colour Palettes
Description: A 'ggplot2' theme and color palettes following the United Nations High Commissioner for Refugees (UNHCR) Data Visualization Guidelines recommendations.
Author: Cedric Vidonne [aut, cre], Ahmadou Dicko [aut], UNHCR [cph]
Maintainer: Cedric Vidonne <cedric@vidonne.me>

Diff between unhcrthemes versions 0.6.3 dated 2025-01-16 and 0.7.0 dated 2025-06-27

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Package spaMM updated to version 4.6.1 with previous version 4.5.0 dated 2024-06-09

Title: Mixed-Effect Models, with or without Spatial Random Effects
Description: Inference based on models with or without spatially-correlated random effects, multivariate responses, or non-Gaussian random effects (e.g., Beta). Variation in residual variance (heteroscedasticity) can itself be represented by a mixed-effect model. Both classical geostatistical models (Rousset and Ferdy 2014 <doi:10.1111/ecog.00566>), and Markov random field models on irregular grids (as considered in the 'INLA' package, <https://www.r-inla.org>), can be fitted, with distinct computational procedures exploiting the sparse matrix representations for the latter case and other autoregressive models. Laplace approximations are used for likelihood or restricted likelihood. Penalized quasi-likelihood and other variants discussed in the h-likelihood literature (Lee and Nelder 2001 <doi:10.1093/biomet/88.4.987>) are also implemented.
Author: Francois Rousset [aut, cre, cph] , Jean-Baptiste Ferdy [aut, cph], Alexandre Courtiol [aut]
Maintainer: Francois Rousset <francois.rousset@umontpellier.fr>

Diff between spaMM versions 4.5.0 dated 2024-06-09 and 4.6.1 dated 2025-06-27

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 spaMM-4.6.1/spaMM/NAMESPACE                                       |   13 
 spaMM-4.6.1/spaMM/R/Beta.R                                        |    4 
 spaMM-4.6.1/spaMM/R/COMPoisson.R                                  |   21 
 spaMM-4.6.1/spaMM/R/GLM.fit.R                                     |    5 
 spaMM-4.6.1/spaMM/R/HLCor_body.R                                  |   10 
 spaMM-4.6.1/spaMM/R/HLFactorList.R                                |  448 +++++++---
 spaMM-4.6.1/spaMM/R/HLfit.R                                       |    2 
 spaMM-4.6.1/spaMM/R/HLfit_Internals.R                             |  266 ++++-
 spaMM-4.6.1/spaMM/R/HLfit_b_internals.R                           |   43 
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 spaMM-4.6.1/spaMM/R/HLfit_loop.R                                  |   17 
 spaMM-4.6.1/spaMM/R/HLframes.R                                    |    2 
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 spaMM-4.6.1/spaMM/R/LLM.R                                         |   35 
 spaMM-4.6.1/spaMM/R/LR.R                                          |   40 
 spaMM-4.6.1/spaMM/R/LevM_internals.R                              |    2 
 spaMM-4.6.1/spaMM/R/LevM_v_h.R                                    |    2 
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 spaMM-4.6.1/spaMM/R/calc_logdisp_cov.R                            |  259 +++--
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 spaMM-4.6.1/spaMM/R/fit_as_ZX.R                                   |   17 
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 spaMM-4.6.1/spaMM/R/fitme.R                                       |   13 
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 spaMM-4.6.1/spaMM/R/fitmecorrHLfit_body_internals.R               |  108 ++
 spaMM-4.6.1/spaMM/R/fitmv_body.R                                  |    8 
 spaMM-4.6.1/spaMM/R/generateName.R                                |    1 
 spaMM-4.6.1/spaMM/R/geo_info.R                                    |   11 
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 spaMM-4.6.1/spaMM/R/locoptim.R                                    |    6 
 spaMM-4.6.1/spaMM/R/mapMM.R                                       |  119 +-
 spaMM-4.6.1/spaMM/R/negbin1.R                                     |    4 
 spaMM-4.6.1/spaMM/R/negbin2.R                                     |   34 
 spaMM-4.6.1/spaMM/R/numInfo.R                                     |    2 
 spaMM-4.6.1/spaMM/R/plot_effects.R                                |   27 
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 spaMM-4.6.1/spaMM/R/poisson.R                                     |    6 
 spaMM-4.6.1/spaMM/R/postfit_internals.R                           |  121 +-
 spaMM-4.6.1/spaMM/R/predict.R                                     |   71 -
 spaMM-4.6.1/spaMM/R/predict_marg.R                                |    6 
 spaMM-4.6.1/spaMM/R/predict_mv.R                                  |  191 +---
 spaMM-4.6.1/spaMM/R/preprocess.R                                  |   86 +
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 spaMM-4.6.1/spaMM/R/preprocess_internals.R                        |  172 ++-
 spaMM-4.6.1/spaMM/R/profile.R                                     |   18 
 spaMM-4.6.1/spaMM/R/sXaug_EigenDense_QRP_Chol_scaled.R            |    8 
 spaMM-4.6.1/spaMM/R/sXaug_Matrix_CHM_Hess.R                       |   41 
 spaMM-4.6.1/spaMM/R/sXaug_Matrix_QRP_CHM.R                        |   68 -
 spaMM-4.6.1/spaMM/R/sXaug_sparsePrecisions.R                      |   36 
 spaMM-4.6.1/spaMM/R/safe_opt.R                                    |    6 
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 spaMM-4.6.1/spaMM/R/separator.R                                   |   52 -
 spaMM-4.6.1/spaMM/R/simulate.HL.R                                 |    5 
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 spaMM-4.6.1/spaMM/R/spaMM_boot.R                                  |   42 
 spaMM-4.6.1/spaMM/R/summary.HL.R                                  |   23 
 spaMM-4.6.1/spaMM/R/utils.R                                       |   30 
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 spaMM-4.6.1/spaMM/man/vcov.Rd                                     |   15 
 spaMM-4.6.1/spaMM/src/PLS.cpp                                     |   24 
 spaMM-4.6.1/spaMM/src/RcppExports.cpp                             |   13 
 spaMM-4.6.1/spaMM/src/internals.cpp                               |    9 
 spaMM-4.6.1/spaMM/tests/test-all.R                                |   16 
 spaMM-4.6.1/spaMM/tests/testthat/extralong/test-composite-extra.R |  105 +-
 spaMM-4.6.1/spaMM/tests/testthat/extralong/test-mv-corrFamily.R   |    8 
 spaMM-4.6.1/spaMM/tests/testthat/extralong/test-mv-extra.R        |  102 +-
 spaMM-4.6.1/spaMM/tests/testthat/test-ANOVA-&-lmerTest.R          |    2 
 spaMM-4.6.1/spaMM/tests/testthat/test-AR1.R                       |    2 
 spaMM-4.6.1/spaMM/tests/testthat/test-CAR.R                       |    2 
 spaMM-4.6.1/spaMM/tests/testthat/test-COMPoisson.R                |    4 
 spaMM-4.6.1/spaMM/tests/testthat/test-GxE_variance_stability.R    |    4 
 spaMM-4.6.1/spaMM/tests/testthat/test-HLCor.R                     |    2 
 spaMM-4.6.1/spaMM/tests/testthat/test-HLfit.R                     |    2 
 spaMM-4.6.1/spaMM/tests/testthat/test-IMRF.R                      |    4 
 spaMM-4.6.1/spaMM/tests/testthat/test-Infusion.R                  |    4 
 spaMM-4.6.1/spaMM/tests/testthat/test-IsoriX-new.R                |    2 
 spaMM-4.6.1/spaMM/tests/testthat/test-LLM.R                       |    2 
 spaMM-4.6.1/spaMM/tests/testthat/test-LRT-boot.R                  |    2 
 spaMM-4.6.1/spaMM/tests/testthat/test-MSFDR.R                     |    2 
 spaMM-4.6.1/spaMM/tests/testthat/test-Nugget.R                    |    2 
 spaMM-4.6.1/spaMM/tests/testthat/test-Rasch.R                     |    4 
 spaMM-4.6.1/spaMM/tests/testthat/test-X.GCA.R                     |    2 
 spaMM-4.6.1/spaMM/tests/testthat/test-adjacency-corrMatrix.R      |    6 
 spaMM-4.6.1/spaMM/tests/testthat/test-adjacency-long.R            |    4 
 spaMM-4.6.1/spaMM/tests/testthat/test-augZXy.R                    |    2 
 spaMM-4.6.1/spaMM/tests/testthat/test-blackbox.R                  |    4 
 spaMM-4.6.1/spaMM/tests/testthat/test-cAIC.R                      |    2 
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 spaMM-4.6.1/spaMM/tests/testthat/test-confint.R                   |   19 
 spaMM-4.6.1/spaMM/tests/testthat/test-corMatern.R                 |    2 
 spaMM-4.6.1/spaMM/tests/testthat/test-corrFamilies.R              |   22 
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 spaMM-4.6.1/spaMM/tests/testthat/test-covStruct.R                 |only
 spaMM-4.6.1/spaMM/tests/testthat/test-dhglm.R                     |    6 
 spaMM-4.6.1/spaMM/tests/testthat/test-distMatrix.R                |    2 
 spaMM-4.6.1/spaMM/tests/testthat/test-extractors-spprec.R         |    2 
 spaMM-4.6.1/spaMM/tests/testthat/test-filled.mapMM.R              |    2 
 spaMM-4.6.1/spaMM/tests/testthat/test-fixedLRT.R                  |    2 
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 spaMM-4.6.1/spaMM/tests/testthat/test-mv.R                        |    2 
 spaMM-4.6.1/spaMM/tests/testthat/test-negbin1.R                   |    2 
 spaMM-4.6.1/spaMM/tests/testthat/test-nested-geostat.R            |    2 
 spaMM-4.6.1/spaMM/tests/testthat/test-numInfo.R                   |    2 
 spaMM-4.6.1/spaMM/tests/testthat/test-obsInfo.R                   |    7 
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 spaMM-4.6.1/spaMM/tests/testthat/test-poly.R                      |   12 
 spaMM-4.6.1/spaMM/tests/testthat/test-predVar-Matern-corrMatrix.R |   10 
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 spaMM-4.6.1/spaMM/tests/testthat/test-rank.R                      |    6 
 spaMM-4.6.1/spaMM/tests/testthat/test-salamander.R                |    2 
 spaMM-4.6.1/spaMM/tests/testthat/test-simulate.R                  |    2 
 spaMM-4.6.1/spaMM/tests/testthat/test-spaMM.R                     |    2 
 spaMM-4.6.1/spaMM/tests/testthat/test-spaMM.filled.contour.R      |    2 
 spaMM-4.6.1/spaMM/tests/testthat/test-spaMM_glm.R                 |    2 
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 194 files changed, 2806 insertions(+), 1620 deletions(-)

More information about spaMM at CRAN
Permanent link

New package safeframe with initial version 1.0.0
Package: safeframe
Title: Generic Data Tagging and Validation Tool
Version: 1.0.0
Description: Provides tools to help tag and validate data according to user-specified rules. The 'safeframe' class adds variable level attributes to 'data.frame' columns. Once tagged, these variables can be seamlessly used in downstream analyses, making data pipelines clearer, more robust, and more reliable.
License: MIT + file LICENSE
URL: https://epiverse-trace.github.io/safeframe/, https://github.com/epiverse-trace/safeframe
BugReports: https://github.com/epiverse-trace/safeframe/issues
Depends: R (>= 4.1.0)
Imports: checkmate, lifecycle, rlang, tidyselect
Suggests: callr, dplyr, knitr, magrittr, rmarkdown, spelling, testthat, tibble
VignetteBuilder: knitr
Encoding: UTF-8
Language: en-GB
NeedsCompilation: no
Packaged: 2025-06-24 08:18:01 UTC; chartgerink
Author: Chris Hartgerink [cre, aut] , Hugo Gruson [rev] , data.org [cph]
Maintainer: Chris Hartgerink <chris@data.org>
Repository: CRAN
Date/Publication: 2025-06-27 13:00:02 UTC

More information about safeframe at CRAN
Permanent link

New package REMixed with initial version 0.1.0
Package: REMixed
Title: Regularized Estimation in Mixed Effect Model
Version: 0.1.0
Maintainer: Auriane Gabaut <auriane.gabaut@inria.fr>
Description: Implementation of an algorithm in two steps to estimate parameters of a model whose latent dynamics are inferred through latent processes, jointly regularized. This package uses 'Monolix' software (<https://monolixsuite.slp-software.com/>), which provide robust statistical method for non-linear mixed effects modeling. 'Monolix' must have been installed prior to use.
SystemRequirements: 'Monolix' (<https://monolixsuite.slp-software.com/>)
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
Imports: deSolve, Rsmlx, doSNOW, dplyr, fastGHQuad, ggplot2, snow, stringr, Rmpfr
Depends: R (>= 3.5.0), foreach
NeedsCompilation: no
Packaged: 2025-06-23 12:19:34 UTC; auria
Author: Auriane Gabaut [aut, cre], Ariane Bercu [aut], Melanie Prague [aut], Cecile Proust-Lima [aut]
Repository: CRAN
Date/Publication: 2025-06-27 12:50:06 UTC

More information about REMixed at CRAN
Permanent link

New package mdsOpt with initial version 0.7-7
Package: mdsOpt
Title: Searching for Optimal MDS Procedure for Metric and Interval-Valued Data
Version: 0.7-7
Date: 2025-06-26
Depends: R (>= 3.6.0), smacof, clusterSim, symbolicDA
Imports: animation, plotrix, spdep
Suggests: testthat, R.rsp
VignetteBuilder: R.rsp
Description: Selecting the optimal multidimensional scaling (MDS) procedure for metric data via metric MDS (ratio, interval, mspline) and nonmetric MDS (ordinal). Selecting the optimal multidimensional scaling (MDS) procedure for interval-valued data via metric MDS (ratio, interval, mspline).Selecting the optimal multidimensional scaling procedure for interval-valued data by varying all combinations of normalization and optimization methods.Selecting the optimal MDS procedure for statistical data referring to the evaluation of tourist attractiveness of Lower Silesian counties. (Borg, I., Groenen, P.J.F., Mair, P. (2013) <doi:10.1007/978-3-642-31848-1>, Walesiak, M. (2016) <doi:10.15611/ekt.2016.2.01>, Walesiak, M. (2017) <doi:10.15611/ekt.2017.3.01>).
License: GPL (>= 2)
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2025-06-27 09:59:17 UTC; andrzej
Author: Marek Walesiak [aut] , Andrzej Dudek [aut, cre]
Maintainer: Andrzej Dudek <andrzej.dudek@ue.wroc.pl>
Repository: CRAN
Date/Publication: 2025-06-27 12:10:02 UTC

More information about mdsOpt at CRAN
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Package EMC2 updated to version 3.2.0 with previous version 3.1.1 dated 2025-04-06

Title: Bayesian Hierarchical Analysis of Cognitive Models of Choice
Description: Fit Bayesian (hierarchical) cognitive models using a linear modeling language interface using particle Metropolis Markov chain Monte Carlo sampling with Gibbs steps. The diffusion decision model (DDM), linear ballistic accumulator model (LBA), racing diffusion model (RDM), and the lognormal race model (LNR) are supported. Additionally, users can specify their own likelihood function and/or choose for non-hierarchical estimation, as well as for a diagonal, blocked or full multivariate normal group-level distribution to test individual differences. Prior specification is facilitated through methods that visualize the (implied) prior. A wide range of plotting functions assist in assessing model convergence and posterior inference. Models can be easily evaluated using functions that plot posterior predictions or using relative model comparison metrics such as information criteria or Bayes factors. References: Stevenson et al. (2024) <doi:10.31234/osf.io/2e4dq>.
Author: Niek Stevenson [aut, cre] , Michelle Donzallaz [aut], Andrew Heathcote [aut], Steven Miletic [ctb], Raphael Hartmann [ctb], Karl C. Klauer [ctb], Steven G. Johnson [ctb], Jean M. Linhart [ctb], Brian Gough [ctb], Gerard Jungman [ctb], Rudolf Schuerer [...truncated...]
Maintainer: Niek Stevenson <niek.stevenson@gmail.com>

Diff between EMC2 versions 3.1.1 dated 2025-04-06 and 3.2.0 dated 2025-06-27

 EMC2-3.1.1/EMC2/R/variant_blocked.R                                          |only
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 EMC2-3.2.0/EMC2/DESCRIPTION                                                  |   16 
 EMC2-3.2.0/EMC2/MD5                                                          |  194 -
 EMC2-3.2.0/EMC2/NAMESPACE                                                    |   27 
 EMC2-3.2.0/EMC2/NEWS.md                                                      |   19 
 EMC2-3.2.0/EMC2/R/EMC2-package.R                                             |    9 
 EMC2-3.2.0/EMC2/R/MRI.R                                                      | 1201 ++++++++--
 EMC2-3.2.0/EMC2/R/RcppExports.R                                              |   84 
 EMC2-3.2.0/EMC2/R/bridge_sampling.R                                          |    8 
 EMC2-3.2.0/EMC2/R/define_variants.R                                          |   38 
 EMC2-3.2.0/EMC2/R/design.R                                                   |  392 +--
 EMC2-3.2.0/EMC2/R/factor_analysis.R                                          |  386 +--
 EMC2-3.2.0/EMC2/R/fitting.R                                                  |   98 
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 EMC2-3.2.0/EMC2/R/group_design.R                                             |only
 EMC2-3.2.0/EMC2/R/joint.R                                                    |    4 
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New package detectXOR with initial version 0.1.0
Package: detectXOR
Title: XOR Pattern Detection and Visualization
Version: 0.1.0
Description: Provides tools for detecting XOR-like patterns in variable pairs in two-class data sets. Includes visualizations for pattern exploration and reporting capabilities with both text and HTML output formats.
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: dplyr (>= 1.1.0), ggplot2 (>= 3.4.0), ggh4x (>= 0.2.3), tibble (>= 3.1.8), reshape2 (>= 1.4.4), glue (>= 1.6.0), magrittr (>= 2.0.0), stats, ggthemes, DescTools (>= 0.99.50), utils, methods, grDevices, knitr, kableExtra, htmltools, base64enc
Suggests: testthat (>= 3.0.0), rmarkdown, doParallel, foreach, parallel (>= 4.2.0), future (>= 1.28.0), future.apply (>= 1.10.0), pbmcapply (>= 1.5.0)
SystemRequirements: GNU make
Depends: R (>= 3.5.0)
URL: https://github.com/JornLotsch/detectXOR
BugReports: https://github.com/JornLotsch/detectXOR/issues
NeedsCompilation: no
Packaged: 2025-06-24 05:54:01 UTC; joern
Author: Jorn Lotsch [aut, cre] , Alfred Ultsch [aut]
Maintainer: Jorn Lotsch <j.lotsch@em.uni-frankfurt.de>
Repository: CRAN
Date/Publication: 2025-06-27 13:00:06 UTC

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Package BayesMallows updated to version 2.2.5 with previous version 2.2.4 dated 2025-06-13

Title: Bayesian Preference Learning with the Mallows Rank Model
Description: An implementation of the Bayesian version of the Mallows rank model (Vitelli et al., Journal of Machine Learning Research, 2018 <https://jmlr.org/papers/v18/15-481.html>; Crispino et al., Annals of Applied Statistics, 2019 <doi:10.1214/18-AOAS1203>; Sorensen et al., R Journal, 2020 <doi:10.32614/RJ-2020-026>; Stein, PhD Thesis, 2023 <https://eprints.lancs.ac.uk/id/eprint/195759>). Both Metropolis-Hastings and sequential Monte Carlo algorithms for estimating the models are available. Cayley, footrule, Hamming, Kendall, Spearman, and Ulam distances are supported in the models. The rank data to be analyzed can be in the form of complete rankings, top-k rankings, partially missing rankings, as well as consistent and inconsistent pairwise preferences. Several functions for plotting and studying the posterior distributions of parameters are provided. The package also provides functions for estimating the partition function (normalizing constant) of the Mallows rank mo [...truncated...]
Author: Oystein Sorensen [aut, cre] , Waldir Leoncio [aut], Valeria Vitelli [aut] , Marta Crispino [aut], Qinghua Liu [aut], Cristina Mollica [aut], Luca Tardella [aut], Anja Stein [aut]
Maintainer: Oystein Sorensen <oystein.sorensen.1985@gmail.com>

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Package PatientProfiles updated to version 1.4.1 with previous version 1.4.0 dated 2025-05-30

Title: Identify Characteristics of Patients in the OMOP Common Data Model
Description: Identify the characteristics of patients in data mapped to the Observational Medical Outcomes Partnership (OMOP) common data model.
Author: Marti Catala [aut, cre] , Yuchen Guo [aut] , Mike Du [aut] , Kim Lopez-Guell [aut] , Edward Burn [aut] , Nuria Mercade-Besora [aut] , Xintong Li [ctb] , Xihang Chen [ctb]
Maintainer: Marti Catala <marti.catalasabate@ndorms.ox.ac.uk>

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Package GCCfactor updated to version 1.1.0 with previous version 1.0.1 dated 2023-10-30

Title: GCC Estimation of the Multilevel Factor Model
Description: Provides methods for model selection, estimation, inference, and simulation for the multilevel factor model, based on the principal component estimation and generalised canonical correlation approach. Details can be found in "Generalised Canonical Correlation Estimation of the Multilevel Factor Model." Lin and Shin (2025) <doi:10.2139/ssrn.4295429>.
Author: Rui Lin [aut, cre], Yongcheol Shin [aut]
Maintainer: Rui Lin <ruilin1081@gmail.com>

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Package EpiEstim updated to version 2.2-5 with previous version 2.2-4.1 dated 2025-06-23

Title: Estimate Time Varying Reproduction Numbers from Epidemic Curves
Description: Tools to quantify transmissibility throughout an epidemic from the analysis of time series of incidence as described in Cori et al. (2013) <doi:10.1093/aje/kwt133> and Wallinga and Teunis (2004) <doi:10.1093/aje/kwh255>.
Author: Anne Cori [aut, cre] , Simon Cauchemez [ctb], Neil M. Ferguson [ctb] , Christophe Fraser [ctb] , Elisabeth Dahlqwist [ctb] , P. Alex Demarsh [ctb], Thibaut Jombart [ctb] , Zhian N. Kamvar [ctb] , Justin Lessler [ctb] , Shikun Li [ctb], Jonathan A. Po [...truncated...]
Maintainer: Anne Cori <a.cori@imperial.ac.uk>

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Package resquin updated to version 0.1.1 with previous version 0.0.2 dated 2024-09-11

Title: Response Quality Indicators for Survey Research
Description: Calculate common survey data quality indicators for multi-item scales and matrix questions. Currently supports the calculation of response style indicators and response distribution indicators. For an overview on response quality indicators see Bhaktha N, Henning S, Clemens L (2024). 'Characterizing response quality in surveys with multi-item scales: A unified framework' <https://osf.io/9gs67/>.
Author: Matthias Roth [aut, cre, cph] , Nivedita Bhaktha [aut, ctb], Matthias Bluemke [aut, ctb], Thomas Knopf [aut, ctb], Fabienne Kraemer [aut, ctb], Clemens Lechner [aut, ctb], Cagla Yildiz [aut, ctb]
Maintainer: Matthias Roth <matthias.roth@gesis.org>

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New package oppr with initial version 1.0.5
Package: oppr
Version: 1.0.5
Title: Optimal Project Prioritization
Description: A decision support tool for prioritizing conservation projects. Prioritizations can be developed by maximizing expected feature richness, expected phylogenetic diversity, the number of features that meet persistence targets, or identifying a set of projects that meet persistence targets for minimal cost. Constraints (e.g. lock in specific actions) and feature weights can also be specified to further customize prioritizations. After defining a project prioritization problem, solutions can be obtained using exact algorithms, heuristic algorithms, or random processes. In particular, it is recommended to install the 'Gurobi' optimizer (available from <https://www.gurobi.com>) because it can identify optimal solutions very quickly. Finally, methods are provided for comparing different prioritizations and evaluating their benefits. For more information, see Hanson et al. (2019) <doi:10.1111/2041-210X.13264>.
Imports: utils, methods, stats, Matrix, magrittr (>= 1.5), uuid (>= 0.1.2), proto (>= 1.0.0), cli (>= 1.0.1), assertthat (>= 0.2.0), tibble (>= 2.0.0), ape (>= 5.2), tidytree (>= 0.3.3), ggplot2 (>= 3.5.0), viridisLite (>= 0.3.0), lpSolveAPI (>= 5.5.2.0.17), withr (>= 2.4.1), rlang (>= 1.1.3)
Suggests: testthat (>= 2.0.0), knitr (>= 1.20), roxygen2 (>= 6.1.0), rmarkdown (>= 1.10), gurobi (>= 8.0.0), Rsymphony (>= 0.1.28), ggtree (>= 2.4.2), lpsymphony (>= 1.10.0), shiny (>= 1.2.0), rhandsontable (>= 0.3.7), tidyr (>= 0.8.2), fansi (>= 1.0.6)
Depends: R(>= 3.4.0)
LinkingTo: Rcpp (>= 0.12.19), RcppArmadillo (>= 0.9.100.5.0), RcppProgress (>= 0.4.1)
License: GPL-3
LazyData: true
URL: https://prioritizr.github.io/oppr/
BugReports: https://github.com/prioritizr/oppr/issues
VignetteBuilder: knitr, rmarkdown
Encoding: UTF-8
Language: en-US
NeedsCompilation: yes
Packaged: 2025-06-26 23:39:54 UTC; jeff
Author: Jeffrey O Hanson [aut, cre] , Richard Schuster [aut] , Matthew Strimas-Mackey [aut] , Joseph R Bennett [aut]
Maintainer: Jeffrey O Hanson <jeffrey.hanson@uqconnect.edu.au>
Repository: CRAN
Date/Publication: 2025-06-27 07:30:02 UTC

More information about oppr at CRAN
Permanent link

Package madshapR updated to version 2.0.0 with previous version 1.1.0 dated 2024-04-23

Title: Functions to Support Data Management and Processing Using the Maelstrom Research Approach
Description: Functions to support data cleaning, evaluation, and description, developed for integration with Maelstrom Research software tools. 'madshapR' provides functions primarily to evaluate and manipulate datasets and data dictionaries in preparation for data harmonization with the package 'Rmonize' and to facilitate integration and transfer between RStudio servers and secure Opal environments. 'madshapR' functions can be used independently but are optimized in conjunction with ‘Rmonize’ functions for streamlined and coherent harmonization processing.
Author: Guillaume Fabre [aut, cre] , Maelstrom Research [aut, fnd, cph]
Maintainer: Guillaume Fabre <guijoseph.fabre@gmail.com>

Diff between madshapR versions 1.1.0 dated 2024-04-23 and 2.0.0 dated 2025-06-27

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Package LorenzRegression updated to version 2.2.0 with previous version 2.1.0 dated 2024-10-11

Title: Lorenz and Penalized Lorenz Regressions
Description: Inference for the Lorenz and penalized Lorenz regressions. More broadly, the package proposes functions to assess inequality and graphically represent it. The Lorenz Regression procedure is introduced in Heuchenne and Jacquemain (2022) <doi:10.1016/j.csda.2021.107347> and in Jacquemain, A., C. Heuchenne, and E. Pircalabelu (2024) <doi:10.1214/23-EJS2200>.
Author: Alexandre Jacquemain [aut, cre] , Xingjie Shi [ctb]
Maintainer: Alexandre Jacquemain <aljacquemain@gmail.com>

Diff between LorenzRegression versions 2.1.0 dated 2024-10-11 and 2.2.0 dated 2025-06-27

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Package libdeflate updated to version 1.24-3 with previous version 1.24-2 dated 2025-06-24

Title: DEFLATE Compression and Static Library
Description: Whole-buffer DEFLATE-based compression and decompression of raw vectors using the 'libdeflate' library (see <https://github.com/ebiggers/libdeflate>). Provides the user with additional control over the speed and the quality of DEFLATE compression compared to the fixed level of compression offered in R's 'memCompress()' function. Also provides the 'libdeflate' static library and 'C' headers along with a 'CMake' target and 'package‑config' file that ease linking of 'libdeflate' in packages that compile and statically link bundled libraries using 'CMake'.
Author: Tyler Morgan-Wall [aut, cre] , Eric Biggers [aut, cph], Google LLC [cph], Kevin Ushey [cph]
Maintainer: Tyler Morgan-Wall <tylermw@gmail.com>

Diff between libdeflate versions 1.24-2 dated 2025-06-24 and 1.24-3 dated 2025-06-27

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Package CooccurrenceAffinity updated to version 1.0.2 with previous version 1.0 dated 2023-05-03

Title: Affinity in Co-Occurrence Data
Description: Computes a novel metric of affinity between two entities based on their co-occurrence (using binary presence/absence data). The metric and its MLE, alpha hat, were advanced in Mainali, Slud, et al, 2021 <doi:10.1126/sciadv.abj9204>. Various types of confidence intervals and median interval were developed in Mainali and Slud, 2022 <doi:10.1101/2022.11.01.514801>. The `finches` dataset is now bundled internally (no longer pulled via the cooccur package, which has been dropped).
Author: Kumar Mainali [aut, cre], Eric Slud [aut]
Maintainer: Kumar Mainali <kpmainali@gmail.com>

Diff between CooccurrenceAffinity versions 1.0 dated 2023-05-03 and 1.0.2 dated 2025-06-27

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Permanent link

Package lfl updated to version 2.3.0 with previous version 2.2.1 dated 2024-10-22

Title: Linguistic Fuzzy Logic
Description: Various algorithms related to linguistic fuzzy logic: mining for linguistic fuzzy association rules, composition of fuzzy relations, performing perception-based logical deduction (PbLD), and forecasting time-series using fuzzy rule-based ensemble (FRBE). The package also contains basic fuzzy-related algebraic functions capable of handling missing values in different styles (Bochvar, Sobocinski, Kleene etc.), computation of Sugeno integrals and fuzzy transform.
Author: Michal Burda [aut, cre]
Maintainer: Michal Burda <michal.burda@osu.cz>

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