New package xsdm with initial version 1.0.2
Package: xsdm
Title: Demographic Approach to Species Distribution Model
Version: 1.0.2
Description: Integrates concepts of stochastic demography into species distribution modelling. The main approach maximizes a likelihood function based on environmental information and presence/absence records. This is used to reconstruct species' fundamental ecological niches and to project their potential geographic range. Data requirements include species presence/absence records and a timeseries of environmental data.
License: AGPL (>= 3)
Imports: checkmate, expm, Rcpp (>= 1.1.0), RcppParallel (>= 5.1.10), stats, terra, tibble, ucminfcpp, furrr, future, future.callr, sobol, purrr
LinkingTo: Rcpp, RcppParallel, ucminfcpp
SystemRequirements: GNU make, C++17
Encoding: UTF-8
Depends: R (>= 4.1.0)
LazyData: true
LazyDataCompression: xz
Suggests: clue, knitr, rmarkdown, testthat (>= 3.0.0)
URL: https://xsdm-project.github.io/xsdm/, https://xsdm-project.github.io/xsdm-devel/
BugReports: https://github.com/xsdm-project/xsdm-devel/issues
NeedsCompilation: yes
Packaged: 2026-08-03 17:40:22 UTC; alrobles
Author: Emilio Berti [aut] , Daniel C. Reuman [aut] , Angel Luis Robles Fernandez [aut, cre]
Maintainer: Angel Luis Robles Fernandez <a.l.robles.fernandez@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-08 14:50:02 UTC

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New package wordorientation with initial version 0.1.0
Package: wordorientation
Title: Detect Attraction and Repulsion Between Words in Text
Version: 0.1.0
Description: Provides tools to quantify how strongly pairs of words attract or repel each other in a text corpus, based on co-occurrence patterns. For each word pair, the phi coefficient (a correlation measure for binary variables) is computed from a document-term matrix and tested for significance, then classified as showing attraction (co-occurring more than chance would predict), repulsion (co-occurring less than chance would predict), or no significant relationship. A full pipeline is provided from raw text to a labeled network visualization. Unlike general-purpose pairwise correlation tools, 'wordorientation' is built specifically for text: it handles tokenization and stopword removal, applies significance-based classification rather than reporting a raw correlation coefficient alone, and produces a ready-to-plot attraction/ repulsion network.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 3.5.0)
Imports: stats, graphics, igraph, scales
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
URL: https://github.com/yosleycarrero2025/wordorientation
BugReports: https://github.com/yosleycarrero2025/wordorientation/issues
NeedsCompilation: no
Packaged: 2026-08-03 22:16:13 UTC; yosle
Author: Yosley Carrero [aut, cre]
Maintainer: Yosley Carrero <c3046338@newcastle.ac.uk>
Repository: CRAN
Date/Publication: 2026-08-08 14:40:02 UTC

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New package RIFanalysis with initial version 0.9.1
Package: RIFanalysis
Title: Relative Importance Factor Analysis
Version: 0.9.1
Description: Tools for estimating, comparing, and visualizing Relative Importance Factor (RIF) indices based on rank-frequency distributions and discrete power-law models. The package provides reproducible workflows for data preparation, model fitting, goodness-of-fit assessment, bootstrap inference, and publication-ready outputs. The implemented methodology is described in Llinas et al. (2026) <doi:10.3390/math14060966>.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: checkmate, dplyr, ggplot2, ggraph, cowplot, igraph, openxlsx, poweRlaw (>= 0.70.0), rlang, ggrepel, stringr
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-04 03:18:42 UTC; zirox
Author: Humberto J. Llinas M. [aut, cre], Humberto J. Llinas S. [aut], Javier A. De la Hoz M. [aut], Brian J. Llinas M. [aut], Jose J. Padilla [aut]
Maintainer: Humberto J. Llinas M. <lhumberto@uninorte.edu.co>
Repository: CRAN
Date/Publication: 2026-08-08 14:30:10 UTC

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New package Rhobots with initial version 0.1.10
Package: Rhobots
Title: 'BERTopic'-Style Topic Modeling Without 'Python'
Version: 0.1.10
Description: Implements the 'BERTopic' topic modeling pipeline directly in R: transformer-based sentence embedding, Uniform Manifold Approximation and Projection dimensionality reduction, Hierarchical Density-Based Spatial Clustering of Applications with Noise clustering, and class-based term frequency-inverse document frequency topic extraction - all without any dependency on 'Python', 'conda', or 'reticulate'. Every stage runs in R through 'torch', 'safetensors', 'tok', 'uwot', and 'dbscan'. The package mirrors the accessor API of the original 'Python' package, adds integrated quality metrics and hyperparameter search tools, and introduces part-of-speech filtered and C-value-ranked representation models.
License: MIT + file LICENSE
URL: https://github.com/JPvdP/RhoBots
BugReports: https://github.com/JPvdP/RhoBots/issues
SystemRequirements: Microsoft Visual C++ Redistributable 2022 (Windows only; required by torch)
Depends: R (>= 4.1.0)
Encoding: UTF-8
Imports: torch, safetensors, hfhub, tok, jsonlite, uwot, dbscan, Matrix, stats, wordpiece, Rcpp
LinkingTo: Rcpp
Suggests: testthat (>= 3.0.0), plotly, httr2, gutenbergr, udpipe
NeedsCompilation: yes
Packaged: 2026-08-02 20:01:56 UTC; janpieter
Author: J.P.G. van der Pol [aut, cre]
Maintainer: J.P.G. van der Pol <j.p.g.vanderpol@uu.nl>
Repository: CRAN
Date/Publication: 2026-08-08 14:30:02 UTC

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New package MEMWAS with initial version 0.9.3
Package: MEMWAS
Title: Mixed-Effects Models with Autocorrelation Structures
Version: 0.9.3
Date: 2026-08-04
Description: Fits longitudinal generalized mixed-effects models through the 'MEMWAS' interface and a registered 'C++' numerical backend. Supported serial covariance structures include first-order autoregressive (AR(1)), exponential or Ornstein-Uhlenbeck, higher-order autoregressive (AR(p)), first-order autoregressive moving-average (ARMA(1,1)), compound symmetry, Toeplitz, and unstructured covariance. Serial processes can be unified or attached independently to numeric predictor loadings. Candidate temporal structures can be ranked on a common sample by primary-cluster grouped cross-validation, the Akaike information criterion, the Bayesian information criterion, or log-likelihood. Clustered, crossed, and nested random intercepts and slopes are assembled jointly with diagonal or term-specific unstructured covariance. Available approximation methods include Laplace, saddlepoint likelihood with latent Laplace integration, adaptive Gaussian quadrature, full-covariance Gaussian variational inference, a [...truncated...]
License: GPL (>= 3)
Depends: R (>= 4.1.0)
Imports: stats, utils
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr, rmarkdown
NeedsCompilation: yes
Language: en-US
Encoding: UTF-8
Packaged: 2026-08-04 03:02:10 UTC; KYN
Author: Enoch Kang [aut, cre, trl]
Maintainer: Enoch Kang <y.enoch.kang@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-08 14:00:02 UTC

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New package ggmultiglyph with initial version 0.1.0
Package: ggmultiglyph
Title: Multivariate Data Visualization using Glyphs
Version: 0.1.0
Description: Provides 'ggplot2' geoms for visualizing multivariate data using glyphs. The package implements several established glyph designs described in the information visualization literature, including the review by Borgo et al. (2013) <doi:10.2312/conf/EG2013/stars/039-063>.
Copyright: 2021-2026, ICAR-NBPGR
License: GPL-2 | GPL-3
Encoding: UTF-8
LinkingTo: Rcpp
Depends: R (>= 3.5.0)
Imports: cli, ggplot2, grid, methods, packcircles, Rcpp, Rdpack, rlang, scales
Suggests: ggrepel, gridExtra, RColorBrewer
URL: https://github.com/aravind-j/ggmultiglyph, https://aravind-j.github.io/ggmultiglyph/
BugReports: https://github.com/aravind-j/ggmultiglyph/issues
Language: en-GB
NeedsCompilation: yes
Packaged: 2026-08-03 09:17:45 UTC; Aravind-DGC
Author: J. Aravind [aut, cre] , Kamil Slowikowski [ctb] , ICAR-NBGPR [cph]
Maintainer: J. Aravind <j.aravind@icar.org.in>
Repository: CRAN
Date/Publication: 2026-08-08 13:50:03 UTC

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New package GammaFrailtySPC with initial version 0.1.0
Package: GammaFrailtySPC
Title: Statistical Process Control Based on Gamma-Frailty AFT Models
Version: 0.1.0
Description: Implements statistical process control ('SPC') monitoring schemes for heterogeneous reliability observations using Accelerated Failure Time ('AFT') models integrated with continuous gamma frailty. It accommodates both uncensored and right-censored reliability observations in the presence of observed and unobserved covariates. Provides Phase I maximum likelihood estimation of Weibull 'AFT' gamma frailty model parameters, and Phase II monitoring procedures including probability-limits-based control charts, exponentially weighted moving average ('EWMA') charts with conditional expected values, and likelihood-ratio cumulative sum ('CUSUM') control charts. Competing 'CUSUM' schemes (ignoring unobserved frailty or both covariates) and Average Run Length ('ARL') simulation utilities are also provided. The statistical methodology is based on Asadzadeh (2022) <doi:10.1080/00949655.2021.1959582>.
License: GPL-3
Depends: R (>= 4.0.0)
Imports: maxLik, survival, stats, graphics, grDevices, utils
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
Encoding: UTF-8
Language: en-US
LazyData: true
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-03 20:59:39 UTC; shikhar tyagi
Author: Shikhar Tyagi [aut, cre] , Arvind Pandey [aut], Bhupendra Singh [aut], Vrijesh Tripathi [aut]
Maintainer: Shikhar Tyagi <shikhar1093tyagi@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-08 13:50:16 UTC

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New package densemlp with initial version 0.5.0
Package: densemlp
Title: Dense Neural Networks for Tabular Classification and Regression
Version: 0.5.0
Author: Imad EL BADISY [aut, cre]
Maintainer: Imad EL BADISY <elbadisyimad@gmail.com>
Description: Provides dense feed-forward neural network models for tabular regression and classification using 'torch'. The package supports modern extensions around dense neural network blocks, including dropout, batch normalization, residual connections, gated blocks, and optional input projection.
URL: https://github.com/ielbadisy/densemlp
BugReports: https://github.com/ielbadisy/densemlp/issues
License: MIT + file LICENSE
Encoding: UTF-8
Imports: ggplot2, stats, torch
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-03 18:54:34 UTC; imad-el-badisy
Repository: CRAN
Date/Publication: 2026-08-08 13:50:11 UTC

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New package BKQualit with initial version 0.1.1
Package: BKQualit
Title: Analysis of Qualitative Traits, Segregation and Genetic Linkage
Version: 0.1.1
Description: A colour-first toolkit for the analysis of qualitative (categorical) traits in plant breeding and genetics. It tests observed segregation against the classical Mendelian expectations, fitting every standard mono-, di- and trihybrid ratio automatically and ranking them by goodness of fit, with Yates continuity correction and Monte Carlo exact tests for sparse tables. It partitions chi-square across families into pooled and heterogeneity components, so that a poor overall fit can be attributed either to the hypothesised ratio or to variation between families. Genetic linkage is estimated by maximum likelihood from two-locus second filial generation and backcross data, with logarithm of odds scores and likelihood-ratio confidence intervals for the recombination fraction. The package further computes Shannon-Weaver and Simpson diversity for descriptor states used in distinctness, uniformity and stability testing, and performs multiple correspondence analysis and Gower-distance clustering o [...truncated...]
License: GPL-3
Encoding: UTF-8
Depends: R (>= 4.0.0)
Imports: stats, utils, grDevices, ggplot2
Suggests: ggrepel, patchwork, knitr, rmarkdown, testthat (>= 3.0.0)
URL: https://github.com/bkpraveenars-del/BKQualit
BugReports: https://github.com/bkpraveenars-del/BKQualit/issues
NeedsCompilation: no
Packaged: 2026-08-04 05:01:13 UTC; ASUS
Author: Praveen Kumar B. K. [aut, cre]
Maintainer: Praveen Kumar B. K. <bkpraveenars@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-08 13:20:02 UTC

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New package SingRegKrig with initial version 0.1.0
Package: SingRegKrig
Title: Singularity Regression Kriging for Spatial Prediction
Version: 0.1.0
Description: Implements the Singularity Regression Kriging ('SRK') model for spatial prediction by integrating covariate singularity feature construction, nonlinear trend estimation via random forest, and geostatistical interpolation of residuals using ordinary kriging. Singularity-based anomaly indices are computed from environmental covariates at multiple spatial scales to capture local multiscale heterogeneity and augment the random forest feature set for trend estimation. The resulting residuals are interpolated using ordinary kriging to generate final spatial predictions with uncertainty quantification. Tools for spatial block cross-validation, parameter sensitivity analysis, and diagnostic visualization are also provided. Methods are based on Ren, Song, Chen, and Yu (2026) <doi:10.1080/15481603.2026.2690341>, with singularity theory from Cheng (2012) <doi:10.1016/j.gexplo.2012.07.007> and Cheng (2017) <doi:10.1016/j.gr.2017.07.011>, random forest methodology from Breiman (20 [...truncated...]
License: GPL (>= 3)
Encoding: UTF-8
Depends: R (>= 4.0.0)
Imports: stats, graphics, grDevices, randomForest, gstat, sp
Suggests: testthat (>= 3.0.0)
LazyData: true
NeedsCompilation: no
Packaged: 2026-08-03 14:47:19 UTC; shikhar tyagi
Author: Shikhar Tyagi [aut, cre] , Arvind Pandey [aut], Bhupendra Singh [aut], Vrijesh Tripathi [aut]
Maintainer: Shikhar Tyagi <shikhar1093tyagi@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-08 12:30:18 UTC

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New package secfile with initial version 0.1.1
Package: secfile
Title: SEC 'EDGAR' APIs
Version: 0.1.1
Description: Simple and efficient access to the SEC's 'EDGAR' APIs <https://www.sec.gov/search-filings> for querying and retrieving filings. The 'secfile' package abstracts the complexities of interacting with SEC EDGAR APIs, such as session management, user agent declaration, rate limiting, index parsing, pagination of filing metadata, URL construction, document caching, and inline XBRL parsing. This abstraction allows users to focus on retrieving data rather than managing API details. Use cases include retrieving filings across a range of workflows such as indexes, tenures, submissions, and facts. The package supports flexible query capabilities, including customizable form types, date ranges, and dimensions, and automatic data validation. It handles the SEC's fair access requirements automatically, such as user agent declaration and rate limiting between requests, and caches downloaded documents for efficient retrieval of large datasets. The implementation uses standard HTTP libraries to h [...truncated...]
License: GPL (>= 2)
URL: https://github.com/jasonjfoster/file
BugReports: https://github.com/jasonjfoster/file/issues
Depends: R (>= 3.5.0)
Imports: curl, jsonlite, xml2
Suggests: covr, testthat
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2026-08-03 11:16:20 UTC; jason
Author: Jason Foster [aut, cre]
Maintainer: Jason Foster <jason.j.foster@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-08 12:30:02 UTC

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New package K4Siswa with initial version 0.1.0
Package: K4Siswa
Title: Student Context Data Files for TIMSS 2023 Grade 4
Version: 0.1.0
Description: The official Trends in International Mathematics and Science Study (TIMSS) 2023 website provides Student Context Data Files for Grade 4 in RData format. However, the available data are presented solely as numerical values. This package transforms the numerical data into categorical variables, enabling clearer interpretation and reducing ambiguity in statistical analysis. The category labels are provided in Bahasa Indonesia. This initiative contributes to promoting the use of Bahasa Indonesia in programming, in line with its designation as one of the official languages of the United Nations. For more details see <https://timss2023.org/>.
License: GPL-3
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-08-02 23:23:51 UTC; HP
Author: Fadhlul Mubarak [aut, cre] , Vinny Yuliani Sundara [aut]
Maintainer: Fadhlul Mubarak <mubarakfadhlul@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-08 12:50:16 UTC

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New package K4Rumah with initial version 0.1.0
Package: K4Rumah
Title: Home Context Data Files for TIMSS 2023 Grade 4
Version: 0.1.0
Description: The official Trends in International Mathematics and Science Study (TIMSS) 2023 website provides Home Context Data Files for Grade 4 in RData format. However, the available data are presented solely as numerical values. This package transforms the numerical data into categorical variables, enabling clearer interpretation and reducing ambiguity in statistical analysis. The category labels are provided in Bahasa Indonesia. This initiative contributes to promoting the use of Bahasa Indonesia in programming, in line with its designation as one of the official languages of the United Nations. For more details see <https://timss2023.org/>.
License: GPL-3
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-08-03 14:08:50 UTC; HP
Author: Fadhlul Mubarak [aut, cre] , Vinny Yuliani Sundara [aut]
Maintainer: Fadhlul Mubarak <mubarakfadhlul@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-08 12:30:23 UTC

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New package gpciIntCensor with initial version 0.1.0
Package: gpciIntCensor
Title: Generalized Process Capability Indices for Interval-Censored Data
Version: 0.1.0
Description: A comprehensive framework for computing, estimating, and validating Generalized Process Capability Indices (GPCIs) under interval-censored data. Supports user-supplied probability density functions (PDF/PMF), cumulative distribution functions (CDF), and survival functions (SF). Parameter estimation is performed using Maximum Likelihood Estimation for interval-censored data via the MleCensoR package. Computes classical and generalized capability indices including Cpy (Maiti et al., 2010), Spmk (Dey & Saha, 2019), CpTk (Saha et al., 2019), Cpc (Saha et al., 2022), CNpmc (Alotaibi et al., 2022), CNpmkc (Saha et al., 2024), CNpk (Saha et al., 2018), and Vannman's Cp(u,v) family. Provides parametric and non-parametric bootstrap confidence intervals at 90%, 95%, and 99% confidence levels using percentile, normal, basic, BCa, BCp, and studentized bootstrap methods. Computes standard errors, mean squared errors, and coverage probabilities for both distribution parameters and capability ind [...truncated...]
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.0.0)
Imports: stats, graphics, numDeriv, boot, MleCensoR
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-03 19:18:25 UTC; shikhar tyagi
Author: Shikhar Tyagi [aut, cre] , Sumit Kumar [aut], Arvind Pandey [aut], Bhupendra Singh [aut], Vrijesh Tripathi [aut]
Maintainer: Shikhar Tyagi <shikhar1093tyagi@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-08 13:00:02 UTC

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New package gpciEMprogII with initial version 0.1.0
Package: gpciEMprogII
Title: Generalized Process Capability Indices via EM Algorithm under Progressive Type-II Censoring
Version: 0.1.0
Description: Implements the Expectation-Maximization (EM) algorithm of Dempster, Laird, and Rubin (1977) <doi:10.1111/j.2517-6161.1977.tb01600.x> for parameter estimation under progressive Type-II censored data (Balakrishnan and Aggarwala (2000) <doi:10.1007/978-1-4612-1186-0>) and computes Generalized Process Capability Indices (GPCIs). Uses the 'UniCensorEM' package for EM estimation. Supports classical and generalized capability indices including Cpy (Maiti et al. (2010) <doi:10.1080/16843703.2010.11673233>), Cp, Cpk, Cpu, Cpl, Cpm, Cpmk, Spmk (Dey and Saha (2019) <doi:10.1007/s41872-019-00081-4>), CpTk (Saha et al. (2018) <doi:10.1080/21681015.2018.1437793>), Cpc, CNpmc (Alotaibi et al. (2022) <doi:10.1155/2022/3135264>), CNpmkc (Saha et al. (2024) <doi:10.1142/S021853932450013X>), and CNpk (Saha et al. (2022) <doi:10.1080/02664763.2021.1971632>). Computes point estimates, bias, mean squared error, risk, Heidelberger and Welch convergence diagnost [...truncated...]
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.0.0)
Imports: stats, UniCensorEM
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-08-03 04:02:24 UTC; shikhar tyagi
Author: Shikhar Tyagi [aut, cre]
Maintainer: Shikhar Tyagi <shikhar1093tyagi@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-08 12:50:02 UTC

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New package ghcclm with initial version 0.1.0
Package: ghcclm
Title: Generalized Hybrid Contrast Coding in Linear Models
Version: 0.1.0
Description: Implements generalized hybrid contrast coding methods for K-level categorical predictors in linear models as established by Obulezi (2026)[cite: 3]. The package automates design matrix construction mixing dummy indicators and composite group contrasts, checks rank constraints via singular value decomposition, computes closed-form OLS parameter mappings, and estimates robust heteroscedastic covariance matrices[cite: 3].
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.0.0)
Imports: stats
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-08-03 16:38:47 UTC; Dr. O. J. Obulezi
Author: Okechukwu J. Obulezi [aut, cre]
Maintainer: Okechukwu J. Obulezi <oj.obulezi@unizik.edu.ng>
Repository: CRAN
Date/Publication: 2026-08-08 13:00:06 UTC

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New package diffuseR with initial version 0.2.2
Package: diffuseR
Title: Functional Interface to Diffusion Models in R
Version: 0.2.2
Description: A native R implementation of diffusion models providing a functional interface to state-of-the-art generative AI. Inspired by the 'Python' library 'diffusers' from 'Hugging Face' <https://huggingface.co/>, 'diffuseR' generates and manipulates images from text prompts using models such as 'Stable Diffusion', with no 'Python' dependency. Supports multiple diffusion schedulers and device acceleration.
License: Apache License (>= 2)
URL: https://github.com/cornball-ai/diffuseR
BugReports: https://github.com/cornball-ai/diffuseR/issues
Encoding: UTF-8
Imports: torch, jsonlite, grid, png, jpeg
Suggests: av, hfhub, safetensors, simplermarkdown, tinytest
VignetteBuilder: simplermarkdown
NeedsCompilation: no
Packaged: 2026-08-03 06:24:31 UTC; troy
Author: Troy Hernandez [aut, cre] , cornball.ai [cph], The HuggingFace Team [cph] ; see inst/COPYRIGHTS), Lightricks Ltd. [cph]
Maintainer: Troy Hernandez <troy@cornball.ai>
Repository: CRAN
Date/Publication: 2026-08-08 12:40:02 UTC

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New package CRAFT with initial version 0.1.0
Package: CRAFT
Title: Conditional Regime Analog Forecasting with Trajectories
Version: 0.1.0
Maintainer: Giancarlo Vercellino <giancarlo.vercellino@gmail.com>
Description: Tools for Conditional Regime Analog Forecasting with Trajectories. The package builds lag and lead trajectory embeddings, detects regimes with singular value decomposition and changepoint analysis, estimates transition probabilities between regimes, samples future-trajectory analogues, and fits smooth empirical forecast distributions.
License: GPL-3
Depends: R (>= 4.1.0)
Imports: changepoint, graphics, grDevices, parallel, stats, utils
Encoding: UTF-8
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
URL: https://rpubs.com/giancarlo_vercellino/craft
NeedsCompilation: no
Packaged: 2026-08-03 15:26:40 UTC; gianc
Author: Giancarlo Vercellino [aut, cre, cph]
Repository: CRAN
Date/Publication: 2026-08-08 12:50:20 UTC

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New package Compositionalzerocens with initial version 1.0
Package: Compositionalzerocens
Title: Modelling Zero Values in Compositional Data Using a Censored Model
Version: 1.0
Date: 2026-08-03
Author: Michail Tsagris [aut, cre]
Maintainer: Michail Tsagris <mtsagris@uoc.gr>
Depends: R (>= 4.0)
Imports: Compositional, far, Rfast, stats
Suggests: Rfast2
Description: Modelling structural zeros in compositional data assuming a latent Gaussian model, where MLE is performed via the EM algorithm. The relevant paper is Tsagris M. (2026). Modelling structural zeros in compositional data via a zero-censored multivariate normal model. <doi:10.48550/arXiv.2208.13073>.
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2026-08-03 06:08:09 UTC; mtsag
Repository: CRAN
Date/Publication: 2026-08-08 12:30:28 UTC

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New package codriver with initial version 1.0.0
Package: codriver
Title: Context-Aware AI Assistant for 'RStudio'
Version: 1.0.0
Description: A context-aware AI assistant for 'RStudio' that works directly in the source editor without switching context or opening a separate chat window. Reads the cursor position and selection to automatically choose the right action - generate, complete, continue, edit, or comment. Supports configuration of multiple large language model providers and can be invoked via the keyboard shortcut or Addins menu.
URL: https://vdwulp.github.io/codriver/
BugReports: https://github.com/vdwulp/codriver/issues
License: MIT + file LICENSE
Encoding: UTF-8
VignetteBuilder: knitr
SystemRequirements: RStudio (>= 2026.04, https://posit.co/download/rstudio-desktop/)
Depends: R (>= 4.0.0)
Imports: cli, ellmer (>= 0.3.0), jsonlite, rlang, rstudio.prefs (>= 0.1.6), rstudioapi (>= 0.19.0)
Suggests: testthat (>= 3.0.0), glue, knitr, rmarkdown, withr
NeedsCompilation: no
Packaged: 2026-08-03 13:40:03 UTC; wulps
Author: S.A. van der Wulp [aut, cre, cph]
Maintainer: S.A. van der Wulp <vdwulp@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-08 12:20:02 UTC

More information about codriver at CRAN
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New package cochranSize with initial version 0.1.0
Package: cochranSize
Title: Sample Size Calculation Using Cochran's Formula
Version: 0.1.0
Description: Provides functions to calculate the minimum required sample size for surveys and studies using Cochran's formula, including the finite population correction. Cochran's formula is a standard method in survey methodology for determining sample size based on a desired margin of error, confidence level, and (optionally) known population size. All parameters (margin of error, confidence level, and expected proportion) are fully adjustable by the user rather than fixed to any convention.
License: MIT + file LICENSE
URL: https://github.com/yosleycarrero2025/cochranSize
BugReports: https://github.com/yosleycarrero2025/cochranSize/issues
Encoding: UTF-8
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-02 22:35:00 UTC; yosle
Author: Yosley Carrero [aut, cre]
Maintainer: Yosley Carrero <c3046338@newcastle.ac.uk>
Repository: CRAN
Date/Publication: 2026-08-08 12:30:07 UTC

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New package cincinnatiOpenData with initial version 0.1.0
Package: cincinnatiOpenData
Title: A Lightweight Interface to Cincinnati Open Data APIs
Version: 0.1.0
Description: Provides a unified set of helper functions to access datasets from the Cincinnati Open Data platform <https://data.cincinnati-oh.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 Cincinnati 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/gomes-sh/cincinnatiOpenData
BugReports: https://github.com/gomes-sh/cincinnatiOpenData/issues
VignetteBuilder: knitr
Depends: R (>= 4.1.0)
NeedsCompilation: no
Packaged: 2026-08-03 19:06:47 UTC; magic
Author: Shelby Lyn Gomes [aut] , Christian Martinez [aut, cre]
Maintainer: Christian Martinez <c.martinez0@outlook.com>
Repository: CRAN
Date/Publication: 2026-08-08 12:50:06 UTC

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New package chaidr with initial version 0.1.0
Package: chaidr
Title: CHAID and Exhaustive CHAID Decision Trees
Version: 0.1.0
Description: An implementation in base 'R' of the CHAID (Chi-squared Automatic Interaction Detection) decision tree algorithm of Kass (1980) <doi:10.2307/2986296> and the Exhaustive CHAID variant of Biggs, de Ville, and Suen (1991) <doi:10.1080/02664769100000005>, as specified in the 'IBM SPSS' Statistics Algorithms documentation. Supports nominal, ordinal (with floating missing category), and continuous predictors, and nominal, ordinal, and continuous response variables using Pearson chi-squared, Goodman row-effects, and one-way ANOVA F tests respectively. Includes prediction, rule extraction, gains and lift analysis, validation on holdout data, and visualization via base graphics, 'Graphviz' DOT, 'plotly', and conversion to 'partykit' objects.
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-GB
Depends: R (>= 4.5)
Imports: graphics, grDevices, stats, utils
Suggests: DiagrammeR, ggparty, ggplot2, htmlwidgets, knitr, partykit, plotly, rmarkdown, rpart, spelling, testthat (>= 3.2.0), withr
VignetteBuilder: knitr
URL: https://github.com/morimotoosamu/chaidr, https://morimotoosamu.github.io/chaidr/
BugReports: https://github.com/morimotoosamu/chaidr/issues
NeedsCompilation: no
Packaged: 2026-08-03 02:17:22 UTC; morimoto.osamu
Author: Osamu Morimoto [aut, cre, cph]
Maintainer: Osamu Morimoto <galactic.supermarket@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-08 12:30:12 UTC

More information about chaidr at CRAN
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New package causalgenerics with initial version 0.1.0
Package: causalgenerics
Title: Shared Generics for the 'r-causal' Ecosystem
Version: 0.1.0
Description: A home for the S3 generics shared across the 'r-causal' ecosystem, including 'propensity', 'halfmoon', 'positively', and 'balancing'. Owning the generic definitions in one place lets those packages register methods without masking one another when several are attached at once. The generics cover inverse probability weighted estimation, effective sample size, and the metadata carried by causal weight vectors, and the package supplies the abstract causal weight class and the result class those estimates are returned in, together with the methods both classes carry, so that the ecosystem packages inherit them rather than writing their own. The design follows that of the 'generics' package, which provides commonly used S3 generics for the same purpose: letting packages share a single definition instead of each defining its own.
License: MIT + file LICENSE
URL: https://github.com/r-causal/causalgenerics, https://r-causal.github.io/causalgenerics/
BugReports: https://github.com/r-causal/causalgenerics/issues
Depends: R (>= 4.1.0)
Imports: stats, vctrs
Suggests: testthat (>= 3.2.0), withr
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-08-03 14:56:39 UTC; malcolmbarrett
Author: Malcolm Barrett [aut, cre, cph]
Maintainer: Malcolm Barrett <malcolmbarrett@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-08 12:20:07 UTC

More information about causalgenerics at CRAN
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New package BKMutate with initial version 0.1.0
Package: BKMutate
Title: Statistical Analysis of Induced Mutagenesis Experiments in Crop Plants
Version: 0.1.0
Description: A colour-first toolkit for the statistical analysis of induced mutagenesis experiments in crop plants. It fits dose-response models to physical and chemical mutagen data and estimates the median lethal and growth-reduction doses (LD50, GR50) with confidence intervals obtained from Fieller's theorem; quantifies first-generation biological damage (lethality, injury and pollen sterility); and estimates mutagenic effectiveness and mutagenic efficiency. Effectiveness and efficiency are conventionally reported as point estimates only; this package treats them as functions of binomial proportions and supplies interval estimates by the delta method on the logarithmic scale and by the nonparametric bootstrap. It further provides chlorophyll mutation spectrum analysis with tests of homogeneity and diversity, generalised linear models for second-generation mutant counts with formal assessment of overdispersion, and formal comparison of mutagens including relative biological effectiveness. Every a [...truncated...]
License: GPL-3
Encoding: UTF-8
Depends: R (>= 4.0.0)
Imports: stats, utils, grDevices, ggplot2
Suggests: ggrepel, patchwork, knitr, rmarkdown, testthat (>= 3.0.0)
URL: https://github.com/bkpraveenars-del/BKMutate
BugReports: https://github.com/bkpraveenars-del/BKMutate/issues
NeedsCompilation: no
Packaged: 2026-08-03 11:43:45 UTC; ASUS
Author: Praveen Kumar B. K. [aut, cre]
Maintainer: Praveen Kumar B. K. <bkpraveenars@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-08 12:10:07 UTC

More information about BKMutate at CRAN
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New package bigbang with initial version 0.1.0
Package: bigbang
Title: Build 'Tidyverse'-Style Meta-Packages from Local Package Files
Version: 0.1.0
Description: Creates meta-packages (in the style of the 'tidyverse') from locally stored package archives (.tar.gz, .zip). Designed for teams working behind institutional firewalls without access to package repositories. Resolves dependencies between local packages by building a dependency graph with topological ordering and cycle detection, classifies dependencies as local or CRAN, detects implicit dependencies by scanning source code, and generates the full meta-package scaffold including re-exports, vignettes and documentation.
License: GPL (>= 3)
URL: https://github.com/sebollin/bigbang
BugReports: https://github.com/sebollin/bigbang/issues
Encoding: UTF-8
Language: en
VignetteBuilder: knitr
Depends: R (>= 3.6.0)
Imports: brio, glue, utils, whisker
Suggests: devtools, knitr, rmarkdown, testthat (>= 3.0.0), withr
NeedsCompilation: no
Packaged: 2026-08-03 16:20:59 UTC; user
Author: Sebastian Lucas [aut, cre], Richard Detomasi [ctb]
Maintainer: Sebastian Lucas <sebalucas@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-08 12:50:11 UTC

More information about bigbang at CRAN
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New package ascribe with initial version 0.1.1
Package: ascribe
Title: Static Detection and Citation of R Package and Function Usage
Version: 0.1.1
Description: Scans R source files for package and function use, then builds citations from configurable package universes. Supports .R, .Rmd, and .qmd files, resolves unqualified calls by attachment order and re-export origin, and leaves each package collection to define its own citations. See 'stanflow' <https://github.com/VisruthSK/stanflow> for an example usage.
License: MIT + file LICENSE
URL: https://ascribe.visruth.com
BugReports: https://github.com/VisruthSK/ascribe/issues
Depends: R (>= 4.2.0)
Imports: cli, fastmatch
Suggests: knitr, quarto, spelling, testthat (>= 3.0.0), withr
VignetteBuilder: quarto
Encoding: UTF-8
Language: en-US
NeedsCompilation: no
Packaged: 2026-08-02 21:17:17 UTC; visru
Author: Visruth Srimath Kandali [aut, cre, cph]
Maintainer: Visruth Srimath Kandali <public@visruth.com>
Repository: CRAN
Date/Publication: 2026-08-08 12:10:02 UTC

More information about ascribe at CRAN
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New package xegaMigration with initial version 0.5.0.4
Package: xegaMigration
Title: 'Xega' Island Models
Version: 0.5.0.4
Description: Implements asynchronous message-passing communication protocols for island models of extended and evolutionary algorithms (see Tomassini, Marco (2005, ISBN:978-3-540-24193-5)) for the R-package 'xega' <https://CRAN.R-project.org/package=xega>. Basic asynchronous as well as synchronized communication primitives are supplied based on file I/O operations ('rds') on a shared file system or by 'openMPI' (MPI) messages. The gene selection and replacement strategies, the migration policy as well as the communication topology between islands are configurable. Homogeneous and heterogeneous island algorithms are supported. For examples (R and shell-scripts), see <https://github.com/ageyerschulz/xega/tree/main/examples/IslandModels>.
License: MIT + file LICENSE
URL: https://github.com/ageyerschulz/xegaMigration
Encoding: UTF-8
Depends: R (>= 3.5.0)
Imports: xegaSelectGene (>= 1.0.0.4), xegaPopulation
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-07-31 16:16:01 UTC; dj2333
Author: Andreas Geyer-Schulz [aut, cre] , Seyedmostafa Zamanishandiz [aut]
Maintainer: Andreas Geyer-Schulz <Andreas.Geyer-Schulz@kit.edu>
Repository: CRAN
Date/Publication: 2026-08-08 11:30:02 UTC

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New package Usmile with initial version 0.2.0
Package: Usmile
Title: Threshold-Free Class-Specific Comparison of Binary Classifiers
Version: 0.2.0
Description: Implements the U-smile methodology for threshold-free, class-specific comparison of probabilistic binary classifiers. The package quantifies prediction improvement and worsening separately for non-events and events using the Brier alteration (BA), relative Brier (RB), improvement proportion (I) coefficients, and relative likelihood ratio (rLR) coefficients, and provides U-smile, prediction improvement-worsening, receiver operating characteristic, and precision-recall plots. The original U-smile framework is described in Kubiak et al. (2024) <doi:10.1371/journal.pone.0303276>, its three-level extension for imbalanced binary classification in Wieckowska et al. (2025) <doi:10.1371/journal.pone.0321661>, and the likelihood-based extension in Wieckowska and Guzik (2026) <doi:10.1038/s41598-026-40545-z>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
LazyDataCompression: xz
Depends: R (>= 3.5.0)
Imports: ggplot2, grid, pROC,
Suggests: e1071, naivebayes, nnet, parsnip, randomForest, ranger, testthat (>= 3.0.0), xgboost
URL: https://github.com/bbwieckowska/Usmile
BugReports: https://github.com/bbwieckowska/Usmile/issues
NeedsCompilation: no
Packaged: 2026-08-02 10:50:51 UTC; p008587
Author: Barbara Wieckowska [aut, cre]
Maintainer: Barbara Wieckowska <bbwieckowska@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-08 12:00:11 UTC

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New package transferegovr with initial version 0.1.0
Package: transferegovr
Title: Access the 'TransfereGov' Open Data APIs
Version: 0.1.0
Description: Provides a modern interface to the open data application programming interfaces of the Brazilian federal government's 'TransfereGov' platform (<https://www.gov.br/transferegov/pt-br/ferramentas-gestao/dados-abertos>). Covers the special transfers, fund-to-fund transfers, and decentralized credit ('TED') modules, which together publish forty-eight tables on action plans, programs, budget commitments, financial execution, management reports, and payment orders. The APIs are built on 'PostgREST', so the package exposes its filtering, column selection, and ordering operators directly, and returns tidy tibbles with types taken from the published schema. Automatic pagination, request throttling, retries with exponential backoff, and an optional response cache are included.
License: MIT + file LICENSE
URL: https://github.com/StrategicProjects/transferegovr, https://strategicprojects.github.io/transferegovr/
BugReports: https://github.com/StrategicProjects/transferegovr/issues
Depends: R (>= 4.1.0)
Imports: cli, httr2 (>= 1.0.0), purrr (>= 1.0.0), rlang (>= 1.1.0), stats, tibble (>= 3.2.0), utils
Suggests: covr, dplyr, jsonlite, knitr, rmarkdown, testthat (>= 3.2.0), withr
VignetteBuilder: knitr
Encoding: UTF-8
Language: en-US
NeedsCompilation: no
Packaged: 2026-07-31 22:51:57 UTC; leite
Author: Andre Leite [aut, cre] , Marcos Wasiliew [aut], Hugo Vasconcelos [aut] , Carlos Amorim [aut] , Diogo Bezerra [aut] , Julia Nascimento Barreto [aut]
Maintainer: Andre Leite <leite@castlab.org>
Repository: CRAN
Date/Publication: 2026-08-08 11:30:08 UTC

More information about transferegovr at CRAN
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New package tplyr2 with initial version 0.2.0
Package: tplyr2
Title: A Grammar of Clinical Summary Tables
Version: 0.2.0
Description: Implements a grammar of summary data for clinical reports. Clinical summary tables are decomposed into modular layers, each representing an independent summary block. Supports count, descriptive statistics, and shift layer types with a declarative spec-based API built on data.table for performance.
License: MIT + file LICENSE
URL: https://github.com/atorus-research/tplyr2, https://atorus-research.github.io/tplyr2/
BugReports: https://github.com/atorus-research/tplyr2/issues
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: data.table, jsonlite, purrr, rlang, stringr
Suggests: testthat (>= 3.0.0), withr, yaml, knitr, rmarkdown
VignetteBuilder: knitr
LazyData: true
NeedsCompilation: no
Packaged: 2026-08-02 14:12:57 UTC; mstackhouse
Author: Mike Stackhouse [aut, cre]
Maintainer: Mike Stackhouse <mike.stackhouse@atorusresearch.com>
Repository: CRAN
Date/Publication: 2026-08-08 12:00:02 UTC

More information about tplyr2 at CRAN
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New package pathintdid with initial version 0.1.0
Package: pathintdid
Title: Path-Integrated Difference-in-Differences
Version: 0.1.0
Description: Implements the Path-Integrated Difference-in-Differences ('PI-DiD') framework of Salavi (2026), which treats the treatment effect as a trajectory tau(t) = c1(t) - c0(t) and integrates the baseline-differenced gap over a post-treatment window to obtain a cumulative causal effect and a path-integrated average treatment effect on the treated, together with cluster-robust standard errors, confidence intervals, diagnostic plots, and the pre-treatment parallel-trends, grid-density, and anticipation-robustness checks of section 5 of the companion paper. This approach avoids the endpoint-subtraction bias that arises whenever a transitory policy's effect has fully decayed by the evaluation date, in which case the conventional static difference-in-differences estimate can be zero even though the cumulative benefit delivered to treated units was strictly positive. Formerly distributed as a Stata package under the names 'pidid' and 'pididplot'.
License: MIT + file LICENSE
URL: https://github.com/FabriceSALAVI/PathIntDID
BugReports: https://github.com/FabriceSALAVI/PathIntDID/issues
Depends: R (>= 3.5)
Imports: graphics, grDevices, stats
Suggests: testthat (>= 3.0.0)
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2026-08-01 23:28:50 UTC; HP
Author: Comlan Apollinaire-Fabrice Salavi [aut, cre]
Maintainer: Comlan Apollinaire-Fabrice Salavi <fsalavi@africanschoolofeconomics.com>
Repository: CRAN
Date/Publication: 2026-08-08 11:50:02 UTC

More information about pathintdid at CRAN
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New package nof1kit with initial version 0.1.0
Package: nof1kit
Title: Design, Monitor, and Analyze Single-Case (N-of-1) Intensive Longitudinal Studies
Version: 0.1.0
Description: Tools for the stages of a single-case (N-of-1) experimental study that come before analysis: generating randomization schedules that can be preregistered and reproduced exactly, under run-length constraints, exporting them for mobile data collection, validating incoming ecological momentary assessment (EMA) records, and monitoring compliance. Designed around the workflow of a 70-day randomized N-of-1 study collected with stock 'iOS' tools at 92.9% compliance; the package ships with that study's complete dataset.
License: MIT + file LICENSE
URL: https://github.com/haomeng797-ship-it/nof1kit, https://haomeng797-ship-it.github.io/nof1kit/
BugReports: https://github.com/haomeng797-ship-it/nof1kit/issues
Encoding: UTF-8
Imports: jsonlite, stats, tools, utils
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-02 10:36:34 UTC; menghao
Author: Miura Meng [aut, cre]
Maintainer: Miura Meng <haomeng797@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-08 11:50:07 UTC

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New package nimbleExtra with initial version 0.1.15
Package: nimbleExtra
Title: Interoperating with 'NIMBLE' for Generic Analysis of MCMC Samples
Version: 0.1.15
Description: 'NIMBLE' is a general purpose modeling framework that facilitates the analysis of Markov Chain Monte Carlo (MCMC) models. However, it constructs a complex and variable data structure, which is difficult to use in a general way. The 'nimbleExtra' package provides a set of functions to insulate users from the complexity and variability of 'NIMBLE' data structures. It also complements 'NIMBLE' and other MCMC analysis packages by providing missing functionality to encourage generic programming. Together these features ease the burden of working with MCMC data and encourage more systematic approaches to MCMC analysis.
License: BSD_3_clause + file LICENSE | GPL (>= 2)
Encoding: UTF-8
LazyData: true
Imports: coda, dplyr, ggplot2, grDevices, nimble, posterior, purrr, rlang, tidyselect, utils
Suggests: ggmcmc, scales, testthat (>= 3.0.0), tidyr
Depends: R (>= 4.1.0)
NeedsCompilation: no
Packaged: 2026-07-31 19:30:44 UTC; brook
Author: Brook Milligan [aut, cre, cph]
Maintainer: Brook Milligan <brook@biology.nmsu.edu>
Repository: CRAN
Date/Publication: 2026-08-08 11:30:13 UTC

More information about nimbleExtra at CRAN
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New package EDAForge with initial version 0.1.1
Package: EDAForge
Title: Automatic Exploratory Data Analysis
Version: 0.1.1
Description: Automatically performs exploratory data analysis (EDA) for tabular datasets, including data summaries, missing value analysis, descriptive statistics, visualizations, correlation analysis, outlier detection, and automated report generation. The package provides a streamlined workflow for rapid data exploration and produces publication-ready tables and graphics. For methodological details see Tukey (1977, ISBN:9780201076165), Pearson (1895) <doi:10.1098/rspl.1895.0041>, and Wickham (2014) <doi:10.18637/jss.v059.i10>.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.2)
Imports: e1071, rlang, dplyr, ggplot2, tidyr, psych, factoextra, openxlsx, GGally, visdat, igraph
Suggests: knitr,mice, rmarkdown, testthat (>= 3.0.0), tibble
URL: https://github.com/vinodhpmd/EDAForge
BugReports: https://github.com/vinodhpmd/EDAForge/issues
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-01 00:38:33 UTC; m
Author: Vinodhkumar Obli Rajendran [aut, cre], Keerthi Aaradhana [aut]
Maintainer: Vinodhkumar Obli Rajendran <vinodhkumar.rajendran@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-08 11:30:20 UTC

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New package dashboardapi with initial version 0.1.0
Package: dashboardapi
Title: Access Japan's Statistics Dashboard API
Version: 0.1.0
Description: An unofficial, tidy, rate-conscious interface to the Statistics Dashboard Web API provided by the Statistics Bureau of Japan. Search indicators, regions, terms, social events, and statistical surveys, then retrieve observations as normalized long or wide data frames. The API requires no registration or API key.
URL: https://github.com/kenjimyzk/dashboardapi
BugReports: https://github.com/kenjimyzk/dashboardapi/issues
License: MIT + file LICENSE
Depends: R (>= 4.1.0)
Imports: httr2 (>= 1.1.0), tibble
Suggests: knitr, rmarkdown, testthat (>= 3.2.0)
VignetteBuilder: knitr
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-07-31 14:37:16 UTC; kenjimyzk
Author: Kenji Miyazaki [aut, cre]
Maintainer: Kenji Miyazaki <kenjimyzk@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-08 11:10:02 UTC

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New package cpge with initial version 1.0.1
Package: cpge
Title: Career Possibilities after French Selective Engineering Schools in France
Version: 1.0.1
Description: To help French students from Classes Preparatoires aux Grandes Ecoles (CPGE) in their choice of field of study and career options, this package provides an interactive tool and data visualization of a graph clustered by different competitive exams and sectors of activity for French selective engineering schools and selective higher education institutions like Ecoles Normales Superieures (ENS) or specialized university programs. Besides, there are two drop-down menus to select on the graph many fields or more than 200 engineering schools or ENS. It gives the opportunity to expand, collapse clusters of selective exams interactively too. For more information, see the demonstration video: <https://valerierobert-maths.re/index.php/maths-en-cpge/>. The data was collected via the official French website: <https://www.scei-concours.fr/statistiques.html>.
License: GPL (>= 3)
Encoding: UTF-8
Depends: R (>= 3.5)
Imports: dplyr, quarto, shiny, stringr, tidyr, visNetwork
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-07-31 18:36:49 UTC; rv
Author: Valerie Robert [aut, cre]
Maintainer: Valerie Robert <valerie.robert.math@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-08 11:20:02 UTC

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New package compstatslib with initial version 0.8.0
Package: compstatslib
Title: Interactive 2D and 3D Visualization of Data and Statistical Concepts
Version: 0.8.0
Date: 2026-08-02
Description: Interactive gadgets and plotting functions for visualizing data sets and statistical concepts in two and three dimensions. Explore a data frame as a 3D point cloud you can rotate, fit a moderated (interaction) regression and view its surface as a 3D wireframe, or plot principal components and regression fits in two dimensions. Each interactive gadget returns the call that reproduces its final view, including the viewing angle, so an exploratory session can be pasted into a script or report. Also provides simulation-based demonstrations of sampling distributions, confidence intervals, t-tests, and matrix inversion for teaching and self-study.
Imports: lattice, miniUI, plotly, shiny
Depends: R (>= 4.1.0)
License: MIT + file LICENSE
URL: https://github.com/compstatslib/compstatslib
BugReports: https://github.com/compstatslib/compstatslib/issues
Encoding: UTF-8
Language: en-US
Suggests: testthat (>= 3.0.0)
LazyData: true
NeedsCompilation: no
Packaged: 2026-08-01 16:51:45 UTC; soumyaray
Author: Soumya Ray [aut, cre], Daniele Melotti [aut]
Maintainer: Soumya Ray <soumya.ray@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-08 11:50:13 UTC

More information about compstatslib at CRAN
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New package ALSBinary with initial version 1.0.0
Package: ALSBinary
Title: 'ALS-Binary': Allele Size to Binary Converter
Version: 1.0.0
Description: Converts microsatellite allele sizes into binary matrices and provides a 'Shiny' interface.
Depends: R (>= 4.3.0)
Imports: shiny, readr, readxl, DT
Suggests: testthat (>= 3.0.0)
License: GPL-3
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-08-01 11:28:07 UTC; vppra
Author: Prasanth VP [aut, cre], Subhash Chandra [aut]
Maintainer: Prasanth VP <prasanth.stat@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-08 11:40:02 UTC

More information about ALSBinary at CRAN
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New package AgriDataTools with initial version 0.1.2
Package: AgriDataTools
Title: Automated Statistical Analysis and Tools for Agricultural Research
Version: 0.1.2
Description: A comprehensive suite of statistical tools tailored for agricultural and plant breeding research. Provides automated pipelines for analysis of variance and covariance under randomized complete block designs and completely randomized designs, descriptive summary statistics, and post-hoc multiple range tests including Least Significant Difference, Tukey, and Scheffe based on Steel et al. (1997) <isbn:978-0070610286>. Quantitative genetic parameters including genotypic, phenotypic, and environmental variance components and broad-sense heritability follow Burton and Devane (1953) <doi:10.2134/agronj1953.00021962004500100005x>. Genetic advance and genetic advance as percentage of mean estimation follow Johnson et al. (1955) <doi:10.2134/agronj1955.00021962004700070009x>. Genotypic, phenotypic, and environmental correlations follow Miller et al. (1958) <doi:10.2134/agronj1958.00021962005000100020x>. Genotypic and phenotypic path coefficient analysis direct and indirec [...truncated...]
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Depends: R (>= 4.0.0)
Imports: ggplot2, reshape2, factoextra, dendextend, circlize, stats, graphics, dplyr, utils
VignetteBuilder: knitr
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-08-01 08:55:04 UTC; Faheem khan
Author: Faheem Khan [aut, cre]
Maintainer: Faheem Khan <2022ag94@uaf.edu.pk>
Repository: CRAN
Date/Publication: 2026-08-08 11:20:06 UTC

More information about AgriDataTools at CRAN
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New package agridatasets with initial version 0.1.0
Package: agridatasets
Title: A Comprehensive Collection of Agricultural and Agronomic Datasets
Version: 0.1.0
Maintainer: Renzo Caceres Rossi <arenzocaceresrossi@gmail.com>
Description: Offers a rich and diverse collection of datasets focused on agriculture, agronomy, animal science, and related fields. The package includes experimental, observational, and field-trial data on crops such as rice, wheat, corn, soybean, cotton, coffee, avocado, and orange, as well as forestry species including bamboo, eucalyptus, and timber. Datasets cover plant breeding and genetics, factorial and randomized block experiments, herbicide and insecticide efficacy trials, pest and disease infestation, soil characteristics and land suitability, plant growth regulators, seed germination, and crop yield modeling. Additional datasets address animal science topics such as cattle insemination and conception, pig and broiler growth, lamb births, and toxicology studies on aquatic and non-target species. Data sources include peer-reviewed agronomic studies, uniformity and Latin square field trials, glasshouse experiments, and international agricultural surveys. Designed for agronomists, researchers [...truncated...]
License: GPL-3
Language: en
URL: https://github.com/lightbluetitan/agridatasets, https://lightbluetitan.github.io/agridatasets/
BugReports: https://github.com/lightbluetitan/agridatasets/issues
Encoding: UTF-8
LazyData: true
Suggests: ggplot2, testthat (>= 3.0.0), dplyr, knitr, rmarkdown
Depends: R (>= 4.1.0)
Imports: utils
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-03 03:53:27 UTC; Renzo
Author: Renzo Caceres Rossi [aut, cre]
Repository: CRAN
Date/Publication: 2026-08-08 11:50:18 UTC

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New package tarpolyglot with initial version 0.2.0
Package: tarpolyglot
Title: Run Python, Julia, and Rust Inside 'targets' Pipeline Steps
Version: 0.2.0
Description: Adds target constructors that make it easy to use Python, Julia, and Rust inside a 'targets' pipeline using 'reticulate', 'JuliaCall', and 'rextendr'. Provides tar_target_py(), tar_target_jl(), and tar_target_rs() (with matching _raw() variants), each mirroring 'targets::tar_target()' and 'targets::tar_target_raw()'. Python and Julia steps run a script via a live interpreter with optional R pre- and post-scripts; Rust steps compile '#[extendr]' functions and call them from an R post-script. Results are returned either as converted R objects or as files written to disk (format = "file"). Dynamic branching, environment/version selection, a 'crew' controller for isolation, and the full set of tar_target_raw() arguments are supported.
License: MIT + file LICENSE
URL: https://github.com/Pierre9344/tarpolyglot, https://pierre9344.github.io/tarpolyglot/
BugReports: https://github.com/Pierre9344/tarpolyglot/issues
Encoding: UTF-8
Imports: targets, reticulate, JuliaCall, crew, rextendr
Suggests: knitr, rmarkdown, tarchetypes, testthat (>= 3.0.0), withr
VignetteBuilder: knitr
SystemRequirements: The external language toolchains are optional and each is only required by its matching targets constructor: a Python installation for tar_target_py(), a Julia installation for tar_target_jl(), and a Rust toolchain with Cargo for tar_target_rs() (on Windows, the GNU toolchain, to match R's ABI). A pipeline that uses a single language needs only that language's toolchain, and a pipeline that uses none of these constructors needs no external toolchain at all.
NeedsCompilation: no
Packaged: 2026-07-31 12:45:18 UTC; pierre
Author: Pierre Solomon [aut, cre]
Maintainer: Pierre Solomon <pierre.solomon@laposte.net>
Repository: CRAN
Date/Publication: 2026-08-08 10:50:02 UTC

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New package BCGcalc with initial version 2.3.1
Package: BCGcalc
Title: Biological Condition Gradient, Calculator
Version: 2.3.1
Maintainer: Erik W. Leppo <Erik.Leppo@tetratech.com>
Description: Functions to calculate Biological Condition Gradient (BCG) using input files with one row per sample with metric values and site classes as columns. A second file with the BCG Rules (example included) to define the memberships is also needed. The three main functions convert metric scores to metric memberships following fuzzy set BCG Rules (BCG.Level.Assignment), combine metric memberships to level memberships according to BCG Rules (BCG.Level.Membership), and then assign a BCG primary and secondary level based on level memberships (BCG.Level.Assignment). Originally developed as a package for use with BCG for Puget Lowland/Willamette Valley but has been further enhanced for use with multiple communities (benthic macroinvertebrates, fish, periphyton, or coral) and different rule sets. Oregon and Washington reference - "Stamp, J. and J. Gerritsen. 2018. Calibration of the Biological Condition Gradient (BCG) for Macroinvertebrate Assemblages in Puget Lowland/Willamette Valley Freshwate [...truncated...]
License: MIT + file LICENSE
Depends: R (>= 3.5.0)
Imports: dplyr, reshape2
Suggests: BioMonTools, readxl, knitr, rmarkdown, ggplot2, shiny, DT, httr, testthat (>= 3.0.0), plyr, tidyr, tibble, rioja, nhdplusTools, ComplexUpset
Encoding: UTF-8
LazyData: true
URL: https://github.com/leppott/BCGcalc
BugReports: https://github.com/leppott/BCGcalc/issues
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-07-31 15:18:06 UTC; Erik.Leppo
Author: Erik W. Leppo [aut, cre], Jen Stamp [ctb], Matt Hedin [ctb], Ben Block [ctb]
Repository: CRAN
Date/Publication: 2026-08-08 10:30:02 UTC

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New package erglm with initial version 0.1.1
Package: erglm
Title: Exposure-Response Tools for GLM-Based Models
Version: 0.1.1
Description: Provides estimation tools for exposure-response models based on glm(): model fitting and prediction, stepwise covariate modelling, and simulation-based visual predictive checks. Tested and supported for binomial, Poisson, Gaussian, and gamma families. For a model-agnostic mini-language to visualise exposure-response models (including those fitted with 'erglm'), see the companion package 'erplots'.
License: MIT + file LICENSE
Language: en-GB
Encoding: UTF-8
Imports: dplyr, mvtnorm, rlang, stats, tibble, withr
Suggests: erplots, ggplot2, knitr, rmarkdown, testthat (>= 3.0.0)
URL: https://github.com/djnavarro/erglm, https://erglm.djnavarro.net/
BugReports: https://github.com/djnavarro/erglm/issues
Additional_repositories: https://djnavarro.r-universe.dev
Depends: R (>= 4.1.0)
LazyData: true
NeedsCompilation: no
Packaged: 2026-07-30 15:18:22 UTC; danielle
Author: Danielle Navarro [aut, cre]
Maintainer: Danielle Navarro <djnavarro@protonmail.com>
Repository: CRAN
Date/Publication: 2026-08-08 09:00:02 UTC

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