Fri, 22 Aug 2025

Package qualtRics updated to version 3.2.2 with previous version 3.2.1 dated 2024-08-16

Title: Download 'Qualtrics' Survey Data
Description: Provides functions to access survey results directly into R using the 'Qualtrics' API. 'Qualtrics' <https://www.qualtrics.com/about/> is an online survey and data collection software platform. See <https://api.qualtrics.com/> for more information about the 'Qualtrics' API. This package is community-maintained and is not officially supported by 'Qualtrics'.
Author: Jasper Ginn [aut], Jackson Curtis [ctb], Shaun Jackson [ctb], Samuel Kaminsky [ctb], Eric Knudsen [ctb], Joseph O'Brien [aut], Daniel Seneca [ctb], Julia Silge [aut, cre] , Phoebe Wong [ctb]
Maintainer: Julia Silge <julia.silge@gmail.com>

Diff between qualtRics versions 3.2.1 dated 2024-08-16 and 3.2.2 dated 2025-08-22

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Package nlmixr2plot updated to version 3.0.3 with previous version 3.0.2 dated 2025-06-25

Title: Nonlinear Mixed Effects Models in Population PK/PD, Plot Functions
Description: Fit and compare nonlinear mixed-effects models in differential equations with flexible dosing information commonly seen in pharmacokinetics and pharmacodynamics (Almquist, Leander, and Jirstrand 2015 <doi:10.1007/s10928-015-9409-1>). Differential equation solving is by compiled C code provided in the 'rxode2' package (Wang, Hallow, and James 2015 <doi:10.1002/psp4.12052>). This package is for 'ggplot2' plotting methods for 'nlmixr2' objects.
Author: Matthew Fidler [aut, cre] , Bill Denney [ctb] , Wenping Wang [aut], Vipul Mann [aut]
Maintainer: Matthew Fidler <matthew.fidler@gmail.com>

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Package door updated to version 0.0.3 with previous version 0.0.2 dated 2025-07-08

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

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Package discrim updated to version 1.0.2 with previous version 1.0.1 dated 2023-03-08

Title: Model Wrappers for Discriminant Analysis
Description: Bindings for additional classification models for use with the 'parsnip' package. Models include flavors of discriminant analysis, such as linear (Fisher (1936) <doi:10.1111/j.1469-1809.1936.tb02137.x>), regularized (Friedman (1989) <doi:10.1080/01621459.1989.10478752>), and flexible (Hastie, Tibshirani, and Buja (1994) <doi:10.1080/01621459.1994.10476866>), as well as naive Bayes classifiers (Hand and Yu (2007) <doi:10.1111/j.1751-5823.2001.tb00465.x>).
Author: Emil Hvitfeldt [aut, cre] , Max Kuhn [aut] , Posit Software, PBC [cph, fnd]
Maintainer: Emil Hvitfeldt <emil.hvitfeldt@posit.co>

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Package demodelr updated to version 2.0.0 with previous version 1.0.1 dated 2022-09-16

Title: Simulating Differential Equations with Data
Description: Designed to support the visualization, numerical computation, qualitative analysis, model-data fusion, and stochastic simulation for autonomous systems of differential equations. Euler and Runge-Kutta methods are implemented, along with tools to visualize the two-dimensional phaseplane. Likelihood surfaces and a simple Markov Chain Monte Carlo parameter estimator can be used for model-data fusion of differential equations and empirical models. The Euler-Maruyama method is provided for simulation of stochastic differential equations. The package was originally written for internal use to support teaching by Zobitz, and refined to support the text "Exploring modeling with data and differential equations using R" by John Zobitz (2021) <https://jmzobitz.github.io/ModelingWithR/index.html>.
Author: John Zobitz [aut, cre]
Maintainer: John Zobitz <zobitz@augsburg.edu>

Diff between demodelr versions 1.0.1 dated 2022-09-16 and 2.0.0 dated 2025-08-22

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Package starwarsdb updated to version 0.1.3 with previous version 0.1.2 dated 2020-11-02

Title: Relational Data from the 'Star Wars' API for Learning and Teaching
Description: Provides data about the 'Star Wars' movie franchise in a set of relational tables or as a complete 'DuckDB' database. All data was collected from the open source 'Star Wars' API.
Author: Garrick Aden-Buie [aut, cre]
Maintainer: Garrick Aden-Buie <garrick@adenbuie.com>

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Package MapperAlgo updated to version 1.0.4 with previous version 1.0.3 dated 2025-06-20

Title: Topological Data Analysis: Mapper Algorithm
Description: The Mapper algorithm from Topological Data Analysis, the steps are as follows 1. Define a filter (lens) function on the data. 2. Perform clustering within each level set. 3. Generate a complex from the clustering results.
Author: ChiChien Wang [aut, cre, trl], Paul Pearson [ctb], Daniel Muellner [ctb], Gurjeet Singh [ctb]
Maintainer: ChiChien Wang <kennywang2003@gmail.com>

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Package SVEMnet updated to version 1.5.3 with previous version 1.4.0 dated 2025-08-18

Title: Self-Validated Ensemble Models with Elastic Net Regression
Description: Implements Self-Validated Ensemble Models (SVEM, Lemkus et al. (2021) <doi:10.1016/j.chemolab.2021.104439>) using Elastic Net regression via 'glmnet' (Friedman et al. <doi:10.18637/jss.v033.i01>). SVEM averages predictions from multiple models fitted to fractionally weighted bootstraps of the data, tuned with anti-correlated validation weights. Also implements the randomized permutation whole model test for SVEM (Karl (2024) <doi:10.1016/j.chemolab.2024.105122>). \\Code for the whole model test was taken from the supplementary material of Karl (2024). Development of this package was assisted by 'GPT o1-preview' for code structure and documentation.
Author: Andrew T. Karl [cre, aut]
Maintainer: Andrew T. Karl <akarl@asu.edu>

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Package Rtrack updated to version 2.0.4 with previous version 2.0.3 dated 2023-12-11

Title: Spatial Navigation Strategy Analysis
Description: A toolkit for the analysis of paths from spatial tracking experiments and calculation of goal-finding strategies. This package is centered on an approach using machine learning for path classification.
Author: Rupert Overall [aut, cre]
Maintainer: Rupert Overall <rtrack@rupertoverall.net>

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Package rSDI updated to version 0.2.2 with previous version 0.2.1 dated 2024-05-30

Title: Spatial Dispersion Index (SDI) Family of Metrics for Spatial/Geographic Networks
Description: Spatial Dispersion Index (SDI) is a generalized measurement index, or rather a family of indices to evaluate spatial dispersion of movements/flows in a network in a problem neutral way as described in: Gencer (2023) <doi:10.1007/s12061-023-09545-8>. This package computes and optionally visualizes this index with minimal hassle.
Author: Mehmet Gencer [aut, cre, cph] , Muecahit Zor [aut], Engin Hengirmen [aut]
Maintainer: Mehmet Gencer <mehmetgencer@yahoo.com>

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Package manynet updated to version 1.6.0 with previous version 1.5.1 dated 2025-06-23

Title: Many Ways to Make, Modify, Mark, and Measure Myriad Networks
Description: Many tools for making, modifying, marking, measuring, and motifs and memberships of many different types of networks. All functions operate with matrices, edge lists, and 'igraph', 'network', and 'tidygraph' objects, on directed, multiplex, multimodal, signed, and other networks. The package includes functions for importing and exporting, creating and generating networks, modifying networks and node and tie attributes, and describing networks with sensible defaults.
Author: James Hollway [cre, aut, ctb] , Henrique Sposito [ctb] , Christian Steglich [ctb]
Maintainer: James Hollway <james.hollway@graduateinstitute.ch>

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Package fluxible updated to version 1.3.0 with previous version 1.2.6 dated 2025-06-24

Title: Ecosystem Gas Fluxes Calculations for Closed Loop Chamber Setup
Description: Toolbox to process raw data from closed loop flux chamber (or tent) setups into ecosystem gas fluxes usable for analysis. It goes from a data frame of gas concentration over time (which can contain several measurements) and a meta data file indicating which measurement was done when, to a data frame of ecosystem gas fluxes including quality diagnostics. Organized with one function per step, maximizing user flexibility and backwards compatibility. Different models to estimate the fluxes from the raw data are available: exponential as described in Zhao et al (2018) <doi:10.1016/j.agrformet.2018.08.022>, exponential as described in Hutchinson and Mosier (1981) <doi:10.2136/sssaj1981.03615995004500020017x>, quadratic, and linear. Other functions include quality assessment, plotting for visual check, calculation of fluxes based on the setup specific parameters (chamber size, plot area, ...), gross primary production and transpiration rate calculation, and light response curves.
Author: Joseph Gaudard [aut, cre] , Richard James Telford [aut]
Maintainer: Joseph Gaudard <joseph.gaudard@pm.me>

Diff between fluxible versions 1.2.6 dated 2025-06-24 and 1.3.0 dated 2025-08-22

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Package ggborderline updated to version 0.3.0 with previous version 0.2.0 dated 2022-10-25

Title: Line Plots that Pop
Description: A set of geometries to make line plots a little bit nicer. Use along with 'ggplot2' to: - Improve the clarity of line plots with many overlapping lines - Draw more realistic worms.
Author: Jacob Scott [aut, cre]
Maintainer: Jacob Scott <jscott2718@gmail.com>

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Package viafoundry updated to version 1.0.1 with previous version 1.0.0 dated 2025-01-13

Title: R Client for 'Via Foundry' API
Description: 'Via Foundry' API provides streamlined tools for interacting with and extracting data from structured responses, particularly for use cases involving hierarchical data from Foundry's API. It includes functions to fetch and parse process-level and file-level metadata, allowing users to efficiently query and manipulate nested data structures. Key features include the ability to list all unique process names, retrieve file metadata for specific or all processes, and dynamically load or download files based on their type. With built-in support for handling various file formats (e.g., tabular and non-tabular files) and seamless integration with API through authentication, this package is designed to enhance workflows involving large-scale data management and analysis. Robust error handling and flexible configuration ensure reliable performance across diverse data environments. Please consult the documentation for the API endpoint for your installation.
Author: Alper Kucukural [aut, cre], Via Scientific [aut, cph]
Maintainer: Alper Kucukural <alper@viascientific.com>

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Package mlr updated to version 2.19.3 with previous version 2.19.2 dated 2024-06-12

Title: Machine Learning in R
Description: Interface to a large number of classification and regression techniques, including machine-readable parameter descriptions. There is also an experimental extension for survival analysis, clustering and general, example-specific cost-sensitive learning. Generic resampling, including cross-validation, bootstrapping and subsampling. Hyperparameter tuning with modern optimization techniques, for single- and multi-objective problems. Filter and wrapper methods for feature selection. Extension of basic learners with additional operations common in machine learning, also allowing for easy nested resampling. Most operations can be parallelized.
Author: Bernd Bischl [aut] , Michel Lang [aut] , Lars Kotthoff [aut], Patrick Schratz [aut] , Julia Schiffner [aut], Jakob Richter [aut], Zachary Jones [aut], Giuseppe Casalicchio [aut] , Mason Gallo [aut], Jakob Bossek [ctb] , Erich Studerus [ctb] , Leonard [...truncated...]
Maintainer: Martin Binder <mlr.developer@mb706.com>

Diff between mlr versions 2.19.2 dated 2024-06-12 and 2.19.3 dated 2025-08-22

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Package bartMan updated to version 0.2.0 with previous version 0.1.1 dated 2024-07-24

Title: Create Visualisations for BART Models
Description: Investigating and visualising Bayesian Additive Regression Tree (BART) (Chipman, H. A., George, E. I., & McCulloch, R. E. 2010) <doi:10.1214/09-AOAS285> model fits. We construct conventional plots to analyze a model’s performance and stability as well as create new tree-based plots to analyze variable importance, interaction, and tree structure. We employ Value Suppressing Uncertainty Palettes (VSUP) to construct heatmaps that display variable importance and interactions jointly using colour scale to represent posterior uncertainty. Our visualisations are designed to work with the most popular BART R packages available, namely 'BART' Rodney Sparapani and Charles Spanbauer and Robert McCulloch 2021 <doi:10.18637/jss.v097.i01>, 'dbarts' (Vincent Dorie 2023) <https://CRAN.R-project.org/package=dbarts>, and 'bartMachine' (Adam Kapelner and Justin Bleich 2016) <doi:10.18637/jss.v070.i04>.
Author: Alan Inglis [aut, cre], Andrew Parnell [aut], Catherine Hurley [aut], Claus Wilke [ctb]
Maintainer: Alan Inglis <alan.inglis@mu.ie>

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Package manymodelr updated to version 0.4.0 with previous version 0.3.9 dated 2025-03-20

Title: Build and Tune Several Models
Description: Frequently one needs a convenient way to build and tune several models in one go.The goal is to provide a number of machine learning convenience functions. It provides the ability to build, tune and obtain predictions of several models in one function. The models are built using functions from 'caret' with easier to read syntax. Kuhn(2014) <doi:10.48550/arXiv.1405.6974>.
Author: Nelson Gonzabato [aut, cre]
Maintainer: Nelson Gonzabato <gonzabato@hotmail.com>

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More information about manymodelr at CRAN
Permanent link

Package hce updated to version 0.8.5 with previous version 0.8.0 dated 2025-07-11

Title: Design and Analysis of Hierarchical Composite Endpoints
Description: Simulate and analyze hierarchical composite endpoints. Includes implementation for the kidney hierarchical composite endpoint as defined in Heerspink HL et al (2023) “Development and validation of a new hierarchical composite end point for clinical trials of kidney disease progression” (Journal of the American Society of Nephrology 34 (2): 2025–2038, <doi:10.1681/ASN.0000000000000243>). Win odds, also called Wilcoxon-Mann-Whitney or success odds, is the main analysis method. Other win statistics (win probability, win ratio, net benefit) are also implemented in the univariate case, provided there is no censoring. The win probability analysis is based on the Brunner-Munzel test and uses the DeLong-DeLong-Clarke-Pearson variance estimator, as described by Brunner and Konietschke (2025) in “An unbiased rank-based estimator of the Mann–Whitney variance including the case of ties” (Statistical Papers 66 (1): 20, <doi:10.1007/s00362-024-01635-0>). Stratification and covariate adju [...truncated...]
Author: Samvel B. Gasparyan [aut, cre]
Maintainer: Samvel B. Gasparyan <gasparyan.co@gmail.com>

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Package TOSTER updated to version 0.8.6 with previous version 0.8.4 dated 2025-02-06

Title: Two One-Sided Tests (TOST) Equivalence Testing
Description: Two one-sided tests (TOST) procedure to test equivalence for t-tests, correlations, differences between proportions, and meta-analyses, including power analysis for t-tests and correlations. Allows you to specify equivalence bounds in raw scale units or in terms of effect sizes. See: Lakens (2017) <doi:10.1177/1948550617697177>.
Author: Daniel Lakens [aut], Aaron Caldwell [aut, cre]
Maintainer: Aaron Caldwell <arcaldwell49@gmail.com>

Diff between TOSTER versions 0.8.4 dated 2025-02-06 and 0.8.6 dated 2025-08-22

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More information about TOSTER at CRAN
Permanent link

Package mikropml updated to version 1.6.2 with previous version 1.6.1 dated 2023-08-21

Title: User-Friendly R Package for Supervised Machine Learning Pipelines
Description: An interface to build machine learning models for classification and regression problems. 'mikropml' implements the ML pipeline described by Topçuoğlu et al. (2020) <doi:10.1128/mBio.00434-20> with reasonable default options for data preprocessing, hyperparameter tuning, cross-validation, testing, model evaluation, and interpretation steps. See the website <https://www.schlosslab.org/mikropml/> for more information, documentation, and examples.
Author: Beguem Topcuoglu [aut] , Zena Lapp [aut] , Kelly Sovacool [aut, cre] , Evan Snitkin [aut] , Jenna Wiens [aut] , Patrick Schloss [aut] , Nick Lesniak [ctb] , Courtney Armour [ctb] , Sarah Lucas [ctb]
Maintainer: Kelly Sovacool <sovacool@umich.edu>

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Package desirability2 updated to version 0.2.0 with previous version 0.1.0 dated 2025-07-22

Title: Desirability Functions for Multiparameter Optimization
Description: In-line functions for multivariate optimization via desirability functions (Derringer and Suich, 1980, <doi:10.1080/00224065.1980.11980968>) with easy use within 'dplyr' pipelines.
Author: Max Kuhn [aut, cre] , Posit Software, PBC [cph, fnd]
Maintainer: Max Kuhn <max@posit.co>

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Package autograph updated to version 0.2.0 with previous version 0.1.2 dated 2025-07-02

Title: Automatic Plotting of Many Graphs
Description: Visual exploration and presentation of networks should not be difficult. This package includes functions for plotting networks and network-related metrics with sensible and pretty defaults. It includes 'ggplot2'-based plot methods for many popular network package classes. It also includes some novel layout algorithms, and options for straightforward, consistent themes.
Author: James Hollway [cre, aut, ctb] , Henrique Sposito [ctb]
Maintainer: James Hollway <james.hollway@graduateinstitute.ch>

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Package sport updated to version 0.2.2 with previous version 0.2.1 dated 2024-01-08

Title: Sequential Pairwise Online Rating Techniques
Description: Calculates ratings for two-player or multi-player challenges. Methods included in package such as are able to estimate ratings (players strengths) and their evolution in time, also able to predict output of challenge. Algorithms are based on Bayesian Approximation Method, and they don't involve any matrix inversions nor likelihood estimation. Parameters are updated sequentially, and computation doesn't require any additional RAM to make estimation feasible. Additionally, base of the package is written in C++ what makes sport computation even faster. Methods used in the package refer to Mark E. Glickman (1999) <https://www.glicko.net/research/glicko.pdf>; Mark E. Glickman (2001) <doi:10.1080/02664760120059219>; Ruby C. Weng, Chih-Jen Lin (2011) <https://www.jmlr.org/papers/volume12/weng11a/weng11a.pdf>; W. Penny, Stephen J. Roberts (1999) <doi:10.1109/IJCNN.1999.832603>.
Author: Dawid Kaledkowski [aut, cre]
Maintainer: Dawid Kaledkowski <dawid.kaledkowski@gmail.com>

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Package spinifex updated to version 0.3.9 with previous version 0.3.8 dated 2025-01-08

Title: Manual Tours, Manual Control of Dynamic Projections of Numeric Multivariate Data
Description: Data visualization tours animates linear projection of multivariate data as its basis (ie. orientation) changes. The 'spinifex' packages generates paths for manual tours by manipulating the contribution of a single variable at a time Cook & Buja (1997) <doi:10.1080/10618600.1997.10474754>. Other types of tours, such as grand (random walk) and guided (optimizing some objective function) are available in the 'tourr' package Wickham et al. <doi:10.18637/jss.v040.i02>. 'spinifex' builds on 'tourr' and can render tours with 'gganimate' and 'plotly' graphics, and allows for exporting as an .html widget and as an .gif, respectively. This work is fully discussed in Spyrison & Cook (2020) <doi:10.32614/RJ-2020-027>.
Author: Nicholas Spyrison [aut, cre] , Dianne Cook [aut, ths]
Maintainer: Nicholas Spyrison <spyrison@gmail.com>

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More information about spinifex at CRAN
Permanent link

Package scrutiny updated to version 0.6.0 with previous version 0.5.0 dated 2024-09-22

Title: Error Detection in Science
Description: Test published summary statistics for consistency (Brown and Heathers, 2017, <doi:10.1177/1948550616673876>; Allard, 2018, <https://aurelienallard.netlify.app/post/anaytic-grimmer-possibility-standard-deviations/>; Heathers and Brown, 2019, <https://osf.io/5vb3u/>). The package also provides infrastructure for implementing new error detection techniques.
Author: Lukas Jung [aut, cre], Aurelien Allard [ctb], Nicolas Roman Posner [ctb]
Maintainer: Lukas Jung <jung-lukas@gmx.net>

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New package rPublic with initial version 1.0.0
Package: rPublic
Title: 'Public Trading API'
Version: 1.0.0
Description: The 'Public Trading API' <https://public.com/api/docs> allows clients to access their brokerage accounts, request market data, and place stock/etf/option orders.
License: GPL-3
Language: en-US
Encoding: UTF-8
Imports: httr, jsonlite, data.table, lubridate, stringr, uuid
VignetteBuilder: knitr
Suggests: testthat, knitr, rmarkdown
NeedsCompilation: no
Packaged: 2025-08-09 09:36:10 UTC; jason
Author: Jason Guevara [aut, cre]
Maintainer: Jason Guevara <Jason.guevara.yt@gmail.com>
Repository: CRAN
Date/Publication: 2025-08-22 18:10:11 UTC

More information about rPublic at CRAN
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Package PieGlyph updated to version 1.1.0 with previous version 1.0.0 dated 2024-06-28

Title: Axis Invariant Scatter Pie Plots
Description: Extends 'ggplot2' to help replace points in a scatter plot with pie-chart glyphs showing the relative proportions of different categories. The pie glyphs are independent of the axes and plot dimensions, to prevent distortions when the plot dimensions are changed.
Author: Rishabh Vishwakarma [aut, cre] , Caroline Brophy [aut], Catherine Hurley [aut]
Maintainer: Rishabh Vishwakarma <vishwakr@tcd.ie>

Diff between PieGlyph versions 1.0.0 dated 2024-06-28 and 1.1.0 dated 2025-08-22

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 51 files changed, 1814 insertions(+), 1608 deletions(-)

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New package plotannotate with initial version 1.4-0
Package: plotannotate
Version: 1.4-0
Date: 2025-08-19
Title: Annotate Plots
Depends: R (>= 4.2.0)
Imports: stats, graphics, grDevices, grid, conicfit
Description: Interactively annotate 'base R graphics' plots with freehand drawing, symbols (points, lines, arrows, rectangles, circles, ellipses), and text. This is useful for teaching, for example to visually explain certain plot elements, and creating quick sketches.
License: GPL-3
Encoding: UTF-8
URL: https://github.com/wviechtb/plotannotate https://www.wvbauer.com
BugReports: https://github.com/wviechtb/plotannotate/issues
NeedsCompilation: no
Packaged: 2025-08-19 14:23:26 UTC; wviechtb
Author: Wolfgang Viechtbauer [aut, cre]
Maintainer: Wolfgang Viechtbauer <wvb@wvbauer.com>
Repository: CRAN
Date/Publication: 2025-08-22 18:50:02 UTC

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New package mclink with initial version 1.1
Package: mclink
Title: Metabolic Pathway Completeness and Abundance Calculation
Version: 1.1
Description: Provides tools for analyzing metabolic pathway completeness, abundance, and transcripts using KEGG Orthology (KO) data from (meta)genomic and (meta)transcriptomic studies. Supports both completeness (presence/absence) and abundance-weighted analyses. Includes built-in KEGG reference datasets. For more details see Li et al. (2023) <doi:10.1038/s41467-023-42193-7>.
URL: https://github.com/LiuyangLee/mclink
BugReports: https://github.com/LiuyangLee/mclink/issues
License: GPL-3
Encoding: UTF-8
Imports: data.table (>= 1.17.0), dplyr (>= 1.1.4), stringr (>= 1.5.1), tibble (>= 3.2.1), utils
Depends: R (>= 3.5)
LazyData: false
NeedsCompilation: no
Packaged: 2025-08-19 10:17:04 UTC; Administrator
Author: Liuyang Li [aut, cre]
Maintainer: Liuyang Li <cyanobacteria@yeah.net>
Repository: CRAN
Date/Publication: 2025-08-22 18:20:06 UTC

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New package imfweo with initial version 0.1.0
Package: imfweo
Title: Seamless Access to IMF World Economic Outlook (WEO) Data
Version: 0.1.0
Description: Provides tools to download, process, and analyze data from the International Monetary Fund's World Economic Outlook (WEO) database <https://www.imf.org/en/Publications/SPROLLs/world-economic-outlook-databases>. Functions support downloading complete WEO releases, accessing specific economic indicators for selected countries, and listing available data.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: cli, dplyr, httr2, readr, readxl, rlang, tidyr
Suggests: curl, testthat, withr, tibble
URL: https://teal-insights.github.io/r-imfweo/, https://github.com/teal-insights/r-imfweo/
BugReports: https://github.com/teal-insights/r-imfweo/issues
NeedsCompilation: no
Packaged: 2025-08-19 07:22:09 UTC; krise
Author: Teal Emery [aut, cre], Teal Insights [cph], Christoph Scheuch [aut]
Maintainer: Teal Emery <lte@tealinsights.com>
Repository: CRAN
Date/Publication: 2025-08-22 18:30:02 UTC

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New package gwas2crispr with initial version 0.1.2
Package: gwas2crispr
Title: GWAS-to-CRISPR Data Pipeline for High-Throughput SNP Target Extraction
Version: 0.1.2
Description: Provides a reproducible pipeline to conduct genome‑wide association studies (GWAS) and extract single‑nucleotide polymorphisms (SNPs) for a human trait or disease. Given aggregated GWAS dataset(s) and a user‑defined significance threshold, the package retrieves significant SNPs from the GWAS Catalog and the Experimental Factor Ontology (EFO), annotates their gene context, and can write a harmonised metadata table in comma-separated values (CSV) format, genomic intervals in the Browser Extensible Data (BED) format, and sequences in the FASTA (text-based sequence) format with user-defined flanking regions for clustered regularly interspaced short palindromic repeats (CRISPR) guide design. For details on the resources and methods see: Buniello et al. (2019) <doi:10.1093/nar/gky1120>; Sollis et al. (2023) <doi:10.1093/nar/gkac1010>; Jinek et al. (2012) <doi:10.1126/science.1225829>; Malone et al. (2010) <doi:10.1093/bioinformatics/btq099>; Experimental Factor Ontolo [...truncated...]
License: MIT + file LICENSE
URL: https://github.com/leopard0ly/gwas2crispr
BugReports: https://github.com/leopard0ly/gwas2crispr/issues
Depends: R (>= 4.1)
Imports: httr, dplyr, purrr, tibble, tidyr, readr, methods
Suggests: gwasrapidd, Biostrings, BSgenome.Hsapiens.UCSC.hg38, optparse, testthat, knitr, rmarkdown
VignetteBuilder: knitr, rmarkdown
Encoding: UTF-8
Language: en-US
NeedsCompilation: no
Packaged: 2025-08-19 14:14:00 UTC; hp
Author: Othman S. I. Mohammed [aut, cre], LEOPARD.LY LTD [cph]
Maintainer: Othman S. I. Mohammed <admin@leopard.ly>
Repository: CRAN
Date/Publication: 2025-08-22 18:50:06 UTC

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New package CMTFtoolbox with initial version 1.0.1
Package: CMTFtoolbox
Title: Create (Advanced) Coupled Matrix and Tensor Factorization Models
Version: 1.0.1
Description: Creation and selection of (Advanced) Coupled Matrix and Tensor Factorization (ACMTF) and ACMTF-Regression (ACMTF-R) models. Selection of the optimal number of components can be done using 'ACMTF_modelSelection()' and 'ACMTFR_modelSelection()'. The CMTF and ACMTF methods were originally described by Acar et al., 2011 <doi:10.48550/arXiv.1105.3422> and Acar et al., 2014 <doi:10.1186/1471-2105-15-239>, respectively.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: clue, doParallel, dplyr, foreach, ggplot2, magrittr, methods, mize, multiway, parallel, pracma, rTensor, stats, tidyr
Suggests: knitr, ggpubr, NPLStoolbox, plotrix, parafac4microbiome, rmarkdown, testthat (>= 3.0.0), scales
VignetteBuilder: knitr
Depends: R (>= 2.10)
LazyData: true
URL: https://grvanderploeg.com/CMTFtoolbox/, https://github.com/GRvanderPloeg/CMTFtoolbox
BugReports: https://github.com/GRvanderPloeg/CMTFtoolbox/issues
NeedsCompilation: no
Packaged: 2025-08-19 08:11:02 UTC; roelv
Author: Geert Roelof van der Ploeg [aut, cre] , Johan Westerhuis [ctb] , Anna Heintz-Buschart [ctb] , Age Smilde [ctb] , University of Amsterdam [cph, fnd]
Maintainer: Geert Roelof van der Ploeg <g.r.ploeg@uva.nl>
Repository: CRAN
Date/Publication: 2025-08-22 18:20:17 UTC

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Package causact updated to version 0.5.8 with previous version 0.5.7 dated 2025-01-15

Title: Fast, Easy, and Visual Bayesian Inference
Description: Accelerate Bayesian analytics workflows in 'R' through interactive modelling, visualization, and inference. Define probabilistic graphical models using directed acyclic graphs (DAGs) as a unifying language for business stakeholders, statisticians, and programmers. This package relies on interfacing with the 'numpyro' python package.
Author: Adam Fleischhacker [aut, cre, cph], Daniela Dapena [ctb], Rose Nguyen [ctb], Jared Sharpe [ctb]
Maintainer: Adam Fleischhacker <ajf@udel.edu>

Diff between causact versions 0.5.7 dated 2025-01-15 and 0.5.8 dated 2025-08-22

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Package biclustermd updated to version 0.2.4 with previous version 0.2.3 dated 2021-06-17

Title: Biclustering with Missing Data
Description: Biclustering is a statistical learning technique that simultaneously partitions and clusters rows and columns of a data matrix. Since the solution space of biclustering is in infeasible to completely search with current computational mechanisms, this package uses a greedy heuristic. The algorithm featured in this package is, to the best our knowledge, the first biclustering algorithm to work on data with missing values. Li, J., Reisner, J., Pham, H., Olafsson, S., and Vardeman, S. (2020) Biclustering with Missing Data. Information Sciences, 510, 304–316.
Author: John Reisner [cre, aut, cph], Hieu Pham [ctb, cph], Jing Li [ctb, cph]
Maintainer: John Reisner <johntreisner@gmail.com>

Diff between biclustermd versions 0.2.3 dated 2021-06-17 and 0.2.4 dated 2025-08-22

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New package aRD with initial version 0.1.0
Package: aRD
Title: Adjusted Risk Differences via Specifically Penalized Likelihood
Version: 0.1.0
Date: 2025-08-18
Description: Fits a linear-binomial model using a modified Newton-type algorithm for solving the maximum likelihood estimation problem under linear box constraints. Similar methods are described in Wagenpfeil, Schöpe and Bekhit (2025, ISBN:9783111341972) "Estimation of adjusted relative risks in log-binomial regression using the BSW algorithm". In: Mau, Mukhin, Wang and Xu (Eds.), Biokybernetika. De Gruyter, Berlin, pp. 665–676.
License: GPL (>= 3)
Encoding: UTF-8
URL: https://github.com/UdS-MF-IMBEI/aRD
BugReports: https://github.com/UdS-MF-IMBEI/aRD/issues
VignetteBuilder: knitr
Depends: R (>= 4.0)
Imports: Matrix, matrixStats, osqp, quadprog, methods, stats, boot, checkmate
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2025-08-18 13:55:41 UTC; thomaswolf
Author: Thomas Wolf [aut, cre], Julius Johannes Weise [aut], Stefan Wagenpfeil [aut]
Maintainer: Thomas Wolf <imbei@med-imbei.uni-saarland.de>
Repository: CRAN
Date/Publication: 2025-08-22 18:20:12 UTC

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Package tidysdm updated to version 1.0.2 with previous version 1.0.0 dated 2025-03-05

Title: Species Distribution Models with Tidymodels
Description: Fit species distribution models (SDMs) using the 'tidymodels' framework, which provides a standardised interface to define models and process their outputs. 'tidysdm' expands 'tidymodels' by providing methods for spatial objects, models and metrics specific to SDMs, as well as a number of specialised functions to process occurrences for contemporary and palaeo datasets. The full functionalities of the package are described in Leonardi et al. (2023) <doi:10.1101/2023.07.24.550358>.
Author: Michela Leonardi [aut], Margherita Colucci [aut], Andrea Vittorio Pozzi [aut], Eleanor M.L. Scerri [aut], Ben Tupper [ctb], Andrea Manica [aut, cre]
Maintainer: Andrea Manica <am315@cam.ac.uk>

Diff between tidysdm versions 1.0.0 dated 2025-03-05 and 1.0.2 dated 2025-08-22

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 tests/testthat/test_thin_by_dist_time.R       |    1 
 vignettes/a3_troubleshooting.Rmd              |   37 +++-
 61 files changed, 588 insertions(+), 356 deletions(-)

More information about tidysdm at CRAN
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New package senseweight with initial version 0.0.1
Package: senseweight
Title: Sensitivity Analysis for Weighted Estimators
Version: 0.0.1
Description: Provides tools to conduct interpretable sensitivity analyses for weighted estimators, introduced in Huang (2024) <doi:10.1093/jrsssa/qnae012> and Hartman and Huang (2024) <doi:10.1017/pan.2023.12>. The package allows researchers to generate the set of recommended sensitivity summaries to evaluate the sensitivity in their underlying weighting estimators to omitted moderators or confounders. The tools can be flexibly applied in causal inference settings (i.e., in external and internal validity contexts) or survey contexts.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
LazyData: true
Imports: dplyr, estimatr, ggplot2, ggrepel, kableExtra, metR, rlang, survey, WeightIt
Suggests: knitr, pkgload, rmarkdown
VignetteBuilder: knitr
URL: https://melodyyhuang.github.io/senseweight/
NeedsCompilation: no
Packaged: 2025-08-18 20:57:38 UTC; mh2735
Author: Melody Huang [aut, cre]
Maintainer: Melody Huang <melody.huang@yale.edu>
Repository: CRAN
Date/Publication: 2025-08-22 17:30:02 UTC

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Package rmweather updated to version 0.2.63 with previous version 0.2.62 dated 2025-02-20

Title: Tools to Conduct Meteorological Normalisation and Counterfactual Modelling for Air Quality Data
Description: An integrated set of tools to allow data users to conduct meteorological normalisation and counterfactual modelling for air quality data. The meteorological normalisation technique uses predictive random forest models to remove variation of pollutant concentrations so trends and interventions can be explored in a robust way. For examples, see Grange et al. (2018) <doi:10.5194/acp-18-6223-2018> and Grange and Carslaw (2019) <doi:10.1016/j.scitotenv.2018.10.344>. The random forest models can also be used for counterfactual or business as usual (BAU) modelling by using the models to predict, from the model's perspective, the future. For an example, see Grange et al. (2021) <doi:10.5194/acp-2020-1171>.
Author: Stuart K. Grange [cre, aut]
Maintainer: Stuart K. Grange <s.k.grange@gmail.com>

Diff between rmweather versions 0.2.62 dated 2025-02-20 and 0.2.63 dated 2025-08-22

 DESCRIPTION                            |   11 ++++++-----
 MD5                                    |    4 ++--
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Package ProteinPCA updated to version 0.1.1 with previous version 0.1.0 dated 2025-04-12

Title: Principal Component Analysis (PCA) Tool on Protein Expression Data
Description: Analysis of protein expression data can be done through Principal Component Analysis (PCA), and this R package is designed to streamline the analysis. This package enables users to perform PCA and it generates biplot and scree plot for advanced graphical visualization. Optionally, it supports grouping/clustering visualization with PCA loadings and confidence ellipses. With this R package, researchers can quickly explore complex protein datasets, interpret variance contributions, and visualize sample clustering through intuitive biplots. For more details, see Jolliffe (2001) <doi:10.1007/b98835>, Gabriel (1971) <doi:10.1093/biomet/58.3.453>, Zhang et al. (2024) <doi:10.1038/s41467-024-53239-9>, and Anandan et al. (2022) <doi:10.1038/s41598-022-07781-5>.
Author: Paul Angelo C. Manlapaz [aut, cre]
Maintainer: Paul Angelo C. Manlapaz <pacmanlapaz@gmail.com>

Diff between ProteinPCA versions 0.1.0 dated 2025-04-12 and 0.1.1 dated 2025-08-22

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Package modeldb updated to version 0.3.1 with previous version 0.3.0 dated 2023-11-01

Title: Fits Models Inside the Database
Description: Uses 'dplyr' and 'tidyeval' to fit statistical models inside the database. It currently supports KMeans and linear regression models.
Author: Edgar Ruiz [aut], Max Kuhn [aut, cre]
Maintainer: Max Kuhn <max@posit.co>

Diff between modeldb versions 0.3.0 dated 2023-11-01 and 0.3.1 dated 2025-08-22

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Package implicitMeasures updated to version 0.3.1 with previous version 0.3.0 dated 2025-07-10

Title: Compute Scores for Different Implicit Measures
Description: A tool for computing the scores for the Implicit Association Test (IAT; Greenwald, McGhee & Schwartz (1998) <doi:10.1037/0022-3514.74.6.1464>) and the Single Category-IAT (SC-IAT: Karpinski & Steinman (2006) <doi:10.1037/0022-3514.91.1.16>). Functions for preparing the data (both for the IAT and the SC-IAT), plotting the results, and obtaining a table with the scores of implicit measures descriptive statistics are provided.
Author: Ottavia M. Epifania [aut, cre], Pasquale Anselmi [ctb], Egidio Robusto [ctb]
Maintainer: Ottavia M. Epifania <otta.epifania@gmail.com>

Diff between implicitMeasures versions 0.3.0 dated 2025-07-10 and 0.3.1 dated 2025-08-22

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New package letsRept with initial version 1.0.0
Package: letsRept
Title: An Interface to the Reptile Database
Version: 1.0.0
URL: https://github.com/joao-svalencar/letsRept
BugReports: https://github.com/joao-svalencar/letsRept/issues
Description: Provides tools to retrieve and summarize taxonomic information and synonymy data for reptile species using data scraped from The Reptile Database website (<https://reptile-database.reptarium.cz/>). Outputs include clean and structured data frames useful for ecological, evolutionary, and conservation research.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: dplyr, httr, parallel, pbapply, pbmcapply, rvest, stringr, tidyr, utils, xml2
Depends: R (>= 3.5)
LazyData: true
LazyDataCompression: xz
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2025-08-18 23:49:05 UTC; joaosvalencar
Author: Joao Paulo dos Santos Vieira-Alencar [aut, cre] , Christoph Liedtke [aut]
Maintainer: Joao Paulo dos Santos Vieira-Alencar <joaopaulo.valencar@gmail.com>
Repository: CRAN
Date/Publication: 2025-08-22 17:40:09 UTC

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New package GRANDpriv with initial version 0.1.3
Package: GRANDpriv
Title: Graph Release with Assured Node Differential Privacy
Version: 0.1.3
Description: Implements a novel method for privatizing network data using differential privacy. Provides functions for generating synthetic networks based on LSM (Latent Space Model), applying differential privacy to network latent positions to achieve overall network privatization, and evaluating the utility of privatized networks through various network statistics. The privatize and evaluate functions support both LSM and RDPG (Random Dot Product Graph). For generating RDPG networks, users are encouraged to use the 'randnet' package <https://CRAN.R-project.org/package=randnet>. For more details, see the "proposed method" section of Liu, Bi, and Li (2025) <doi:10.48550/arXiv.2507.00402>.
License: GPL (>= 3)
URL: https://github.com/lsq0000/GRANDpriv
BugReports: https://github.com/lsq0000/GRANDpriv/issues
Encoding: UTF-8
Imports: EnvStats, rmutil, RSpectra, diffpriv, truncnorm, randnet, igraph, HCD, transport
NeedsCompilation: no
Packaged: 2025-08-19 01:32:31 UTC; liusu
Author: Suqing Liu [aut, cre], Xuan Bi [aut], Tianxi Li [aut]
Maintainer: Suqing Liu <liusuqing0123@uchicago.edu>
Repository: CRAN
Date/Publication: 2025-08-22 17:50:07 UTC

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Package GitAI updated to version 0.1.2 with previous version 0.1.1 dated 2025-05-20

Title: Extracts Knowledge from 'Git' Repositories
Description: Scan multiple 'Git' repositories, pull specified files content and process it with large language models. You can summarize the content in specific way, extract information and data, or find answers to your questions about the repositories. The output can be stored in vector database and used for semantic search or as a part of a RAG (Retrieval Augmented Generation) prompt.
Author: Kamil Wais [aut, cre], Krystian Igras [aut], Maciej Banas [aut]
Maintainer: Kamil Wais <kamil.wais@gmail.com>

Diff between GitAI versions 0.1.1 dated 2025-05-20 and 0.1.2 dated 2025-08-22

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Package ggbrain updated to version 0.9.1 with previous version 0.9.0 dated 2025-03-19

Title: Create Images of Volumetric Brain Data in NIfTI Format Using 'ggplot2' Syntax
Description: A 'ggplot2'-consistent approach to generating 2D displays of volumetric brain imaging data. Display data from multiple NIfTI images using standard 'ggplot2' conventions such scales, limits, and themes to control the appearance of displays. The resulting plots are returned as 'patchwork' objects, inheriting from 'ggplot', allowing for any standard modifications of display aesthetics supported by 'ggplot2'.
Author: Michael Hallquist [aut, cre]
Maintainer: Michael Hallquist <michael.hallquist@gmail.com>

Diff between ggbrain versions 0.9.0 dated 2025-03-19 and 0.9.1 dated 2025-08-22

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Package flowchart updated to version 0.9.0 with previous version 0.8.0 dated 2025-04-23

Title: Tidy Flowchart Generator
Description: Creates participant flow diagrams directly from a dataframe. Representing the flow of participants through each stage of a study, especially in clinical trials, is essential to assess the generalisability and validity of the results. This package provides a set of functions that can be combined with a pipe operator to create all kinds of flowcharts from a data frame in an easy way.
Author: Pau Satorra [aut, cre] , Joao Carmezim [aut] , Natalia Pallares [aut] , Cristian Tebe [aut] , Kenneth Taylor [aut]
Maintainer: Pau Satorra <psatorra@igtp.cat>

Diff between flowchart versions 0.8.0 dated 2025-04-23 and 0.9.0 dated 2025-08-22

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New package ExactVaRTest with initial version 0.1.3
Package: ExactVaRTest
Title: Exact Finite-Sample Value-at-Risk Back-Testing
Version: 0.1.3
Language: en-US
Maintainer: Yujian Chen <yjc4996@gmail.com>
Description: Provides fast dynamic-programming algorithms in 'C++'/'Rcpp' (with pure 'R' fallbacks) for the exact finite-sample distributions and p-values of Christoffersen (1998) independence (IND) and conditional-coverage (CC) VaR backtests. For completeness, it also provides the exact unconditional-coverage (UC) test following Kupiec (1995) via a closed-form binomial enumeration. See Christoffersen (1998) <doi:10.2307/2527341> and Kupiec (1995) <doi:10.3905/jod.1995.407942>.
License: GPL (>= 3)
Depends: R (>= 3.5.0)
Imports: Rcpp, stats
LinkingTo: Rcpp
Suggests: bench, dplyr, tidyr, purrr, ggplot2, xts, quantmod, knitr, rmarkdown, testthat (>= 3.0.0)
Encoding: UTF-8
URL: https://github.com/YujianCHEN219/ExactVaRTest
BugReports: https://github.com/YujianCHEN219/ExactVaRTest/issues
Acknowledgements: I greatly appreciate Christian Francq, Christophe Hurlin, and Jean-Michel Zakoian's guidance and support. In particular, Christian Francq generously shared the initial idea; without his help, this package would not exist.
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2025-08-18 19:43:47 UTC; chenyujian
Author: Yujian Chen [aut, cre]
Repository: CRAN
Date/Publication: 2025-08-22 17:20:02 UTC

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New package ecodive with initial version 1.0.0
Package: ecodive
Title: Parallel and Memory-Efficient Ecological Diversity Metrics
Version: 1.0.0
Date: 2025-08-18
Description: Computes alpha and beta diversity metrics using concurrent 'C' threads. Metrics include 'UniFrac', Faith's phylogenetic diversity, Bray-Curtis dissimilarity, Shannon diversity index, and many others. Also parses newick trees into 'phylo' objects and rarefies feature tables.
URL: https://cmmr.github.io/ecodive/, https://github.com/cmmr/ecodive
BugReports: https://github.com/cmmr/ecodive/issues
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.6.0)
Imports: parallel, utils
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2025-08-18 22:41:52 UTC; Daniel
Author: Daniel P. Smith [aut, cre] , Alkek Center for Metagenomics and Microbiome Research [cph, fnd]
Maintainer: Daniel P. Smith <dansmith01@gmail.com>
Repository: CRAN
Date/Publication: 2025-08-22 17:40:15 UTC

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Package shinyMixR updated to version 0.5.2 with previous version 0.5.1 dated 2025-07-18

Title: Interactive 'shiny' Dashboard for 'nlmixr2'
Description: An R shiny user interface for the 'nlmixr2' (Fidler et al (2019) <doi:10.1002/psp4.12445>) package, designed to simplify the modeling process for users. Additionally, this package includes supplementary functions to further enhances the usage of 'nlmixr2'.
Author: Richard Hooijmaijers [aut, cre, cph], Teun Post [aut, cph], LAPP Consultants [fnd, cph], Matthew Fidler [ctb], Veerle van Leemput [ctb]
Maintainer: Richard Hooijmaijers <richardhooijmaijers@gmail.com>

Diff between shinyMixR versions 0.5.1 dated 2025-07-18 and 0.5.2 dated 2025-08-22

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Package roclang updated to version 0.2.3 with previous version 0.2.2 dated 2023-05-26

Title: Functions for Diffusing Function Documentations into 'Roxygen' Comments
Description: Efficient diffusing of content across function documentations. Sections, parameters or dot parameters are extracted from function documentations and turned into valid Rd character strings, which are ready to diffuse into the 'roxygen' comments of another function by inserting inline code.
Author: Xiurui Zhu [aut, cre]
Maintainer: Xiurui Zhu <zxr6@163.com>

Diff between roclang versions 0.2.2 dated 2023-05-26 and 0.2.3 dated 2025-08-22

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Package gimme updated to version 0.9.2 with previous version 0.9.1 dated 2025-06-26

Title: Group Iterative Multiple Model Estimation
Description: Data-driven approach for arriving at person-specific time series models. The method first identifies which relations replicate across the majority of individuals to detect signal from noise. These group-level relations are then used as a foundation for starting the search for person-specific (or individual-level) relations. See Gates & Molenaar (2012) <doi:10.1016/j.neuroimage.2012.06.026>.
Author: Stephanie Lane [aut, trl], Kathleen M Gates [aut, cre, ccp], Zachary Fisher [aut], Cara Arizmendi [aut], Peter Molenaar [aut, ccp], Edgar Merkle [ctb], Michael Hallquist [ctb], Hallie Pike [ctb], Teague Henry [ctb], Kelly Duffy [ctb], Lan Luo [ctb], [...truncated...]
Maintainer: Kathleen M Gates <gateskm@email.unc.edu>

Diff between gimme versions 0.9.1 dated 2025-06-26 and 0.9.2 dated 2025-08-22

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Package ecolottery updated to version 1.0.2 with previous version 1.0.1 dated 2025-04-14

Title: Coalescent-Based Simulation of Ecological Communities
Description: Coalescent-Based Simulation of Ecological Communities as proposed by Munoz et al. (2018) <doi:10.1111/2041-210X.12918>. The package includes a tool for estimating parameters of community assembly by using Approximate Bayesian Computation.
Author: Francois Munoz [aut, cre], Matthias Grenie [aut], Pierre Denelle [aut], Adrien Taudiere [ctb], Fabien Laroche [ctb], Caroline Tucker [ctb], Cyrille Violle [ctb]
Maintainer: Francois Munoz <francois.munoz@hotmail.fr>

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Package usmapdata updated to version 1.0.0 with previous version 0.6.0 dated 2025-06-14

Title: Mapping Data for 'usmap' Package
Description: Provides a container for data used by the 'usmap' package. The data used by 'usmap' has been extracted into this package so that the file size of the 'usmap' package can be reduced greatly. The data in this package will be updated roughly once per year as new map data files are provided by the US Census Bureau.
Author: Paolo Di Lorenzo [aut, cre]
Maintainer: Paolo Di Lorenzo <paolo@dilorenzo.org>

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Package TreeDist updated to version 2.10.0 with previous version 2.9.2 dated 2025-01-11

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>; 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 of trees (Silva and Wilkinson 2021) <doi:10.1093/sysbio/syab015>, for calculating the median [...truncated...]
Author: Martin R. Smith [aut, cre, cph, prg] , Roy Jonker [prg, cph], Yong Yang [ctb, cph], Yi Cao [ctb, cph]
Maintainer: Martin R. Smith <martin.smith@durham.ac.uk>

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Package tensorflow updated to version 2.20.0 with previous version 2.16.0 dated 2024-04-15

Title: R Interface to 'TensorFlow'
Description: Interface to 'TensorFlow' <https://www.tensorflow.org/>, an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more 'CPUs' or 'GPUs' in a desktop, server, or mobile device with a single 'API'. 'TensorFlow' was originally developed by researchers and engineers working on the Google Brain Team within Google's Machine Intelligence research organization for the purposes of conducting machine learning and deep neural networks research, but the system is general enough to be applicable in a wide variety of other domains as well.
Author: JJ Allaire [aut, cph], Tomasz Kalinowski [ctb, cph, cre], Daniel Falbel [ctb, cph], Dirk Eddelbuettel [ctb, cph], Yuan Tang [aut, cph] , Nick Golding [ctb, cph], Google Inc. [ctb, cph] , Posit, PBC [cph, fnd]
Maintainer: Tomasz Kalinowski <tomasz.kalinowski@posit.co>

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Package Superpower updated to version 0.2.4.1 with previous version 0.2.4 dated 2025-06-24

Title: Simulation-Based Power Analysis for Factorial Designs
Description: Functions to perform simulations of ANOVA designs of up to three factors. Calculates the observed power and average observed effect size for all main effects and interactions in the ANOVA, and all simple comparisons between conditions. Includes functions for analytic power calculations and additional helper functions that compute effect sizes for ANOVA designs, observed error rates in the simulations, and functions to plot power curves. Please see Lakens, D., & Caldwell, A. R. (2021). "Simulation-Based Power Analysis for Factorial Analysis of Variance Designs". <doi:10.1177/2515245920951503>.
Author: Aaron Caldwell [aut, cre], Daniel Lakens [aut], Lisa DeBruine [ctb], Jonathon Love [ctb], Frederik Aust [ctb]
Maintainer: Aaron Caldwell <arcaldwell49@gmail.com>

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Package robCompositions updated to version 2.4.2 with previous version 2.4.1 dated 2023-08-25

Title: Compositional Data Analysis
Description: Methods for analysis of compositional data including robust methods (<doi:10.1007/978-3-319-96422-5>), imputation of missing values (<doi:10.1016/j.csda.2009.11.023>), methods to replace rounded zeros (<doi:10.1080/02664763.2017.1410524>, <doi:10.1016/j.chemolab.2016.04.011>, <doi:10.1016/j.csda.2012.02.012>), count zeros (<doi:10.1177/1471082X14535524>), methods to deal with essential zeros (<doi:10.1080/02664763.2016.1182135>), (robust) outlier detection for compositional data, (robust) principal component analysis for compositional data, (robust) factor analysis for compositional data, (robust) discriminant analysis for compositional data (Fisher rule), robust regression with compositional predictors, functional data analysis (<doi:10.1016/j.csda.2015.07.007>) and p-splines (<doi:10.1016/j.csda.2015.07.007>), contingency (<doi:10.1080/03610926.2013.824980>) and compositional tables (<doi:10.1111/sjos.12326>, <doi: [...truncated...]
Author: Matthias Templ [aut, cre] , Karel Hron [aut] , Peter Filzmoser [aut] , Kamila Facevicova [ctb], Petra Kynclova [ctb], Jan Walach [ctb], Veronika Pintar [ctb], Jiajia Chen [ctb], Dominika Miksova [ctb], Bernhard Meindl [ctb], Alessandra Menafoglio [ct [...truncated...]
Maintainer: Matthias Templ <matthias.templ@gmail.com>

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Package gtrendsR updated to version 1.5.2 with previous version 1.5.1 dated 2022-05-23

Title: Perform and Display Google Trends Queries
Description: An interface for retrieving and displaying the information returned online by Google Trends is provided. Trends (number of hits) over the time as well as geographic representation of the results can be displayed.
Author: Philippe Massicotte [aut, cre], Dirk Eddelbuettel [aut]
Maintainer: Philippe Massicotte <pmassicotte@hotmail.com>

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Package gdalraster updated to version 2.2.0 with previous version 2.1.0 dated 2025-07-14

Title: Bindings to 'GDAL'
Description: API bindings to the Geospatial Data Abstraction Library ('GDAL', <https://gdal.org>). Implements the 'GDAL' Raster and Vector Data Models. Bindings are implemented with 'Rcpp' modules. Exposed C++ classes and stand-alone functions wrap much of the 'GDAL' API and provide additional functionality. Calling signatures resemble the native C, C++ and Python APIs provided by the 'GDAL' project. Class 'GDALRaster' encapsulates a 'GDALDataset' and its raster band objects. Class 'GDALVector' encapsulates an 'OGRLayer' and the 'GDALDataset' that contains it. Initial bindings are provided to the unified 'gdal' command line interface added in 'GDAL' 3.11. C++ stand-alone functions provide bindings to most 'GDAL' "traditional" raster and vector utilities, including 'OGR' facilities for vector geoprocessing, several algorithms, as well as the Geometry API ('GEOS' via 'GDAL' headers), the Spatial Reference Systems API, and methods for coordinate transformation. Bindings to the Virtual Systems In [...truncated...]
Author: Chris Toney [aut, cre] , Michael D. Sumner [ctb], Frank Warmerdam [ctb, cph] , Even Rouault [ctb, cph] , Marius Appel [ctb, cph] , Daniel James [ctb, cph] , Peter Dimov [ctb, cph]
Maintainer: Chris Toney <jctoney@gmail.com>

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Package EQUALSTATS updated to version 0.5.1 with previous version 0.5.0 dated 2024-09-23

Title: Algorithm Driven Statistical Analysis for Researchers without Coding Skills
Description: Support functions for R-based 'EQUAL-STATS' software which automatically classifies the data and performs appropriate statistical tests. 'EQUAL-STATS' software is a shiny application with an user-friendly interface to perform complex statistical analysis. Gurusamy,K (2024)<doi:10.5281/zenodo.13354162>.
Author: Kurinchi Gurusamy [aut, cre]
Maintainer: Kurinchi Gurusamy <k.gurusamy@ucl.ac.uk>

Diff between EQUALSTATS versions 0.5.0 dated 2024-09-23 and 0.5.1 dated 2025-08-22

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Package coconots updated to version 2.0.2 with previous version 2.0.1 dated 2025-07-24

Title: Convolution-Closed Models for Count Time Series
Description: Useful tools for fitting, validating, and forecasting of practical convolution-closed time series models for low counts are provided. Marginal distributions of the data can be modelled via Poisson and Generalized Poisson innovations. Regression effects can be incorporated through time varying innovation rates. The models are described in Jung and Tremayne (2011) <doi:10.1111/j.1467-9892.2010.00697.x> and the model assessment tools are presented in Czado et al. (2009) <doi:10.1111/j.1541-0420.2009.01191.x> and, Tsay (1992) <doi:10.2307/2347612>.
Author: Manuel Huth [aut, cre], Robert C. Jung [aut], Andy Tremayne [aut]
Maintainer: Manuel Huth <manuel.huth@yahoo.com>

Diff between coconots versions 2.0.1 dated 2025-07-24 and 2.0.2 dated 2025-08-22

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Package cffdrs updated to version 1.9.2 with previous version 1.9.0 dated 2024-02-22

Title: Canadian Forest Fire Danger Rating System
Description: This project provides a group of new functions to calculate the outputs of the two main components of the Canadian Forest Fire Danger Rating System (CFFDRS) Van Wagner and Pickett (1985) <https://ostrnrcan-dostrncan.canada.ca/entities/publication/29706108-2891-4e5d-a59a-a77c96bc507c>) at various time scales: the Fire Weather Index (FWI) System Wan Wagner (1985) <https://ostrnrcan-dostrncan.canada.ca/entities/publication/d96e56aa-e836-4394-ba29-3afe91c3aa6c> and the Fire Behaviour Prediction (FBP) System Forestry Canada Fire Danger Group (1992) <https://cfs.nrcan.gc.ca/pubwarehouse/pdfs/10068.pdf>. Some functions have two versions, table and raster based.
Author: Xianli Wang [aut], Alan Cantin [aut], Marc-Andre Parisien [aut], Mike Wotton [aut], Kerry Anderson [aut], Brett Moore [cre, aut], Tom Schiks [aut], Mike Flannigan [aut]
Maintainer: Brett Moore <Brett.Moore@nrcan-rncan.gc.ca>

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Package sdcMicro updated to version 5.7.9 with previous version 5.7.8 dated 2024-03-11

Title: Statistical Disclosure Control Methods for Anonymization of Data and Risk Estimation
Description: Data from statistical agencies and other institutions are mostly confidential. This package, introduced in Templ, Kowarik and Meindl (2017) <doi:10.18637/jss.v067.i04>, can be used for the generation of anonymized (micro)data, i.e. for the creation of public- and scientific-use files. The theoretical basis for the methods implemented can be found in Templ (2017) <doi:10.1007/978-3-319-50272-4>. Various risk estimation and anonymization methods are included. Note that the package includes a graphical user interface published in Meindl and Templ (2019) <doi:10.3390/a12090191> that allows to use various methods of this package.
Author: Matthias Templ [aut, cre] , Bernhard Meindl [aut], Alexander Kowarik [aut] , Johannes Gussenbauer [aut], Organisation For Economic Co-Operation And Development [cph] code code for rank swapping, mdav-microaggregation, suda2 and other risk measures [...truncated...]
Maintainer: Matthias Templ <matthias.templ@gmail.com>

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Package psborrow updated to version 0.2.4 with previous version 0.2.3 dated 2025-06-23

Title: Bayesian Dynamic Borrowing with Propensity Score
Description: A tool which aims to help evaluate the effect of external borrowing using an integrated approach described in Lewis et al., (2019) <doi:10.1080/19466315.2018.1497533> that combines propensity score and Bayesian dynamic borrowing methods.
Author: Isaac Gravestock [cre, ctb], Craig Gower-Page [aut], Matt Secrest [ctb], Yichen Lu [aut], Aijing Lin [aut], F. Hoffmann-La Roche AG [cph, fnd]
Maintainer: Isaac Gravestock <isaac.gravestock@roche.com>

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Package ibdsim2 updated to version 2.3.1 with previous version 2.3.0 dated 2025-07-22

Title: Simulation of Chromosomal Regions Shared by Family Members
Description: Simulation of segments shared identical-by-descent (IBD) by pedigree members. Using sex specific recombination rates along the human genome (Halldorsson et al. (2019) <doi:10.1126/science.aau1043>), phased chromosomes are simulated for all pedigree members. Applications include calculation of realised relatedness coefficients and IBD segment distributions. 'ibdsim2' is part of the 'pedsuite' collection of packages for pedigree analysis. A detailed presentation of the 'pedsuite', including a separate chapter on 'ibdsim2', is available in the book 'Pedigree analysis in R' (Vigeland, 2021, ISBN:9780128244302). A 'Shiny' app for visualising and comparing IBD distributions is available at <https://magnusdv.shinyapps.io/ibdsim2-shiny/>.
Author: Magnus Dehli Vigeland [aut, cre]
Maintainer: Magnus Dehli Vigeland <m.d.vigeland@medisin.uio.no>

Diff between ibdsim2 versions 2.3.0 dated 2025-07-22 and 2.3.1 dated 2025-08-22

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Package TreeTools updated to version 1.16.0 with previous version 1.15.0 dated 2025-07-21

Title: Create, Modify and Analyse Phylogenetic Trees
Description: Efficient implementations of functions for the creation, modification and analysis of phylogenetic trees. Applications include: generation of trees with specified shapes; tree rearrangement; analysis of tree shape; rooting of trees and extraction of subtrees; calculation and depiction of split support; plotting the position of rogue taxa (Klopfstein & Spasojevic 2019) <doi:10.1371/journal.pone.0212942>; calculation of ancestor-descendant relationships, of 'stemwardness' (Asher & Smith, 2022) <doi:10.1093/sysbio/syab072>, and of tree balance (Mir et al. 2013, Lemant et al. 2022) <doi:10.1016/j.mbs.2012.10.005>, <doi:10.1093/sysbio/syac027>; artificial extinction (Asher & Smith, 2022) <doi:10.1093/sysbio/syab072>; import and export of trees from Newick, Nexus (Maddison et al. 1997) <doi:10.1093/sysbio/46.4.590>, and TNT <https://www.lillo.org.ar/phylogeny/tnt/> formats; and analysis of splits and cladistic information.
Author: Martin R. Smith [aut, cre, cph] , Emmanuel Paradis [cph] , Robert Noble [cph]
Maintainer: Martin R. Smith <martin.smith@durham.ac.uk>

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More information about TreeTools at CRAN
Permanent link

Package risk.assessr updated to version 2.0.1 with previous version 2.0.0 dated 2025-07-10

Title: Assessing Package Risk Metrics
Description: Provides a structured approach to assess the quality and trustworthiness of R packages (documentation, testing, popularity, dependencies), supporting informed decisions in production or research by highlighting strengths and potential risks in adoption or development.
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>

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Package priorsense updated to version 1.1.1 with previous version 1.1.0 dated 2025-04-10

Title: Prior Diagnostics and Sensitivity Analysis
Description: Provides functions for prior and likelihood sensitivity analysis in Bayesian models. Currently it implements methods to determine the sensitivity of the posterior to power-scaling perturbations of the prior and likelihood.
Author: Noa Kallioinen [aut, cre, cph], Topi Paananen [aut], Paul-Christian Buerkner [aut], Aki Vehtari [aut], Frank Weber [ctb]
Maintainer: Noa Kallioinen <noa.kallioinen@aalto.fi>

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Package modi updated to version 0.1.3 with previous version 0.1.2 dated 2023-03-14

Title: Multivariate Outlier Detection and Imputation for Incomplete Survey Data
Description: Algorithms for multivariate outlier detection when missing values occur. Algorithms are based on Mahalanobis distance or data depth. Imputation is based on the multivariate normal model or uses nearest neighbour donors. The algorithms take sample designs, in particular weighting, into account. The methods are described in Bill and Hulliger (2016) <doi:10.17713/ajs.v45i1.86>.
Author: Beat Hulliger [aut, cre], Martin Sterchi [ctb], Tobias Schoch [ctb]
Maintainer: Beat Hulliger <beat.hulliger@fhnw.ch>

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Package longevity updated to version 1.2.2 with previous version 1.2.1 dated 2025-07-03

Title: Statistical Methods for the Analysis of Excess Lifetimes
Description: A collection of parametric and nonparametric methods for the analysis of survival data. Parametric families implemented include Gompertz-Makeham, exponential and generalized Pareto models and extended models. The package includes an implementation of the nonparametric maximum likelihood estimator for arbitrary truncation and censoring pattern based on Turnbull (1976) <doi:10.1111/j.2517-6161.1976.tb01597.x>, along with graphical goodness-of-fit diagnostics. Parametric models for positive random variables and peaks over threshold models based on extreme value theory are described in Rootzén and Zholud (2017) <doi:10.1007/s10687-017-0305-5>; Belzile et al. (2021) <doi:10.1098/rsos.202097> and Belzile et al. (2022) <doi:10.1146/annurev-statistics-040120-025426>.
Author: Leo Belzile [aut, cre]
Maintainer: Leo Belzile <belzilel@gmail.com>

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Package xega updated to version 0.9.0.17 with previous version 0.9.0.12 dated 2025-07-30

Title: Extended Evolutionary and Genetic Algorithms
Description: Implementation of a scalable, highly configurable, and e(x)tended architecture for (e)volutionary and (g)enetic (a)lgorithms. Multiple representations (binary, real-coded, permutation, and derivation-tree), a rich collection of genetic operators, as well as an extended processing pipeline are provided for genetic algorithms (Goldberg, D. E. (1989, ISBN:0-201-15767-5)), differential evolution (Price, Kenneth V., Storn, Rainer M. and Lampinen, Jouni A. (2005) <doi:10.1007/3-540-31306-0>), simulated annealing (Aarts, E., and Korst, J. (1989, ISBN:0-471-92146-7)), grammar-based genetic programming (Geyer-Schulz (1997, ISBN:978-3-7908-0830-X)), grammatical evolution (Ryan, C., O'Neill, M., and Collins, J. J. (2018) <doi:10.1007/978-3-319-78717-6>), and grammatical differential evolution (O'Neill, M. and Brabazon, A. (2006) in Arabinia, H. (2006, ISBN:978-193-241596-3). All algorithms reuse basic adaptive mechanisms for performance optimization. Sequential or parallel execution ( [...truncated...]
Author: Andreas Geyer-Schulz [aut, cre]
Maintainer: Andreas Geyer-Schulz <Andreas.Geyer-Schulz@kit.edu>

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Package SynergyLMM updated to version 1.1.1 with previous version 1.1.0 dated 2025-07-29

Title: Statistical Framework for in Vivo Drug Combination Studies
Description: A framework for evaluating drug combination effects in preclinical in vivo studies. 'SynergyLMM' provides functions to analyze longitudinal tumor growth experiments using mixed-effects models, perform time-resolved analyses of synergy and antagonism, evaluate model diagnostics and performance, and assess both post-hoc and a priori statistical power. The calculation of drug combination synergy follows the statistical framework provided by Demidenko and Miller (2019, <doi:10.1371/journal.pone.0224137>). The implementation and analysis of linear mixed-effect models is based on the methods described by Pinheiro and Bates (2000, <doi:10.1007/b98882>), and Gałecki and Burzykowski (2013, <doi:10.1007/978-1-4614-3900-4>).
Author: Rafael Romero-Becerra [aut, cre] , Zhi Zhao [ctb], Tero Aittokallio [ctb]
Maintainer: Rafael Romero-Becerra <r.r.becerra@medisin.uio.no>

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Package smer updated to version 0.0.2 with previous version 0.0.1 dated 2025-01-16

Title: Sparse Marginal Epistasis Test
Description: The Sparse Marginal Epistasis Test is a computationally efficient genetics method which detects statistical epistasis in complex traits; see Stamp et al. (2025, <doi:10.1101/2025.01.11.632557>) for details.
Author: Julian Stamp [cre, aut] , Lorin Crawford [aut] , sriramlab [cph]
Maintainer: Julian Stamp <julian.d.stamp@gmail.com>

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Package simplecolors updated to version 0.1.3 with previous version 0.1.2 dated 2023-08-31

Title: Access Color Names Using a Standardized Nomenclature
Description: A curated set of colors that are called using a standardized syntax: saturation + hue + lightness. For example, "brightblue4" and "mutedred2". Functions exists to return individual colors by name or to build palettes across or within hues. Most functions allow you to visualize the palettes in addition to returning the desired hex codes.
Author: Jake Riley [aut, cre]
Maintainer: Jake Riley <rjake@sas.upenn.edu>

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Package moveEZ updated to version 1.1.0 with previous version 1.0.3 dated 2025-07-05

Title: Animated Biplots
Description: Create animated biplots that enables dynamic visualisation of temporal or sequential changes in multivariate data by animating a single biplot across the levels of a time variable. It builds on objects from the 'biplotEZ' package, Lubbe S, le Roux N, Nienkemper-Swanepoel J, Ganey R, Buys R, Adams Z, Manefeldt P (2024) <doi:10.32614/CRAN.package.biplotEZ>, allowing users to create animated biplots that reveal how both samples and variables evolve over time.
Author: Raeesa Ganey [aut, cre, cph] , Johane Nienkemper-Swanepoel [aut, cph]
Maintainer: Raeesa Ganey <raeesa.ganey@wits.ac.za>

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Package roll updated to version 1.2.0 with previous version 1.1.7 dated 2024-04-05

Title: Rolling and Expanding Statistics
Description: Fast and efficient computation of rolling and expanding statistics for time-series data.
Author: Jason Foster [aut, cre]
Maintainer: Jason Foster <jason.j.foster@gmail.com>

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Package moderate.mediation updated to version 0.0.12 with previous version 0.0.11 dated 2025-04-03

Title: Causal Moderated Mediation Analysis
Description: Causal moderated mediation analysis using the methods proposed by Qin and Wang (2023) <doi:10.3758/s13428-023-02095-4>. Causal moderated mediation analysis is crucial for investigating how, for whom, and where a treatment is effective by assessing the heterogeneity of mediation mechanism across individuals and contexts. This package enables researchers to estimate and test the conditional and moderated mediation effects, assess their sensitivity to unmeasured pre-treatment confounding, and visualize the results. The package is built based on the quasi-Bayesian Monte Carlo method, because it has relatively better performance at small sample sizes, and its running speed is the fastest. The package is applicable to a treatment of any scale, a binary or continuous mediator, a binary or continuous outcome, and one or more moderators of any scale.
Author: Xu Qin [aut, cre, cph], Lijuan Wang [ctb]
Maintainer: Xu Qin <xuqin@pitt.edu>

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Package xegaPopulation updated to version 1.0.0.10 with previous version 1.0.0.8 dated 2025-07-30

Title: Genetic Population Level Functions
Description: This collection of gene representation-independent functions implements the population layer of extended evolutionary and genetic algorithms and its support. The population layer consists of functions for initializing, logging, observing, evaluating a population of genes, as well as of computing the next population. For parallel evaluation of a population of genes 4 execution models - named Sequential, MultiCore, FutureApply, and Cluster - are provided. They are implemented by configuring the lapply() function. The execution model FutureApply can be externally configured as recommended by Bengtsson (2021) <doi:10.32614/RJ-2021-048>. Configurable acceptance rules and cooling schedules (see Kirkpatrick, S., Gelatt, C. D. J, and Vecchi, M. P. (1983) <doi:10.1126/science.220.4598.671>, and Aarts, E., and Korst, J. (1989, ISBN:0-471-92146-7) offer simulated annealing or greedy randomized approximate search procedure elements. Adaptive crossover and mutation rates depending on po [...truncated...]
Author: Andreas Geyer-Schulz [aut, cre]
Maintainer: Andreas Geyer-Schulz <Andreas.Geyer-Schulz@kit.edu>

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Package xegaGpGene updated to version 1.0.0.3 with previous version 1.0.0.2 dated 2025-04-17

Title: Genetic Operations for Grammar-Based Genetic Programming
Description: An implementation of the representation-dependent gene level operations of grammar-based genetic programming with genes which are derivation trees of a context-free grammar: Initialization of a gene with a complete random derivation tree, decoding of a derivation tree. Crossover is implemented by exchanging subtrees. Depth-bounds for the minimal and the maximal depth of the roots of the subtrees exchanged by crossover can be set. Mutation is implemented by replacing a subtree by a random subtree. The depth of the random subtree and the insertion node are configurable. For details, see Geyer-Schulz (1997, ISBN:978-3-7908-0830-X).
Author: Andreas Geyer-Schulz [aut, cre]
Maintainer: Andreas Geyer-Schulz <Andreas.Geyer-Schulz@kit.edu>

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Package gicf updated to version 1.0.1 with previous version 1.0 dated 2025-05-16

Title: Penalised Likelihood Estimation of a Covariance Matrix
Description: Penalised likelihood estimation of a covariance matrix via the ridge-regularised covglasso estimator described in Cibinel et al. (2024) <doi:10.48550/arXiv.2410.02403>. Based on the 'C++' code of the 'R' package 'covglasso' (by Michael Fop, <https://orcid.org/0000-0003-3936-2757>) and the 'R' code of 'icf' (by Mathias Drton, <https://orcid.org/0000-0001-5614-3025>) within the 'R' package 'ggm'.
Author: Luca Cibinel [cre, aut] , Alberto Roverato [aut] , Veronica Vinciotti [aut]
Maintainer: Luca Cibinel <lcibinel@gmail.com>

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Package disaggregation updated to version 0.4.1 with previous version 0.4.0 dated 2024-10-02

Title: Disaggregation Modelling
Description: Fits disaggregation regression models using 'TMB' ('Template Model Builder'). When the response data are aggregated to polygon level but the predictor variables are at a higher resolution, these models can be useful. Regression models with spatial random fields. The package is described in detail in Nandi et al. (2023) <doi:10.18637/jss.v106.i11>.
Author: Anita Nandi [aut] , Tim Lucas [aut, cre] , Rohan Arambepola [aut], Andre Python [aut] , Simon Smart [ctb]
Maintainer: Tim Lucas <timcdlucas@gmail.com>

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Package datefixR updated to version 2.0.0 with previous version 1.7.0 dated 2024-09-08

Title: Standardize Dates in Different Formats or with Missing Data
Description: There are many different formats dates are commonly represented with: the order of day, month, or year can differ, different separators ("-", "/", or whitespace) can be used, months can be numerical, names, or abbreviations and year given as two digits or four. 'datefixR' takes dates in all these different formats and converts them to R's built-in date class. If 'datefixR' cannot standardize a date, such as because it is too malformed, then the user is told which date cannot be standardized and the corresponding ID for the row. 'datefixR' also allows the imputation of missing days and months with user-controlled behavior.
Author: Nathan Constantine-Cooke [aut, cre] , Jonathan Kitt [ctb, trl], Antonio J. Perez-Luque [ctb, trl] , Daniel Possenriede [ctb, trl] , Michal Lauer [ctb, trl], Kaique dos S. Alves [rev] , Al-Ahmadgaid B. Asaad [rev] , Anatoly Tsyplenkov [ctb, trl] , Chi [...truncated...]
Maintainer: Nathan Constantine-Cooke <nathan.constantine-cooke@ed.ac.uk>

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Package xegaGaGene updated to version 1.0.0.5 with previous version 1.0.0.4 dated 2025-07-28

Title: Binary Gene Operations for Genetic Algorithms
Description: Representation-dependent gene level operations of a genetic algorithm with binary coded genes: Initialization of random binary genes, several gene maps for binary genes, several mutation operators, several crossover operators with 1 and 2 kids, replication pipelines for 1 and 2 kids, and, last but not least, function factories for configuration. See Goldberg, D. E. (1989, ISBN:0-201-15767-5). For crossover operators, see Syswerda, G. (1989, ISBN:1-55860-066-3), Spears, W. and De Jong, K. (1991, ISBN:1-55860-208-9). For mutation operators, see Stanhope, S. A. and Daida, J. M. (1996, ISBN:0-18-201-031-7).
Author: Andreas Geyer-Schulz [aut, cre]
Maintainer: Andreas Geyer-Schulz <Andreas.Geyer-Schulz@kit.edu>

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Package xegaDfGene updated to version 1.0.0.7 with previous version 1.0.0.5 dated 2025-07-29

Title: Gene Operations for Real-Coded Genes
Description: Representation-dependent gene-level operations for genetic and evolutionary algorithms with real-coded genes are collected in this package. The common feature of the gene operations is that all of them are useful for derivation-free optimization algorithms. At the moment the package implements initialization, mutation, crossover, and replication operations for differential evolution as described in Price, Kenneth V., Storn, Rainer M. and Lampinen, Jouni A. (2005) <doi:10.1007/3-540-31306-0>. In addition, several (more recent) methods for determining the scale factor are provided.
Author: Andreas Geyer-Schulz [aut, cre]
Maintainer: Andreas Geyer-Schulz <Andreas.Geyer-Schulz@kit.edu>

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Package tidyllm updated to version 0.3.5 with previous version 0.3.4 dated 2025-03-27

Title: Tidy Integration of Large Language Models
Description: A tidy interface for integrating large language model (LLM) APIs such as 'Claude', 'Openai', 'Gemini','Mistral' and local models via 'Ollama' into R workflows. The package supports text and media-based interactions, interactive message history, batch request APIs, and a tidy, pipeline-oriented interface for streamlined integration into data workflows. Web services are available at <https://www.anthropic.com>, <https://openai.com>, <https://aistudio.google.com/>, <https://mistral.ai/> and <https://ollama.com>.
Author: Eduard Bruell [aut, cre], Jia Zhang [ctb]
Maintainer: Eduard Bruell <eduard.bruell@zew.de>

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Package teal.modules.clinical updated to version 0.11.1 with previous version 0.11.0 dated 2025-08-21

Title: 'teal' Modules for Standard Clinical Outputs
Description: Provides user-friendly tools for creating and customizing clinical trial reports. By leveraging the 'teal' framework, this package provides 'teal' modules to easily create an interactive panel that allows for seamless adjustments to data presentation, thereby streamlining the creation of detailed and accurate reports.
Author: Joe Zhu [aut] , Jana Stoilova [aut], Davide Garolini [aut], Emily de la Rua [aut], Abinaya Yogasekaram [aut], Mahmoud Hallal [aut], Dawid Kaledkowski [aut, cre], Rosemary Li [aut], Heng Wang [aut], Pawel Rucki [aut], Nikolas Burkoff [aut], Konrad Pag [...truncated...]
Maintainer: Dawid Kaledkowski <dawid.kaledkowski@roche.com>

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Package SYNCSA readmission to version 1.3.5 with previous version 1.3.4 dated 2020-01-09

Title: Analysis of Functional and Phylogenetic Patterns in Metacommunities
Description: Analysis of metacommunities based on functional traits and phylogeny of the community components. The functions that are offered here implement for the R environment methods that have been available in the 'SYNCSA' application written in C++ (by Valerio Pillar, available at <http://ecoqua.ecologia.ufrgs.br/SYNCSA.html>).
Author: Vanderlei Julio Debastiani [aut, cre]
Maintainer: Vanderlei Julio Debastiani <vanderleidebastiani@yahoo.com.br>

This is a re-admission after prior archival of version 1.3.4 dated 2020-01-09

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Package SeaGraphs updated to version 0.1.3 with previous version 0.1.2 dated 2025-05-30

Title: Sea Currents to Connectivity Transformation
Description: Transformation of sea currents to connectivity data. Two files of horizontal and vertical currents flows are transformed into connectivity data in the form of 'sfnetwork', shapefile, edge list and adjacency matrix. An application example is shown at Nagkoulis et al. (2025) <doi:10.1016/j.dib.2024.111268>.
Author: Nikolaos Nagkoulis [aut] , Christos Adam [aut, cre] , Ioannis G. Mamoutos [aut] , Antonios D. Mazaris [aut] , Stelios Katsanevakis [aut]
Maintainer: Christos Adam <econp266@econ.soc.uoc.gr>

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Package finbif updated to version 0.9.11 with previous version 0.9.10 dated 2025-04-15

Title: Interface for the 'Finnish Biodiversity Information Facility' API
Description: A programmatic interface to the 'Finnish Biodiversity Information Facility' ('FinBIF') API (<https://api.laji.fi>). 'FinBIF' aggregates Finnish biodiversity data from multiple sources in a single open access portal for researchers, citizen scientists, industry and government. 'FinBIF' allows users of biodiversity information to find, access, combine and visualise data on Finnish plants, animals and microorganisms. The 'finbif' package makes the publicly available data in 'FinBIF' easily accessible to programmers. Biodiversity information is available on taxonomy and taxon occurrence. Occurrence data can be filtered by taxon, time, location and other variables. The data accessed are conveniently preformatted for subsequent analyses.
Author: Finnish Museum of Natural History - Luomus [cph] , Finnish Biodiversity Information Facility [cph] , William K. Morris [aut, cre]
Maintainer: William K. Morris <willi@mmorris.email>

Diff between finbif versions 0.9.10 dated 2025-04-15 and 0.9.11 dated 2025-08-22

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Package dunlin updated to version 0.1.11 with previous version 0.1.10 dated 2025-04-14

Title: Preprocessing Tools for Clinical Trial Data
Description: A collection of functions to preprocess data and organize them in a format amenable to use by chevron.
Author: Liming Li [aut] , Benoit Falquet [aut] , Xiaoli Duan [ctb], Pawel Rucki [ctb], Joe Zhu [cre] , F. Hoffmann-La Roche AG [cph, fnd]
Maintainer: Joe Zhu <joe.zhu@roche.com>

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Package XML updated to version 3.99-0.19 with previous version 3.99-0.18 dated 2025-01-01

Title: Tools for Parsing and Generating XML Within R and S-Plus
Description: Many approaches for both reading and creating XML (and HTML) documents (including DTDs), both local and accessible via HTTP or FTP. Also offers access to an 'XPath' "interpreter".
Author: CRAN Team [ctb, cre] , Duncan Temple Lang [aut] , Tomas Kalibera [ctb], Ivan Krylov [ctb]
Maintainer: CRAN Team <CRAN@r-project.org>

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Package wrProteo updated to version 1.13.3 with previous version 1.13.1 dated 2025-04-01

Title: Proteomics Data Analysis Functions
Description: Data analysis of proteomics experiments by mass spectrometry is supported by this collection of functions mostly dedicated to the analysis of (bottom-up) quantitative (XIC) data. Fasta-formatted proteomes (eg from UniProt Consortium <doi:10.1093/nar/gky1049>) can be read with automatic parsing and multiple annotation types (like species origin, abbreviated gene names, etc) extracted. Initial results from multiple software for protein (and peptide) quantitation can be imported (to a common format): MaxQuant (Tyanova et al 2016 <doi:10.1038/nprot.2016.136>), Dia-NN (Demichev et al 2020 <doi:10.1038/s41592-019-0638-x>), Fragpipe (da Veiga et al 2020 <doi:10.1038/s41592-020-0912-y>), ionbot (Degroeve et al 2021 <doi:10.1101/2021.07.02.450686>), MassChroq (Valot et al 2011 <doi:10.1002/pmic.201100120>), OpenMS (Strauss et al 2021 <doi:10.1038/nmeth.3959>), ProteomeDiscoverer (Orsburn 2021 <doi:10.3390/proteomes9010015>), Proline (Bouyssie et a [...truncated...]
Author: Wolfgang Raffelsberger [aut, cre]
Maintainer: Wolfgang Raffelsberger <w.raffelsberger@gmail.com>

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Package SimSurvey updated to version 0.1.7 with previous version 0.1.6 dated 2023-09-19

Title: Test Surveys by Simulating Spatially-Correlated Populations
Description: Simulate age-structured populations that vary in space and time and explore the efficacy of a range of built-in or user-defined sampling protocols to reproduce the population parameters of the known population. (See Regular et al. (2020) <doi:10.1371/journal.pone.0232822> for more details).
Author: Paul Regular [aut, cre] , Jonathan Babyn [ctb], Greg Robertson [ctb]
Maintainer: Paul Regular <Paul.Regular@dfo-mpo.gc.ca>

Diff between SimSurvey versions 0.1.6 dated 2023-09-19 and 0.1.7 dated 2025-08-22

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Package BioVizSeq updated to version 1.0.4 with previous version 1.0.3 dated 2025-04-11

Title: Visualizing the Elements Within Bio-Sequences
Description: Visualizing the types and distribution of elements within bio-sequences. At the same time, We have developed a geom layer, geom_rrect(), that can generate rounded rectangles. No external references are used in the development of this package.
Author: Shiqi Zhao [aut, cre, cph]
Maintainer: Shiqi Zhao <zhaosq89@163.com>

Diff between BioVizSeq versions 1.0.3 dated 2025-04-11 and 1.0.4 dated 2025-08-22

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Package semPower updated to version 2.1.3 with previous version 2.1.1 dated 2024-09-29

Title: Power Analyses for SEM
Description: Provides a-priori, post-hoc, and compromise power-analyses for structural equation models (SEM).
Author: Morten Moshagen [aut, cre] , Martina Bader [aut]
Maintainer: Morten Moshagen <morten.moshagen@uni-ulm.de>

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Package PopGenReport updated to version 3.1.3 with previous version 3.1 dated 2023-10-11

Title: A Simple Framework to Analyse Population and Landscape Genetic Data
Description: Provides beginner friendly framework to analyse population genetic data. Based on 'adegenet' objects it uses 'knitr' to create comprehensive reports on spatial genetic data. For detailed information how to use the package refer to the comprehensive tutorials or visit <http://www.popgenreport.org/>.
Author: Bernd Gruber [aut, cre], Aaron Adamack [aut]
Maintainer: Bernd Gruber <bernd.gruber@canberra.edu.au>

Diff between PopGenReport versions 3.1 dated 2023-10-11 and 3.1.3 dated 2025-08-22

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Package lancor updated to version 0.1.3 with previous version 0.1.2 dated 2024-05-02

Title: Statistical Inference via Lancaster Correlation
Description: Implementation of the methods described in Holzmann, Klar (2024) <doi: 10.1111/sjos.12733>. Lancaster correlation is a correlation coefficient which equals the absolute value of the Pearson correlation for the bivariate normal distribution, and is equal to or slightly less than the maximum correlation coefficient for a variety of bivariate distributions. Rank and moment-based estimators and corresponding confidence intervals are implemented, as well as independence tests based on these statistics.
Author: Bernhard Klar [aut, cre] , Hajo Holzmann [aut], Lucas Iglesias [ctb]
Maintainer: Bernhard Klar <bernhard.klar@kit.edu>

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Package CoTiMA updated to version 1.0.2 with previous version 0.8.0 dated 2024-04-25

Title: Continuous Time Meta-Analysis ('CoTiMA')
Description: The 'CoTiMA' package performs meta-analyses of correlation matrices of repeatedly measured variables taken from studies that used different time intervals. Different time intervals between measurement occasions impose problems for meta-analyses because the effects (e.g. cross-lagged effects) cannot be simply aggregated, for example, by means of common fixed or random effects analysis. However, continuous time math, which is applied in 'CoTiMA', can be used to extrapolate or intrapolate the results from all studies to any desired time lag. By this, effects obtained in studies that used different time intervals can be meta-analyzed. 'CoTiMA' fits models to empirical data using the structural equation model (SEM) package 'ctsem', the effects specified in a SEM are related to parameters that are not directly included in the model (i.e., continuous time parameters; together, they represent the continuous time structural equation model, CTSEM). Statistical model comparisons and significance [...truncated...]
Author: Christian Dormann [aut, cph], Markus Homberg [aut, com, cre], Olga Diener [ctb], Christina Guthier [ctb], Manuel Voelkle [ctb]
Maintainer: Markus Homberg <cotima@uni-mainz.de>

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Package carcass updated to version 1.9 with previous version 1.7 dated 2023-10-03

Title: Estimation of the Number of Fatalities from Carcass Searches
Description: The number of bird or bat fatalities from collisions with buildings, towers or wind energy turbines can be estimated based on carcass searches and experimentally assessed carcass persistence times and searcher efficiency. Functions for estimating the probability that a bird or bat that died is found by a searcher are provided. Further functions calculate the posterior distribution of the number of fatalities based on the number of carcasses found and the estimated detection probability.
Author: Fraenzi Korner-Nievergelt [aut, cre], Ivo Niermann [aut], Oliver Behr [aut], Matthew A. Etterson [aut], Robert Brinkmann [aut], Pius Korner [aut], Barbara Hellriegel [aut], Tobias Roth [aut], Manuela M. P. Huso [aut], Dan Dalthorp [aut]
Maintainer: Fraenzi Korner-Nievergelt <fraenzi.korner@oikostat.ch>

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Package BeviMed updated to version 7.0 with previous version 6.0 dated 2025-04-29

Title: Bayesian Evaluation of Variant Involvement in Mendelian Disease
Description: A fast integrative genetic association test for rare diseases based on a model for disease status given allele counts at rare variant sites. Probability of association, mode of inheritance and probability of pathogenicity for individual variants are all inferred in a Bayesian framework - 'A Fast Association Test for Identifying Pathogenic Variants Involved in Rare Diseases', Greene et al 2017 <doi:10.1016/j.ajhg.2017.05.015>.
Author: Daniel Greene [aut, cre]
Maintainer: Daniel Greene <dg333@cam.ac.uk>

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Package ShiVa updated to version 1.0.2 with previous version 1.0.1 dated 2025-07-22

Title: Detection of Evolutionary Shifts in Both Optimal Value and Variance
Description: Implements statistical methods for detecting evolutionary shifts in both the optimal trait value (mean) and evolutionary diffusion variance. The method uses an L1-penalized optimization framework to identify branches where shifts occur, and the shift magnitudes. It also supports the inclusion of measurement error. For more details, see Zhang, Ho, and Kenney (2023) <doi:10.48550/arXiv.2312.17480>.
Author: Wensha Zhang [aut, cre], Lam Si Tung Ho [aut], Toby Kenney [aut]
Maintainer: Wensha Zhang <wn209685@dal.ca>

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Package modeldata updated to version 1.5.1 with previous version 1.5.0 dated 2025-07-31

Title: Data Sets Useful for Modeling Examples
Description: Data sets used for demonstrating or testing model-related packages are contained in this package.
Author: Max Kuhn [aut, cre], Posit Software, PBC [cph, fnd]
Maintainer: Max Kuhn <max@posit.co>

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Package ipaddress updated to version 1.0.3 with previous version 1.0.2 dated 2023-12-01

Title: Data Analysis for IP Addresses and Networks
Description: Classes and functions for working with IP (Internet Protocol) addresses and networks, inspired by the Python 'ipaddress' module. Offers full support for both IPv4 and IPv6 (Internet Protocol versions 4 and 6) address spaces. It is specifically designed to work well with the 'tidyverse'.
Author: David Hall [aut, cre]
Maintainer: David Hall <david.hall.physics@gmail.com>

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Package gam updated to version 1.22-6 with previous version 1.22-5 dated 2024-09-12

Title: Generalized Additive Models
Description: Functions for fitting and working with generalized additive models, as described in chapter 7 of "Statistical Models in S" (Chambers and Hastie (eds), 1991), and "Generalized Additive Models" (Hastie and Tibshirani, 1990).
Author: Trevor Hastie [aut, cre], Balasubramanian Narasimhan [ctb]
Maintainer: Trevor Hastie <hastie@stanford.edu>

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Package Certara.RsNLME updated to version 3.1.0 with previous version 3.0.1 dated 2024-11-20

Title: Pharmacometric Modeling
Description: Facilitate Pharmacokinetic (PK) and Pharmacodynamic (PD) modeling and simulation with powerful tools for Nonlinear Mixed-Effects (NLME) modeling. The package provides access to the same advanced Maximum Likelihood algorithms used by the NLME-Engine in the Phoenix platform. These tools support a range of analyses, from parametric methods to individual and pooled data, and support integrated use within the Pirana pharmacometric workbench <doi:10.1002/psp4.70067>. Execution is supported both locally or on remote machines.
Author: James Craig [aut, cre], Michael Tomashevskiy [aut], Vitalii Nazarov [aut], Shuhua Hu [ctb], Soltanshahi Fred [aut], Certara USA, Inc. [cph, fnd]
Maintainer: James Craig <james.craig@certara.com>

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Package Andromeda updated to version 1.1.1 with previous version 1.1.0 dated 2025-07-24

Title: Asynchronous Disk-Based Representation of Massive Data
Description: Storing very large data objects on a local drive, while still making it possible to manipulate the data in an efficient manner.
Author: Adam Black [aut], Egill Fridgeirsson [aut], Martijn Schuemie [aut, cre], Marc A. Suchard [aut], Observational Health Data Science and Informatics [cph]
Maintainer: Martijn Schuemie <schuemie@ohdsi.org>

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Package zephyr updated to version 0.1.3 with previous version 0.1.2 dated 2025-03-13

Title: Structured Messages and Options
Description: Provides a structured framework for consistent user communication and configuration management for package developers.
Author: Aksel Thomsen [aut, cre], Mathias Lerbech Jeppesen [aut], Cervan Girard [aut], Kristian Troejelsgaard [aut], Lovemore Gakava [aut], Steffen Falgreen Larsen [aut], Vladimir Obucina [aut], Novo Nordisk A/S [cph]
Maintainer: Aksel Thomsen <oath@novonordisk.com>

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Package r2rtf updated to version 1.2.0 with previous version 1.1.4 dated 2025-03-11

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, cre], Nan Xiao [ctb], Madhusudhan Ginnaram [ctb], Ruchitbhai Patel [ctb], Huei-Ling Chen [ctb], Peikun Wu [ctb], Uday Preetham Palukuru [c [...truncated...]
Maintainer: Benjamin Wang <benjamin.wang@merck.com>

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Package mrgsolve updated to version 1.6.1 with previous version 1.5.2 dated 2024-10-18

Title: Simulate from ODE-Based Models
Description: Fast simulation from ordinary differential equation (ODE) based models typically employed in quantitative pharmacology and systems biology.
Author: Kyle T Baron [aut, cre] , Bill Gillespie [ctb], Charles Margossian [ctb], Devin Pastoor [ctb], Bill Denney [ctb] , Dilawar Singh [ctb], Felicien Le Louedec [ctb] , Timothy Waterhouse [ctb] , Kyle Meyer [ctb], Metrum Research Group [cph]
Maintainer: Kyle T Baron <kyleb@metrumrg.com>

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Package manymome updated to version 0.3.1 with previous version 0.2.9 dated 2025-06-21

Title: Mediation, Moderation and Moderated-Mediation After Model Fitting
Description: Computes indirect effects, conditional effects, and conditional indirect effects in a structural equation model or path model after model fitting, with no need to define any user parameters or label any paths in the model syntax, using the approach presented in Cheung and Cheung (2024) <doi:10.3758/s13428-023-02224-z>. Can also form bootstrap confidence intervals by doing bootstrapping only once and reusing the bootstrap estimates in all subsequent computations. Supports bootstrap confidence intervals for standardized (partially or completely) indirect effects, conditional effects, and conditional indirect effects as described in Cheung (2009) <doi:10.3758/BRM.41.2.425> and Cheung, Cheung, Lau, Hui, and Vong (2022) <doi:10.1037/hea0001188>. Model fitting can be done by structural equation modeling using lavaan() or regression using lm().
Author: Shu Fai Cheung [aut, cre] , Sing-Hang Cheung [aut] , Rong Wei Sun [ctb]
Maintainer: Shu Fai Cheung <shufai.cheung@gmail.com>

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Package lpacf updated to version 1.0.2 with previous version 1.0.1 dated 2023-05-12

Title: Local Partial Autocorrelation Function Estimation for Locally Stationary Wavelet Processes
Description: Provides the method for computing the local partial autocorrelation function for locally stationary wavelet time series from Killick, Knight, Nason, Eckley (2020) <doi:10.1214/20-EJS1748>.
Author: Rebecca Killick [aut, cre], Guy Nason [aut], Marina Knight [aut], Matt Nunes [aut], Idris Eckley [ctb]
Maintainer: Rebecca Killick <r.killick@lancs.ac.uk>

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Package lessR updated to version 4.4.5 with previous version 4.4.4 dated 2025-06-16

Title: Less Code, More Results
Description: Each function replaces multiple standard R functions. For example, two function calls, Read() and CountAll(), generate summary statistics for all variables in the data frame, plus histograms and bar charts as appropriate. Other functions provide for summary statistics via pivot tables, a comprehensive regression analysis, ANOVA and t-test, visualizations including the Violin/Box/Scatter plot for a numerical variable, bar chart, histogram, box plot, density curves, calibrated power curve, reading multiple data formats with the same function call, variable labels, time series with aggregation and forecasting, color themes, and Trellis (facet) graphics. Also includes a confirmatory factor analysis of multiple indicator measurement models, pedagogical routines for data simulation such as for the Central Limit Theorem, generation and rendering of regression instructions for interpretative output, and interactive visualizations.
Author: David W. Gerbing [aut, cre]
Maintainer: David W. Gerbing <gerbing@pdx.edu>

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 lessR-4.4.5/lessR/R/date.infer.R                  |only
 lessR-4.4.5/lessR/R/order_by.R                    |    8 
 lessR-4.4.5/lessR/R/pc.main.R                     |    1 
 lessR-4.4.5/lessR/R/plt.by.legend.R               |   11 
 lessR-4.4.5/lessR/R/plt.forecast.R                |  838 +++++++++++++++-------
 lessR-4.4.5/lessR/R/plt.lattice.R                 |   10 
 lessR-4.4.5/lessR/R/plt.main.R                    |   51 -
 lessR-4.4.5/lessR/R/plt.time.R                    |   17 
 lessR-4.4.5/lessR/R/style.R                       |    2 
 lessR-4.4.5/lessR/R/train_test.R                  |   12 
 lessR-4.4.5/lessR/R/zzz.R                         |   51 +
 lessR-4.4.5/lessR/R/zzz_ts.R                      |only
 lessR-4.4.5/lessR/build/vignette.rds              |binary
 lessR-4.4.5/lessR/data/dataStockPrice.rda         |binary
 lessR-4.4.5/lessR/inst/doc/intro.R                |    6 
 lessR-4.4.5/lessR/inst/doc/intro.Rmd              |   11 
 lessR-4.4.5/lessR/inst/doc/intro.html             |  439 ++++++-----
 lessR-4.4.5/lessR/inst/shiny_apps/BarChart/app.R  |   26 
 lessR-4.4.5/lessR/inst/shiny_apps/Histogram/app.R |   64 -
 lessR-4.4.5/lessR/man/PieChart.Rd                 |    4 
 lessR-4.4.5/lessR/man/Plot.Rd                     |  195 +++--
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 lessR-4.4.5/lessR/man/reshape_long.Rd             |    1 
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 lessR-4.4.5/lessR/vignettes/intro.Rmd             |   11 
 33 files changed, 1496 insertions(+), 827 deletions(-)

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