Sat, 11 Oct 2025

Package nlmixr2rpt updated to version 0.2.2 with previous version 0.2.1 dated 2025-07-17

Title: Templated Word and PowerPoint Reporting of 'nlmixr2' Fitting Results
Description: This allows you to generate reporting workflows around 'nlmixr2' analyses with outputs in Word and PowerPoint. You can specify figures, tables and report structure in a user-definable 'YAML' file. Also you can use the internal functions to access the figures and tables to allow their including in other outputs (e.g. R Markdown).
Author: John Harrold [aut, cre]
Maintainer: John Harrold <john.m.harrold@gmail.com>

Diff between nlmixr2rpt versions 0.2.1 dated 2025-07-17 and 0.2.2 dated 2025-10-11

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Package omixVizR updated to version 1.4.0 with previous version 1.1.3 dated 2025-07-20

Title: A Toolkit for Omics Data Visualization
Description: Provides a suite of tools for the comprehensive visualization of multi-omics data, including genomics, transcriptomics, and proteomics. Offers user-friendly functions to generate publication-quality plots, thereby facilitating the exploration and interpretation of complex biological datasets. Supports seamless integration with popular R visualization frameworks and is well-suited for both exploratory data analysis and the presentation of final results. Key formats and methods are presented in Huang, S., et al. (2024) "The Born in Guangzhou Cohort Study enables generational genetic discoveries" <doi:10.1038/s41586-023-06988-4>.
Author: Zhen Lu [aut, cre]
Maintainer: Zhen Lu <luzh29@mail2.sysu.edu.cn>

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Package DepthProc updated to version 2.1.6 with previous version 2.1.5 dated 2022-02-03

Title: Statistical Depth Functions for Multivariate Analysis
Description: Data depth concept offers a variety of powerful and user friendly tools for robust exploration and inference for multivariate data. The offered techniques may be successfully used in cases of lack of our knowledge on parametric models generating data due to their nature. The package consist of among others implementations of several data depth techniques involving multivariate quantile-quantile plots, multivariate scatter estimators, multivariate Wilcoxon tests and robust regressions.
Author: Zygmunt Zawadzki [aut, cre], Daniel Kosiorowski [aut], Krzysztof Slomczynski [ctb], Mateusz Bocian [ctb], Anna Wegrzynkiewicz [ctb]
Maintainer: Zygmunt Zawadzki <zygmunt@zstat.pl>

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Package import updated to version 1.3.3 with previous version 1.3.2 dated 2024-01-21

Title: An Import Mechanism for R
Description: Alternative mechanism for importing objects from packages and R modules. The syntax allows for importing multiple objects with a single command in an expressive way. The import package bridges some of the gap between using library (or require) and direct (single-object) imports. Furthermore the imported objects are not placed in the current environment.
Author: Stefan Milton Bache [aut], Magnus Thor Torfason [aut, cre]
Maintainer: Magnus Thor Torfason <m@zulutime.net>

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Package datawizard updated to version 1.3.0 with previous version 1.2.0 dated 2025-07-17

Title: Easy Data Wrangling and Statistical Transformations
Description: A lightweight package to assist in key steps involved in any data analysis workflow: (1) wrangling the raw data to get it in the needed form, (2) applying preprocessing steps and statistical transformations, and (3) compute statistical summaries of data properties and distributions. It is also the data wrangling backend for packages in 'easystats' ecosystem. References: Patil et al. (2022) <doi:10.21105/joss.04684>.
Author: Indrajeet Patil [aut] , Etienne Bacher [aut, cre] , Dominique Makowski [aut] , Daniel Luedecke [aut] , Mattan S. Ben-Shachar [aut] , Brenton M. Wiernik [aut] , Remi Theriault [ctb] , Thomas J. Faulkenberry [rev], Robert Garrett [rev]
Maintainer: Etienne Bacher <etienne.bacher@protonmail.com>

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Package bistablehistory updated to version 1.1.3 with previous version 1.1.2 dated 2023-09-13

Title: Cumulative History Analysis for Bistable Perception Time Series
Description: Estimates cumulative history for time-series for continuously viewed bistable perceptual rivalry displays. Computes cumulative history via a homogeneous first order differential process. I.e., it assumes exponential growth/decay of the history as a function time and perceptually dominant state, Pastukhov & Braun (2011) <doi:10.1167/11.10.12>. Supports Gamma, log normal, and normal distribution families. Provides a method to compute history directly and example of using the computation on a custom Stan code.
Author: Alexander Pastukhov [aut, cre]
Maintainer: Alexander Pastukhov <pastukhov.alexander@gmail.com>

Diff between bistablehistory versions 1.1.2 dated 2023-09-13 and 1.1.3 dated 2025-10-11

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Package ppmlasso updated to version 1.5 with previous version 1.4 dated 2024-01-31

Title: Point Process Models with LASSO-Type Penalties
Description: Toolkit for fitting point process models with sequences of LASSO penalties ("regularisation paths"), as described in Renner, I.W. and Warton, D.I. (2013) <doi:10.1111/j.1541-0420.2012.01824.x>. Regularisation paths of Poisson point process models or area-interaction models can be fitted with LASSO, adaptive LASSO or elastic net penalties. A number of criteria are available to judge the bias-variance tradeoff.
Author: Ian Renner [aut, cre]
Maintainer: Ian Renner <Ian.Renner@newcastle.edu.au>

Diff between ppmlasso versions 1.4 dated 2024-01-31 and 1.5 dated 2025-10-11

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Package GSEMA (with last version 0.99.3) was removed from CRAN

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

2024-10-14 0.99.3

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Package SpaDES.tools updated to version 2.0.8 with previous version 2.0.7 dated 2024-05-15

Title: Additional Tools for Developing Spatially Explicit Discrete Event Simulation (SpaDES) Models
Description: Provides GIS and map utilities, plus additional modeling tools for developing cellular automata, dynamic raster models, and agent based models in 'SpaDES'. Included are various methods for spatial spreading, spatial agents, GIS operations, random map generation, and others. See '?SpaDES.tools' for an categorized overview of these additional tools. The suggested package 'NLMR' can be installed from the following repository: (<https://PredictiveEcology.r-universe.dev>).
Author: Eliot J B McIntire [aut] , Alex M Chubaty [aut, cre] , Yong Luo [ctb], Ceres Barros [ctb] , Steve Cumming [ctb], Jean Marchal [ctb], His Majesty the King in Right of Canada, as represented by the Minister of Natural Resources Canada [cph]
Maintainer: Alex M Chubaty <achubaty@for-cast.ca>

Diff between SpaDES.tools versions 2.0.7 dated 2024-05-15 and 2.0.8 dated 2025-10-11

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More information about SpaDES.tools at CRAN
Permanent link

Package HighFive updated to version 3.2.0 with previous version 3.1.0 dated 2025-07-22

Title: The 'HighFive' 'C++' Interface to 'HDF5'
Description: A modern idiomatic header-only 'C++'' interface for 'libhdf5'. Original software can be found at <https://github.com/highfive-devs/highfive/>.
Author: Andrew Robbins [aut, cre] , Luc Grosheintz [aut] , Blue Brain Project/EPFL [aut]
Maintainer: Andrew Robbins <robbiand@umich.edu>

Diff between HighFive versions 3.1.0 dated 2025-07-22 and 3.2.0 dated 2025-10-11

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More information about HighFive at CRAN
Permanent link

Package hesim updated to version 0.5.7 with previous version 0.5.6 dated 2025-09-28

Title: Health Economic Simulation Modeling and Decision Analysis
Description: A modular and computationally efficient R package for parameterizing, simulating, and analyzing health economic simulation models. The package supports cohort discrete time state transition models (Briggs et al. 1998) <doi:10.2165/00019053-199813040-00003>, N-state partitioned survival models (Glasziou et al. 1990) <doi:10.1002/sim.4780091106>, and individual-level continuous time state transition models (Siebert et al. 2012) <doi:10.1016/j.jval.2012.06.014>, encompassing both Markov (time-homogeneous and time-inhomogeneous) and semi-Markov processes. Decision uncertainty from a cost-effectiveness analysis is quantified with standard graphical and tabular summaries of a probabilistic sensitivity analysis (Claxton et al. 2005, Barton et al. 2008) <doi:10.1002/hec.985>, <doi:10.1111/j.1524-4733.2008.00358.x>. Use of C++ and data.table make individual-patient simulation, probabilistic sensitivity analysis, and incorporation of patient heterogeneity fast.
Author: Devin Incerti [aut, cre], Jeroen P. Jansen [aut], Mark Clements [aut], R Core Team [ctb]
Maintainer: Devin Incerti <devin.incerti@gmail.com>

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 hesim-0.5.7/hesim/MD5                                                                                |  156 +++++-----
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Package future.callr updated to version 0.10.2 with previous version 0.10.1 dated 2025-07-10

Title: A Future API for Parallel Processing using 'callr'
Description: Implementation of the Future API <doi:10.32614/RJ-2021-048> on top of the 'callr' package. This allows you to process futures, as defined by the 'future' package, in parallel out of the box, on your local (Linux, macOS, Windows, ...) machine. Contrary to backends relying on the 'parallel' package (e.g. 'future::multisession') and socket connections, the 'callr' backend provided here can run more than 125 parallel R processes.
Author: Henrik Bengtsson [aut, cre, cph]
Maintainer: Henrik Bengtsson <henrikb@braju.com>

Diff between future.callr versions 0.10.1 dated 2025-07-10 and 0.10.2 dated 2025-10-11

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Package coneproj updated to version 1.21 with previous version 1.20 dated 2025-02-19

Title: Primal or Dual Cone Projections with Routines for Constrained Regression
Description: Routines doing cone projection and quadratic programming, as well as doing estimation and inference for constrained parametric regression and shape-restricted regression problems. See Mary C. Meyer (2013)<doi:10.1080/03610918.2012.659820> for more details.
Author: Mary C. Meyer [aut], Xiyue Liao [aut, cre]
Maintainer: Xiyue Liao <xliao@sdsu.edu>

Diff between coneproj versions 1.20 dated 2025-02-19 and 1.21 dated 2025-10-11

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Package ACSSpack updated to version 1.0.0.2 with previous version 0.0.1.4 dated 2024-07-04

Title: ACSS, Corresponding INSS, and GLP Algorithms
Description: Allow user to run the Adaptive Correlated Spike and Slab (ACSS) algorithm, corresponding INdependent Spike and Slab (INSS) algorithm, and Giannone, Lenza and Primiceri (GLP) algorithm with adaptive burn-in. All of the three algorithms are used to fit high dimensional data set with either sparse structure, or dense structure with smaller contributions from all predictors. The state-of-the-art GLP algorithm is in Giannone, D., Lenza, M., & Primiceri, G. E. (2021, ISBN:978-92-899-4542-4) "Economic predictions with big data: The illusion of sparsity". The two new algorithms, ACSS algorithm and INSS algorithm, and the discussion on their performance can be seen in Yang, Z., Khare, K., & Michailidis, G. (2024, submitted to Journal of Business & Economic Statistics) "Bayesian methodology for adaptive sparsity and shrinkage in regression".
Author: Ziqian Yang [cre, aut], Kshitij Khare [aut], George Michailidis [aut]
Maintainer: Ziqian Yang <zi.yang@ufl.edu>

Diff between ACSSpack versions 0.0.1.4 dated 2024-07-04 and 1.0.0.2 dated 2025-10-11

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