Thu, 17 Sep 2026

Package codyn updated to version 2.0.6 with previous version 2.0.5 dated 2020-12-01

Title: Community Dynamics Metrics
Description: Univariate and multivariate temporal and spatial diversity indices, rank abundance curves, and community stability measures. The functions implement measures that are either explicitly temporal and include the option to calculate them over multiple replicates, or spatial and include the option to calculate them over multiple time points. Functions fall into five categories: static diversity indices, temporal diversity indices, spatial diversity indices, rank abundance curves, and community stability measures. The diversity indices are temporal and spatial analogs to traditional diversity indices. Specifically, the package includes functions to calculate community richness, evenness and diversity at a given point in space and time. In addition, it contains functions to calculate species turnover, mean rank shifts, and lags in community similarity between two time points. Details of the methods are available in Hallett et al. (2016) <doi:10.1111/2041-210X.12569> and Avolio et al. ( [...truncated...]
Author: Lauren Hallett [aut] , Meghan L. Avolio [aut] , Ian T. Carroll [aut] , Sydney K. Jones [aut], A. Andrew M. MacDonald [aut] , Dan F. B. Flynn [aut] , Peter Slaughter [aut] , Julie Ripplinger [aut] , Scott L. Collins [aut] , Corinna Gries [aut] , Matth [...truncated...]
Maintainer: Matthew B. Jones <jones@nceas.ucsb.edu>

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Package stpphawkes updated to version 0.2.4 with previous version 0.2.2 dated 2025-03-10

Title: Missing Data for Marked Hawkes Process
Description: Estimation of model parameters for marked Hawkes process. Accounts for missing data in the estimation of the parameters. Technical details found in (Tucker et al., 2019 <DOI:10.1016/j.spasta.2018.12.004>).
Author: J. Derek Tucker [aut, cre], Lyndsay Shand [aut], Stephen Rowe [aut], John Lewis [aut]
Maintainer: J. Derek Tucker <jdtuck@sandia.gov>

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Package Rdistance updated to version 4.5.0 with previous version 4.4.3 dated 2026-05-14

Title: Density and Abundance from Distance-Sampling Surveys
Description: Distance-sampling (<doi:10.1007/978-3-319-19219-2>) is a field survey and analytical method that estimates density and abundance of survey targets (e.g., animals) when detection probability declines with observation distance. Distance-sampling is popular in ecology, especially when survey targets are observed from aerial platforms (e.g., airplane or drone), surface vessels (e.g., boat or truck), or along walking transects. Analysis involves fitting smooth (parametric) curves to histograms of observation distances and using those functions to adjust density estimates for missed targets. Routines included here fit curves to observation distance histograms, estimate effective sampling area, density of targets in surveyed areas, and the abundance of targets in a surrounding study area. Confidence interval estimation uses built-in bootstrap resampling. Help files are extensive and have been vetted by multiple authors. Many tutorials are available on the package's website (URL below).
Author: Trent McDonald [cre, aut], Jason Carlisle [aut], Aidan McDonald [aut] , Ryan Nielson [ctb] , Ben Augustine [ctb] , James Griswald [ctb] , Patrick McKann [ctb] , Lacey Jeroue [ctb] , Hoffman Abigail [ctb] , Kleinsausser Michael [ctb] , Joel Reynolds [ [...truncated...]
Maintainer: Trent McDonald <trent@mcdonalddatasciences.com>

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Package mvBayes updated to version 1.2.3 with previous version 1.2.2 dated 2026-07-30

Title: Multivariate Bayesian Regression
Description: Fit, plot, and predict a multivariate response, using an arbitrary univariate Bayesian regression model to independently fit basis components (e.g., principal components) of the response (Francom et al., 2025 <DOI:10.1137/24M1644092>).
Author: Gavin Collins [aut, ctb], J. Derek Tucker [ctb, cre] , Sandia National Laboratories [cph, fnd]
Maintainer: J. Derek Tucker <jdtuck@sandia.gov>

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Package BayesPPR updated to version 0.2.0 with previous version 0.1.0 dated 2026-05-18

Title: Bayesian Projection Pursuit Regression
Description: Bayesian fitting of projection pursuit regression model. Built to handle continuous and categorical inputs and scalar output (Collins et al., 2023 <DOI:10.1007/s11222-023-10334-z>).
Author: Gavin Collins [aut, ctb], J. Derek Tucker [ctb, cre]
Maintainer: J. Derek Tucker <jdtuck@sandia.gov>

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Package RTMB updated to version 2.0 with previous version 1.9 dated 2026-03-20

Title: 'R' Bindings for 'TMB'
Description: Native 'R' interface to 'TMB' (Template Model Builder) so models can be written entirely in 'R' rather than 'C++'. Automatic differentiation, to any order, is available for a rich subset of 'R' features, including linear algebra for dense and sparse matrices, complex arithmetic, Fast Fourier Transform, probability distributions and special functions. 'RTMB' provides easy access to model fitting and validation following the principles of Kristensen, K., Nielsen, A., Berg, C. W., Skaug, H., & Bell, B. M. (2016) <DOI:10.18637/jss.v070.i05> and Thygesen, U.H., Albertsen, C.M., Berg, C.W. et al. (2017) <DOI:10.1007/s10651-017-0372-4>.
Author: Kasper Kristensen [aut, cre]
Maintainer: Kasper Kristensen <kaskr@dtu.dk>

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Package dataseries updated to version 1.1.0 with previous version 1.0.0 dated 2026-06-13

Title: Switzerland's Data Series in One Place
Description: Download and import open Swiss economic time series from 'dataseries.org' <https://dataseries.org>, a comprehensive and up-to-date collection of public data from Switzerland. Series are retrieved through the public 'dataseries.org' API and imported as a 'data.frame' or 'ts' object.
Author: Christoph Sax [aut, cre, cph], Jannes Muenchow [ctb]
Maintainer: Christoph Sax <christoph.sax@gmail.com>

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Package tinytex updated to version 0.61 with previous version 0.60 dated 2026-06-16

Title: Helper Functions to Install and Maintain TeX Live, and Compile LaTeX Documents
Description: Helper functions to install and maintain the 'LaTeX' distribution named 'TinyTeX' (<https://yihui.org/tinytex/>), a lightweight, cross-platform, portable, and easy-to-maintain version of 'TeX Live'. This package also contains helper functions to compile 'LaTeX' documents, and install missing 'LaTeX' packages automatically.
Author: Yihui Xie [aut, cre, cph] , Posit Software, PBC [cph, fnd], Christophe Dervieux [ctb] , Devon Ryan [ctb] , Ethan Heinzen [ctb], Fernando Cagua [ctb]
Maintainer: Yihui Xie <xie@yihui.name>

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Package roundRobinR updated to version 2.0.0 with previous version 1.0.1 dated 2026-04-21

Title: Manipulate and Analyze Round Robin Dyadic Data
Description: Provides utilities for processing and analyzing dyadic data collected using a round-robin design, in which each person in a group rates or interacts with every other person on at least one variable. Data manipulation functions prepare datasets for dyadic data analysis by creating the actor and partner dummy variables required by the social relations model (SRM). Analysis functions implement the SRM using multilevel modeling via a custom 'nlme' covariance class ('pdSRM'), following the approach of Snijders and Kenny (1999) <doi:10.1111/j.1475-6811.1999.tb00204.x> and Knight and Humphrey (2019) <doi:10.1037/0000115-019>. The package estimates group, actor, partner, and relationship variance components along with generalized and dyadic reciprocity correlations, and supports both null and fixed-effects models.
Author: Andrew Knight [aut, cre, cph]
Maintainer: Andrew Knight <knightap@wustl.edu>

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Package nnR updated to version 0.2.0 with previous version 0.1.0 dated 2024-02-14

Title: Neural Networks Made Algebraic
Description: Build, compose, stack, sum, and realize feed-forward neural networks as algebraic objects. Implements the calculus and constructive approximations described by Rafi, Padgett, and Nakarmi (2024) <doi:10.48550/arXiv.2402.01058>, Grohs, Hornung, Jentzen, et al. (2023) <doi:10.1007/s10444-022-09970-2>, and Jentzen, Kuckuck, and von Wurstemberger (2023) <doi:10.48550/arXiv.2310.20360>. Includes neural network polynomials, transcendental-function approximations, multidimensional maximum convolution, and vectorized batch realization.
Author: Shakil Rafi [aut, cre] , Joshua Lee Padgett [aut] , Ukash Nakarmi [ctb]
Maintainer: Shakil Rafi <sarafi@uark.edu>

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Package netmeta updated to version 3.7-0 with previous version 3.6-1 dated 2026-06-20

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

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Package atime updated to version 2026.9.17 with previous version 2026.4.2 dated 2026-04-04

Title: Asymptotic Timing
Description: Computing and visualizing comparative asymptotic timings of different algorithms and code versions. Also includes functionality for comparing empirical timings with expected references such as linear or quadratic, <https://en.wikipedia.org/wiki/Asymptotic_computational_complexity> Also includes functionality for measuring asymptotic memory and other quantities.
Author: Toby Hocking [aut, cre]
Maintainer: Toby Hocking <toby.hocking@r-project.org>

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Package shinyreprex updated to version 0.3.0 with previous version 0.2.0 dated 2026-06-29

Title: Reproducible Code for 'Shiny' Objects
Description: Provides functionality to extract reactive expressions from a 'shiny' application and convert them into stand-alone R scripts. This enables users to reproduce tables and visualisations outside the interactive UI, facilitating integration into static reports or automated workflows without requiring access to the original application source code.
Author: Ashley Baldry [aut, cre]
Maintainer: Ashley Baldry <ashley.baldry@acuityanalytics.com>

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Package ssutil updated to version 1.2.0 with previous version 1.1.0 dated 2026-09-06

Title: Sample Size Calculation Tools
Description: Functions for sample size estimation and simulation in clinical trials. Includes methods for selecting the best group using the Indifference-zone approach, as well as designs for non-inferiority, equivalence, and negative binomial models. For the sample size calculation for non-inferiority of vaccines, the approach is based on Fleming, Powers, and Huang (2021) <doi:10.1177/1740774520988244>. The Indifference-zone approach is based on Sobel and Huyett (1957) <doi:10.1002/j.1538-7305.1957.tb02411.x> and Bechhofer, Santner, and Goldsman (1995, ISBN:978-0-471-57427-9).
Author: John J. Aponte [aut, cre] , Chris Gast [ctb]
Maintainer: John J. Aponte <john.j.aponte@gmail.com>

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Package quadrupen updated to version 1.1-0 with previous version 1.0-0 dated 2026-06-05

Title: Sparse and Group Sparse Linear Models
Description: Fits the solution paths of classical sparse regression models with efficient active set algorithms by solving small sub-problems. Include LASSO, SCAD, MCP, (Sparse) Group-LASSO, Cooperative-LASSO, (Group) LAVA, (Generalized) Fused-Lasso and (Generalized) Elastic-Net. Also provides methods for model selection purpose (information criteria, cross-validation, stability selection).
Author: Julien Chiquet [aut, cre]
Maintainer: Julien Chiquet <julien.chiquet@inrae.fr>

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Package locuszoomr updated to version 1.1.0 with previous version 1.0.0 dated 2026-09-03

Title: Gene Locus Plot with Gene Annotations
Description: Publication-ready regional gene locus plots similar to those produced by the web interface 'LocusZoom' <https://my.locuszoom.org>, but running locally in R. Genetic or genomic data with gene annotation tracks are plotted via R base graphics, 'ggplot2' or 'plotly', allowing flexibility and easy customisation including laying out multiple locus plots on the same page. It uses the 'LDlink' API <https://ldlink.nih.gov/?tab=apiaccess> to query linkage disequilibrium data from the 1000 Genomes Project and can overlay this on plots <doi:10.1093/bioadv/vbaf006>.
Author: Myles Lewis [aut, cre] , Tom Willis [ctb]
Maintainer: Myles Lewis <myles.lewis@qmul.ac.uk>

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Package hypervolume updated to version 3.1.7 with previous version 3.1.6 dated 2025-06-15

Title: High Dimensional Geometry, Set Operations, Projection, and Inference Using Kernel Density Estimation, Support Vector Machines, and Convex Hulls
Description: Estimates the shape and volume of high-dimensional datasets and performs set operations: intersection / overlap, union, unique components, inclusion test, and hole detection. Uses stochastic geometry approach to high-dimensional kernel density estimation, support vector machine delineation, and convex hull generation. Applications include modeling trait and niche hypervolumes and species distribution modeling.
Author: Benjamin Blonder [aut, cre], Cecina Babich Morrow [aut], Stuart Brown [aut], Gregoire Butruille [aut], Daniel Chen [aut], Alex Laini [aut], David J. Harris [aut], Clement Violet [aut]
Maintainer: Benjamin Blonder <benjamin.blonder@berkeley.edu>

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Package bbotk updated to version 1.13.1 with previous version 1.13.0 dated 2026-09-02

Title: Black-Box Optimization Toolkit
Description: Features highly configurable search spaces via the 'paradox' package and optimizes every user-defined objective function. The package includes several optimization algorithms e.g. Random Search, Iterated Racing, Bayesian Optimization (in 'mlr3mbo') and Hyperband (in 'mlr3hyperband'). bbotk is the base package of 'mlr3tuning', 'mlr3fselect' and 'miesmuschel'.
Author: Marc Becker [cre, aut] , Jakob Richter [aut] , Michel Lang [aut] , Bernd Bischl [aut] , Martin Binder [aut], Olaf Mersmann [ctb]
Maintainer: Marc Becker <marcbecker@posteo.de>

Diff between bbotk versions 1.13.0 dated 2026-09-02 and 1.13.1 dated 2026-09-17

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Package adheaping updated to version 1.1.0 with previous version 1.0.0 dated 2026-07-24

Title: Characteristic-Function De-Heaping Density Estimation
Description: Tuning-free kernel density estimation for heaped and rounded data using a characteristic-function theory of heaping. Rounding to a grid is convolution with a box followed by lattice sampling, so the density is recovered by deconvolving the known box and tapering against a data-driven noise floor. Provides a box-deconvolution de-heaping estimator, a superposition variant, and a single combined estimator selected by a band-capacity gate; grid, heaped-fraction, and mixed-grain readers; and a spectral higher-order comb detector. Base-R replicas of the Heitjan-Rubin multiple-imputation and measurement-error deconvolution methods are included for comparison, and the 'Kernelheaping' stochastic expectation-maximization estimator is used when installed.
Author: Mitchell A. Thornton [aut, cre]
Maintainer: Mitchell A. Thornton <mitchat@sbcglobal.net>

Diff between adheaping versions 1.0.0 dated 2026-07-24 and 1.1.0 dated 2026-09-17

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Package archeofrag updated to version 1.3.0 with previous version 1.2.4 dated 2026-04-22

Title: Spatial Analysis in Archaeology from Refitting Fragments
Description: Methods to analyse spatial units in archaeology from the refitting relationships between fragments of objects scattered in these units (e.g. stratigraphic layers). Graphs are used to model archaeological observations. The package is mainly based on the 'igraph' package for graph analysis. Functions can: 1) create, manipulate, visualise, and simulate fragmentation graphs, 2) measure the cohesion and admixture of archaeological spatial units, and 3) characterise the topology of a specific set of refitting relationships. A series of published empirical datasets is included. Documentation about 'archeofrag' is provided by a vignette and by the accompanying scientific papers: Plutniak (2021, Journal of Archaeological Science, <doi:10.1016/j.jas.2021.105501>) and Plutniak (2022, Journal of Open Source Software, <doi:10.21105/joss.04335>). This package is complemented by the 'archeofrag.gui' R package, a companion GUI application available at <https://analytics.huma-num.fr/arch [...truncated...]
Author: Sebastien Plutniak [aut, cre]
Maintainer: Sebastien Plutniak <sebastien.plutniak@posteo.net>

Diff between archeofrag versions 1.2.4 dated 2026-04-22 and 1.3.0 dated 2026-09-17

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Package PlotFTIR updated to version 1.3.1 with previous version 1.3.0 dated 2026-07-21

Title: Plot FTIR Spectra
Description: The goal of 'PlotFTIR' is to easily and quickly kick-start the production of journal-quality Fourier Transform Infra-Red (FTIR) spectral plots in R using 'ggplot2'. The produced plots can be published directly or further modified by 'ggplot2' functions. L'objectif de 'PlotFTIR' est de démarrer facilement et rapidement la production des tracés spectraux de spectroscopie infrarouge à transformée de Fourier (IRTF) de qualité journal dans R à l'aide de 'ggplot2'. Les tracés produits peuvent être publiés directement ou modifiés davantage par les fonctions 'ggplot2'.
Author: Philip Bulsink [aut, cre] , Ulrich Makanda [trl] , His Majesty the King in Right of Canada, as represented by the Minister of Natural Resources [cph]
Maintainer: Philip Bulsink <philip.bulsink@nrcan-rncan.gc.ca>

Diff between PlotFTIR versions 1.3.0 dated 2026-07-21 and 1.3.1 dated 2026-09-17

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Package missMDA updated to version 1.23 with previous version 1.22 dated 2026-07-07

Title: Handling Missing Values with Multivariate Data Analysis
Description: Imputation of incomplete continuous or categorical datasets; Missing values are imputed with a principal component analysis (PCA), a multiple correspondence analysis (MCA) model or a multiple factor analysis (MFA) model; Perform multiple imputation with and in PCA or MCA.
Author: Francois Husson [aut, cre] , Julie Josse [aut]
Maintainer: Francois Husson <francois.husson@institut-agro.fr>

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Package hbal updated to version 1.3.0 with previous version 1.2.15 dated 2025-09-10

Title: Hierarchically Regularized Entropy Balancing
Description: Implements hierarchically regularized entropy balancing proposed by Xu and Yang (2022) <doi:10.1017/pan.2022.12>. The method adjusts the covariate distributions of the control group to match those of the treatment group. 'hbal' automatically expands the covariate space to include higher order terms and uses cross-validation to select variable penalties for the balancing conditions.
Author: Yiqing Xu [aut, cre] , Eddie Yang [aut]
Maintainer: Yiqing Xu <yiqingxu@stanford.edu>

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Package FORTLS readmission to version 2.0.2 with previous version 2.0.1 dated 2026-04-20

Title: Automatic Processing of Terrestrial-Based Technologies Point Cloud Data for Forestry Purposes
Description: Process automation of point cloud data derived from terrestrial-based technologies such as Terrestrial Laser Scanner (TLS) or Mobile Laser Scanner. 'FORTLS' enables (i) detection of trees and estimation of tree-level attributes (e.g. diameters and heights), (ii) estimation of stand-level variables (e.g. density, basal area, mean and dominant height), (iii) computation of metrics related to important forest attributes estimated in Forest Inventories at stand-level, and (iv) optimization of plot design for combining TLS data and field measured data. Documentation about 'FORTLS' is described in Molina-Valero et al. (2022, <doi:10.1016/j.envsoft.2022.105337>).
Author: Juan Alberto Molina-Valero [aut, cph, cre], Adela Martinez-Calvo [aut, com], Juan Gabriel Alvarez-Gonzalez [aut, ths], Fernando Montes [aut], Cesar Perez-Cruzado [aut, ths]
Maintainer: Juan Alberto Molina-Valero <jamolinavalero@gmail.com>

This is a re-admission after prior archival of version 2.0.1 dated 2026-04-20

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Package archeofrag.gui updated to version 1.2.0 with previous version 1.1.4 dated 2026-01-11

Title: Spatial Analysis in Archaeology from Refitting Fragments (GUI)
Description: A 'Shiny' application to access the functionalities and datasets of the 'archeofrag' package for spatial analysis in archaeology from refitting data. Quick and seamless exploration of archaeological refitting datasets, focusing on physical refits only. Features include: built-in documentation and convenient workflow, plot generation and export, anomaly detection in the spatial distribution of refitting connection, exploration of spatial units merging solutions, data export to the 'fabryka' application for spatial orientation analysis, simulation of archaeological site formation processes, support for parallel computing, R code generation to re-execute simulations and ensure reproducibility, code generation for the 'openMOLE' model exploration software. A demonstration of the app is available at <https://analytics.huma-num.fr/archeofrag/>.
Author: Sebastien Plutniak [aut, cre]
Maintainer: Sebastien Plutniak <sebastien.plutniak@posteo.net>

Diff between archeofrag.gui versions 1.1.4 dated 2026-01-11 and 1.2.0 dated 2026-09-17

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Package actibase updated to version 0.6.0 with previous version 0.5.0 dated 2026-08-21

Title: Baseline Functions for Actigraphy and Activity Processing and Analysis
Description: Provides baseline functions for actigraphy and activity data. This package is intended to be extended by downstream overlays such as 'actiread', 'actimetrics', and 'stepcount'.
Author: John Muschelli [aut, cre]
Maintainer: John Muschelli <muschellij2@gmail.com>

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Package tidyEmoji updated to version 0.4.0 with previous version 0.3.0 dated 2026-08-04

Title: Discover, Count, Categorise, Score, Translate and Relate Emoji in Text
Description: A tidy toolkit for working with the emoji in any text column, such as social-media posts, product reviews, chat logs or survey responses. Unicode is awkward to handle and not every code point is an emoji, which makes emoji statistics fiddly to obtain. 'tidyEmoji' extracts, counts, categorises, sentiment-scores and emotion-scores emoji, converts them to and from text (for accessibility and NLP preprocessing), searches the emoji catalogue, maps emoji co-occurrence and sequences (graph-ready edge lists and n-grams), measures where and how densely emoji are used, and builds document-by-emoji feature tables for machine learning, with grapheme-aware detection (so skin-tone and multi-person sequences stay intact), returning tidy data frames that slot straight into a 'tidyverse' workflow. It also quantifies how much annotators disagreed about an emoji (interpretation risk), extracts the words around each emoji, tracks emoji use over time, measures text-emoji sentiment mismatch, and applies exp [...truncated...]
Author: Youzhi Yu [aut, cre]
Maintainer: Youzhi Yu <yuyouzhi666@icloud.com>

Diff between tidyEmoji versions 0.3.0 dated 2026-08-04 and 0.4.0 dated 2026-09-17

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Permanent link

New package spatstat.convert with initial version 1.0-1
Package: spatstat.convert
Title: Extension to 'spatstat' for Converting Data Formats
Version: 1.0-1
Date: 2026-09-10
Depends: R (>= 3.4.0), spatstat (>= 3.6-2), spatstat.geom (>= 3.8-2), spatstat.linnet (>= 3.5-3), sp (>= 2.1), stats, graphics, methods
Imports: spatstat.utils (>= 3.2-4), spatstat.univar (>= 3.2-0)
Suggests: terra (>= 1.7-83), sf (>= 1.0-21)
Maintainer: Adrian Baddeley <Adrian.Baddeley@curtin.edu.au>
Description: Extension to the 'spatstat' package, enabling the user to convert spatial data between formats defined in `spatstat' and formats defined in 'sp', 'sf' and 'terra'.
License: GPL (>= 2)
ByteCompile: true
NeedsCompilation: no
Packaged: 2026-09-10 02:20:12 UTC; adrian
Author: Adrian Baddeley [aut, cre], Ege Rubak [aut], Rolf Turner [aut], Edzer Pebesma [aut], Roger Bivand [aut], Michael Sumner [ctb], Matthew Lewis [ctb], Mathieu Rajerison [ctb], Mehdi Moradi [ctb]
Repository: CRAN
Date/Publication: 2026-09-17 14:40:02 UTC

More information about spatstat.convert at CRAN
Permanent link

Package smer readmission to version 0.0.3 with previous version 0.0.2 dated 2025-08-22

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>

This is a re-admission after prior archival of version 0.0.2 dated 2025-08-22

Diff between smer versions 0.0.2 dated 2025-08-22 and 0.0.3 dated 2026-09-17

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More information about smer at CRAN
Permanent link

Package rswipl readmission to version 10.1.15 with previous version 10.1.9 dated 2026-06-16

Title: Embed 'SWI'-'Prolog'
Description: Interface to 'SWI'-'Prolog', <https://www.swi-prolog.org/>. This package is normally not loaded directly, please refer to package 'rolog' instead. The purpose of this package is to provide the 'Prolog' runtime on systems that do not have a software installation of 'SWI'-'Prolog'.
Author: Matthias Gondan [aut, com, cre] , Jan Wielemaker [ctb, cph] , European Commission [fnd]
Maintainer: Matthias Gondan <Matthias.Gondan-Rochon@uibk.ac.at>

This is a re-admission after prior archival of version 10.1.9 dated 2026-06-16

Diff between rswipl versions 10.1.9 dated 2026-06-16 and 10.1.15 dated 2026-09-17

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New package rGrSPTT with initial version 0.1.0
Package: rGrSPTT
Title: Group Sampling Inspection Plan for Time Truncated Life Test
Version: 0.1.0
Description: Designing group acceptance sampling inspection plans under time-truncated life tests. The package calculates the required minimum number of groups subject to a consumer's risk constraint on the probability of acceptance. Users can supply failure probabilities obtained from any lifetime distribution, allowing the methodology to be applied without restricting the analysis to a particular probability model. The package also provides a function for plotting the required minimum number of groups against the termination ratio. Saha et al. (2025) <doi:10.1007/s41872-025-00305-w>; Tripathi et al. (2020) <doi:10.1080/02664763.2020.1759031>; Tripathi and Aslam (2024) <doi:10.1285/i20705948v17n3p636>.
License: GPL-3
Encoding: UTF-8
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-09-10 06:03:11 UTC; Admin
Author: Harsh Tripathi [aut, cre], Mahendra Saha [aut]
Maintainer: Harsh Tripathi <rsearchstat21@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-17 14:40:28 UTC

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Permanent link

New package rgrpc with initial version 0.1.1
Package: rgrpc
Title: Asynchronous 'gRPC' Client and Server Runtime
Version: 0.1.1
Date: 2026-09-09
Description: A first-class asynchronous 'gRPC' <https://grpc.io/> runtime built on the generic asynchronous 'C++' API ('GenericStub', 'AsyncGenericService') <https://grpc.github.io/grpc/cpp/>. Requests and responses cross the native boundary as method names plus opaque byte buffers; 'RProtoBuf' supplies and consumes the bytes, so schemas are loaded at runtime and no generated service stubs are required. Native completion threads never call the R API: completions are queued natively and delivered in batches on the R main thread. Complements 'RProtoBuf' rather than replacing it. Links against the system 'gRPC' library for 'C++'.
License: Apache License (>= 2)
URL: https://github.com/cornball-ai/rgrpc
BugReports: https://github.com/cornball-ai/rgrpc/issues
Depends: R (>= 4.3.0)
Imports: methods
Suggests: RProtoBuf, tinytest
SystemRequirements: gRPC C++ and protobuf libraries with development headers, found via 'pkg-config grpc++ protobuf' (Ubuntu/Debian: 'libgrpc++-dev', 'libprotobuf-dev'; on Windows both ship with Rtools 4.3 and later).
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2026-09-10 01:55:42 UTC; troy
Author: Troy Hernandez [aut, cre] , cornball.ai [cph]
Maintainer: Troy Hernandez <troy@cornball.ai>
Repository: CRAN
Date/Publication: 2026-09-17 14:40:21 UTC

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New package rcxl with initial version 0.1.0
Package: rcxl
Title: Read xlsx Files with a Native Parser
Version: 0.1.0
Description: Reads tabular data from xlsx files with a specialized C parser. Worksheet XML is scanned in a single pass and decoded directly into R vectors, with no intermediate document model. Bundles the 'miniz' and 'libdeflate' decompressors to read the underlying archive.
License: MIT + file LICENSE
Copyright: file inst/COPYRIGHTS
URL: https://github.com/vlshields/rcxl
BugReports: https://github.com/vlshields/rcxl/issues
Encoding: UTF-8
Depends: R (>= 4.0)
Suggests: readxl, cellranger
NeedsCompilation: yes
Packaged: 2026-09-09 23:03:10 UTC; pots
Author: Vincent Shields [aut, cre, cph], Rich Geldreich [ctb, cph] , Tenacious Software LLC [cph] , RAD Game Tools and Valve Software [cph] , Martin Raiber [ctb, cph] , Alex Evans [ctb] , Alistair Moffat [ctb] , Jyrki Katajainen [ctb] , Eric Biggers [ctb, cp [...truncated...]
Maintainer: Vincent Shields <vince.shields913@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-17 14:20:02 UTC

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Package opencv updated to version 0.6.1 with previous version 0.6.0 dated 2026-09-14

Title: Bindings to 'OpenCV' Computer Vision Library
Description: Exposes some of the available 'OpenCV' <https://opencv.org/> algorithms, such as a QR code scanner, and edge, body or face detection. These can either be applied to analyze static images, or to filter live video footage from a camera device.
Author: Jeroen Ooms [aut, cre] , Jan Wijffels [aut]
Maintainer: Jeroen Ooms <jeroenooms@gmail.com>

Diff between opencv versions 0.6.0 dated 2026-09-14 and 0.6.1 dated 2026-09-17

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 3 files changed, 8 insertions(+), 5 deletions(-)

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Package marcher updated to version 0.0.3 with previous version 0.0-2 dated 2017-04-12

Title: Migration and Range Change Estimation in R
Description: A set of tools for likelihood-based estimation, model selection and testing of two- and three-range shift and migration models for animal movement data as described in Gurarie et al. (2017) <doi:10.1111/1365-2656.12674>. Provided movement data (X, Y and Time), including irregularly sampled data, functions estimate the time, duration and location of one or two range shifts, as well as the ranging area and auto-correlation structure of the movement. Tests assess, for example, whether the shift was "significant", and whether a two-shift migration was a true return migration.
Author: Eliezer Gurarie [aut, cre], Faridedin Cheraghi [ctb]
Maintainer: Eliezer Gurarie <egurarie@esf.edu>

Diff between marcher versions 0.0-2 dated 2017-04-12 and 0.0.3 dated 2026-09-17

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Package fromo updated to version 0.2.5 with previous version 0.2.4 dated 2024-11-29

Title: Fast Robust Moments
Description: Fast, numerically robust computation of weighted moments via 'Rcpp'. Supports computation on vectors and matrices, and Monoidal append of moments. Moments and cumulants over running fixed length windows can be computed, as well as over time-based windows. Moment computations are via a generalization of Welford's method, as described by Bennett et. (2009) <doi:10.1109/CLUSTR.2009.5289161>.
Author: Steven E. Pav [aut, cre]
Maintainer: Steven E. Pav <shabbychef@gmail.com>

Diff between fromo versions 0.2.4 dated 2024-11-29 and 0.2.5 dated 2026-09-17

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More information about fromo at CRAN
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Package deformula readmission to version 0.1.3 with previous version 0.1.2 dated 2022-05-30

Title: Integration of One-Dimensional Functions with Double Exponential Formulas
Description: Numerical quadrature of functions of one variable over a finite or infinite interval with double exponential formulas.
Author: Hiroyuki Okamura [aut, cre]
Maintainer: Hiroyuki Okamura <okamu@hiroshima-u.ac.jp>

This is a re-admission after prior archival of version 0.1.2 dated 2022-05-30

Diff between deformula versions 0.1.2 dated 2022-05-30 and 0.1.3 dated 2026-09-17

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Package CrownScorchTLS readmission to version 0.1.2 with previous version 0.1.1 dated 2026-01-18

Title: Estimate Crown Scorch from Terrestrial LiDAR Scans
Description: Estimates tree crown scorch from terrestrial lidar scans collected with a RIEGL vz400i. The methods follow those described in Cannon et al. (2025, Fire Ecology 21:71, <doi:10.1186/s42408-025-00420-0>).
Author: Jeffery Cannon [aut, cre], Andrew Whelan [ctb]
Maintainer: Jeffery Cannon <Jeffery.Cannon@jonesctr.org>

This is a re-admission after prior archival of version 0.1.1 dated 2026-01-18

Diff between CrownScorchTLS versions 0.1.1 dated 2026-01-18 and 0.1.2 dated 2026-09-17

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New package Coreset with initial version 1.0.0
Package: Coreset
Title: Discrete Diversity, Dispersion, and Coverage Subset Selection
Version: 1.0.0
Description: Solves discrete location objectives on a distance matrix or Euclidean coordinate set. The Max-Min Diversity (MMDP / p-dispersion) objective, which maximizes the minimum pairwise distance within a selection of k items, is solved by farthest-first selection (Gonzalez 1985) <doi:10.1016/0304-3975(85)90224-5>; the DropAdd tabu-search heuristic (Porumbel, Hao & Glover 2011) <doi:10.1007/s10479-011-0898-z>, GRASP with path-relinking (Resende, Marti, Gallego & Duarte 2010) <doi:10.1016/j.cor.2008.05.011>, and an exact node-packing integer program (Sayyady & Fathi 2016) <doi:10.1016/j.ejor.2016.02.026>. The Max-Mean Dispersion objective, which selects a subset of unrestricted size maximising the sum of its pairwise distances divided by the number of selected elements, is solved by reinforcement-learning-guided tabu search (Nijimbere et al. 2020) <doi:10.3934/jimo.2020115>. The discrete k-centre (min-max covering / facility location) objective, which ch [...truncated...]
License: GPL (>= 3)
Encoding: UTF-8
Language: en-GB
Depends: R (>= 4.1)
Imports: cli (>= 3.0.0), Rcpp, Rdpack (>= 0.7), stats
Suggests: highs, knitr, Matrix, quarto, rprojroot, spelling, testthat (>= 3.0.0)
VignetteBuilder: quarto
LinkingTo: Rcpp
URL: https://ms609.github.io/Coreset/
BugReports: https://github.com/ms609/Coreset/issues
ByteCompile: true
NeedsCompilation: yes
Packaged: 2026-09-10 06:44:59 UTC; pjjg18
Author: Martin R. Smith [aut, cre, cph]
Maintainer: Martin R. Smith <martin.smith@durham.ac.uk>
Repository: CRAN
Date/Publication: 2026-09-17 14:50:29 UTC

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Permanent link

Package binGroup2 readmission to version 1.3.4 with previous version 1.3.3 dated 2025-09-13

Title: Identification and Estimation using Group Testing
Description: Methods for the group testing identification problem: 1) Operating characteristics (e.g., expected number of tests) for commonly used hierarchical and array-based algorithms, and 2) Optimal testing configurations for these same algorithms. Methods for the group testing estimation problem: 1) Estimation and inference procedures for an overall prevalence, and 2) Regression modeling for commonly used hierarchical and array-based algorithms.
Author: Brianna Hitt [aut, cre] , Christopher Bilder [aut] , Frank Schaarschmidt [aut] , Brad Biggerstaff [aut] , Christopher McMahan [aut] , Joshua Tebbs [aut] , Boan Zhang [ctb], Michael Black [ctb], Peijie Hou [ctb], Peng Chen [ctb], Minh Nguyen [ctb]
Maintainer: Brianna Hitt <brianna.hitt@afacademy.af.edu>

This is a re-admission after prior archival of version 1.3.3 dated 2025-09-13

Diff between binGroup2 versions 1.3.3 dated 2025-09-13 and 1.3.4 dated 2026-09-17

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Package splitGraph updated to version 0.4.0 with previous version 0.3.0 dated 2026-07-03

Title: Dataset Dependency Graphs for Leakage-Aware Evaluation
Description: Represent biomedical dataset structure as typed dependency graphs so that sample provenance, repeated-measure structure, study design, batch effects, and temporal relationships are explicit and inspectable. Validates dataset structure, detects sample-level overlap, derives deterministic split constraints, and produces a tool-agnostic split specification for leakage-aware evaluation workflows.
Author: Selcuk Korkmaz [aut, cre]
Maintainer: Selcuk Korkmaz <selcukorkmaz@gmail.com>

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Package rdist updated to version 0.0.6 with previous version 0.0.5 dated 2020-05-04

Title: Calculate Pairwise Distances
Description: A common framework for calculating distance matrices.
Author: Nello Blaser [aut, cre]
Maintainer: Nello Blaser <nello.blaser@uib.no>

Diff between rdist versions 0.0.5 dated 2020-05-04 and 0.0.6 dated 2026-09-17

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Package randomForestRHF updated to version 2.1.0 with previous version 2.0.3 dated 2026-09-01

Title: Random Hazard Forests
Description: Random Hazard Forests (RHF) extend Random Survival Forests (RSF) by directly estimating the hazard function and by accommodating time-dependent covariates through counting-process style inputs. The package fits tree ensembles for dynamic survival prediction, returning hazard, cumulative hazard, integrated hazard, and related performance summaries for training and test data. The methods build on Random Survival Forests described by Ishwaran et al. (2008) <doi:10.1214/08-AOAS169> and on nonparametric hazard modeling with time-dependent covariates described by Lee et al. (2021) <doi:10.1214/20-AOS2028>.
Author: Hemant Ishwaran [aut], Udaya B. Kogalur [aut, cre]
Maintainer: Udaya B. Kogalur <ubk@kogalur.com>

Diff between randomForestRHF versions 2.0.3 dated 2026-09-01 and 2.1.0 dated 2026-09-17

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New package OmopIndices with initial version 0.1.0
Package: OmopIndices
Title: Patient-Level Indices from the OMOP Common Data Model
Version: 0.1.0
Maintainer: Marti Catala <marti.catalasabate@ndorms.ox.ac.uk>
Description: Provides tools to derive standardised, reproducible patient-level indices and covariates from Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) databases. Functions calculate comorbidity and frailty scores, including the Charlson Comorbidity Index, Electronic Frailty Index, and Hospital Frailty Risk Score, as well as body mass index, polypharmacy, ethnicity, location, and socioeconomic status measures.
License: Apache License (>= 2)
Encoding: UTF-8
Suggests: CDMConnector, CodelistGenerator, CohortConstructor, DBI, duckdb, gt, here, htmltools, knitr, odbc, omock, PhenotypeR, rmarkdown, RPostgres, testthat, visOmopResults
URL: https://OHDSI.github.io/OmopIndices/
BugReports: https://github.com/OHDSI/OmopIndices/issues
Imports: cli, clock, dplyr, omopgenerics (>= 1.4.0), PatientProfiles, purrr, rlang
Depends: R (>= 4.1.0)
NeedsCompilation: no
Packaged: 2026-09-09 17:30:20 UTC; martics
Author: Marti Catala [aut, cre] , Marta Alcalde-Herraiz [aut] , Maria T Sanchez-Santos [aut]
Repository: CRAN
Date/Publication: 2026-09-17 13:20:27 UTC

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New package iPEB with initial version 0.1.1
Package: iPEB
Title: Improved Parametric Empirical Bayes for Longitudinal Biomarker Analysis
Version: 0.1.1
Description: Extends parametric empirical Bayes (PEB) for longitudinal biomarker screening with a time-gap-aware standardization layer, covariate adjustment, and objective-driven multi-marker weighting. The layer models each subject's biomarker history with a random intercept (and an optional random slope) and autocorrelated, gap-scaled residuals, so that prediction uncertainty grows with the time between visits and per-visit specificity is preserved under irregular sampling. Marker weights are learned to optimize a user-selected clinical objective -- maximizing sensitivity at a fixed specificity, extending detection lead time, or a combined objective -- with optional feature selection and a choice of scalar or multivariate combiner. Functions for fitting, prediction, and evaluation (sensitivity, lead time, and specificity at chosen operating points) are provided. A manuscript describing the method is in preparation.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Depends: R (>= 4.0.0)
Imports: nlme, stats, graphics, utils
Suggests: testthat (>= 3.0.0), knitr, rmarkdown, shiny
VignetteBuilder: knitr
URL: https://github.com/bitansa/iPEB
BugReports: https://github.com/bitansa/iPEB/issues
NeedsCompilation: no
Packaged: 2026-09-09 18:47:02 UTC; bitansarkar
Author: Bitan Sarkar [aut, cre, cph] , Ana Maria Kenney [aut], James P. Long [aut], Johannes F. Fahrmann [aut], Samir Hanash [aut], Kim-Anh Do [aut], Ehsan Irajizad [aut]
Maintainer: Bitan Sarkar <bitansarkar010899@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-17 13:20:08 UTC

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New package ggbipart with initial version 0.1.3
Package: ggbipart
Title: Plots for Bipartite Networks in R
Version: 0.1.3
Description: Provides functions to plot bipartite ecological networks using 'ggplot2' graphics, including interaction webs, node-link layouts, and matrix representations. Species interaction data in the form of adjacency matrices, or 'network' and 'igraph' graph objects, can be plotted directly.
Depends: R (>= 3.1), ggplot2 (>= 2.0.0)
License: GPL-3
Imports: network, igraph, GGally
Suggests: knitr, rmarkdown, bipartite, testthat (>= 3.0.0)
VignetteBuilder: knitr
URL: http://pjordanolab.ebd.csic.es/resources/
BugReports: https://github.com/pedroj/bipartite_plots/issues
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-09-09 15:27:03 UTC; pedro
Author: Pedro Jordano [aut, cre]
Maintainer: Pedro Jordano <jordano@ebd.csic.es>
Repository: CRAN
Date/Publication: 2026-09-17 13:20:15 UTC

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New package filters.trade with initial version 0.0.1
Package: filters.trade
Title: A Filter System for Selecting Trading Instruments
Version: 0.0.1
Description: Enables filtering datasets of tradable instruments by prior specified identifiers which correspond to saved filter expressions. A filter is a named expression bound to a target dataset, stored once in a package level registry, and later applied to select trading codes such as tickers or symbols out of a universe, price or signal dataset. The design follows the `filters` package, replacing the clinical study dataset convention with a trading instrument convention.
Depends: R (>= 4.1.0)
Imports: yaml
Suggests: roxygen2 (>= 7.0.0), testthat (>= 3.0.0)
Encoding: UTF-8
License: Apache License (>= 2.0)
LazyData: true
NeedsCompilation: no
Packaged: 2026-09-09 15:55:59 UTC; joezhu-hp
Author: Joe Zhu [aut, cre]
Maintainer: Joe Zhu <sha.joe.zhu@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-17 13:20:20 UTC

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Package EconCausal updated to version 1.0.4 with previous version 1.0.2 dated 2025-10-08

Title: Causal Analysis for Macroeconomic Time Series (ECM-MARS, BSTS, Bayesian GLM-AR(1))
Description: Implements three complementary pipelines for causal analysis on macroeconomic time series: (1) Error-Correction Models with Multivariate Adaptive Regression Splines (ECM-MARS), (2) Bayesian Structural Time Series (BSTS), and (3) Bayesian GLM with AR(1) errors validated with Leave-Future-Out (LFO). Heavy backends (Stan) are optional and never used in examples or tests.
Author: Jose Mauricio Gomez Julian [aut, cre]
Maintainer: Jose Mauricio Gomez Julian <isadore.nabi@pm.me>

Diff between EconCausal versions 1.0.2 dated 2025-10-08 and 1.0.4 dated 2026-09-17

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 EconCausal-1.0.4/EconCausal/NAMESPACE                  |    3 
 EconCausal-1.0.4/EconCausal/NEWS.md                    |only
 EconCausal-1.0.4/EconCausal/R/bglmar1.R                |  177 -
 EconCausal-1.0.4/EconCausal/R/bsts_model.R             |  725 +++--
 EconCausal-1.0.4/EconCausal/R/ecm_mars.R               |  836 ++++--
 EconCausal-1.0.4/EconCausal/R/zzz_imports.R            |    8 
 EconCausal-1.0.4/EconCausal/README.md                  |   48 
 EconCausal-1.0.4/EconCausal/build/partial.rdb          |only
 EconCausal-1.0.4/EconCausal/build/vignette.rds         |binary
 EconCausal-1.0.4/EconCausal/inst/doc/bglmar-esp.R      |   18 
 EconCausal-1.0.4/EconCausal/inst/doc/bglmar-esp.Rmd    |  586 ++--
 EconCausal-1.0.4/EconCausal/inst/doc/bglmar-esp.html   | 1610 ++++++------
 EconCausal-1.0.4/EconCausal/inst/doc/bglmar1-eng.R     |   18 
 EconCausal-1.0.4/EconCausal/inst/doc/bglmar1-eng.Rmd   |  586 ++--
 EconCausal-1.0.4/EconCausal/inst/doc/bglmar1-eng.html  | 1598 ++++++------
 EconCausal-1.0.4/EconCausal/inst/doc/bsts-eng.R        |   18 
 EconCausal-1.0.4/EconCausal/inst/doc/bsts-eng.Rmd      |  924 +++----
 EconCausal-1.0.4/EconCausal/inst/doc/bsts-eng.html     | 2200 ++++++++--------
 EconCausal-1.0.4/EconCausal/inst/doc/bsts-esp.R        |   18 
 EconCausal-1.0.4/EconCausal/inst/doc/bsts-esp.Rmd      |  924 +++----
 EconCausal-1.0.4/EconCausal/inst/doc/bsts-esp.html     | 2229 ++++++++---------
 EconCausal-1.0.4/EconCausal/inst/doc/ecm-mars-eng.R    |   18 
 EconCausal-1.0.4/EconCausal/inst/doc/ecm-mars-eng.Rmd  |  597 ++--
 EconCausal-1.0.4/EconCausal/inst/doc/ecm-mars-eng.html | 1454 +++++------
 EconCausal-1.0.4/EconCausal/inst/doc/ecm-mars-esp.R    |   18 
 EconCausal-1.0.4/EconCausal/inst/doc/ecm-mars-esp.Rmd  |  597 ++--
 EconCausal-1.0.4/EconCausal/inst/doc/ecm-mars-esp.html | 1467 +++++------
 EconCausal-1.0.4/EconCausal/man/bglmar1.Rd             |  164 -
 EconCausal-1.0.4/EconCausal/man/bsts_model.Rd          |  132 -
 EconCausal-1.0.4/EconCausal/man/ecm_mars.Rd            |  165 -
 EconCausal-1.0.4/EconCausal/tests                      |only
 EconCausal-1.0.4/EconCausal/vignettes/bglmar-esp.Rmd   |  586 ++--
 EconCausal-1.0.4/EconCausal/vignettes/bglmar1-eng.Rmd  |  586 ++--
 EconCausal-1.0.4/EconCausal/vignettes/bsts-eng.Rmd     |  924 +++----
 EconCausal-1.0.4/EconCausal/vignettes/bsts-esp.Rmd     |  924 +++----
 EconCausal-1.0.4/EconCausal/vignettes/ecm-mars-eng.Rmd |  597 ++--
 EconCausal-1.0.4/EconCausal/vignettes/ecm-mars-esp.Rmd |  597 ++--
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Permanent link

New package coOpenData with initial version 0.1.0
Package: coOpenData
Title: A Lightweight Interface to Colorado Open Data APIs
Version: 0.1.0
Description: Provides a unified set of helper functions to access datasets from the Colorado Open Data platform <https://data.colorado.gov/>. Functions return results as tidy tibbles and support optional filtering, sorting, and row limits via the Socrata API. The package provides a consistent interface for discovering and downloading datasets from the Colorado Open Data Portal using human-readable dataset keys or official Socrata dataset identifiers.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: curl, dplyr, httr, janitor, jsonlite, rlang, tibble
Suggests: ggplot2, knitr, rmarkdown, scales, testthat (>= 3.0.0), tidyr, vcr (>= 0.6.0), webmockr
URL: https://github.com/nyc-open-data-lab/coOpenData, https://nyc-open-data-lab.github.io/coOpenData/
BugReports: https://github.com/nyc-open-data-lab/coOpenData/issues
VignetteBuilder: knitr
Depends: R (>= 4.1.0)
NeedsCompilation: no
Packaged: 2026-09-09 18:53:40 UTC; christianmartinez
Author: Shelby Lyn Gomes [aut] , Christian Martinez [aut, cre]
Maintainer: Christian Martinez <c.martinez0@outlook.com>
Repository: CRAN
Date/Publication: 2026-09-17 13:30:15 UTC

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New package midasINLA with initial version 0.1.0
Package: midasINLA
Title: Spatial MIDAS Models Using INLA
Version: 0.1.0
Description: Provides tools for fitting spatial Mixed Data Sampling (MIDAS) regression models using Integrated Nested Laplace Approximation (INLA). The package is designed for settings where responses and explanatory variables are observed at different temporal frequencies and supports both constant and spatially varying regression coefficients.
License: GPL-3
Encoding: UTF-8
Imports: matrixStats, Matrix, stats
Suggests: INLA, knitr, rmarkdown, testthat (>= 3.0.0), dplyr, ggplot2, tidyr
Additional_repositories: https://inla.r-inla-download.org/R/stable
VignetteBuilder: knitr
Depends: R (>= 4.2)
LazyData: true
NeedsCompilation: no
Packaged: 2026-09-09 09:52:04 UTC; stephenjunvillejo
Author: Stephen Jun Villejo [aut, cre]
Maintainer: Stephen Jun Villejo <s.villejo@imperial.ac.uk>
Repository: CRAN
Date/Publication: 2026-09-17 12:30:02 UTC

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Permanent link

New package maposm with initial version 0.5.1
Package: maposm
Title: Get Map Layers from 'OpenStreetMap'
Version: 0.5.1
Description: The 'OpenStreetMap' database provides a wide range of highly detailed geographic layers on a global scale. To obtain synthetic information for cartographic purposes, layers must be selected, simplified, merged, or modified. 'maposm' downloads 'OpenStreetMap' extracts and performs these operations to create a set of composite layers of urban areas, buildings, green spaces, main roads, secondary roads, railways, and water bodies.
URL: https://codeberg.org/riatelab/maposm, https://riatelab.r-universe.dev/maposm
BugReports: https://codeberg.org/riatelab/maposm/issues
License: GPL-3
Depends: R (>= 4.2.0)
Imports: sf, lwgeom, tools, mapsf, graphics, osmextract
Suggests: tinytest
Encoding: UTF-8
Language: en-US
NeedsCompilation: no
Packaged: 2026-09-09 15:29:54 UTC; tim
Author: Timothee Giraud [cre, aut] , Matthieu Viry [ctb] , Louis Laurian [ctb]
Maintainer: Timothee Giraud <timothee.giraud@cnrs.fr>
Repository: CRAN
Date/Publication: 2026-09-17 13:00:02 UTC

More information about maposm at CRAN
Permanent link

Package campsis updated to version 1.9.1 with previous version 1.9.0 dated 2026-08-05

Title: Generic PK/PD Simulation Platform Campsis
Description: A generic, easy-to-use and intuitive pharmacokinetic/pharmacodynamic (PK/PD) simulation platform based on the R packages 'rxode2' and 'mrgsolve'. Campsis provides an abstraction layer over the underlying processes of defining a PK/PD model, assembling a custom dataset and running a simulation. The package has a strong dependency on the R package 'campsismod', which allows models to be read from and written to files, including through a JSON-based interface, and to be adapted further on the fly in the R environment. In addition, 'campsis' allows users to assemble datasets in an intuitive manner, including via a JSON-based interface to import Campsis datasets defined using formal JSON schemas distributed with the package. Once the dataset is ready, the package prepares the simulation, calls 'rxode2' or 'mrgsolve' (at the user's choice), and returns the results for the given model, dataset and desired simulation settings. The package itself is licensed under the GPL (>= 3); the JSON sc [...truncated...]
Author: Nicolas Luyckx [aut, cre]
Maintainer: Nicolas Luyckx <nicolas.luyckx@calvagone.com>

Diff between campsis versions 1.9.0 dated 2026-08-05 and 1.9.1 dated 2026-09-17

 campsis-1.9.0/campsis/man/treatment_iov-class.Rd                                |only
 campsis-1.9.1/campsis/DESCRIPTION                                               |    8 
 campsis-1.9.1/campsis/MD5                                                       |  317 ++---
 campsis-1.9.1/campsis/NAMESPACE                                                 |  564 +++++-----
 campsis-1.9.1/campsis/NEWS.md                                                   |    8 
 campsis-1.9.1/campsis/R/arm.R                                                   |    8 
 campsis-1.9.1/campsis/R/dataset.R                                               |   26 
 campsis-1.9.1/campsis/R/default_settings.R                                      |    4 
 campsis-1.9.1/campsis/R/occasion.R                                              |    6 
 campsis-1.9.1/campsis/R/outfun_core.R                                           |    7 
 campsis-1.9.1/campsis/R/scenario.R                                              |   31 
 campsis-1.9.1/campsis/R/scenarios.R                                             |   18 
 campsis-1.9.1/campsis/R/simulate.R                                              |   36 
 campsis-1.9.1/campsis/R/simulate_preprocess.R                                   |    6 
 campsis-1.9.1/campsis/R/simulation_engine.R                                     |    3 
 campsis-1.9.1/campsis/R/treatment.R                                             |   12 
 campsis-1.9.1/campsis/R/treatment_iov.R                                         |   61 -
 campsis-1.9.1/campsis/R/treatment_iovs.R                                        |    2 
 campsis-1.9.1/campsis/R/utilities.R                                             |   53 
 campsis-1.9.1/campsis/inst/extdata/campsis.schema.json                          |  129 +-
 campsis-1.9.1/campsis/inst/extdata/campsis_scenarios.schema.json                |   25 
 campsis-1.9.1/campsis/inst/extdata/campsis_settings.schema.json                 |    8 
 campsis-1.9.1/campsis/inst/extdata/campsismod.schema.json                       |   58 -
 campsis-1.9.1/campsis/inst/extdata/no_sub_schemas/campsis_scenarios.schema.json |   49 
 campsis-1.9.1/campsis/man/Arm.Rd                                                |   42 
 campsis-1.9.1/campsis/man/Bootstrap.Rd                                          |   70 -
 campsis-1.9.1/campsis/man/BootstrapDistribution.Rd                              |   46 
 campsis-1.9.1/campsis/man/DatasetConfig.Rd                                      |   72 -
 campsis-1.9.1/campsis/man/DefaultSettings.Rd                                    |   78 -
 campsis-1.9.1/campsis/man/EventRelatedObservations.Rd                           |   44 
 campsis-1.9.1/campsis/man/IOV.Rd                                                |    6 
 campsis-1.9.1/campsis/man/Observations.Rd                                       |   46 
 campsis-1.9.1/campsis/man/Occasion.Rd                                           |    4 
 campsis-1.9.1/campsis/man/PI.Rd                                                 |   54 
 campsis-1.9.1/campsis/man/PIOutfun.Rd                                           |   56 
 campsis-1.9.1/campsis/man/Solver.Rd                                             |   62 -
 campsis-1.9.1/campsis/man/StatsOutfun.Rd                                        |   56 
 campsis-1.9.1/campsis/man/TimeVaryingCovariate.Rd                               |   48 
 campsis-1.9.1/campsis/man/apply_action.Rd                                       |   50 
 campsis-1.9.1/campsis/man/apply_compartment_characteristics.Rd                  |   42 
 campsis-1.9.1/campsis/man/apply_scenario.Rd                                     |   40 
 campsis-1.9.1/campsis/man/assign_dose_number.Rd                                 |   36 
 campsis-1.9.1/campsis/man/bootstrap-class.Rd                                    |   46 
 campsis-1.9.1/campsis/man/check_ii_and_addl.Rd                                  |   44 
 campsis-1.9.1/campsis/man/compute_incremental_progress.Rd                       |   40 
 campsis-1.9.1/campsis/man/compute_pi.Rd                                         |   46 
 campsis-1.9.1/campsis/man/compute_stats.Rd                                      |   56 
 campsis-1.9.1/campsis/man/convertTime.Rd                                        |   50 
 campsis-1.9.1/campsis/man/convert_time.Rd                                       |   42 
 campsis-1.9.1/campsis/man/default_settings-class.Rd                             |   58 -
 campsis-1.9.1/campsis/man/dosing_only.Rd                                        |   34 
 campsis-1.9.1/campsis/man/drop_others.Rd                                        |   34 
 campsis-1.9.1/campsis/man/export_delegate.Rd                                    |   58 -
 campsis-1.9.1/campsis/man/export_table_delegate.Rd                              |   60 -
 campsis-1.9.1/campsis/man/generate_iiv.Rd                                       |   42 
 campsis-1.9.1/campsis/man/generate_iiv_.Rd                                      |   38 
 campsis-1.9.1/campsis/man/get_available_time_units.Rd                           |   28 
 campsis-1.9.1/campsis/man/get_campsis_option.Rd                                 |   38 
 campsis-1.9.1/campsis/man/get_campsis_options.Rd                                |   30 
 campsis-1.9.1/campsis/man/get_column.Rd                                         |   40 
 campsis-1.9.1/campsis/man/get_compartment_mapping.Rd                            |   40 
 campsis-1.9.1/campsis/man/get_covariates.Rd                                     |   60 -
 campsis-1.9.1/campsis/man/get_event_covariates.Rd                               |   60 -
 campsis-1.9.1/campsis/man/get_fixed_covariates.Rd                               |   60 -
 campsis-1.9.1/campsis/man/get_initial_conditions.Rd                             |   44 
 campsis-1.9.1/campsis/man/get_iovs.Rd                                           |   52 
 campsis-1.9.1/campsis/man/get_occasions.Rd                                      |   52 
 campsis-1.9.1/campsis/man/get_random_seed_value.Rd                              |   30 
 campsis-1.9.1/campsis/man/get_seed.Rd                                           |   36 
 campsis-1.9.1/campsis/man/get_seed_for_dataset_export.Rd                        |   40 
 campsis-1.9.1/campsis/man/get_seed_for_iteration.Rd                             |   40 
 campsis-1.9.1/campsis/man/get_seed_for_parameters_sampling.Rd                   |   36 
 campsis-1.9.1/campsis/man/get_simulation_engine_type.Rd                         |   36 
 campsis-1.9.1/campsis/man/get_splitting_configuration.Rd                        |   40 
 campsis-1.9.1/campsis/man/get_time_varying_covariates.Rd                        |   60 -
 campsis-1.9.1/campsis/man/get_times.Rd                                          |   90 -
 campsis-1.9.1/campsis/man/import_campsismod_to_namespace.Rd                     |   30 
 campsis-1.9.1/campsis/man/iov-class.Rd                                          |only
 campsis-1.9.1/campsis/man/is_empty_bootstrap.Rd                                 |   36 
 campsis-1.9.1/campsis/man/json_to_campsis_dataset.Rd                            |   40 
 campsis-1.9.1/campsis/man/json_to_campsis_settings.Rd                           |   40 
 campsis-1.9.1/campsis/man/left_join_iiv.Rd                                      |   40 
 campsis-1.9.1/campsis/man/make_vpc_summary.Rd                                   |   68 -
 campsis-1.9.1/campsis/man/obs_only.Rd                                           |   34 
 campsis-1.9.1/campsis/man/on_ci.Rd                                              |   30 
 campsis-1.9.1/campsis/man/on_cran.Rd                                            |   34 
 campsis-1.9.1/campsis/man/open_json.Rd                                          |   40 
 campsis-1.9.1/campsis/man/preprocess_arm_column.Rd                              |   40 
 campsis-1.9.1/campsis/man/preprocess_dest.Rd                                    |   40 
 campsis-1.9.1/campsis/man/preprocess_dosing.Rd                                  |   36 
 campsis-1.9.1/campsis/man/preprocess_events.Rd                                  |   30 
 campsis-1.9.1/campsis/man/preprocess_ids.Rd                                     |   36 
 campsis-1.9.1/campsis/man/preprocess_outfun.Rd                                  |   36 
 campsis-1.9.1/campsis/man/preprocess_outvars.Rd                                 |   40 
 campsis-1.9.1/campsis/man/preprocess_replicates.Rd                              |   40 
 campsis-1.9.1/campsis/man/preprocess_scenarios.Rd                               |   32 
 campsis-1.9.1/campsis/man/preprocess_settings.Rd                                |   40 
 campsis-1.9.1/campsis/man/preprocess_slices.Rd                                  |   36 
 campsis-1.9.1/campsis/man/preprocess_tablefun.Rd                                |   36 
 campsis-1.9.1/campsis/man/preserve_column_levels.Rd                             |only
 campsis-1.9.1/campsis/man/process_arm_labels.Rd                                 |   44 
 campsis-1.9.1/campsis/man/process_drop_others.Rd                                |   44 
 campsis-1.9.1/campsis/man/process_simulate_arguments.Rd                         |   56 
 campsis-1.9.1/campsis/man/remove_column_levels.Rd                               |only
 campsis-1.9.1/campsis/man/remove_initial_conditions.Rd                          |   36 
 campsis-1.9.1/campsis/man/reorder_columns.Rd                                    |   40 
 campsis-1.9.1/campsis/man/repeat_schedule.Rd                                    |   56 
 campsis-1.9.1/campsis/man/retrieve_parameter_value.Rd                           |   46 
 campsis-1.9.1/campsis/man/rxode_engine-class.Rd                                 |   18 
 campsis-1.9.1/campsis/man/sample_covariates_list.Rd                             |   44 
 campsis-1.9.1/campsis/man/sample_distribution_as_tibble.Rd                      |   44 
 campsis-1.9.1/campsis/man/scatterPlot.Rd                                        |   48 
 campsis-1.9.1/campsis/man/scatter_plot.Rd                                       |   38 
 campsis-1.9.1/campsis/man/scatter_plot.std_campsis_tbl.Rd                       |  102 -
 campsis-1.9.1/campsis/man/scenario-class.Rd                                     |    2 
 campsis-1.9.1/campsis/man/setLabel.Rd                                           |   46 
 campsis-1.9.1/campsis/man/setSubjects.Rd                                        |   46 
 campsis-1.9.1/campsis/man/set_label.Rd                                          |   50 
 campsis-1.9.1/campsis/man/set_seed.Rd                                           |   34 
 campsis-1.9.1/campsis/man/set_subjects.Rd                                       |   50 
 campsis-1.9.1/campsis/man/setupPlanDefault.Rd                                   |   50 
 campsis-1.9.1/campsis/man/setupPlanSequential.Rd                                |   36 
 campsis-1.9.1/campsis/man/setup_plan_default.Rd                                 |   50 
 campsis-1.9.1/campsis/man/setup_plan_sequential.Rd                              |   28 
 campsis-1.9.1/campsis/man/shadedPlot.Rd                                         |   70 -
 campsis-1.9.1/campsis/man/shaded_plot.Rd                                        |   38 
 campsis-1.9.1/campsis/man/shaded_plot.std_campsis_tbl.Rd                        |  118 +-
 campsis-1.9.1/campsis/man/simulate.Rd                                           |  296 ++---
 campsis-1.9.1/campsis/man/simulate_delegate.Rd                                  |  106 -
 campsis-1.9.1/campsis/man/simulate_delegate_core.Rd                             |  100 -
 campsis-1.9.1/campsis/man/simulate_scenarios.Rd                                 |  106 -
 campsis-1.9.1/campsis/man/simulation_progress-class.Rd                          |   66 -
 campsis-1.9.1/campsis/man/solver_settings-class.Rd                              |   54 
 campsis-1.9.1/campsis/man/spaghettiPlot.Rd                                      |   44 
 campsis-1.9.1/campsis/man/spaghetti_plot.Rd                                     |   38 
 campsis-1.9.1/campsis/man/spaghetti_plot.std_campsis_tbl.Rd                     |   80 -
 campsis-1.9.1/campsis/man/standardise_time.Rd                                   |   38 
 campsis-1.9.1/campsis/man/to_explicit_distribution.Rd                           |   56 
 campsis-1.9.1/campsis/man/undefined_distribution-class.Rd                       |   26 
 campsis-1.9.1/campsis/man/unite_columns.Rd                                      |   48 
 campsis-1.9.1/campsis/man/unwrap_treatment.Rd                                   |   84 -
 campsis-1.9.1/campsis/man/update_addl.Rd                                        |   92 -
 campsis-1.9.1/campsis/man/update_amount.Rd                                      |   92 -
 campsis-1.9.1/campsis/man/update_ii.Rd                                          |   92 -
 campsis-1.9.1/campsis/man/update_repeat.Rd                                      |   92 -
 campsis-1.9.1/campsis/man/vec_restore.campsis_tbl.Rd                            |   46 
 campsis-1.9.1/campsis/man/vpcPlot.Rd                                            |   64 -
 campsis-1.9.1/campsis/man/vpc_plot.Rd                                           |   38 
 campsis-1.9.1/campsis/man/vpc_plot.pi_campsis_tbl.Rd                            |  110 -
 campsis-1.9.1/campsis/man/vpc_plot.std_campsis_tbl.Rd                           |  142 +-
 campsis-1.9.1/campsis/tests/testthat/json_examples/scenarios_example1b.json     |only
 campsis-1.9.1/campsis/tests/testthat/test-dataset.R                             |   24 
 campsis-1.9.1/campsis/tests/testthat/test-json_interface.R                      |   81 +
 campsis-1.9.1/campsis/tests/testthat/test-occasion.R                            |    6 
 campsis-1.9.1/campsis/tests/testthat/test-occasions.R                           |    4 
 campsis-1.9.1/campsis/tests/testthat/test-scenario.R                            |    7 
 campsis-1.9.1/campsis/tests/testthat/test-scenarios.R                           |   16 
 campsis-1.9.1/campsis/tests/testthat/test-show_method.R                         |    2 
 campsis-1.9.1/campsis/tests/testthat/test-simulate_iov.R                        |   31 
 campsis-1.9.1/campsis/tests/testthat/test-simulate_nocb_locf.R                  |    2 
 campsis-1.9.1/campsis/tests/testthat/test-simulate_scenarios.R                  |   26 
 campsis-1.9.1/campsis/tests/testthat/test-utils.R                               |    2 
 162 files changed, 4240 insertions(+), 3790 deletions(-)

More information about campsis at CRAN
Permanent link

New package rankimp with initial version 1.0.0
Package: rankimp
Title: Consensus Ranking of Variable Importance with Uncertainty
Version: 1.0.0
Description: Variable importance rankings depend on the method, the random seed and the resample used to compute them. This package treats every source of importance as a judge expressing a ranking over the predictors, and synthesises those rankings into a Kemeny median ranking with ties. Uncertainty about the consensus is quantified through bootstrap rank confidence sets, top-k probabilities and clustering of disagreeing judges.
License: MIT + file LICENSE
URL: https://github.com/agostinognasso/rankimp
BugReports: https://github.com/agostinognasso/rankimp/issues
Depends: R (>= 3.5)
Imports: ConsRank, ggplot2, stats, tibble, utils
Suggests: cluster, covr, kernelshap, knitr, randomForest, ranger, rmarkdown, rsample, stabm, testthat (>= 3.1.7)
VignetteBuilder: knitr
LazyData: true
Encoding: UTF-8
Language: en-GB
NeedsCompilation: no
Packaged: 2026-09-09 09:34:03 UTC; agostinognasso
Author: Agostino Gnasso [aut, cre, cph]
Maintainer: Agostino Gnasso <agostino.gnasso@unina.it>
Repository: CRAN
Date/Publication: 2026-09-17 11:30:02 UTC

More information about rankimp at CRAN
Permanent link

New package Proximum with initial version 1.1.0
Package: Proximum
Title: Statistical Analysis of Ensemble Proximity Matrices
Version: 1.1.0
Description: Treats the proximity matrices produced by tree ensembles as first-class statistical objects rather than as model by-products. Provides a unified extractor across ensemble engines, in-bag and out-of-bag definitions, transformations to dissimilarities with metric diagnostics, corrections that make an indefinite proximity usable as a kernel, and permutation inference for comparing two proximity matrices or partitioning one across the terms of a design. Also provides a Nystrom approximation, a thresholded sparse representation and a streaming form that never allocates the matrix at all, for samples too large to hold it, measures how far the proximity moves between replicates of the ensemble, and draws each object through 'ggplot2': the seriated matrix, the configuration it implies, and the thresholded graph with its communities.
License: MIT + file LICENSE
URL: https://github.com/agostinognasso/Proximum
BugReports: https://github.com/agostinognasso/Proximum/issues
Depends: R (>= 3.5)
Imports: ggplot2, Matrix, rlang, stats, utils
Suggests: covr, e2tree, igraph, knitr, randomForest, ranger, rmarkdown, seriation, testthat (>= 3.2.0), vegan
VignetteBuilder: knitr
LazyData: true
Encoding: UTF-8
Language: en-GB
NeedsCompilation: no
Packaged: 2026-09-09 08:28:22 UTC; agostinognasso
Author: Agostino Gnasso [aut, cre, cph]
Maintainer: Agostino Gnasso <agostino.gnasso@unina.it>
Repository: CRAN
Date/Publication: 2026-09-17 11:40:02 UTC

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New package datadict with initial version 0.1.0
Package: datadict
Title: Validate Data Against a 'data-dict.yaml' Data Dictionary
Version: 0.1.0
Description: A data dictionary describes a collection of related tables: their columns, types, constraints, relationships, and glossary. Validate a dataset against its dictionary and read the findings as an HTML report. Reference: <https://data-dict.tidyverse.org>.
License: MIT + file LICENSE
URL: https://data-dict.tidyverse.org, https://github.com/tidyverse/data-dict
BugReports: https://github.com/tidyverse/data-dict/issues
Depends: R (>= 4.1)
Imports: cli (>= 3.2.0), processx, tools, utils
Suggests: nanoparquet, testthat (>= 3.0.0), withr
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-09-09 08:51:05 UTC; gaborcsardi
Author: Gabor Csardi [aut, cre] , Hadley Wickham [aut] , Posit Software, PBC [cph, fnd]
Maintainer: Gabor Csardi <gabor@posit.co>
Repository: CRAN
Date/Publication: 2026-09-17 11:20:02 UTC

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New package corsym with initial version 1.0.1
Package: corsym
Title: Correlation Estimation for Exchangeable/Symmetrical Variables
Version: 1.0.1
Description: We implement a new correlation estimator, CorSym, designed for exchangeable variables, where the ordering of the two values in the pair is arbitrary. This kind of data arises frequently in the study of assortative pairing (for example, income in a couple). The standard Pearson estimator is sensitive to such ordering and can be highly biased when the order is biased (when the first value tends to have lower or higher values than the second value). CorSym gives the same estimate deterministically for all orders within each pair, and estimates the desired correlation without bias (variables must be exchangeable). The package also includes utilities to simulate biased orders and test for order bias. Described in Kennedy and Ochoa (2026) <doi:10.64898/2026.08.22.746446>.
License: GPL (>= 3)
Encoding: UTF-8
Suggests: knitr, rmarkdown, testthat (>= 3.0.0), ggplot2
VignetteBuilder: knitr
URL: https://github.com/OchoaLab/corsym
BugReports: https://github.com/OchoaLab/corsym/issues
NeedsCompilation: no
Packaged: 2026-09-09 13:13:19 UTC; viiia
Author: Alejandro Ochoa [aut, cre] , Gabriel Kennedy [aut]
Maintainer: Alejandro Ochoa <alejandro.ochoa@duke.edu>
Repository: CRAN
Date/Publication: 2026-09-17 11:50:02 UTC

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New package carwatch with initial version 1.0.1
Package: carwatch
Title: Processing of 'CARWatch' Sampling Logs and Saliva Data
Version: 1.0.1
Description: Import and reconstruct saliva-sampling studies recorded by the 'CARWatch' application. Registration metadata and raw barcode events are converted into auditable study days and scheduled sample positions using a two-pass issue-review workflow. Functions assess sampling-time compliance, merge laboratory saliva measurements, calculate response features, and create quality-control visualizations. The application is described by Richer et al. (2023) <doi:10.1016/j.psyneuen.2023.106073>.
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-GB
Depends: R (>= 4.3)
Imports: boot, clock (>= 0.7.0), digest (>= 0.6.0), dplyr (>= 1.1.0), fs (>= 1.6.0), ggplot2 (>= 3.5.0), grid, jsonlite (>= 1.8.0), readr (>= 2.1.0), rlang (>= 1.1.0), tibble (>= 3.2.0), vctrs (>= 0.6.0), withr (>= 3.0.0)
Suggests: covr, DT, knitr, pkgdown, rmarkdown, roxygen2, shiny, shinytest2, testthat (>= 3.2.0)
VignetteBuilder: knitr
URL: https://carwatch-tools.github.io/carwatch-r/, https://github.com/carwatch-tools/carwatch-r
BugReports: https://github.com/carwatch-tools/carwatch-r/issues
NeedsCompilation: no
Packaged: 2026-09-09 12:43:54 UTC; richer
Author: Robert Richer [aut, cre]
Maintainer: Robert Richer <robert.richer@fau.de>
Repository: CRAN
Date/Publication: 2026-09-17 11:50:08 UTC

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New package arimasel with initial version 0.2.0
Package: arimasel
Title: Cartesian Product-Based ARIMA Model Identification and Selection
Version: 0.2.0
Description: Provides an alternative algorithm for ARIMA and seasonal ARIMA model identification based on Cartesian products of user-supplied parameter sets. Rather than relying on ACF/PACF plots or stepwise search (as in auto.arima()), the package exhaustively evaluates every candidate (p,d,q)(P,D,Q)[m] combination in the requested index sets, ranks all converged models by AIC, AICc, BIC, and HQIC simultaneously, computes Akaike weights for model uncertainty quantification, supports exogenous regressors, produces ensemble forecasts, evaluates candidate models by rolling-origin (expanding window) cross-validation, and provides publication-quality diagnostic and comparison plots. A feature-based exploratory data analysis suite computes scale-free time series characteristics (trend and seasonal strength, spectral entropy, autocorrelation, lumpiness, stability) in the spirit of Hyndman, Wang and Laptev (2015), and a feature-guided automatic search narrows the Cartesian product model space before the e [...truncated...]
License: GPL-3
Encoding: UTF-8
LazyData: true
Depends: R (>= 4.0.0)
Imports: stats, graphics, grDevices, utils, parallel
Suggests: tseries, forecast, testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
URL: https://github.com/Olawaleawe/arimasel
BugReports: https://github.com/Olawaleawe/arimasel/issues
NeedsCompilation: no
Packaged: 2026-09-09 12:59:40 UTC; root
Author: Olushina Olawale Awe [aut, cre]
Maintainer: Olushina Olawale Awe <olawaleawe@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-17 12:00:02 UTC

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Package unsurv updated to version 0.7.2 with previous version 0.7.0 dated 2026-08-31

Title: Unsupervised Clustering of Individualized Survival Curves
Description: Tools for clustering individualized survival curves using the Partitioning Around Medoids (PAM) algorithm, with monotonic enforcement, optional smoothing, weighted distances (L1/L2), automatic K selection via silhouette width, prediction for new curves, basic stability checks, and plotting helpers. The method is described in El Badisy (2026) <doi:10.1093/bioadv/vbag218>.
Author: Imad El Badisy [aut, cre]
Maintainer: Imad El Badisy <elbadisyimad@gmail.com>

Diff between unsurv versions 0.7.0 dated 2026-08-31 and 0.7.2 dated 2026-09-17

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Package photobiologyPlants updated to version 0.6.2 with previous version 0.6.1-1 dated 2025-10-04

Title: Plant Photobiology Related Functions and Data
Description: Provides functions for quantifying visible (VIS) and ultraviolet (UV) radiation in relation to the photoreceptors Phytochromes, Cryptochromes, and UVR8 which are present in plants. It also includes data sets on the optical properties of plants. Part of the 'r4photobiology' suite, Aphalo P. J. (2015) <doi:10.19232/uv4pb.2015.1.14>.
Author: Pedro J. Aphalo [aut, cre]
Maintainer: Pedro J. Aphalo <pedro.aphalo@helsinki.fi>

Diff between photobiologyPlants versions 0.6.1-1 dated 2025-10-04 and 0.6.2 dated 2026-09-17

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New package modelskill with initial version 0.1.1
Package: modelskill
Title: Assessing and Visualising the Performance of Prediction Models
Version: 0.1.1
Description: Provides tools for evaluating continuous predictions and their associated predictive uncertainty from statistical, machine-learning, geostatistical, and process-based models. It implements complementary measures of prediction error, association, agreement, efficiency, uncertainty calibration, and predictive-distribution performance, together with Taylor, solar, target, coverage, probability integral transform, and quantile-coverage diagnostics. Methods include the integrated evaluation approach of Wadoux, Walvoort and Brus (2022) <doi:10.1016/j.geoderma.2021.115332> and the uncertainty-validation framework of Schmidinger and Heuvelink (2023) <doi:10.1016/j.geoderma.2023.116585>.
License: MIT + file LICENSE
URL: https://github.com/AlexandreWadoux/modelskill, https://alexandrewadoux.github.io/modelskill/
BugReports: https://github.com/AlexandreWadoux/modelskill/issues
Encoding: UTF-8
Suggests: testthat (>= 3.0.0), knitr, rmarkdown, pkgdown
Imports: ggplot2 (>= 3.5.0), ggrepel, viridis
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-09-09 07:47:43 UTC; jd189549
Author: Alexandre M.J.-C. Wadoux [aut, cre, cph]
Maintainer: Alexandre M.J.-C. Wadoux <alexandre.wadoux@yahoo.fr>
Repository: CRAN
Date/Publication: 2026-09-17 11:00:02 UTC

More information about modelskill at CRAN
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Package mlr3cluster updated to version 0.6.0 with previous version 0.5.0 dated 2026-08-21

Title: Cluster Extension for 'mlr3'
Description: Extends the 'mlr3' package with cluster analysis.
Author: Maximilian Muecke [aut, cre] , Damir Pulatov [aut], Michel Lang [aut] , Marc Becker [ctb]
Maintainer: Maximilian Muecke <muecke.maximilian@gmail.com>

Diff between mlr3cluster versions 0.5.0 dated 2026-08-21 and 0.6.0 dated 2026-09-17

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Package MatchingPursuit updated to version 1.3.0 with previous version 1.2.0 dated 2026-08-19

Title: Processing Time Series Data Using the Matching Pursuit Algorithm
Description: Provides tools for analysing and decomposing time series data using the Matching Pursuit (MP) algorithm, a greedy signal decomposition technique that represents complex signals as a linear combination of simpler functions (called atoms) selected from a redundant dictionary. Support for the Orthogonal Matching Pursuit (OMP) variant of the classical MP algorithm is also provided. For more details see Mallat and Zhang (1993) <doi:10.1109/78.258082>, Pati et al. (1993) <doi:10.1109/ACSSC.1993.342465>, Elad (2010) <doi:10.1007/978-1-4419-7011-4> and Różański (2024) <doi:10.1145/3674832>.
Author: Artur Gramacki [aut, cre] , Jaroslaw Gramacki [ctb] , Piotr T. Rożanski [ctb]
Maintainer: Artur Gramacki <a.gramacki@gmail.com>

Diff between MatchingPursuit versions 1.2.0 dated 2026-08-19 and 1.3.0 dated 2026-09-17

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Package isocountry updated to version 0.8.0 with previous version 0.7.0 dated 2026-08-21

Title: ISO 3166-1 Country Codes
Description: ISO 3166-1 country codes and ISO 4217 currency codes provided by the International Organization for Standardization.
Author: Maximilian Muecke [aut, cre]
Maintainer: Maximilian Muecke <muecke.maximilian@gmail.com>

Diff between isocountry versions 0.7.0 dated 2026-08-21 and 0.8.0 dated 2026-09-17

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New package charport with initial version 0.1.0
Package: charport
Title: ALTREP String Interoperability
Version: 0.1.0
Date: 2026-09-08
Description: Provides infrastructure for interoperable ALTREP character vectors. Producers of ALTREP string classes can register access methods, allowing consumers to read supported character vectors through a common interface without materializing them as ordinary R strings. Also provides 'charvec', a reference ALTREP string implementation backed by stable memory slices, with support for efficient and multithreaded construction.
License: MIT + file LICENSE
Copyright: Benchmark measurements use the enwik8 corpus, the first 10^8 bytes of the English Wikipedia XML dump of 2006-03-03, whose text carries Wikipedia's own terms: the Creative Commons Attribution-ShareAlike License and the GNU Free Documentation License. No Wikipedia data is included in this package.
Encoding: UTF-8
Suggests: cpp11, quarto, Rcpp
VignetteBuilder: quarto
Depends: R (>= 3.6.0)
URL: https://github.com/charbase/charport, https://charbase.github.io/charport/
BugReports: https://github.com/charbase/charport/issues
NeedsCompilation: yes
Packaged: 2026-09-09 07:15:06 UTC; ted
Author: Travers Ching [aut, cre, cph], R Consortium [fnd]
Maintainer: Travers Ching <traversc@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-17 10:50:02 UTC

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Package CDMConnector updated to version 2.8.0 with previous version 2.7.0 dated 2026-08-27

Title: Connect to an OMOP Common Data Model
Description: Provides tools for working with observational health data in the Observational Medical Outcomes Partnership (OMOP) Common Data Model format with a pipe friendly syntax. Common data model database table references are stored in a single compound object along with metadata.
Author: Ger Inberg [aut, cre] , Adam Black [aut] , Artem Gorbachev [aut], Edward Burn [aut], Marti Catala Sabate [aut], Ioanna Nika [aut]
Maintainer: Ger Inberg <g.inberg@erasmusmc.nl>

Diff between CDMConnector versions 2.7.0 dated 2026-08-27 and 2.8.0 dated 2026-09-17

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Package AddiVortes updated to version 1.0.1 with previous version 0.6.9 dated 2026-08-03

Title: (Bayesian) Additive Voronoi Tessellations
Description: Implements the Bayesian Additive Voronoi Tessellation model for non-parametric regression, classification and machine learning as introduced in Stone and Gosling (2025) <doi:10.1080/10618600.2024.2414104>. This package provides a flexible alternative to BART (Bayesian Additive Regression Trees) using Voronoi tessellations instead of trees. Users can fit Bayesian regression and probit classification models, estimate the associated posterior distributions and make predictions. It is particularly useful for spatial data analysis, machine learning, complex function approximation and Bayesian modelling where the underlying structure is unknown.
Author: Adam Stone [aut] , John Paul Gosling [aut, cre] , Andrew Iskauskas [aut] , Leo Thomson [aut]
Maintainer: John Paul Gosling <john-paul.gosling@durham.ac.uk>

Diff between AddiVortes versions 0.6.9 dated 2026-08-03 and 1.0.1 dated 2026-09-17

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New package sleeper with initial version 0.5.0
Package: sleeper
Title: Estimate Sleep Status from Accelerometry Data
Version: 0.5.0
Description: Wraps the classifier from the Sundararajan (2021) <doi:10.1038/s41598-020-79217-x> to estimate sleep using a random forest. Users must download the model files from Sundararajan (2020) <doi:10.5281/zenodo.3752645> in order to use this method.
License: GPL (>= 3)
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: assertthat, curl, dplyr, methods, reticulate, rlang
Suggests: callr, readr, testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-09-08 16:50:58 UTC; johnmuschelli
Author: John Muschelli [aut, cre]
Maintainer: John Muschelli <muschellij2@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-17 09:10:02 UTC

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New package rmoriedata with initial version 0.3.2
Package: rmoriedata
Title: Integrated Datasets for the 'rmorie' Package
Version: 0.3.2
Description: Integrated open data fixtures used by the 'rmorie' package for examples, vignettes, and tests. Split out so 'rmorie' itself stays within the 'CRAN' package-size soft cap. Contains snapshots of publicly available datasets from open-data portals built on the Comprehensive Knowledge Archive Network ('CKAN', <https://ckan.org/>), 'Socrata' (<https://dev.socrata.com/>), and 'Opendatasoft' (<https://www.huwise.com/>) (Chicago, New York City, Toronto, Vancouver, and others), Statistics Canada Canadian Centre for Justice and Community Safety Statistics ('CCJS') tables, a multi-agent-reviewed corpus of Ontario Special Investigations Unit ('SIU', <https://www.siu.on.ca/>) director's reports, and synthetic fixtures for unit tests. Also ships a small set of analyst-facing helpers for releasing aggregate statistics without re-identification risk: Laplace and Gaussian differential privacy mechanisms and k-anonymity, l-diversity, and cell suppression verifiers.
License: AGPL (>= 3)
Encoding: UTF-8
Depends: R (>= 4.3.0)
Imports: stats, rmoriebricklayer (>= 0.2.1)
LinkingTo: rmoriebricklayer
Suggests: testthat (>= 3.0.0), nanoparquet, tibble, curl, jsonlite, knitr, rmarkdown
VignetteBuilder: knitr
LazyData: true
LazyDataCompression: xz
URL: https://github.com/rootcoder007/rmoriedata
BugReports: https://github.com/rootcoder007/rmoriedata/issues
NeedsCompilation: yes
Packaged: 2026-09-08 20:29:29 UTC; rootcoder
Author: Vansh Singh Ruhela [aut, cre]
Maintainer: Vansh Singh Ruhela <vsruhela@proton.me>
Repository: CRAN
Date/Publication: 2026-09-17 10:00:02 UTC

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New package pmsims with initial version 1.0.0
Package: pmsims
Title: Simulation-Based Sample Size Tools for Prediction Models
Version: 1.0.0
Description: Provides a flexible, simulation-based toolkit for exploring how much data are needed to develop reliable prediction models. It works by repeatedly generating data, fitting models, and evaluating performance to show how sample size affects predictive accuracy, calibration, and overfitting. The package supports continuous, binary, and time-to-event outcomes and can be used with both regression-based modelling approaches and machine-learning methods. It is designed to help researchers plan studies, assess feasibility, and build more robust and generalisable models. The methods are described in Olaniran et al. (2026) <doi:10.1186/s12874-026-02935-9> and Shamsutdinova et al. (2026) <doi:10.48550/arXiv.2602.23507>.
License: GPL (>= 3)
URL: https://pmsims-package.github.io/pmsims/, https://github.com/pmsims-package/pmsims
BugReports: https://github.com/pmsims-package/pmsims/issues
Depends: R (>= 4.1.0)
Imports: cli, ggplot2, lifecycle, mlpwr, pROC, stats, survival, timeROC, utils
Suggests: covr, DescTools, doParallel, foreach, glmnet, knitr, mlbench, mlr, randomForestSRC, ranger, rmarkdown, synthpop, testthat (>= 3.0.0), tuneRanger, xgboost
Encoding: UTF-8
LazyData: true
LazyDataCompression: xz
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-09-08 19:30:59 UTC; k1644956
Author: Ewan Carr [aut, cre] , Gordon Forbes [aut] , Ridwan Olaniran [aut] , Diana Shamsutdinova [aut] , Daniel Stahl [aut] , Sarah Markham [aut] , Felix Zimmer [aut]
Maintainer: Ewan Carr <ewan.carr@kcl.ac.uk>
Repository: CRAN
Date/Publication: 2026-09-17 09:30:02 UTC

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New package nowcaster with initial version 1.0.0
Package: nowcaster
Title: Statistical Models for Notification Delay Correction of Epidemiological Data
Version: 1.0.0
Description: Statistical models for correcting notification delays of epidemiological data. The package wraps statistical models to estimate not yet reported data using empirical delay distribution either from individual-level data or from the differences of aggregated time series of cases. For more details see Bastos et al. (2019) <doi:10.1002/sim.8303>.
License: GPL (>= 3)
Encoding: UTF-8
URL: https://covid19br.github.io/nowcaster/
BugReports: https://github.com/covid19br/nowcaster/issues
Suggests: INLA (>= 22.5.3), ggplot2, knitr, rmarkdown, vroom, parallel, lubridate, lme4, sn, stringr
Depends: R (>= 4.1.0)
LazyData: true
Additional_repositories: https://inla.r-inla-download.org/R/stable/
Imports: dplyr, tidyr, tibble, mgcv
NeedsCompilation: no
Packaged: 2026-09-08 16:59:17 UTC; lbastos
Author: Rafael Lopes [aut] , Tatiana Portella [aut] , Leo Bastos [aut, cre]
Maintainer: Leo Bastos <leonardo.bastos@fiocruz.br>
Repository: CRAN
Date/Publication: 2026-09-17 09:20:02 UTC

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Package migraph updated to version 1.7.2 with previous version 1.7.0 dated 2026-08-30

Title: Inferential Methods for Multimodal and Other Networks
Description: A set of tools for testing networks. It includes functions for univariate and multivariate conditional uniform graph and quadratic assignment procedure testing, and network regression. The package is a complement to 'Multimodal Political Networks' (2021, ISBN:9781108985000), and includes various datasets used in the book. Built on the 'manynet' package, all functions operate with matrices, edge lists, and 'igraph', 'network', and 'tidygraph' objects, and on one-mode and two-mode (bipartite) networks.
Author: James Hollway [cre, aut, ctb] , Henrique Sposito [ctb] , Jael Tan [ctb] , Bernhard Bieri [ctb]
Maintainer: James Hollway <james.hollway@graduateinstitute.ch>

Diff between migraph versions 1.7.0 dated 2026-08-30 and 1.7.2 dated 2026-09-17

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New package latentState with initial version 1.0.0
Package: latentState
Title: Simulate Outcomes of a Latent State Reinforcement Learning Model
Version: 1.0.0
Description: Simulates outcomes of an updated version of the latent state reinforcement learning model originally described in Cochran and Cisler (2019) <doi:10.1371/journal.pcbi.1007331>. The package is designed to create results under all reasonable experiment setups, including different reinforcement schedules, number of cues, number of phases, and number of options per trial. Participants can be simulated using either fixed parameters or parameters drawn from a distribution.
License: GPL (>= 3)
URL: https://osf.io/2whcu
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-09-08 19:41:12 UTC; marti
Author: Martin Benada [aut, cre]
Maintainer: Martin Benada <martinibenada@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-17 09:30:09 UTC

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Package enrichit updated to version 0.2.4 with previous version 0.2.1 dated 2026-08-04

Title: 'C++' Implementations of Functional Enrichment Analysis
Description: Fast implementations of functional enrichment analysis methods using 'C++' via 'Rcpp'. Currently provides Over-Representation Analysis (ORA), Gene Set Enrichment Analysis (GSEA), Weighted Enrichment Analysis for ORA and GSEA, Network-based Set Enrichment Analysis (NSEA), multi-layer network-based enrichment, and multi-omics integration workflows. Additional features include early fusion at the feature level, late fusion at the pathway level, multi-omics contribution tracing, topology-aware explanation helpers, Bayesian term selection, and extremely fast Random Walk with Restart (RWR) using 'RcppEigen'. The enrichment methods build on GSEA by Subramanian et al. (2005) <doi:10.1073/pnas.0506580102>, the multilevel strategy derived from 'fgsea' by Korotkevich et al. (2021) <doi:10.1101/060012>, and network-based enrichment ideas described by Glaab et al. (2012) <doi:10.1093/bioinformatics/bts389>.
Author: Guangchuang Yu [aut, cre]
Maintainer: Guangchuang Yu <guangchuangyu@gmail.com>

Diff between enrichit versions 0.2.1 dated 2026-08-04 and 0.2.4 dated 2026-09-17

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New package actimetrics with initial version 0.4.0
Package: actimetrics
Title: Create Metrics Actigraphy and Activity Analysis
Version: 0.4.0
Description: Provides functions for calibrating, counting, and summarizing actigraphy and activity data into specific metrics and sleep measures. The metrics include activity counts, step counts, activity index, Monitor Independent Movement Summary Unit (MIMS), mean amplitude deviation (MAD), and provides wrappers for sleep estimation from activity counts using Tudor-Locke (2014) <doi:10.1139/apnm-2013-0173> and Sadeh (1994) <doi:10.1093/sleep/17.3.201>.
License: GPL-3
Depends: R (>= 4.1.0)
Suggests: testthat, utils, covr, knitr, httr, rmarkdown, MIMSunit, data.table, reticulate, stepcount (>= 0.6.0), actigraph.sleepr (>= 0.3.1), agcounts (>= 0.6.7), callr
Encoding: UTF-8
VignetteBuilder: knitr
Imports: actibase, actiread, dplyr, lubridate, assertthat, purrr, tibble, rlang, stats, tidyr, walking (>= 0.8.0), methods
LazyData: true
URL: https://jhuwit.github.io/actimetrics/
BugReports: https://github.com/jhuwit/actimetrics/issues
NeedsCompilation: no
Packaged: 2026-09-08 16:17:38 UTC; johnmuschelli
Author: John Muschelli [aut, cre]
Maintainer: John Muschelli <muschellij2@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-17 09:10:15 UTC

More information about actimetrics at CRAN
Permanent link

Package smoothSurv updated to version 2.7 with previous version 2.6 dated 2023-12-13

Title: Survival Regression with Smoothed Error Distribution
Description: Contains, as a main contribution, a function to fit a regression model with possibly right, left or interval censored observations and with the error distribution expressed as a mixture of G-splines. Core part of the computation is done in compiled 'C++' written using the 'Scythe' Statistical Library Version 0.3. The methods implemented in the package have been published in Komárek, Lesaffe and Hilton (2005, J. of Comp. and Graph. Stat.) <doi:10.1198/106186005X63734> and Lesaffre, Komárek and Declerck (2005, Stat. Methods in Med. Res.) <doi:10.1191/0962280205sm417oa>.
Author: Arnost Komarek [aut, cre] , Kevin M. Quinn [ctb, cph] , Andrew D. Martin [ctb, cph] , Daniel B. Pemstein [ctb, cph] , Berwin A. Turlach [ctb]
Maintainer: Arnost Komarek <arnost.komarek@matfyz.cuni.cz>

Diff between smoothSurv versions 2.6 dated 2023-12-13 and 2.7 dated 2026-09-17

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More information about smoothSurv at CRAN
Permanent link

Package shinyOAuth updated to version 0.6.0 with previous version 0.5.0 dated 2026-05-23

Title: OIDC Authentication and OAuth Authorization for 'shiny' Applications
Description: Provides a simple, configurable framework for 'OpenID Connect' (OIDC) authentication and 'OAuth 2.0' authorization in 'shiny' applications using 'S7' classes. Defines providers, clients, and tokens, as well as various supporting functions and a 'shiny' module. Features include cross-site request forgery (CSRF) protection, state encryption, 'Proof Key for Code Exchange' (PKCE) handling, validation of OIDC identity tokens (nonces, signatures, claims), automatic user info retrieval for OIDC and supported 'OAuth' providers, asynchronous flows, and hooks for audit logging.
Author: Luka Koning [aut, cre, cph]
Maintainer: Luka Koning <koningluka@gmail.com>

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Package disordR updated to version 0.9-8-7 with previous version 0.9-8-6 dated 2026-03-12

Title: Non-Ordered Vectors
Description: Functionality for manipulating values of associative maps. The package is a dependency for mvp-type packages that use the STL map class: it traps plausible idiom that is ill-defined (implementation-specific) and returns an informative error, rather than returning a possibly incorrect result. To cite the package in publications please use Hankin (2022) <doi:10.48550/ARXIV.2210.03856>.
Author: Robin K. S. Hankin [aut, cre]
Maintainer: Robin K. S. Hankin <hankin.robin@gmail.com>

Diff between disordR versions 0.9-8-6 dated 2026-03-12 and 0.9-8-7 dated 2026-09-17

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New package bonsaisitter with initial version 0.1.2
Package: bonsaisitter
Title: Bindings to the 'Tree-Sitter' Parsing Library
Version: 0.1.2
Date: 2026-09-08
Description: A runtime for the 'Tree-sitter' parsing library <https://tree-sitter.github.io/tree-sitter/> that mirrors the API of the 'treesitter' package, so it can serve as a drop-in replacement. Parses source code into concrete syntax trees and updates them incrementally as the source changes. Grammars are supplied by separate packages such as 'treesitter.r', so the runtime itself depends on nothing beyond base R.
License: MIT + file LICENSE
Copyright: cornball.ai, except the bundled tree-sitter sources under src/tree-sitter, whose holders are listed in inst/COPYRIGHTS.
URL: https://github.com/cornball-ai/bonsaisitter
BugReports: https://github.com/cornball-ai/bonsaisitter/issues
Encoding: UTF-8
NeedsCompilation: yes
Suggests: tinytest, treesitter, treesitter.r
Packaged: 2026-09-08 16:12:58 UTC; troy
Author: Troy Hernandez [aut, cre] , cornball.ai [cph], Max Brunsfeld [ctb, cph] , International Business Machines Corporation [cph] , Unicode, Inc. [cph] , Mathias Panzenboeck [ctb]
Maintainer: Troy Hernandez <troy@cornball.ai>
Repository: CRAN
Date/Publication: 2026-09-17 09:00:09 UTC

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Package tinyshinyserver updated to version 0.2.0 with previous version 0.1.0 dated 2026-01-06

Title: Tiny 'shiny' Server - Lightweight Multi-App 'shiny' Proxy
Description: A lightweight, 'WebSocket'-enabled proxy server for hosting multiple 'shiny' applications with automatic health monitoring, session management, and resource cleanup. Provides a simple entry point to run the server using a JSON configuration file.
Author: Lars Bernhardsson [aut, cre]
Maintainer: Lars Bernhardsson <cran.sherry228@passinbox.com>

Diff between tinyshinyserver versions 0.1.0 dated 2026-01-06 and 0.2.0 dated 2026-09-17

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Package selectr updated to version 0.7-0 with previous version 0.6-0 dated 2026-06-23

Title: Translate CSS Selectors to XPath Expressions
Description: Translates a CSS selector into an equivalent XPath expression. This allows us to use CSS selectors when working with the 'XML' and 'xml2' packages, which can only evaluate XPath expressions. Also provided are convenience functions for querying XML and HTML documents with CSS selectors. This package was originally a port of the Python package 'cssselect' (<https://cssselect.readthedocs.io/>).
Author: Simon Potter [aut, trl, cre], Simon Sapin [aut], Ian Bicking [aut]
Maintainer: Simon Potter <simon@sjp.co.nz>

Diff between selectr versions 0.6-0 dated 2026-06-23 and 0.7-0 dated 2026-09-17

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Package dyn updated to version 0.2-11.0 with previous version 0.2-9.6 dated 2018-03-19

Title: Time Series Regression
Description: Time series regression. The dyn class interfaces ts, irts(), zoo() and zooreg() time series classes to lm(), glm(), loess(), quantreg::rq(), MASS::rlm(), MCMCpack::MCMCregress(), quantreg::rq(), randomForest::randomForest() and other regression functions allowing those functions to be used with time series including specifications that may contain lags, diffs and missing values.
Author: G. Grothendieck [aut], M. Leeds [cre]
Maintainer: M. Leeds <markleeds2@gmail.com>

Diff between dyn versions 0.2-9.6 dated 2018-03-19 and 0.2-11.0 dated 2026-09-17

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Package mathml (with last version 1.9) was removed from CRAN

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

2026-07-02 1.9
2026-05-22 1.8
2026-01-17 1.7
2025-08-19 1.6
2025-06-13 1.5
2025-05-18 1.4
2025-02-02 1.3
2023-07-15 1.2
2023-07-11 1.1
2023-06-29 1.0
2023-04-24 0.8
2023-04-21 0.7
2023-04-19 0.6
2023-01-17 0.5

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Package rswipl (with last version 10.1.9) was removed from CRAN

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2026-06-16 10.1.9
2026-05-29 10.1.8
2026-05-12 10.1.7
2026-04-26 10.1.6
2026-03-12 10.1.5
2026-02-23 10.1.4
2026-01-21 10.1.1.1
2026-01-08 10.1.1
2025-12-06 10.0.0
2025-03-21 9.3.21
2025-03-09 9.3.20
2025-01-07 9.3.18
2024-12-04 9.3.16
2024-09-29 9.3.12
2024-09-17 9.3.11
2024-07-09 9.3.7.2
2024-05-13 9.3.5.1
2024-05-01 9.3.5
2024-03-26 9.3.3.1
2024-03-16 9.3.3
2024-01-25 9.1.22
2023-10-31 9.1.17.1
2023-10-16 9.1.17
2023-09-27 9.1.16
2023-09-06 9.1.15
2023-08-07 9.1.12
2023-07-05 9.1.11
2023-05-04 9.1.9
2023-03-24 9.1.8
2023-03-19 9.1.7
2023-02-20 9.1.6
2023-01-27 9.1.4
2023-01-15 9.1.3
2022-12-20 9.1.2
2022-11-09 8.5.20

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Package competitiontoolbox (with last version 0.7.4) was removed from CRAN

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2026-08-26 0.7.4
2022-08-25 0.7.1
2021-05-21 0.7.0
2020-06-30 0.1.3

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Package optiSel (with last version 2.1.0) was removed from CRAN

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

2026-02-19 2.1.0
2024-07-08 2.0.9
2024-06-12 2.0.8

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Package rolog (with last version 0.9.28) was removed from CRAN

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

2026-06-25 0.9.28
2026-06-18 0.9.27
2026-04-21 0.9.26
2026-02-24 0.9.25
2026-01-14 0.9.24
2025-05-19 0.9.23
2025-03-11 0.9.21
2025-02-15 0.9.20
2024-07-09 0.9.18
2024-05-01 0.9.17
2024-03-28 0.9.16
2024-03-18 0.9.15
2023-06-29 0.9.14
2023-05-08 0.9.13
2023-04-20 0.9.12
2023-01-27 0.9.11
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2022-04-29 0.9.2
2022-04-28 0.9.1
2022-04-25 0.9

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