Sat, 04 Jul 2026

New package WMFM with initial version 1.0.4
Package: WMFM
Title: Explore Fitted Linear and Generalised Linear Models with 'shiny'
Version: 1.0.4
Description: Provides a 'shiny' application that helps learners connect regression tables to fitted generalised linear models. Users construct models via drag-and-drop controls, obtain fitted equations and plain-language explanations generated by a large language model, and can view plots of the fitted model in settings with a single continuous covariate.
License: GPL (>= 3)
Encoding: UTF-8
URL: https://github.com/jmcurran/WMFM
BugReports: https://github.com/jmcurran/WMFM/issues
Depends: R (>= 4.1.0)
Imports: bslib, ellmer, ggplot2, ggrepel, glue, grDevices, htmltools, jsonlite, patchwork, rlang, s20x, sandwich, scales, shiny, sodium, sortable, tibble, utils, yaml
Suggests: clipr, devtools, rstudioapi, testthat (>= 3.0.0), withr
NeedsCompilation: no
Packaged: 2026-06-21 21:50:38 UTC; james
Author: James Curran [aut, cre]
Maintainer: James Curran <j.curran@auckland.ac.nz>
Repository: CRAN
Date/Publication: 2026-07-04 08:10:06 UTC

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New package tinytrail with initial version 0.1.0
Package: tinytrail
Title: Lightweight Auto-Updating Project Tracker and Data Dictionary
Version: 0.1.0
Description: Once initialized, the package leaves a 'tiny trail' of human- and AI-readable text that makes it effortless to keep track of small to medium-sized projects. The package is lightweight (hence 'tiny') and maintains a YAML trail file recording which scripts produced which output files. Call tinytrail() once at the top of each script to record metadata, wrap any save call with tinytrail_write() to log the output path, and optionally use tinytrail_dict() to capture a data dictionary for each input data frame.
License: MIT + file LICENSE
Depends: R (>= 4.1.0)
Imports: yaml
Encoding: UTF-8
Language: en-US
URL: https://github.com/tinytrail-r/tinytrail, https://tinytrail-r.github.io/tinytrail/
BugReports: https://github.com/tinytrail-r/tinytrail/issues
Suggests: arrow, data.table, ggplot2, haven, jsonlite, kableExtra, knitr, openxlsx, purrr, readr, rmarkdown, rstudioapi, testthat (>= 3.0.0), tinytable, withr, writexl
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-06-30 06:26:03 UTC; tomas
Author: Tomas Reivinger [aut, cre, cph]
Maintainer: Tomas Reivinger <tomas.reivinger@gmail.com>
Repository: CRAN
Date/Publication: 2026-07-04 08:40:02 UTC

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New package thamesblock with initial version 0.1.0
Package: thamesblock
Title: Truncated Harmonic Mean Estimator of the Marginal Likelihood for Block Models
Version: 0.1.0
Description: Implements the truncated harmonic mean estimator (THAMES) and other estimators of the reciprocal marginal likelihood for block models. This is done via reciprocal importance sampling, using posterior samples and unnormalized log posterior values. For further information see Metodiev, Perrot-Dockès, Fouetilou, Latouche & Raftery (2026).
License: GPL (>= 3)
Encoding: UTF-8
Imports: mclust, stats, combinat, withr, Matrix, label.switching
NeedsCompilation: no
Packaged: 2026-06-29 11:51:06 UTC; metodiev
Author: Martin Metodiev [aut, cre, cph]
Maintainer: Martin Metodiev <m.metodiev@tutanota.com>
Repository: CRAN
Date/Publication: 2026-07-04 08:40:08 UTC

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New package rCTOOL with initial version 3.1.0
Package: rCTOOL
Title: Soil Organic Carbon Turnover Modelling with 'C-TOOL'
Version: 3.1.0
Description: Provides an 'R' interface to the 'C-TOOL' soil carbon turnover model for simulating soil organic carbon dynamics in agricultural systems. The package supports the definition of carbon inputs, management schedules, soil parameters, and temperature forcing, and includes tools for scenario analysis and calibration of selected model parameters against observed soil organic carbon stocks. The 'C-TOOL' model and related modelling framework are described by Petersen et al. (2002) <doi:10.1016/S0304-3800(02)00034-0>, Petersen et al. (2005) <doi:10.1016/j.soilbio.2004.08.006>, Petersen et al. (2013) <doi:10.1016/j.jclepro.2013.03.007>, and Taghizadeh-Toosi et al. (2014) <doi:10.1016/j.ecolmodel.2014.08.016>. Further applications and developments are described by Taghizadeh-Toosi et al. (2016) <doi:10.1016/j.agsy.2016.03.004>, Keel et al. (2017) <doi:10.1111/ejss.12454>, Taghizadeh-Toosi et al. (2020) <doi:10.1007/s11104-020-04500-9>, and Taghizadeh-Toos [...truncated...]
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.5.0)
Imports: data.table, utils
Suggests: dplyr, ggplot2, knitr, rmarkdown, reshape2, testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-06-30 06:59:36 UTC; au801188
Author: Evandro H. Figueiredo Moura da Silva [aut], Joao Serra [aut], Franca Giannini-Kurina [aut, cre]
Maintainer: Franca Giannini-Kurina <francagk@agro.au.dk>
Repository: CRAN
Date/Publication: 2026-07-04 08:50:02 UTC

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New package outliersHD with initial version 1.0
Package: outliersHD
Title: Detection of Outliers in High Dimensional Data
Version: 1.0
Date: 2026-06-29
Author: Michail Tsagris [aut, cre]
Maintainer: Michail Tsagris <mtsagris@uoc.gr>
Depends: R (>= 4.0)
Imports: Rfast, Rfast2, Rnanoflann, stats
Description: Algorithms to detect high-dimensional outliers. The minimum diagonal product of Ro, Zou, Wang and Yin (2015) <doi:10.1093/biomet/asv021>, the algorithm of Wilkinson (2018) <doi:10.1109/TVCG.2017.2744685>, and the distances of distances of Lee and Jeon (2025) <doi:10.48550/arXiv.2511.02199>.
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2026-06-29 07:05:41 UTC; mtsag
Repository: CRAN
Date/Publication: 2026-07-04 08:10:02 UTC

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New package kernda with initial version 1.0
Package: kernda
Title: Kernel Discriminant Analysis
Version: 1.0
Date: 2026-06-29
Author: Michail Tsagris [aut, cre], Nikolaos Kontemeniotis [aut]
Maintainer: Michail Tsagris <mtsagris@uoc.gr>
Depends: R (>= 4.0)
Imports: Compositional, Rfast, Rcpp, kernreg
LinkingTo: Rcpp
Description: Functions to perform discriminant analysis using kernel density estimation. For the case of binary classification the package relies on the Nadaraya-Watson estimator. References: Wand M.P. and Jones M.C. (1995). "Kernel smoothing". CRC Press. <ISBN: 0412552701>.
License: GPL (>= 2)
NeedsCompilation: yes
Packaged: 2026-06-29 11:40:13 UTC; mtsag
Repository: CRAN
Date/Publication: 2026-07-04 08:40:13 UTC

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New package IBGS with initial version 1.0.0
Package: IBGS
Title: Iterated Block Gibbs Sampler for Ultrahigh-Dimensional Variable Selection and Model Averaging
Version: 1.0.0
Description: Variable selection for generalized linear models and the Cox proportional-hazards model in ultrahigh dimensions via the iterated block Gibbs sampler (IBGS). The sampler is implemented in C with parallel block screening through 'OpenMP', and supports the gaussian, binomial and poisson families (fitted by least squares or iteratively reweighted least squares) as well as the Cox model for survival analysis (fitted by its Efron partial likelihood), together with the AIC, BIC, AICc and extended BIC model selection criteria.
License: GPL-3
Encoding: UTF-8
Depends: R (>= 3.5.0)
Imports: graphics, stats
NeedsCompilation: yes
Packaged: 2026-06-29 10:07:42 UTC; lizhongc
Author: Lizhong Chen [aut, cre]
Maintainer: Lizhong Chen <chen.l@wehi.edu.au>
Repository: CRAN
Date/Publication: 2026-07-04 08:30:06 UTC

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New package abcpp with initial version 1.0.0
Package: abcpp
Title: Shared C++ Backend for Approximate Bayesian Computation
Version: 1.0.0
Author: Mengzhen Hu [aut, cre], Katalin Csillery [ctb, cph], Louisiane Lemaire [ctb, cph], Olivier Francois [ctb, cph], Michael Blum [ctb, cph]
Maintainer: Mengzhen Hu <hmz1969a@gmail.com>
Description: Provides a compact C++ backend for Approximate Bayesian Computation (ABC) with a thin R frontend. The current implementation is primarily a C++ reimplementation of offline ABC workflows provided by the R 'abc' package <doi:10.32614/CRAN.package.abc>, with the public R interface intentionally kept small and centered on abc() and summary() methods. The computational work is performed by shared C++ code. In addition to reproducing common 'abc' workflows, the package adds optional dimensionality reduction of summary statistics through Principal Component Analysis (PCA) and Partial Least Squares (PLS), following related ideas described by Bazin et al. (2010) <doi:10.1534/genetics.109.112391> and Wegmann et al. (2009) <doi:10.1534/genetics.109.102509>.
License: GPL-3
URL: https://github.com/yuki-961004/abcpp
BugReports: https://github.com/yuki-961004/abcpp/issues
Encoding: UTF-8
ByteCompile: true
Depends: R (>= 4.1.0)
Imports: Rcpp
LinkingTo: Rcpp
SystemRequirements: C++17
Suggests: abc, testthat
NeedsCompilation: yes
Packaged: 2026-06-29 09:24:21 UTC; hmz19
Repository: CRAN
Date/Publication: 2026-07-04 08:30:02 UTC

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New package vrpr with initial version 0.1.0
Package: vrpr
Title: Vehicle Routing Problem Solver Built on 'PyVRP'
Version: 0.1.0
Description: A 'tidyverse'-style interface to high-performance vehicle routing problem (VRP) solving. Vendors the C++ core of the 'PyVRP' solver (<https://github.com/PyVRP/PyVRP>) and rewires it through 'cpp11', with no 'Python' runtime dependency. Supports the capacitated VRP, time windows, multiple depots, heterogeneous fleets, prize-collecting and multi-trip variants, driven by an iterated local search metaheuristic.
License: MIT + file LICENSE
URL: https://github.com/StrategicProjects/vrpr, https://strategicprojects.github.io/vrpr/
BugReports: https://github.com/StrategicProjects/vrpr/issues
Encoding: UTF-8
Depends: R (>= 4.3)
Imports: cli, rlang, stats, tibble, vctrs
LinkingTo: cpp11
Suggests: ggplot2, knitr, reticulate, rmarkdown, testthat (>= 3.0.0), withr
VignetteBuilder: knitr
SystemRequirements: C++20, GNU make
NeedsCompilation: yes
Packaged: 2026-06-28 13:14:25 UTC; leite
Author: Andre Leite [aut, cre], Marcos Wasilew [aut], Hugo Vasconcelos [aut], Carlos Amorin [aut], Diogo Bezerra [aut], Niels Wouda [ctb, cph] , Thibaut Vidal [cph] , ORTEC [cph]
Maintainer: Andre Leite <leite@castlab.org>
Repository: CRAN
Date/Publication: 2026-07-04 07:10:02 UTC

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New package tripaccess with initial version 0.1.0
Package: tripaccess
Title: American Travel Behavior and Access Datasets
Version: 0.1.0
Description: Subsets of data from the National Household Travel Survey 2017. It includes personal trips, mobility, demographic, and household information. It is suitable for data visualization, data wrangling, joining datasets, exploratory data analysis, group comparisons, simple linear regression, categorical data analysis, and data ethics discussion in data science and statistics classes.
License: CC0 | file LICENSE
Encoding: UTF-8
URL: https://github.com/scao53/tripaccess
BugReports: https://github.com/scao53/tripaccess/issues
Depends: R (>= 4.1.0)
LazyData: true
LazyDataCompression: xz
Suggests: knitr, rmarkdown, testthat (>= 3.0.0), tidyverse, tidytree, dplyr
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-06-28 11:58:25 UTC; scao
Author: Shiya Cao [aut, cre], Amber Zhang [ctb], Anna Zhao [ctb], Smith College [cph]
Maintainer: Shiya Cao <scao53@smith.edu>
Repository: CRAN
Date/Publication: 2026-07-04 07:10:08 UTC

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New package NPBBBdesigns with initial version 1.0.0
Package: NPBBBdesigns
Title: Construction and a-Efficiency of Nested Partially Balanced Bipartite Block Designs
Version: 1.0.0
Maintainer: Vinayaka <vinayaka.b3vs@gmail.com>
Description: Construction and evaluation of nested partially balanced bipartite block (NPBBB) designs for comparing a set of test treatments with a set of control treatments under a nested (blocks within blocks) structure. Six systematic construction methods are provided: composing partially balanced bipartite block designs with nested balanced incomplete block designs; augmenting nested partially balanced incomplete block designs with controls; merging rows of group-divisible nested designs; direct construction from group-divisible schemes; and expansion of partially balanced incomplete block designs (Vinayaka et al. 2026: In press). The A-efficiencies of the block and sub-block classifications are computed against the A-optimal completely symmetric reference design, following the test-versus-control optimality framework of Gupta and Parsad (1996) <doi:10.1080/03610929608831743> and Vinayaka et al. (2024) <doi:10.1080/03610926.2023.2251623>. These designs are particularly suited to agr [...truncated...]
License: GPL-3
Encoding: UTF-8
Depends: R (>= 3.5.0)
NeedsCompilation: no
Packaged: 2026-06-28 19:46:19 UTC; DELL
Author: Vinayaka [aut, cre] , Rajender Parsad [aut, ctb], B.N. Mandal [aut, ctb], L.N. Vinaykumar [aut, ctb], Gopalareddy Krishnappa [aut, ctb]
Repository: CRAN
Date/Publication: 2026-07-04 07:30:02 UTC

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New package Linda with initial version 1.3
Package: Linda
Title: Line Transect-Based Nearest Neighbor Distance Analysis
Version: 1.3
Date: 2026-06-28
Description: Conducting Line transect-based one-dimensional nearest neighbor distance and conducting hypothesis testing related to local distributional aggregation pattern of species. The reason that such a package is needed is because traditional two-dimensional nearest neighbor distance is not applicable when biodiversity data are sampled via optimal ecological survey methods, like line transects. In comparison to the entire studied region, line transect-collected local biodiversity data are spatially constrained and sampling-limited. To this end, two-dimensional nearest neighbor distance would tend to over-estimate distributional aggregation pattern of species when using this limited biodiversity information. Accordingly, one-dimensional nearest neighbor distance is needed and the associated statistical testing should be established for analyzing line transect-derived biodiversity data.
Maintainer: Youhua Chen <chenyh@cib.ac.cn>
License: GPL-3
Imports: doParallel, foreach,iterators,parallel,stats
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-06-28 15:14:27 UTC; lloony
Author: Youhua Chen [aut, cre], Tsung-Jen Shen [aut], Xiaoqin Shi [ctb]
Repository: CRAN
Date/Publication: 2026-07-04 07:20:02 UTC

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New package gpbiometrics with initial version 0.1.0
Package: gpbiometrics
Title: Process and Report Gazepoint Biometrics Data
Version: 0.1.0
Description: Imports, validates, quality-checks, preprocesses, summarises, synchronises, models, plots, and reports Gazepoint Biometrics exports. The package focuses on Gazepoint-specific biometric channels such as GSR/EDA, heart rate, interbeat intervals, pulse signals, engagement dial, TTL markers, and synchronisation fields that can be combined with Gazepoint GP3 and GP3 HD eye-tracking workflows.
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-US
VignetteBuilder: knitr
Suggests: ggplot2, knitr, reticulate, rmarkdown, shiny, testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-06-28 01:00:37 UTC; Stefanos-PC
Author: Stefanos Balaskas [aut, cre]
Maintainer: Stefanos Balaskas <s.balaskas@ac.upatras.gr>
Repository: CRAN
Date/Publication: 2026-07-04 07:10:15 UTC

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New package ggChinaFlag with initial version 0.2.0
Package: ggChinaFlag
Title: Drawing Chinese National and Historical Flags with 'ggplot2'
Version: 0.2.0
Description: Provides programmatic implementations for drawing Chinese national and historical flags using analytic geometry and 'ggplot2'-based vector graphics. Flag designs are constructed entirely from geometric primitives such as polygons and rectangles, without relying on external image files. The package is intended for educational demonstration, reproducible visualization, and procedural graphics in R.
License: GPL-3
Encoding: UTF-8
Imports: ggplot2, dplyr, showtext, ggforce
URL: https://github.com/XLions/ggChinaFlag
BugReports: https://github.com/XLions/ggChinaFlag/issues
NeedsCompilation: no
Packaged: 2026-06-28 13:25:23 UTC; lzs19
Author: Zhaoshuo Liu [aut, cre]
Maintainer: Zhaoshuo Liu <liuzhaoshuo1997@outlook.com>
Repository: CRAN
Date/Publication: 2026-07-04 07:10:28 UTC

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New package BJM with initial version 0.1.0
Package: BJM
Title: Backward Joint Model for the Dynamic Prediction of Both Time-to-Event and Longitudinal Outcomes
Version: 0.1.0
Maintainer: Wenhao Li <wenhaoli.jlu@gmail.com>
Description: Provides tools to fit joint models of multivariate longitudinal data and time-to-event data for dynamic prediction. It allows the joint prediction of both future time-to-event outcomes and future longitudinal outcomes conditional on survival. The models accommodate irregularly measured longitudinal data and competing risks outcomes. The use of the backward joint model enables fast and efficient computation, especially for applications with large sample sizes and many longitudinal variables.
License: MIT + file LICENSE
LazyData: true
Encoding: UTF-8
Depends: R (>= 3.5.0), survival
Imports: nlme, mvtnorm, ggplot2, Matrix
Author: Wenhao Li [aut, cre], Liang Li [aut]
Repository: CRAN
Date/Publication: 2026-07-04 07:50:02 UTC
NeedsCompilation: no
Packaged: 2026-06-28 23:49:55 UTC; wenhaoli

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New package attestix with initial version 0.4.1
Package: attestix
Title: Offline Verifier for Attestix Ed25519 Credentials and UCAN Delegations
Version: 0.4.1
Description: An offline verifier for verifiable credentials and delegation chains issued by the Attestix Python core. Verifies Ed25519 (RFC 8032) signatures over W3C Verifiable Credentials, decodes Ed25519 'did:key' identifiers, and verifies UCAN delegation chains (EdDSA 'JWT's) including capability attenuation, with no Python runtime required. Reproduces the Attestix JCS-style JSON canonical form (a practical subset of RFC 8785 that additionally applies 'NFC' Unicode normalization) byte-for-byte so that signatures produced by the reference implementation verify here. Useful for compliance, research and biostatistics users who work in R and need to check AI-agent compliance credentials. See <https://attestix.io> for the project and <https://attestix.io/spec/bundle/v1> for the bundle wire format.
License: Apache License (>= 2)
URL: https://github.com/VibeTensor/attestix-r, https://attestix.io
BugReports: https://github.com/VibeTensor/attestix-r/issues
Encoding: UTF-8
Depends: R (>= 4.0.0)
Imports: sodium, openssl, stringi
Suggests: jsonlite, testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-06-26 15:36:15 UTC; runner
Author: Pavan Kumar Dubasi [aut, cre], VibeTensor [cph, fnd]
Maintainer: Pavan Kumar Dubasi <info@vibetensor.com>
Repository: CRAN
Date/Publication: 2026-07-04 07:00:02 UTC

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Fri, 03 Jul 2026

New package panelbuild with initial version 0.1.0
Description: Provides tools for auditing, validating, and preparing panel datasets before statistical analysis. Functions identify duplicate unit-time observations, missing unit-time cells, panel gaps, and balance issues. The package also provides audit summaries, row-level diagnostic flags, panel-completion utilities, and a concise audit report.
Package: panelbuild
Title: Panel Data Auditing, Validation, and Preparation Tools
Version: 0.1.0
License: MIT + file LICENSE
Encoding: UTF-8
Imports: dplyr, tidyr, tibble, rlang
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
URL: https://desirajulavanya.github.io/panelbuild/, https://github.com/desirajulavanya/panelbuild
BugReports: https://github.com/desirajulavanya/panelbuild/issues
Depends: R (>= 4.1.0)
LazyData: true
NeedsCompilation: no
Packaged: 2026-06-28 00:24:29 UTC; nagal
Author: Lavanya Desiraju [aut, cre]
Maintainer: Lavanya Desiraju <desirajulavanya@gmail.com>
Repository: CRAN
Date/Publication: 2026-07-03 13:00:02 UTC

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New package crawlee with initial version 0.1.0
Package: crawlee
Title: Tidy Interface for Reproducible Web Crawling
Version: 0.1.0
Description: A tidy, pipe-friendly toolkit for reproducible web crawling and structured data collection, inspired by the architecture of the 'Crawlee' library. Provides a unified crawler with a deduplicating, resumable request queue, content-type aware handlers, structured storage backends and rich console logging via 'cli'. Supports crawling HTML pages, sitemaps, RSS and Atom feeds and PDF documents, with optional headless-browser rendering and helpers for retrieval-augmented generation.
License: MIT + file LICENSE
URL: https://github.com/StrategicProjects/crawlee, https://strategicprojects.github.io/crawlee/
BugReports: https://github.com/StrategicProjects/crawlee/issues
Depends: R (>= 4.1.0)
Imports: cli, httr2, R6, rlang, rvest, tibble, vctrs, xml2
Suggests: arrow, chromote, DBI, dplyr, duckdb, httptest2, jsonlite, knitr, later, nanoparquet, pdftools, polite, promises, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
Encoding: UTF-8
Language: en-US
NeedsCompilation: no
Packaged: 2026-06-27 19:45:27 UTC; leite
Author: Andre Leite [aut, cre], Marcos Wasilew [aut], Hugo Vasconcelos [aut], Carlos Amorin [aut], Diogo Bezerra [aut]
Maintainer: Andre Leite <leite@castlab.org>
Repository: CRAN
Date/Publication: 2026-07-03 12:10:02 UTC

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New package canpumf with initial version 0.5.2
Package: canpumf
Title: Parse StatCan PUMF Files
Version: 0.5.2
Description: Facilitate working with Statistics Canada (StatCan) Public Use Microdata Files (PUMF). Enables downloading of available PUMF data, parsing of metadata from command files or other sources to infer the layout structure, variable labels and value labels as well as missing data values, and returns a connection to a 'DuckDB' database with the labelled data. Data and documentation come from Statistics Canada's Public Use Microdata Files <https://www.statcan.gc.ca/en/microdata/pumf>, distributed under the Statistics Canada Open Licence <https://www.statcan.gc.ca/en/terms-conditions/open-licence>.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.2)
Imports: dplyr (>= 1.1.0), readr, stringr, rlang, utils, tibble, rvest, httr, purrr, DBI, duckdb (>= 1.5.2), duckplyr (>= 1.2.1), dbplyr, haven (>= 2.5.0), zip
Suggests: rmarkdown, knitr, scales, ggplot2, testthat (>= 3.0.0), withr, microbenchmark, DiagrammeR, DiagrammeRsvg, rsvg, pdftools, tidyr
URL: https://github.com/mountainMath/canpumf, https://mountainmath.github.io/canpumf/
BugReports: https://github.com/mountainMath/canpumf/issues
VignetteBuilder: knitr
Language: en-CA
NeedsCompilation: no
Packaged: 2026-06-27 16:14:21 UTC; jens
Author: Jens von Bergmann [aut, cre]
Maintainer: Jens von Bergmann <jens@mountainmath.ca>
Repository: CRAN
Date/Publication: 2026-07-03 12:10:09 UTC

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New package TestREnlme with initial version 0.1.0
Package: TestREnlme
Title: Nonparametric Tests for Random Effects in Linear and Nonlinear Mixed-Effects Models
Version: 0.1.0
Description: Provides nonparametric permutation tests for testing all or any subset of random effects in linear and nonlinear mixed-effects models, without requiring normality or other distributional assumptions on random effects or errors. Three distribution-free variance-component estimators are implemented: Variance Least Squares ('VLS'), Method of Moments ('MM'), and Method of Moments with First-Order Approximation ('MMF'). A permutation procedure is used to obtain finite-sample p-values. Plotting functions support data exploration, model evaluation, and communication of results. Methods are described in Uwimpuhwe, Drikvandi, and Blozis (2026) <doi:10.1002/sim.70605>.
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
Depends: R (>= 4.1.0)
Imports: nlme (>= 3.1-150), Matrix (>= 1.3-0), MASS (>= 7.3-54), mgsub (>= 1.7.3), matrixcalc (>= 1.0-5), nls.multstart (>= 2.0.0), ggplot2 (>= 3.3.5), expm (>= 0.999-6), withr (>= 3.0.2), stats, utils, rlang
Suggests: knitr, rmarkdown, ggpubr (>= 0.4.0), testthat (>= 3.0.0), reshape2 (>= 1.4.4)
VignetteBuilder: knitr
URL: https://github.com/germaine86/TestREnlme
BugReports: https://github.com/germaine86/TestREnlme/issues
NeedsCompilation: no
Packaged: 2026-06-27 13:24:25 UTC; germu
Author: Germaine Uwimpuhwe [aut, cre], Reza Drikvandi [aut], Shelley A. Blozis [aut]
Maintainer: Germaine Uwimpuhwe <germaine.uwimpuhwe@durham.ac.uk>
Repository: CRAN
Date/Publication: 2026-07-03 12:00:15 UTC

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New package jpmap with initial version 0.1.3
Package: jpmap
Title: Japan Maps with Insets for Okinawa and Ogasawara
Version: 0.1.3
URL: https://yhoriuchi.github.io/jpmap/, https://github.com/yhoriuchi/jpmap
BugReports: https://github.com/yhoriuchi/jpmap/issues
Description: Provides tools for drawing maps of Japan with prefecture and municipal boundaries. The plotting workflow mirrors the 'usmap' package and includes a transform that moves Okinawa and Ogasawara into visible inset locations. Boundary helpers build local 'GeoPackage' files from Japan's official MLIT N03 administrative area data <https://nlftp.mlit.go.jp/ksj/gml/datalist/KsjTmplt-N03-2024.html>.
License: MIT + file LICENSE
Copyright: See inst/COPYRIGHTS.
Encoding: UTF-8
Depends: R (>= 4.1.0)
LazyData: true
Imports: ggplot2, rlang, sf
Suggests: dplyr, ggthemes, knitr, leaflet, pkgdown, rmarkdown, testthat (>= 3.0.0), tibble, tidyverse
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-06-27 10:53:36 UTC; yh25m
Author: Yusaku Horiuchi [aut, cre]
Maintainer: Yusaku Horiuchi <yusaku.horiuchi@gmail.com>
Repository: CRAN
Date/Publication: 2026-07-03 12:00:02 UTC

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New package HomeRangeR with initial version 0.1.0
Package: HomeRangeR
Title: Predict Vertebrate Home-Range Sizes Using Allometric Models
Version: 0.1.0
Description: Provides empirically strong allometric predictions of the home-range size of most vertebrate species. Based on inputs of mean body size, taxonomic class, and optional classifications of environment and trophic level or foraging mode, 'HomeRangeR' predicts home-range size using the most appropriate model for the species selected from a collection of empirically derived vertebrate home-range allometries.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.5)
Imports: dplyr
NeedsCompilation: no
Packaged: 2026-06-27 12:26:21 UTC; dalemoskoff
Author: Dale Moskoff [aut, cre]
Maintainer: Dale Moskoff <d.moskoff@mail.utoronto.ca>
Repository: CRAN
Date/Publication: 2026-07-03 12:00:21 UTC

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New package cyclicwave with initial version 0.1.0
Package: cyclicwave
Title: Cyclic Wave Analysis for Time-Series Clustering
Version: 0.1.0
Description: A modular toolkit for feature extraction and density-based clustering of time-series data. It provides classical statistical, discrete wavelet, Hilbert-based phase, and circular statistical features. The Hilbert-based phase representation can support the analysis of periodic patterns, phase relationships, and circular behavior in time-series data. The package supports DBSCAN and OPTICS clustering, cluster evaluation, visualization, data preparation, and comparison of multiple feature extraction and clustering combinations. Methods are described in Karakaya and Purutcuoglu (2026) <doi:10.15672/hujms.1821412> and Karakaya et al. (2026) <doi:10.1007/978-3-032-17020-0_27>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: stats, utils, dbscan, gsignal, waveslim, MASS, e1071, ggplot2
Suggests: FNN, testthat (>= 3.0.0), knitr, rmarkdown
Depends: R (>= 3.5.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-06-25 23:37:58 UTC; buaht
Author: Şule Şevval Karakaya [aut, cre], Ahmet Bursali [aut], Vilda Purutcuoglu [aut]
Maintainer: Şule Şevval Karakaya <sule.karakaya@metu.edu.tr>
Repository: CRAN
Date/Publication: 2026-07-03 12:00:08 UTC

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Thu, 02 Jul 2026

New package parcxl with initial version 0.1.0
Package: parcxl
Title: Fast Formula Stripping and Exporting Excel Sheets to Separate Files
Version: 0.1.0
Description: Provides fast, dependency-minimal tools to strip all cell formulas from standard Excel (.xlsx) files while preserving evaluated calculated values intact. It also supports exporting multi-sheet workbooks into standalone single-sheet files. By design, the package extracts only cell values and their formatting (styles) to ensure maximum speed and safety, discarding complex embedded objects such as images or charts.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: xml2, zip
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-06-27 05:44:31 UTC; HOMMA
Author: Shunsuke Homma [aut, cre]
Maintainer: Shunsuke Homma <shunsuke.homma@proton.me>
Repository: CRAN
Date/Publication: 2026-07-02 19:00:02 UTC

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New package testflow with initial version 0.8.2
Package: testflow
Title: A Workflow for Statistical Testing, Interpretation, and 'ggplot2'-Based Visualization
Version: 0.8.2
Author: Imad EL BADISY [aut, cre]
Maintainer: Imad EL BADISY <elbadisyimad@gmail.com>
Description: Provides a unified workflow for choosing, running, interpreting, and visualizing common statistical tests. The package combines assumption checks, test selection, effect sizes, formatted results, plain-language interpretation, and 'ggplot2'-based statistical visualizations. Implemented methods follow standard references including Casella and Berger (2002, ISBN:9780534243128), Hollander et al. (2013, ISBN:9781118553299), Agresti (2013, ISBN:9780470463635), and Cohen (1988, ISBN:9780805802832).
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: stats, cli, rlang, dplyr, tidyr, tidyselect, tibble, purrr, broom, ggplot2
Suggests: testthat (>= 3.0.0), knitr, rmarkdown, car, effectsize, rstatix, patchwork
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-06-26 18:39:54 UTC; imad-el-badisy
Repository: CRAN
Date/Publication: 2026-07-02 18:40:02 UTC

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New package SDALGCP2 with initial version 0.1.0
Package: SDALGCP2
Title: Fast Spatially Discrete Approximation to Log-Gaussian Cox Processes for Aggregated Disease Count Data
Version: 0.1.0
Description: Fits a spatially discrete approximation to a log-Gaussian Cox process model for spatially aggregated disease count data, estimated by Monte Carlo Maximum Likelihood as in Christensen (2004) <doi:10.1198/106186004X2525> and Johnson, Diggle and Giorgi (2019) <doi:10.1002/sim.8339>. Performance-critical steps (aggregated correlation assembly, 'MALA' sampling, the Monte Carlo likelihood, and the Kronecker-structured space-time likelihood) are implemented in C++ via 'RcppArmadillo'. Provides a one-line, 'glm'-like interface and statistical extensions including a nugget term, general 'Matern' smoothness, raster and misaligned covariates, restricted spatial regression, importance-sampling diagnostics and re-anchored 'MCML'.
Depends: R (>= 4.2.0)
License: GPL-2 | GPL-3
Encoding: UTF-8
Language: en-GB
LazyData: true
LinkingTo: Rcpp, RcppArmadillo
Imports: Rcpp, sf, terra, spatstat.geom, spatstat.random, ggplot2, progress, stats, utils
Suggests: knitr, rmarkdown, testthat (>= 3.0.0), numDeriv, bench
VignetteBuilder: knitr
URL: https://github.com/olatunjijohnson/SDALGCP2, https://olatunjijohnson.github.io/SDALGCP2/
BugReports: https://github.com/olatunjijohnson/SDALGCP2/issues
NeedsCompilation: yes
Packaged: 2026-06-26 16:46:31 UTC; olatunji-johnson
Author: Olatunji Johnson [aut, cre], Emanuele Giorgi [aut], Peter Diggle [aut]
Maintainer: Olatunji Johnson <olatunjijohnson21111@gmail.com>
Repository: CRAN
Date/Publication: 2026-07-02 18:40:25 UTC

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New package peeky with initial version 0.1.0
Package: peeky
Title: Download and Extract 'shinylive' Applications
Version: 0.1.0
Description: Peek into published 'shinylive' applications by retrieving their source code. Supports downloading and extracting 'shiny' application source from 'quarto' documents and standalone 'shinylive' applications.
URL: https://r-pkg.thecoatlessprofessor.com/peeky/, https://github.com/coatless-rpkg/peeky
BugReports: https://github.com/coatless-rpkg/peeky/issues
License: AGPL (>= 3)
Imports: jsonlite, httr, rvest, fs, cli
Suggests: knitr, rmarkdown, quarto, withr, testthat (>= 3.0.0)
Encoding: UTF-8
VignetteBuilder: quarto
NeedsCompilation: no
Packaged: 2026-06-26 21:10:04 UTC; ronin
Author: James Joseph Balamuta [aut, cre]
Maintainer: James Joseph Balamuta <james.balamuta@gmail.com>
Depends: R (>= 4.1.0)
Repository: CRAN
Date/Publication: 2026-07-02 18:40:08 UTC

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New package mixedsubjects with initial version 1.0.0
Package: mixedsubjects
Title: Causal Inference in Experiments with Mixed-Subjects Designs
Version: 1.0.0
Description: Implements seven estimators for average treatment effect (ATE) estimation in mixed-subjects designs (MSDs), where human subjects data is augmented with predictions from large language models (LLMs). Includes Difference-in-Means, GREG, PPI++, Doubly-Tuned, Difference-in-Predictions (DiP), DiP++, and D-T DiP estimators. Provides point estimates, variance estimation via delta-method or bootstrap, and optimal design selection for budget allocation between human observations and LLM predictions.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: stats
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
URL: https://klintkanopka.com/mixedsubjects/
BugReports: https://github.com/klintkanopka/mixedsubjects/issues
NeedsCompilation: no
Packaged: 2026-06-26 16:15:06 UTC; klintkanopka
Author: Austin van Loon [aut], Klint Kanopka [aut, cre], Yuan Huang [ctb]
Maintainer: Klint Kanopka <klint.kanopka@nyu.edu>
Repository: CRAN
Date/Publication: 2026-07-02 18:30:02 UTC

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New package mergersim with initial version 0.1.0
Package: mergersim
Title: Merger Simulation and Calibration
Version: 0.1.0
Description: Analyze mergers between firms. Models of competition include differentiated Bertrand price-setting, Nash bargaining, and second score auctions, as implemented in Panhans and Taragin (2023) <doi:10.1016/j.ijindorg.2023.102986>. Calibrates demand systems including standard logit, nested logit, and generalized nested logit as implemented in Panhans and Wiemer (2026) <doi:10.1093/joclec/nhaf037>.
License: CC0
Encoding: UTF-8
Imports: BB, numDeriv, rootSolve, stats
Suggests: antitrust, knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-06-26 14:38:42 UTC; mattpanhans
Author: Matthew T Panhans [aut, cre]
Maintainer: Matthew T Panhans <mpanhans@gmail.com>
Repository: CRAN
Date/Publication: 2026-07-02 18:20:02 UTC

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New package deaviz with initial version 0.1.0
Package: deaviz
Title: Visualization of Data Envelopment Analysis Problems
Version: 0.1.0
Description: High-dimensional visualization methods for data envelopment analysis (DEA), gathering in one place techniques that have appeared in the literature but remained scattered and largely unimplemented: cross-efficiency matrix unfolding, the Porembski network with lambda edges, principal component analysis biplots, multidimensional-scaling colour-plots, self-organizing maps, the Costa bi-dimensional efficient frontier, parallel coordinates, radar charts, panel-data trajectory biplots, peer and reference networks, and a set of descriptive plots. The package is built around a single validated dea_data() object and uses the 'Benchmarking' package as its DEA engine. The implemented methods draw on a body of literature; representative references include Doyle and Green (1994) <doi:10.1057/jors.1994.84>, Porembski, Breitenstein and Alpar (2005) <doi:10.1007/s11123-005-1328-5> and Bana e Costa, Soares de Mello and Angulo Meza (2016) <doi:10.1016/j.ejor.2016.05.012>.
License: AGPL (>= 3)
Encoding: UTF-8
Language: en-GB
URL: https://github.com/Pomelo64/deaviz
BugReports: https://github.com/Pomelo64/deaviz/issues
LazyData: true
Depends: R (>= 3.6.0)
Imports: rlang, stats, utils, grDevices, graphics, ggplot2 (>= 3.4.0)
Suggests: Benchmarking, lpSolve, lpSolveAPI, kohonen, smacof, plotly, ggrepel, igraph, graphlayouts, MASS, testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-06-26 16:56:01 UTC; shaahin
Author: Shahin Ashkiani [aut, cre]
Maintainer: Shahin Ashkiani <Contact@Shahin-Ashkiani.com>
Repository: CRAN
Date/Publication: 2026-07-02 18:30:07 UTC

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New package checktor with initial version 0.1.0
Package: checktor
Title: Extra CRAN Submission Checks
Version: 0.1.0
Description: Provides automated checks for common Comprehensive R Archive Network (CRAN) submission issues that are not caught by standard 'R CMD check'. Consolidates ad-hoc requirements that CRAN reviewers enforce but standard checks do not surface, helping 'R' package maintainers identify and fix issues before submission to reduce rejection rates. Covers code-pattern issues, DESCRIPTION-field formatting, documentation problems, and general package structure concerns.
License: AGPL (>= 3)
URL: https://github.com/coatless-rpkg/checktor, https://r-pkg.thecoatlessprofessor.com/checktor/
BugReports: https://github.com/coatless-rpkg/checktor/issues
Depends: R (>= 3.5.0)
Imports: utils, tools, cli (>= 3.0.0), generics, xml2, xmlparsedata
Suggests: testthat (>= 3.0.0), quarto
VignetteBuilder: quarto
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-06-26 21:16:06 UTC; ronin
Author: James Joseph Balamuta [aut, cre, cph]
Maintainer: James Joseph Balamuta <james.balamuta@gmail.com>
Repository: CRAN
Date/Publication: 2026-07-02 18:50:02 UTC

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New package araponga with initial version 1.0.1
Package: araponga
Title: Estimate 3D Orientations from 2D Landmarks
Version: 1.0.1
Description: Estimates possible 3D orientations of an object from the 2D image coordinates of two landmarks and an approximate camera-object elevation angle. Because a projected 2D angle can be compatible with multiple 3D pitch, yaw, and view-elevation angles, the package returns compatible sets of orientations rather than a single unconstrained estimate.
License: GPL (>= 3)
Depends: R (>= 4.1.0)
Imports: arrow, dplyr, graphics, rlang
Suggests: curl, httr, knitr, rmarkdown, testthat (>= 3.0.0)
Encoding: UTF-8
URL: https://github.com/jocateme/araponga
BugReports: https://github.com/jocateme/araponga/issues
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-06-26 14:20:00 UTC; jocateme
Author: Joao C T Menezes [aut, cre, cph]
Maintainer: Joao C T Menezes <jocateme@gmail.com>
Repository: CRAN
Date/Publication: 2026-07-02 18:10:02 UTC

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New package apifetch with initial version 0.1.0
Package: apifetch
Title: Token-Authenticated REST API Retrieval Toolkit
Version: 0.1.0
Date: 2026-06-26
Description: A small, dependency-light toolkit for talking to token-authenticated REST APIs. It manages authentication tokens in process environment variables (never written to disk), builds requests with configurable authentication and pagination strategies, and retrieves paginated data either one page at a time or in chunks combined into a single tibble. The design is API-agnostic: a single 'apifetch_api' profile describes an endpoint together with how it authenticates and paginates, so the same verbs work across different services.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: cli, dplyr, httr2, stats, tibble, utils
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
URL: https://github.com/StrategicProjects/apifetch, https://strategicprojects.github.io/apifetch/
BugReports: https://github.com/StrategicProjects/apifetch/issues
NeedsCompilation: no
Packaged: 2026-06-26 19:37:47 UTC; leite
Author: Andre Leite [aut, cre], Hugo Vasconcelos [aut], Diogo Bezerra [aut], Marcos Wasilew [aut], Carlos Amorin [aut]
Maintainer: Andre Leite <leite@castlab.org>
Repository: CRAN
Date/Publication: 2026-07-02 18:40:19 UTC

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Wed, 01 Jul 2026

New package trackclean with initial version 0.1.0
Package: trackclean
Title: Tools for Cleaning High-Frequency Real-Time Location Tracking Data
Version: 0.1.0
Description: Provides data cleaning and preprocessing tools for high-frequency positional data from real-time location tracking systems (UWB, RFID, and similar technologies), with functions for ID mapping, time period marking, data standardization, and two-phase conditional gap interpolation. See Bilevicius (2026) <doi:10.5281/zenodo.20783488>.
License: CC BY 4.0
URL: https://github.com/tomasbil/trackclean
BugReports: https://github.com/tomasbil/trackclean/issues
Encoding: UTF-8
Language: en-US
Imports: dplyr, lubridate, magrittr, readr, rlang, tibble
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-06-26 08:09:33 UTC; tomas
Author: Tomas Bilevicius [aut, cre]
Maintainer: Tomas Bilevicius <Tomas.Bilevicius@vub.be>
Repository: CRAN
Date/Publication: 2026-07-01 09:40:02 UTC

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New package saeHB.Spatial.Beta with initial version 0.1.0
Package: saeHB.Spatial.Beta
Title: Small Area Estimation Hierarchical Bayes for Spatial Beta Model
Version: 0.1.0
Description: Provides several functions and datasets for area-level Small Area Estimation using the Hierarchical Bayesian (HB) method. Model-based estimators are designed for variables of interest that follow a Beta distribution. The package supports spatial structures under the Simultaneous Autoregressive (SAR) and Leroux Conditional Autoregressive (CAR) models, accommodating survey design effect (DEFF) adjustments. The 'rjags' package is employed to obtain parameter estimates via Gibbs Sampling. For references, see Rao and Molina (2015) <doi:10.1002/9781118735855>, Kubacki and Jedrzejczak (2016) <doi:10.59170/stattrans-2016-022>, Leroux et al. (2000) <doi:10.1007/978-1-4612-1284-3_4>, and Chung and Datta (2020) <https://www.census.gov/content/dam/Census/library/working-papers/2020/adrm/RRS2020-07.pdf>.
License: GPL-3
Encoding: UTF-8
LazyData: true
Depends: R (>= 4.1.0)
Imports: rjags, coda, stats, grDevices, graphics, sf, spdep
SystemRequirements: JAGS (http://mcmc-jags.sourceforge.net)
Suggests: knitr, rmarkdown, testthat (>= 3.0.0), ggplot2
VignetteBuilder: knitr
URL: https://github.com/BobyIwan/saeHB.Spatial.Beta
BugReports: https://github.com/BobyIwan/saeHB.Spatial.Beta/issues
NeedsCompilation: no
Packaged: 2026-06-14 06:01:44 UTC; diann
Author: Boby Iwan [aut, cre], Cucu Sumarni [aut]
Maintainer: Boby Iwan <bobyiwanboby2122@gmail.com>
Repository: CRAN
Date/Publication: 2026-07-01 09:30:07 UTC

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New package rtransparency with initial version 1.0.0
Package: rtransparency
Title: Identifies Indicators of Transparency
Version: 1.0.0
Description: Use this package to identify indicators of transparency within the published literature. It can identify and extract text related to indicators of transparency from specifically formatted TXT files and from PMC XML files (i.e. XML files downloaded from the PubMed Central). It builds on the original 'rtransparent' tool of Serghiou et al. (2021) <doi:10.1371/journal.pbio.3001107>.
License: GPL-3
Encoding: UTF-8
LazyData: true
URL: https://github.com/choxos/rtransparency, https://choxos.github.io/rtransparency/
BugReports: https://github.com/choxos/rtransparency/issues
Depends: R (>= 3.5.0)
Imports: dplyr, magrittr, purrr, readr, rlang, stringr, tibble, tidyselect, utf8, xml2
Suggests: furrr, future, ggplot2, knitr, readxl, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-06-25 11:35:18 UTC; choxos
Author: Stylianos Serghiou [aut], Ahmad Sofi-Mahmudi [cre, aut]
Maintainer: Ahmad Sofi-Mahmudi <a.sofimahmudi@gmail.com>
Repository: CRAN
Date/Publication: 2026-07-01 09:00:02 UTC

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New package rfair with initial version 0.1.0
Package: rfair
Title: Assess the FAIRness of Research Data Objects and Software
Version: 0.1.0
Description: A native R implementation of the F-UJI (FAIRsFAIR Research Data Object Assessment) and FRSM (FAIR for Research Software) metrics for evaluating how well a research data object or piece of research software satisfies the FAIR principles (Findable, Accessible, Interoperable, Reusable). The software metrics operationalize the FAIR Principles for Research Software (FAIR4RS) of Chue Hong et al. (2022) <doi:10.15497/RDA00068>. Given a persistent identifier, URL, or code repository, 'rfair' resolves it, harvests metadata from landing pages and registries, and scores it against the FAIRsFAIR metrics of Devaraju and Huber (2020) <doi:10.5281/zenodo.3775793> entirely in R, without requiring an external assessment server. 'rfair' began as a fork of the 'rfuji' F-UJI API client and reimplements the assessment engine natively.
License: GPL-3
URL: https://github.com/choxos/rfair, https://choxos.github.io/rfair/
BugReports: https://github.com/choxos/rfair/issues
Depends: R (>= 4.1)
Imports: digest, httr2, jsonlite, mime, rvest, stats, stringdist, utils, xml2, yaml
Suggests: bslib, chromote, covr, DT, httptest2, jqr, knitr, plumber, rdflib, rmarkdown, shiny, testthat (>= 3.0.0), wand
VignetteBuilder: knitr
Encoding: UTF-8
Language: en-US
NeedsCompilation: no
Packaged: 2026-06-25 11:44:53 UTC; choxos
Author: Ahmad Sofi-Mahmudi [aut, cre] , Steffen Neumann [ctb] , PANGAEA [cph]
Maintainer: Ahmad Sofi-Mahmudi <a.sofimahmudi@gmail.com>
Repository: CRAN
Date/Publication: 2026-07-01 09:10:02 UTC

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New package palsr with initial version 0.1.0
Package: palsr
Title: Projected Actor Locations for Spatial Interaction Modeling
Version: 0.1.0
Description: Implements the Projected Actor Locations (PALS) method for spatial modeling of dyadic interactions between geographically mobile actors, as described in Kim, Liu and Desmarais (2023) <doi:10.1017/psrm.2022.6>. PALS applies exponential-smoothing weights to the spatiotemporal histories of a focal actor and its interaction partners ("alters") to project the location of future interactions. The package provides projection, maximum-similarity parameter estimation by minimizing great-circle (Haversine) prediction error, nonparametric bootstrap with multiple-imputation (Rubin's Rules) pooling, dyadic distance covariate construction, visualization, and a simulated example dataset of subnational conflict.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Depends: R (>= 4.1.0)
Imports: Rcpp, stats
LinkingTo: Rcpp
Suggests: testthat (>= 3.0.0), knitr, rmarkdown, mice, ggplot2
URL: https://github.com/bdesmarais/palsr
BugReports: https://github.com/bdesmarais/palsr/issues
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2026-06-25 11:47:24 UTC; bbd5087
Author: Bruce A. Desmarais [aut, cre], Sangyeon Kim [aut], Howard Liu [aut]
Maintainer: Bruce A. Desmarais <bruce.desmarais@gmail.com>
Repository: CRAN
Date/Publication: 2026-07-01 10:00:13 UTC

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New package axprism with initial version 0.2.0
Package: axprism
Title: Client for the 'AxPrism' Institutional XBRL and Shariah Compliance API
Version: 0.2.0
Description: Provides an R client for the 'AxPrism' Application Programming Interface (API) (<https://axprism.com>), which serves institutional financial data in the eXtensible Business Reporting Language (XBRL) format together with Shariah compliance screening. Supported compliance rulesets include those of the Accounting and Auditing Organization for Islamic Financial Institutions (AAOIFI), the Morgan Stanley Capital International (MSCI) Islamic methodology, the Dow Jones Islamic Market (DJIM), the Financial Times Stock Exchange (FTSE) and the Saudi Capital Market Authority (CMA). Convenience functions wrap company fundamentals, compliance verdicts and portfolio screening, company profiles, equity screeners, regulatory disclosures and filing text search, and the Tadawul (Saudi Exchange), Bursa Malaysia and Indonesia Stock Exchange (IDX) markets, as well as webhooks and bulk data export. Requests use 'X-API-Key' header authentication, automatic retries with exponential backoff, and a generic [...truncated...]
License: MIT + file LICENSE
Encoding: UTF-8
URL: https://axprism.com, https://axprism.com/api-reference
BugReports: https://axprism.com/contact
Imports: httr, jsonlite
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-06-26 01:30:20 UTC; code
Author: Marco Corleone [aut, cre]
Maintainer: Marco Corleone <dev@axprism.com>
Repository: CRAN
Date/Publication: 2026-07-01 09:20:02 UTC

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Tue, 30 Jun 2026

New package vbm with initial version 0.1.0
Package: vbm
Title: Variance-Based Sensitivity Analysis for Weighting Estimators
Version: 0.1.0
Maintainer: Jiayao Gan <u3612852@connect.hku.hk>
Description: Provides methods for variance-based sensitivity analysis and weighting estimators in observational studies based on methodology by Huang & Pimentel (2025) <doi:10.1093/biomet/asae040>. Includes bootstrap inference, bias bounds estimation, and visualization tools for sensitivity parameters.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: parallel, magrittr, dplyr, WeightIt, estimatr, ggplot2, scales
URL: https://github.com/Staniks0/vbm
BugReports: https://github.com/Staniks0/vbm/issues
Suggests: jointVIP, knitr, rmarkdown, pkgdown, cobalt, osqp
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-06-25 15:53:37 UTC; staniks
Author: Jiayao Gan [aut, cre], Melody Huang [aut], Samuel D. Pimentel [aut], Andy A. Shen [aut], National Science Foundation [fnd]
Repository: CRAN
Date/Publication: 2026-06-30 20:30:02 UTC

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New package uddbart with initial version 0.2.0
Package: uddbart
Title: Unified Dynamic Deep 'BART' for Interval-Censored Survival
Version: 0.2.0
Author: Xulin Pan [aut, cre]
Maintainer: Xulin Pan <xulinpanias@gmail.com>
Description: Implements U-DDBART-IC, a unified Bayesian workflow for dynamic risk prediction from irregular longitudinal biomarkers when event times are interval-censored between clinical visits. The package turns long-format biomarker histories and patient-level interval endpoints L, R, C and delta into a discrete-time follow-up grid, summarises each landmark history with nine interpretable trajectory features (current, baseline and previous biomarker values, last visit gap, local slope, cumulative decline, best value, elapsed time and visit count), fits discrete-time interval hazards using optional logit-link Bayesian additive regression trees, a generalized linear model fallback, or a lightweight variational approximation, accumulates survival from the discrete-time product, and evaluates the interval-censored likelihood. Fitted models return landmark risk predictions over user-specified horizons with posterior or bootstrap uncertainty by evaluating survival ratios across fitted hazard draws. Ut [...truncated...]
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-US
LazyData: true
Depends: R (>= 4.1.0)
Imports: stats, graphics, grDevices
Suggests: testthat (>= 3.0.0), knitr, rmarkdown, BART (>= 2.9)
VignetteBuilder: knitr
URL: https://github.com/xulinpan/uddbart
BugReports: https://github.com/xulinpan/uddbart/issues
NeedsCompilation: no
Packaged: 2026-06-25 14:29:20 UTC; CodexSandboxOffline
Repository: CRAN
Date/Publication: 2026-06-30 20:20:02 UTC

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New package sportsfeatures with initial version 0.1.0
Package: sportsfeatures
Title: Longitudinal Sports Analytics Asset and Workload Feature Processing
Version: 0.1.0
Description: A synthetic, longitudinal athletic dataset generated through a transparent, rule-based simulation engine. Captures individual activity sessions across multiple athletes, environmental conditions, and physiological responses. Specifically designed as an alternative to legacy teaching datasets by introducing realistic hierarchical repeated measures, complex two-way covariate interactions, and a deliberate Missing Not At Random (MNAR) tracking mechanism suitable for advanced imputation workflows. Methodologies implemented are based on van Buuren (2018) <doi:10.1201/9780429492259> and Bates et al. (2015) <doi:10.18637/jss.v067.i01>.
License: MIT + file LICENSE
Depends: R (>= 4.1.0)
Imports: tibble, mice, modelsummary, lme4
Suggests: tidyverse
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2026-06-24 19:39:55 UTC; abbasxma
Author: Mohammad Abbas [aut, cre]
Maintainer: Mohammad Abbas <ma.abbas3107@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-30 20:00:02 UTC

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New package reaborn with initial version 1.0.0
Package: reaborn
Title: Statistical Data Visualization, the 'seaborn' Way
Version: 1.0.0
Description: An 'R' port of the 'Python' 'seaborn' library. 'reaborn' mirrors the 'seaborn' public function API (identical function names, argument names, and defaults) and renders visually indistinguishable plots using 'ggplot2'. Because every 'reaborn' plot is a 'ggplot' object, it can be extended with the full 'ggplot2' grammar of graphics.
License: BSD_3_clause + file LICENSE
Encoding: UTF-8
Language: en-US
Depends: R (>= 4.1)
Imports: ggplot2 (>= 4.0.0), grDevices, grid, rlang, scales, stats
Suggests: colorspace, ggbeeswarm, ggdendro, jsonlite, knitr, MASS, patchwork, ragg, rmarkdown, testthat (>= 3.0.0), vdiffr
VignetteBuilder: knitr
URL: https://reaborn.org, https://github.com/shawntz/reaborn
BugReports: https://github.com/shawntz/reaborn/issues
NeedsCompilation: no
Packaged: 2026-06-25 19:16:10 UTC; shawnschwartz
Author: Shawn Schwartz [aut, cre]
Maintainer: Shawn Schwartz <shawn.t.schwartz@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-30 20:40:02 UTC

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New package proximetricsR with initial version 0.6.4
Package: proximetricsR
Title: Spectral Preprocessing and Chemometric Calibration of NIR Sensors
Version: 0.6.4
Date: 2026-06-22
Maintainer: Leonardo Ramirez-Lopez <ramirez-lopez.l@buchi.com>
BugReports: https://github.com/l-ramirez-lopez/proximetricsr/issues
Description: Provides tools to build quantitative chemometric models and applications for near-infrared (NIR) sensors. Chemometric regression models are based on partial least squares regression as described by Wold (1975) <doi:10.1016/B978-0-12-103950-9.50017-4> and modified partial least squares regression as described by Shenk and Westerhaus (1991) <doi:10.2135/cropsci1991.0011183X003100020049x>, with further discussion by Westerhaus (2014) <doi:10.1255/nirn.1492>.
License: MIT + file LICENSE
URL: https://github.com/l-ramirez-lopez/proximetricsr
VignetteBuilder: quarto
Depends: R (>= 4.2.0)
Imports: callr, digest (>= 0.6), foreach, mathjaxr (>= 1.0), plotly (>= 4.0), prospectr (>= 0.2.10), quarto, uuid, withr, zip, readxl, jsonlite, Rcpp
Suggests: knitr, testthat, covr, doParallel, parallel, devtools
LinkingTo: Rcpp, RcppArmadillo
NeedsCompilation: yes
LazyData: true
LazyDataCompression: xz
Encoding: UTF-8
Packaged: 2026-06-25 17:37:39 UTC; leo
Author: Leonardo Ramirez-Lopez [aut, cre] , Claudio Orellano [aut] , Nicolae Cudlenco [aut] , Mai Said [aut] , Mohamed Abushosha [aut], Marcal Plans [aut]
Repository: CRAN
Date/Publication: 2026-06-30 20:30:07 UTC

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New package netify with initial version 1.5.3
Package: netify
Title: Tools for Network Data Workflows
Version: 1.5.3
Description: Builds, validates, analyzes, and visualizes network data from dyadic, event, matrix, 'igraph', and 'network' inputs. Supports cross-sectional, longitudinal, bipartite, and multi-layer networks, with conversion helpers for common modeling workflows and plotting utilities for exploratory analysis. Network methods are described in Wasserman and Faust (1994, ISBN:9780521387071), Cranmer et al. (2021) <doi:10.1017/9781316662915>, and Minhas et al. (2022) <doi:10.1017/psrm.2021.56>.
Depends: R (>= 3.5.0)
Imports: Rcpp, stats, methods, rlang, cli, checkmate, igraph, ggplot2 (>= 3.0.0), ggnewscale, ggrepel, withr
LinkingTo: Rcpp, RcppEigen
Suggests: knitr, rmarkdown, abind, tidyr, network, testthat (>= 3.0.0), dplyr, peacesciencer, amen, ergm, latentnet, RSiena, countrycode, scales, ggridges, ggbeeswarm, patchwork, RColorBrewer, tibble, broom, gganimate, generics, Matrix
VignetteBuilder: knitr
License: GPL-3
Encoding: UTF-8
LazyData: false
URL: https://netify-dev.github.io/netify/
BugReports: https://github.com/netify-dev/netify/issues
NeedsCompilation: yes
Packaged: 2026-06-25 13:33:12 UTC; s7m
Author: Ha Eun Choi [ctb], Cassy Dorff [aut], Colin Henry [ctb], Shahryar Minhas [aut, cre], Tosin Salau [ctb]
Maintainer: Shahryar Minhas <minhassh@msu.edu>
Repository: CRAN
Date/Publication: 2026-06-30 20:20:09 UTC

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New package muse with initial version 0.1.0
Package: muse
Title: Multiple Unobserved Sources of Error State Space Models
Version: 0.1.0
Date: 2026-06-26
URL: https://github.com/config-i1/muse
BugReports: https://github.com/config-i1/muse/issues
Language: en-GB
Description: Implements the Power / Trend / Seasonal (PTS) model, a unified state-space framework based on the Multiple Source of Error (MSOE) model. It brings the trend, seasonal and irregular component models of Harvey (1989) <doi:10.1017/CBO9781107049994>, Durbin and Koopman (2012) <doi:10.1093/acprof:oso/9780199641178.001.0001>, Proietti (2000) <doi:10.1016/S0169-2070(00)00037-6>, Sbrana and Silvestrini (2023) <doi:10.1016/j.ijforecast.2022.03.003> and others together under a single estimation, selection and forecasting interface, with an optional Box-Cox power transformation. Models are estimated by maximum likelihood through the Kalman filter and smoother, with automatic component selection by information criteria.
License: LGPL-2.1
Depends: R (>= 3.0.2), greybox, smooth
Imports: Rcpp (>= 0.12.3), generics (>= 0.1.2), zoo
LinkingTo: Rcpp, RcppArmadillo (>= 0.8.100.0.0)
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
Encoding: UTF-8
ByteCompile: true
NeedsCompilation: yes
Packaged: 2026-06-25 16:48:33 UTC; config
Author: Diego J. Pedregal [aut, ctb] , Ivan Svetunkov [aut, cre]
Maintainer: Ivan Svetunkov <ivan@svetunkov.com>
Repository: CRAN
Date/Publication: 2026-06-30 20:30:17 UTC

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New package MultiModalR with initial version 1.0.0
Package: MultiModalR
Title: Fast Bayesian Probability Estimation for Multimodal Categorical Data
Version: 1.0.0
Date: 2026-06-18
Description: Fast Bayesian probability estimation for multimodal categorical data using speed-optimized Markov chain Monte Carlo (MCMC) implementation (Metropolis-Hastings-within-partial-Gibbs). The package provides efficient algorithms for detecting subpopulations, estimating mixture components, and assigning observations to subgroups with probability estimates. The methods are described in Dioszegi, G. et al. (2026) "Automatic Bayesian Mixture Modeling for Multimodal Categorical Data via Integrated Mode Detection and Metropolis-Hastings-within-Gibbs Sampling" (submitted to Journal of Statistical Software).
License: MIT + file LICENSE
URL: https://github.com/DijoG/MultiModalR
BugReports: https://github.com/DijoG/MultiModalR/issues
Depends: R (>= 3.5.0)
Imports: Rcpp (>= 1.0.10), dplyr, purrr, readr, ggplot2, furrr, future, truncnorm, rlang
Suggests: testthat (>= 3.0.0), knitr, rmarkdown, multimode, tictoc, tidyr
LinkingTo: Rcpp, RcppArmadillo
SystemRequirements: C++17
Encoding: UTF-8
NeedsCompilation: yes
LazyData: true
Packaged: 2026-06-25 12:33:16 UTC; Dijo
Author: Gergo Dioszegi [aut, cre]
Maintainer: Gergo Dioszegi <dijogergo@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-30 20:10:08 UTC

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New package icarm with initial version 0.1.0
Package: icarm
Title: Interpretable Contextual-Accountable and Responsible Machine Learning
Version: 0.1.0
Description: A general-purpose framework for Interpretable Contextual-Accountable and Responsible Machine Learning (ICARM) that works with any clean tabular data across any application domain including healthcare, finance, social science, business, and education. Automatically detects whether a prediction task is binary classification, multi-class classification, or regression from the target variable type. Provides a unified entry point icarm_fit() supporting both interpretable learners (Classification and Regression Trees (CART), logistic regression, linear regression, Generalized Additive Models (GAM)) and extended learners (random forest, 'XGBoost', Support Vector Machines (SVM)) with consistent interfaces for global and local model explanation, group-level fairness auditing across protected attributes, probability calibration, threshold analysis, multi-model comparison, reproducible JavaScript Object Notation (JSON) audit trails, and accountability scorecards. The contextual accountability fra [...truncated...]
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-GB
Depends: R (>= 4.1.0)
Imports: stats, utils, rpart, ggplot2, dplyr, tidyr, tibble, purrr, rlang, jsonlite, digest
Suggests: randomForest, xgboost, e1071, mgcv, glmnet, nnet, DALEX, pROC, vip, testthat, covr
LazyData: true
NeedsCompilation: no
Packaged: 2026-06-18 21:08:32 UTC; olawa
Author: Olushina Olawale Awe [aut, cre], Ludwigsburg University of Education [fnd]
Maintainer: Olushina Olawale Awe <olawaleawe@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-30 20:40:10 UTC

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New package evbsreg with initial version 1.0.0
Package: evbsreg
Title: Local Influence Diagnostics for the Extreme-Value Birnbaum-Saunders Regression Model
Version: 1.0.0
Date: 2026-06-17
Description: Implements local influence diagnostics for the Extreme-Value Birnbaum-Saunders (EVBS) regression model: joint maximum likelihood estimation, conformal normal curvature diagnostics under three perturbation schemes (case-weight, response variable, and explanatory variable), randomized quantile residuals with simulation envelope, Monte Carlo simulation utilities, and publication-quality density and diagnostic plots. The methods are described in Ospina, Lima, Barros, and Macedo (2026, submitted) and are applied to monthly maximum wind gust data from Itajai, Brazil.
License: MIT + file LICENSE
URL: https://github.com/Raydonal/evbsreg, https://raydonal.github.io/evbsreg/
BugReports: https://github.com/Raydonal/evbsreg/issues
Encoding: UTF-8
LazyData: true
Depends: R (>= 4.0.0)
Imports: stats, graphics, SpatialExtremes, ggplot2
Suggests: grDevices, knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-06-25 21:04:36 UTC; raydonal
Author: Raydonal Ospina [aut, cre]
Maintainer: Raydonal Ospina <raydonal@de.ufpe.br>
Repository: CRAN
Date/Publication: 2026-06-30 20:40:16 UTC

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New package emaxnls with initial version 0.1.1
Package: emaxnls
Title: Nonlinear Least Squares Estimation for Emax Regression Models
Version: 0.1.1
Description: Provides estimation and covariate selection tools for Emax regression models using nonlinear least squares methods. Supported optimization algorithms are Gauss-Newton, Levenberg-Marquardt, and the port library for bounded optimization. The package also provides tools to assist in simulation work using Emax regression.
License: MIT + file LICENSE
URL: https://github.com/djnavarro/emaxnls, https://emaxnls.djnavarro.net/
BugReports: https://github.com/djnavarro/emaxnls/issues
Depends: R (>= 3.5)
Imports: Deriv, minpack.lm, mvtnorm, rlang, stats, tibble, utils
Suggests: spelling, testthat (>= 3.0.0)
Encoding: UTF-8
LazyData: true
Language: en-US
NeedsCompilation: no
Packaged: 2026-06-25 12:45:44 UTC; danielle
Author: Danielle Navarro [aut, cre, cph]
Maintainer: Danielle Navarro <djnavarro@protonmail.com>
Repository: CRAN
Date/Publication: 2026-06-30 20:10:02 UTC

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New package droughtevents with initial version 0.1.0
Package: droughtevents
Title: Identify and Characterize Drought Events from Drought Index Time Series
Version: 0.1.0
Description: Detects, describes, and analyzes drought events from time series of drought indices, such as the Standardized Precipitation-Evapotranspiration Index (SPEI). Identifies drought episodes based on threshold values and calculates their duration, intensity, severity, and peak month. Includes utilities for summarizing and visualizing drought dynamics over time. The Standardized Precipitation-Evapotranspiration Index is described in Vicente-Serrano et al. (2010) <doi:10.1175/2009JCLI2909.1>.
License: MIT + file LICENSE
Encoding: UTF-8
Suggests: spelling, testthat (>= 3.0.0)
URL: https://github.com/ajpelu/droughtevents, https://ajpelu.github.io/droughtevents/
BugReports: https://github.com/ajpelu/droughtevents/issues
Imports: cli, data.table, dplyr, ggplot2, lubridate, rlang, scales
Depends: R (>= 4.1)
LazyData: true
Language: en-US
NeedsCompilation: no
Packaged: 2026-06-25 10:18:05 UTC; ajpelu
Author: Antonio Jesus Perez-Luque [cre, aut, cph]
Maintainer: Antonio Jesus Perez-Luque <ajpelu@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-30 20:00:06 UTC

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New package clim4health with initial version 0.1.0
Package: clim4health
Title: Post-Processing of Climate Data for Health Applications
Version: 0.1.0
Description: Obtain, transform and export climate data including reanalyses, (seasonal) forecasts and hindcasts, and weather stations for their use in epidemiological analyses. It is organised in three sequential blocks, input (download and load data), transform (downscaling, verification, spatiotemporal aggregation and threshold-based indicators) and output (visualising and exporting data). Downscaling methods include those described in Duzenli et al. (2026) <doi:10.1038/s41598-026-45067-2> and verification methods are based on those in Manubens et al. (2018) <doi:10.1016/j.envsoft.2018.01.018>.
License: AGPL (>= 3)
URL: https://gitlab.earth.bsc.es/ghr/clim4health, https://bsc-es.github.io/GHRtools/docs/clim4health/clim4health
BugReports: https://gitlab.earth.bsc.es/ghr/clim4health/-/issues
Encoding: UTF-8
Imports: CSTools, ecmwfr, ggplot2, GHRexplore, lubridate, s2dv, sf, stars, terra, data.table, units, CSDownscale, ncdf4, ggpattern, startR, rlang
Suggests: testthat (>= 3.0.0), spData, cubelyr, knitr, withr, rmarkdown
VignetteBuilder: knitr
SystemRequirements: CDO (Climate Data Operators, https://code.mpimet.mpg.de/projects/cdo), NCO (NetCDF Operators, https://nco.sourceforge.net/)
NeedsCompilation: no
Packaged: 2026-06-25 12:27:01 UTC; cmilagar
Author: Emily Ball [aut] , Carles Mila [aut, cre] , Alba Llabres [aut] , Raul Capellan [aut], Rebeca Nunes [aut] , Daniela Luehrsen [aut] , Anna B. Kawiecki [aut] , Rachel Lowe [aut]
Maintainer: Carles Mila <carles.milagarcia@bsc.es>
Repository: CRAN
Date/Publication: 2026-06-30 20:00:11 UTC

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New package lvmPlot with initial version 0.1.0
Package: lvmPlot
Title: Publication-Quality Diagrams for Latent Variable Models
Version: 0.1.0
Description: Converts output from latent variable model tools into publication-ready path diagrams and model schematics. 'lavaan' fit objects and parameter tables are supported as a primary workflow, with graph adapters for objects from 'blavaan', 'lavaan.mi', 'semPlot', 'mirt', 'eRm', 'OpenMx', 'psych', 'poLCA', 'mclust', 'flexmix', 'lcmm', 'tidyLPA', and 'MplusAutomation' workflows when those packages are available. Supports structural equation and confirmatory factor analysis diagrams, multilevel structural equation models, growth models, higher-order factor models, latent class and profile models, item response theory models, and common mixture outputs through a unified graph grammar with model-aware defaults, geometry diagnostics, layout quality scoring, automatic layout selection, customizable publication styles, 'RStudio' preview, SVG/PDF/PNG export, 'TikZ' output, and reproducible publication bundles.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: methods
Suggests: eRm, htmltools, jsonlite, lavaan, mclust, mirt, OpenMx, psych, ragg, rstudioapi, semPlot, shiny, svglite, testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-06-24 20:11:40 UTC; jifeng3
Author: Feng Ji [aut, cre]
Maintainer: Feng Ji <f.ji@utoronto.ca>
Repository: CRAN
Date/Publication: 2026-06-30 19:10:02 UTC

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New package lt with initial version 0.1
Package: lt
Title: Lightweight Tables via JSON Specs and JavaScript
Version: 0.1
Description: A lightweight grammar of tables. Build a table by declaring a JSON spec (titles, spanners, row groups, footnotes, formatters, etc.); a tiny vanilla JavaScript runtime builds the HTML table from the spec on page load. No 'sass', no 'V8', no 'htmlwidgets' — just base R and 'xfun' ('htmltools' is used only for the optional Shiny binding).
License: MIT + file LICENSE
URL: https://github.com/yihui/lt
BugReports: https://github.com/yihui/lt/issues
Depends: R (>= 4.1.0)
Encoding: UTF-8
Imports: xfun (>= 0.59)
Suggests: htmltools, knitr, litedown, repr, shiny, testit
NeedsCompilation: no
Packaged: 2026-06-25 00:34:31 UTC; yihui
Author: Yihui Xie [aut, cre, cph]
Maintainer: Yihui Xie <xie@yihui.name>
Repository: CRAN
Date/Publication: 2026-06-30 19:30:02 UTC

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New package huggingfaceR with initial version 2.1.0
Package: huggingfaceR
Title: Access 'Hugging Face' Models and Datasets
Version: 2.1.0
Author: Alex Farach [aut, cre, cph], Sam Terfa [aut, cph], Jack Penzer [aut, cph]
Maintainer: Alex Farach <alexfarach@gmail.com>
Description: Access models and datasets hosted on the 'Hugging Face' Hub through its Inference Application Programming Interface (API). Run text classification, embeddings, chat, translation, image, audio, and other tasks from tidy 'R' workflows without installing 'Python' by default. Results are returned as data frames or simple 'R' objects so they can be composed with 'dplyr', 'tidyr', and related tooling. Helpers also support Hub search, file download, provider discovery, and guarded uploads for authenticated workflows.
License: MIT + file LICENSE
URL: https://farach.github.io/huggingfaceR/, https://github.com/farach/huggingfaceR
BugReports: https://github.com/farach/huggingfaceR/issues
Encoding: UTF-8
LazyData: true
Imports: cli, dplyr, glue, httr2 (>= 1.0.0), jsonlite, magrittr, purrr, rlang, stringr, tibble, tidyr
Suggests: arrow, generics, knitr, lsa, recipes, reticulate, rmarkdown, testthat (>= 3.0.0), tidymodels, tidytext, uwot
Depends: R (>= 4.1.0)
NeedsCompilation: no
Packaged: 2026-06-24 23:33:29 UTC; alexfarach
Repository: CRAN
Date/Publication: 2026-06-30 19:30:08 UTC

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New package fixedCV with initial version 0.1.0
Package: fixedCV
Title: Fixed-b Critical Values for Robust Inference with Time Series Data
Version: 0.1.0
Maintainer: Rebecca Kurtz-Garcia <rkurtzgarcia@smith.edu>
Description: Provides functions for computing fixed-b critical values and conducting robust inference procedures for time series data with unknown correlation structures. Implements long-run variance estimators using various kernel functions and lugsail transformations for improved finite-sample properties as described by Kurtz-Garcia and Flegal (2026) <doi:10.48550/arXiv.2606.17369>.
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.5)
Imports: Matrix
Suggests: aTSA, tseries, dplyr, lubridate, lmtest
NeedsCompilation: no
Packaged: 2026-06-24 19:09:27 UTC; rkurtzgarcia
Author: Rebecca Kurtz-Garcia [aut, cre], Thomas Robacker [aut]
Repository: CRAN
Date/Publication: 2026-06-30 19:00:02 UTC

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New package DAST with initial version 0.1.0
Package: DAST
Title: Spatio-Temporal Disaggregation for Maps with Changing Areal Boundaries
Version: 0.1.0
Description: Tools for spatio-temporal disaggregation of areal data across multiple time points, including support for changing polygon boundaries. Implements methods for spatially aggregated log-Gaussian Cox process models with changing areal boundaries as described in Ripstein, Brown and Stafford (2026) "Spatio-Temporal Disaggregation with Changing Areal Boundaries" <doi:10.48550/arXiv.2606.25074>. Combines polygon-level observations, population rasters and optional covariate rasters to infer fine-scale spatial fields over time. Models can be efficiently fit using 'TMB' (Template Model Builder) and adaptive Gauss-Hermite quadrature for fast approximate inference or via 'tmbstan' for MCMC.
License: MIT + file LICENSE
Encoding: UTF-8
URL: https://github.com/nripstein/DAST
LinkingTo: TMB, RcppEigen
Imports: aghq, cowplot, disaggregation, fmesher, ggplot2, Matrix, numDeriv, rSPDE, sf, sparseMVN, terra, TMB
Suggests: knitr, rmarkdown, rstan, testthat (>= 3.0.0), tmbstan
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2026-06-25 02:47:03 UTC; NoahRipstein
Author: Noah Ripstein [aut, cre]
Maintainer: Noah Ripstein <noah.ripstein@mail.utoronto.ca>
Repository: CRAN
Date/Publication: 2026-06-30 19:40:02 UTC

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New package bitriad with initial version 0.4
Package: bitriad
Title: Triadic Analysis of Affiliation Networks
Version: 0.4
Maintainer: Jason Cory Brunson <cornelioid@gmail.com>
Description: Two principal tools are provided for the triadic analysis of affiliation networks: triad census and triadic closure. These include several variations on both classical tools tailored to affiliation network structure; see Opsahl (2013) <doi:10.1016/j.socnet.2011.07.001>, Liebig and Rao (2014) <doi:10.1109/SITIS.2014.15>, and Brunson (2015) <doi:10.1017/nws.2015.38>. Additional functions support manipulation of affiliation networks. Built on 'igraph' with new C++ calculations exposed via 'Rcpp'.
Depends: R (>= 3.5.0), igraph (>= 1.1.2)
Imports: MASS, Rcpp (>= 0.12.13)
LinkingTo: Rcpp
Suggests: knitr, testthat
License: GPL-2
Encoding: UTF-8
VignetteBuilder: knitr
Classification/MSC: 05C82, 91D30
URL: http://corybrunson.github.io/bitriad/
NeedsCompilation: yes
Packaged: 2026-06-24 22:07:27 UTC; jasoncorybrunson
Author: Jason Cory Brunson [aut, cre]
Repository: CRAN
Date/Publication: 2026-06-30 19:10:07 UTC

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New package baselinr with initial version 0.5.0
Package: baselinr
Title: WWC-Aligned Baseline Equivalence Tables for Education Impact Evaluations
Version: 0.5.0
Description: Produces report-ready baseline equivalence tables for impact evaluations in education research, following the conventions of the What Works Clearinghouse (WWC). Computes standardized mean differences (Hedges' g) between treatment and comparison groups for continuous covariates and classifies each covariate into the WWC baseline-equivalence categories (satisfied, satisfied with statistical adjustment, or not satisfied).
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-US
Imports: rlang, stats
Suggests: ggplot2, gt, knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
URL: https://github.com/zl1212-ship-it/baselinr, https://zl1212-ship-it.github.io/baselinr/
BugReports: https://github.com/zl1212-ship-it/baselinr/issues
Depends: R (>= 3.5)
LazyData: true
NeedsCompilation: no
Packaged: 2026-06-24 20:07:52 UTC; yuxialiang
Author: Yuxia Liang [aut, cre]
Maintainer: Yuxia Liang <zl1212@uw.edu>
Repository: CRAN
Date/Publication: 2026-06-30 19:00:07 UTC

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New package AutoStrataK with initial version 0.1.4
Package: AutoStrataK
Title: Automatic Optimal Stratification for Survey Sampling
Version: 0.1.4
Description: Provides tools for the automatic stratification of survey populations using clustering and optimization techniques. The package assists researchers and survey practitioners in constructing homogeneous strata to improve the efficiency and precision of survey estimates. Functions are provided for generating strata, evaluating stratification quality, summarizing stratified populations, and visualizing stratification results. These tools support the design and implementation of efficient survey sampling strategies. The package utilizes standard statistical methods from survey sampling, clustering, and optimization for automatic stratification. Methods are described in Cochran (1977, ISBN:9780471162405) and Lohr (2021, ISBN:9780367354556).
License: GPL-3
Encoding: UTF-8
Imports: dplyr, ggplot2, rlang, stats
Depends: R (>= 4.1.0)
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-06-25 06:07:03 UTC; Dr. Imtiyaz
Author: Khalid Islam [aut, cre]
Maintainer: Khalid Islam <drkhalidulislam@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-30 19:42:08 UTC

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New package ImprintCapASM with initial version 0.1.1
Package: ImprintCapASM
Title: Allele-Specific Methylation Analysis for Imprinted DMR Diagnostics
Version: 0.1.1
Description: Provides functions for SNP-phased allele-specific methylation (ASM) analysis across the 41 canonical human imprinted differentially methylated regions (DMRs). Reads are assigned to REF or ALT alleles based on bisulfite-aware SNP detection, enabling diagnosis of imprinting disorders from whole-genome bisulfite sequencing data. <https://github.com/19-saha/ImprintCapASM>.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: data.table, readxl, writexl, vcfR, ggplot2, Rsamtools, tools
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
SystemRequirements: samtools (>= 1.10)
VignetteBuilder: knitr
URL: https://github.com/19-saha/ImprintCapASM
BugReports: https://github.com/19-saha/ImprintCapASM/issues
NeedsCompilation: no
Packaged: 2026-06-24 17:26:10 UTC; subham_saha
Author: Subham Saha [aut, cre, cph], Francesco Cecere [aut], Frederic Brioude [aut, fnd]
Maintainer: Subham Saha <saha_19@outlook.com>
Repository: CRAN
Date/Publication: 2026-06-30 18:40:08 UTC

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New package delarr with initial version 0.1.0
Package: delarr
Title: Lazy Delayed Arrays with Fused Execution
Version: 0.1.0
Description: Provides a lightweight delayed array abstraction for lazy, fused evaluation of multi-dimensional numeric data. Compared with Bioconductor's 'DelayedArray', it offers a small S3 API with tidy-friendly verbs, chunked materialisation, and optional backends for HDF5, memory mapping, and shared-memory parallelism. Expression trees are optimised before streaming evaluation, and results can be written directly to disk without fully materialising arrays in memory.
URL: https://bbuchsbaum.github.io/delarr/, https://github.com/bbuchsbaum/delarr
BugReports: https://github.com/bbuchsbaum/delarr/issues
License: MIT + file LICENSE
Depends: R (>= 4.1)
Imports: rlang
Suggests: hdf5r, mmap, matrixStats, shard, testthat (>= 3.1.0), knitr, rmarkdown
VignetteBuilder: knitr
Encoding: UTF-8
Language: en-US
NeedsCompilation: yes
Packaged: 2026-06-24 18:22:09 UTC; bbuchsbaum
Author: Bradley Buchsbaum [aut, cre, cph]
Maintainer: Bradley Buchsbaum <brad.buchsbaum@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-30 18:40:02 UTC

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New package SimplexRegression with initial version 0.1.3
Package: SimplexRegression
Title: Simplex Regression Models with Parametric or Fixed Mean Link Functions
Version: 0.1.3
Author: Maria Eduarda da Cruz Justino [aut, cre] , Francisco Cribari-Neto [ctb, ths]
Maintainer: Maria Eduarda da Cruz Justino <eueduardacruz@gmail.com>
Description: Fits and analyzes simplex regression models with either fixed or parametric mean link functions. Implements the simplex probability density function, cumulative distribution function, quantile function, random number generation, and variance evaluation. Offers several fixed and parametric link functions for the mean submodel, tools for residual analysis and diagnostic plotting, hypothesis testing procedures, and influence measures such as Cook's distance and leverage (hat values). Includes the Scout Score (SS) criterion for model selection, enabling comprehensive inference and diagnostic analysis within the simplex regression framework. For more details see Barndorff-Nielsen and Jorgensen (1991) <doi:10.1016/0047-259X(91)90008-P> and Justino and Cribari-Neto (2026) <doi:10.1016/j.apm.2025.116713>.
License: MIT + file LICENSE
URL: https://github.com/dudajustino/SimplexRegression
BugReports: https://github.com/dudajustino/SimplexRegression/issues
Depends: R (>= 3.5)
Imports: Formula, lmtest, Matrix, pracma, sandwich
Suggests: knitr, moments, rmarkdown, spelling, testthat (>= 3.0.0), tseries
VignetteBuilder: knitr
Encoding: UTF-8
Language: en-US
LazyData: true
LazyDataCompression: xz
NeedsCompilation: no
Packaged: 2026-06-24 16:29:29 UTC; euedu
Repository: CRAN
Date/Publication: 2026-06-30 12:30:12 UTC

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New package seqcomp with initial version 0.1.0
Package: seqcomp
Title: Sequential Comparison of Probabilistic Forecasts
Version: 0.1.0
Description: Implements tools for sequential comparison of probabilistic forecasts, including binary and categorical scoring rules, anytime-valid confidence sequences, e-processes, Winkler-score comparisons, lag handling, and predictable-bound e-processes.
License: MIT + file LICENSE
URL: https://github.com/alasgarliakbar/seqcomp
BugReports: https://github.com/alasgarliakbar/seqcomp/issues
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: lamW
Suggests: scoringRules, VGAM, testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-06-24 15:35:04 UTC; hp
Author: Akbar Alasgarli [aut, cre]
Maintainer: Akbar Alasgarli <alasgarliakbar@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-30 12:20:02 UTC

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New package OptSurvCutR with initial version 0.10.0
Package: OptSurvCutR
Title: Optimal Survival Cut-Point Discovery for Time-to-Event Analysis with 'OptSurvCutR'
Version: 0.10.0
Description: Provides a robust workflow for optimal cut-point analysis in time-to-event ('survival') data. Functions determine the optimal number of cut-points via find_cutpoint_number(), find their precise locations via find_cutpoint() using systematic or genetic algorithms (via the 'rgenoud' package), and validate stability via bootstrapping using validate_cutpoint(). Features include covariate adjustment, parallel processing, and an extensible S3 plotting engine for clinical dashboards and diagnostics.
License: GPL-3
URL: https://github.com/paytonyau/OptSurvCutR, https://paytonyau.github.io/OptSurvCutR/
BugReports: https://github.com/paytonyau/OptSurvCutR/issues
Encoding: UTF-8
VignetteBuilder: knitr
Imports: cli, doParallel, doRNG, foreach, ggplot2, parallel, patchwork, Rcpp, rgenoud, rlang, stats, survival, survminer, tidyr
LinkingTo: Rcpp
Suggests: broom, dplyr, knitr, plotly, readxl, rmarkdown, spelling, testthat (>= 3.0.0), timeROC
Depends: R (>= 3.5)
Language: en-GB
NeedsCompilation: yes
Packaged: 2026-06-24 16:05:32 UTC; Payton
Author: Payton Yau [aut, cre, cph]
Maintainer: Payton Yau <tungon@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-30 12:20:26 UTC

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New package NeighborFinder with initial version 1.0.1
Package: NeighborFinder
Title: Find Neighbor Species of a Bacteria of Interest in the Human Gut Microbiota
Version: 1.0.1
Description: Implementation of the local approach described in Sola et al., 2026 <doi:10.64898/2025.12.05.692507> to identify companion species of a bacteria of interest. From several abundance tables of metagenomic data, 'NeighborFinder' suggests a shortlist of companion species based on the integration of results. A visualization via a network is proposed.
License: MIT + file LICENSE
Depends: R (>= 3.5.0)
Imports: dplyr, GGally, glmnet, glue, igraph, magrittr, Matrix, mvtnorm, network, purrr, rlang, sna, stats, stringr, tibble, tidyr, utils
Suggests: knitr, rmarkdown, testthat
VignetteBuilder: knitr
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2026-06-24 15:05:58 UTC; mmariadasso
Author: Mathilde Sola [aut, cre] , Mahendra Mariadassou [aut] , Magali Berland [aut]
Maintainer: Mathilde Sola <mathilde.sola@inrae.fr>
Repository: CRAN
Date/Publication: 2026-06-30 12:20:32 UTC

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New package dicepro with initial version 1.0.2
Package: dicepro
Title: Semi-Supervised Deconvolution of Bulk RNA-Seq Data with Hyperparameter Optimization
Version: 1.0.2
Description: Performs semi-supervised deconvolution of bulk RNA sequencing (RNA-seq) data. Known cell-type proportions are estimated using supervised methods -- 'CIBERSORTx' (CSx), 'CIBERSORT' (CS), 'FARDEEP' (Fast And Robust DEconvolution of Expression Profiles), and 'DCQ' (Digital Cell Quantifier) -- while unknown components are inferred using non-negative matrix factorization ('NMF') with limited-memory Broyden-Fletcher-Goldfarb-Shanno with bounds ('L-BFGS-B') optimization. Hyperparameters are selected automatically using a Pareto-frontier-based approach with knee-point detection, allowing application when the reference signature matrix is incomplete. More details about 'DICEpro' can be found in Ba et al. (2026) <doi:10.64898/2026.06.17.732876>.
Depends: R (>= 4.1.0)
Encoding: UTF-8
License: MIT + file LICENSE
LazyData: true
LazyDataCompression: xz
VignetteBuilder: knitr
LinkingTo: Rcpp (>= 1.0.12), RcppEigen
Imports: Rcpp (>= 1.0.12), lbfgsb3c, KraljicMatrix, ggplot2, patchwork, FARDEEP, ComICS, lme4, e1071, preprocessCore, parallel
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
URL: https://github.com/kalidouBA/dicepro
BugReports: https://github.com/kalidouBA/dicepro/issues
NeedsCompilation: yes
Packaged: 2026-06-24 10:46:56 UTC; kalidou
Author: Kalidou BA [aut, cre], Boris P. Hejblum [aut]
Maintainer: Kalidou BA <sistm.soft.maintain@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-30 12:20:14 UTC

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New package clusterIV with initial version 0.1.0
Package: clusterIV
Title: Clustered Jackknife Instrumental Variables Estimation
Version: 0.1.0
Description: Tools for instrumental variables estimation and inference under clustered errors with many instruments. The current release provides the cluster-jackknife IV estimator (CJIVE) of Frandsen, Leslie and McIntyre (2025) <doi:10.1162/rest.a.263> for a single endogenous regressor in a just-identified design, with cluster-robust inference: each observation's first-stage value is fitted leaving out its entire cluster, which removes the many-instrument bias that survives clustering. The leave-cluster-out fits use an exact Woodbury block update -- one factorisation of the instrument Gram matrix plus a small solve per cluster -- so the estimator scales to large samples. A companion 'iv_compare()' reports ordinary least squares, two-stage least squares, the observation-level jackknife and CJIVE on a common cluster-robust standard error.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: stats
URL: https://github.com/atal-kat/Clustered-Estimation-and-Inference
BugReports: https://github.com/atal-kat/Clustered-Estimation-and-Inference/issues
NeedsCompilation: no
Packaged: 2026-06-24 15:41:41 UTC; atalkatawazi
Author: Atal Katawazi [aut, cre]
Maintainer: Atal Katawazi <atalkatawazi@hotmail.com>
Repository: CRAN
Date/Publication: 2026-06-30 12:30:02 UTC

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New package caretMultimodal with initial version 1.0.0
Package: caretMultimodal
Title: Multimodal Late Fusion with 'caret'
Version: 1.0.0
Description: Extends the 'caret' framework to support late fusion workflows, enabling users to train models independently across multiple data modalities and combine their predictions into a single meta-model. Designed for developers, data scientists, and biomedical researchers alike, 'caretMultimodal' aims to make late fusion ensemble modelling as accessible and flexible as single-dataset workflows in 'caret'. Late fusion methods are based on Wolpert (1992) <doi:10.1016/S0893-6080(05)80023-1>.
License: MIT + file LICENSE
Encoding: UTF-8
Suggests: testthat (>= 3.0.0), randomForest, doParallel
Imports: caret, data.table, ggplot2, pROC, foreach, viridis, MultiAssayExperiment, glmnet
URL: https://github.com/CompBio-Lab/caretMultimodal, https://compbio-lab.github.io/caretMultimodal/
BugReports: https://github.com/CompBio-Lab/caretMultimodal/issues
Depends: R (>= 3.5)
LazyData: true
NeedsCompilation: no
Packaged: 2026-06-24 16:21:44 UTC; jpdyc
Author: Josh Dyce [aut, cre], Amrit Singh [aut]
Maintainer: Josh Dyce <jpdyce@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-30 12:30:07 UTC

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New package weightflow with initial version 0.1.0
Package: weightflow
Title: Declarative API for Staged Survey Weights
Version: 0.1.0
Description: Builds survey weights from design base weights by chaining hierarchical adjustments (unknown eligibility, nonresponse and calibration) through a declarative, pipeable, 'tidymodels'-style API. Calibration follows Deville and Sarndal (1992) <doi:10.2307/2290268>. Variances are obtained with a bootstrap that resamples primary sampling units and re-applies the whole recipe on each replicate, following the rescaling bootstrap of Rao and Wu (1988) <doi:10.1080/01621459.1988.10478591>, so the replicate weights carry the variability of every adjustment. The weights also bridge to the 'survey' and 'srvyr' packages for design-based inference.
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-US
Depends: R (>= 4.1.0)
Imports: stats, utils, graphics
Suggests: rpart, ranger, testthat (>= 3.0.0), survey, srvyr, dplyr, knitr, rmarkdown, spelling
URL: https://github.com/jpferreira33/weightflow, https://jpferreira33.github.io/weightflow/
BugReports: https://github.com/jpferreira33/weightflow/issues
LazyData: true
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-06-24 12:07:46 UTC; jp
Author: Juan Pablo Ferreira [aut, cre]
Maintainer: Juan Pablo Ferreira <juanpablo.ferreira@fcea.edu.uy>
Repository: CRAN
Date/Publication: 2026-06-30 11:30:02 UTC

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New package UKBAnalytica with initial version 1.0.0
Package: UKBAnalytica
Title: UK Biobank Data Processing and Survival Analysis Toolkit
Version: 1.0.0
Author: Nan He [aut, cre]
Maintainer: Nan He <hinna01@163.com>
Description: Provides an integrated workflow for UK Biobank Research Analysis Platform (RAP) hosted and RAP-generated analysis tables. The package supports RAP phenotype extraction planning, predefined variable sets and disease definitions, standardized baseline preprocessing, multi-source endpoint ascertainment, prevalent and incident case classification, survival-ready cohort construction, regression, multiple imputation, propensity score analysis, mediation analysis, subgroup and sensitivity analyses, machine learning, proteomics enrichment and protein-protein interaction analysis, and publication-oriented visualization. The package workflow is described in He et al. (2026) <doi:10.64898/2026.06.19.26356057>.
License: MIT + file LICENSE
Encoding: UTF-8
URL: https://github.com/Hinna0818/UKBAnalytica, https://hinna0818.github.io/UKBAnalytica/
BugReports: https://github.com/Hinna0818/UKBAnalytica/issues
Imports: data.table, stringi, ggplot2, rlang, scales, survival, pROC, tableone, mice, mitools, sandwich, lmtest, MASS, mgcv, xml2, igraph
Suggests: testthat, rms, gbm, cobalt, survminer, MatchIt, regmedint, ranger, xgboost, glmnet, e1071, nnet, rpart, Boruta, rBayesianOptimization, randomForestSRC, clusterProfiler, AnnotationDbi, org.Hs.eg.db, qs2
Depends: R (>= 4.0)
LazyData: true
NeedsCompilation: no
Packaged: 2026-06-24 04:06:19 UTC; hinna
Repository: CRAN
Date/Publication: 2026-06-30 11:00:07 UTC

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New package taxify with initial version 0.2.12
Package: taxify
Title: Offline Taxonomic Name Matching Against Local Darwin Core Snapshots
Version: 0.2.12
Description: Match taxonomic names against locally stored Darwin Core backbone databases ('WFO', 'COL', 'GBIF', 'ITIS', 'NCBI Taxonomy', 'Open Tree of Life', 'WoRMS', 'Species Fungorum', 'AlgaeBase'). Provides offline fuzzy and exact matching with synonym resolution, hybrid name detection, and a unified output schema across all sources. All heavy computation runs in the 'vectra' C11 columnar engine.
License: MIT + file LICENSE
URL: https://github.com/gcol33/taxify
BugReports: https://github.com/gcol33/taxify/issues
Additional_repositories: https://gcol33.r-universe.dev
Depends: R (>= 4.1.0)
Imports: curl, jsonlite, rlang, vectra
Suggests: DBI, knitr, openxlsx2, rmarkdown, RSQLite, taxifydb, testthat (>= 3.0.0), TR8
VignetteBuilder: knitr
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-06-24 12:03:56 UTC; Gilles Colling
Author: Gilles Colling [aut, cre, cph]
Maintainer: Gilles Colling <gilles.colling051@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-30 11:30:07 UTC

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New package svmodt with initial version 0.1.0
Package: svmodt
Title: Linear SVM-Based Recursive Decision Trees
Version: 0.1.0
Description: Implements Support Vector Machine Oblique Decision Trees (SVMODT). Recursively builds classification trees using linear Support Vector Machines (SVM) hyperplanes at each node instead of axis-parallel splits, creating oblique decision boundaries. Features include multiple feature selection methods, dynamic feature subset strategies, class weight support for imbalanced datasets, pruning and feature penalization.
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
Suggests: knitr, rmarkdown, bookdown, testthat (>= 3.0.0), rpart, rsample, gridExtra, tidyr, kableExtra, palmerpenguins, dplyr
VignetteBuilder: knitr
Depends: R (>= 3.5)
Imports: rlang, e1071, FSelectorRcpp, ggplot2
URL: https://github.com/AneeshAgarwala/svmodt
BugReports: https://github.com/AneeshAgarwala/svmodt/issues
NeedsCompilation: no
Packaged: 2026-06-24 09:10:26 UTC; AneeshAG
Author: Aneesh Agarwal [aut, cre, cph], Jack Jewson [aut, ths], Erik Sverdrup [aut, ths]
Maintainer: Aneesh Agarwal <aaga0022@student.monash.edu>
Repository: CRAN
Date/Publication: 2026-06-30 11:10:02 UTC

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New package HVS with initial version 1.0.0
Package: HVS
Title: Hypergraph Variable Selection
Version: 1.0.0
Description: Performs hypergraph-based setwise variable selection with false discovery rate control (Organ, Kenney & Gu, 2026, <doi:10.48550/arXiv.2606.20514>). The idea is, in addition to selecting individual predictors when there is sufficient evidence, to also test all pairs of predictors, and when there is insufficient evidence to be sure which is the true predictor, it will select possibly overlapping pairs, for which there is strong evidence that at least one is a true predictor. The method is designed to control a generalised false discovery rate, where discoveries are counted based on the number of independent sets. The function of this package is similar to the 'hypergraph.sizing' package, but this package is optimised for faster computation in the case where we test all pairs of predictors. The package also includes functions for counting independent sets in a graph or hypergraph, either exactly or approximately. There is also a very limited function for isotonic regression, whi [...truncated...]
Depends: R (>= 3.2.3)
License: GPL-3
Encoding: UTF-8
Imports:
NeedsCompilation: yes
Maintainer: Toby Kenney <tkenney@mathstat.dal.ca>
LinkingTo: Rcpp
Packaged: 2026-06-24 11:59:05 UTC; tkenney
Author: Toby Kenney [cre], Sarah Organ [aut]
Repository: CRAN
Date/Publication: 2026-06-30 11:30:20 UTC

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New package GSbench with initial version 0.1.0
Package: GSbench
Title: Benchmarking Genomic Selection and Machine-Learning Prediction Models
Version: 0.1.0
Description: A unified interface to fit, cross-validate and benchmark genomic prediction models from SNP marker data. It implements genomic best linear unbiased prediction (GBLUP) and ridge-regression BLUP in base R, and offers a common interface to machine-learning predictors (elastic net, random forest and gradient boosting) through optional packages, together with a stacked ensemble. Cross-validation uses breeding-relevant schemes and reports prediction accuracy honestly, so models can be compared fairly. The genomic relationship matrix follows VanRaden (2008) <doi:10.3168/jds.2007-0980>; the mixed-model solver follows Endelman (2011) <doi:10.3835/plantgenome2011.08.0024>; the genomic-selection framework follows Meuwissen, Hayes and Goddard (2001) <doi:10.1093/genetics/157.4.1819>.
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-GB
Depends: R (>= 4.1.0)
Imports: graphics, stats, withr
Suggests: rrBLUP, glmnet, ranger, xgboost, testthat (>= 3.0.0), knitr, rmarkdown, spelling
VignetteBuilder: knitr
URL: https://github.com/mqfarooqi1/GSbench
BugReports: https://github.com/mqfarooqi1/GSbench/issues
NeedsCompilation: no
Packaged: 2026-06-24 13:09:50 UTC; faroo
Author: Muhammad Farooqi [aut, cre]
Maintainer: Muhammad Farooqi <mqfarooqi@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-30 11:40:02 UTC

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New package GMLTM with initial version 0.1.0
Package: GMLTM
Title: Generalized Multicomponent Latent Trait Model for Diagnosis
Version: 0.1.0
Description: Provides Bayesian estimation of Item Response Theory models that decompose item difficulty into cognitive operations or rules. Implements the Linear Logistic Test Model (LLTM; Fischer (1973) <doi:10.1016/0001-6918(73)90003-6>), the Multicomponent Latent Trait Model for Diagnosis (MLTM-D; Embretson and Yang (2013) <doi:10.1007/s11336-012-9296-y>), and the Generalized Multicomponent Latent Trait Model for Diagnosis (GMLTM-D; Ramirez et al. (2024) <doi:10.3390/jintelligence12070067>). All models are estimated via Hamiltonian Monte Carlo using 'Stan' through the 'rstan' interface. Includes tools for model validation, reliability estimation, and visualization of item characteristic curves. Supports user-defined prior distributions for all model parameters.
License: GPL (>= 3)
URL: https://github.com/Eduar-Ramirez/GMLTM-D
BugReports: https://github.com/Eduar-Ramirez/GMLTM-D/issues
Encoding: UTF-8
LazyData: true
Depends: R (>= 4.1.0)
Imports: rstan (>= 2.21.0), ggplot2, gridExtra, grid, utils, parallel, loo, RColorBrewer
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
SystemRequirements: C++17, GNU make
VignetteBuilder: knitr
Language: en-US
NeedsCompilation: no
Packaged: 2026-06-24 13:17:06 UTC; eduarramirezriveros
Author: Eduar Ramirez [aut, cre], Marcos Jimenez [aut], Vithor R. Franco [aut], Jesus Alvarado [aut]
Maintainer: Eduar Ramirez <edrami02@ucm.es>
Repository: CRAN
Date/Publication: 2026-06-30 11:40:07 UTC

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New package DSGEr with initial version 1.3.1
Package: DSGEr
Title: Transcriptional Disruption Score for Gene Sets
Version: 1.3.1
Description: Computes pathway-level transcriptional disruption scores from differential expression p-values using permutation tests with Generalized Pareto Distribution (GPD) tail extrapolation and false discovery rate (FDR) correction. Reference: Guo P, Li H (2026) DSGE: Disruption Score of Gene Expression for Gene-Set Enrichment Analysis. <https://github.com/LHJLab/DSGE>.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: data.table, evd, methods, POT, Rcpp
LinkingTo: Rcpp
Suggests: AnnotationDbi, GO.db
Enhances: KEGGREST, org.Hs.eg.db, reactome.db
NeedsCompilation: yes
Packaged: 2026-06-24 03:19:16 UTC; Lenovo
Author: Pingwei Guo [aut, cre], Huijuan Li [aut]
Maintainer: Pingwei Guo <1489413126@qq.com>
Repository: CRAN
Date/Publication: 2026-06-30 11:00:21 UTC

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New package cp1919 with initial version 0.1
Package: cp1919
Title: Radio Observations of the Pulse Profiles and Dispersion Measures of Twelve Pulsars
Description: Successive pulses from CP 1919, the first pulsar discovered. The pulses occur every 1.337 seconds. They are caused by rapidly spinning neutron star.
Version: 0.1
Suggests: roxygen2
Depends: R(>= 4.0.0)
License: CC0
BugReports: https://github.com/pachadotdev/cp1919/issues
URL: https://github.com/pachadotdev/cp1919
Encoding: UTF-8
NeedsCompilation: yes
LazyData: true
Packaged: 2026-06-24 10:37:37 UTC; pacha
Author: Mauricio Vargas Sepulveda [aut, cre]
Maintainer: Mauricio Vargas Sepulveda <m.vargas.sepulveda@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-30 11:10:08 UTC

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New package CbKST with initial version 0.1-0
Package: CbKST
Title: Competence-Based Knowledge Space Theory
Date: 2026-06-19
Version: 0.1-0
Description: Competence-based knowledge space theory (CbKST) is an extension of knowledge space theory (KST) modeling the latent skills and competencies underlying the observable response behaviour as described by Heller & Stefanutti (2024) <doi:10.1142/9789811280481_0001>. The package focuses on the mappings between competence and performance ledvel (skill (multi) map, problem function etc.).
License: GPL-3
Depends: R (>= 4.5.0)
Imports: readODS, openxlsx, tools, kstMatrix (>= 2.3-3)
Suggests: litedown
Repository: CRAN
Encoding: UTF-8
LazyData: true
VignetteBuilder: litedown
NeedsCompilation: no
Packaged: 2026-06-24 11:45:24 UTC; cord
Author: Cord Hockemeyer [aut, cre]
Maintainer: Cord Hockemeyer <cord.hockemeyer@uni-graz.at>
Date/Publication: 2026-06-30 11:20:02 UTC

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New package TemporalModelR with initial version 0.2.0
Package: TemporalModelR
Title: Temporally Explicit Species Distribution Modelling
Version: 0.2.0
Description: Increases the ease of implementing a temporally-explicit modeling methodology when building ecological niche and species distribution models. Provides functions to assist with three major steps of temporally-explicit models: (i) preprocessing species and environmental data and generating suitable background or pseudoabsence data, (ii) building a niche model and generating temporally-explicit predictions from that model, and (iii) model postprocessing to explore spatiotemporal trends in model predictions. Methodological and theoretical foundations are described in Ingenloff and Peterson (2021) <doi:10.1111/2041-210X.13564>, Franklin (2010, ISBN:9780521700023), Peterson et al. (2011, ISBN:9780691136882), Blonder (2018) <doi:10.1111/ecog.03187>, Senay et al. (2013) <doi:10.1371/journal.pone.0071218>, and Li and Zhang (2024) <doi:10.48550/arXiv.2404.05933>.
URL: https://github.com/CJHughes926/TemporalModelR, https://cjhughes926.github.io/TemporalModelR/
BugReports: https://github.com/CJHughes926/TemporalModelR/issues
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Depends: R (>= 4.1)
Imports: deldir, graphics, grDevices, sf, stats, terra, tools, utils, exactextractr
Suggests: fastcpd, ggplot2, hypervolume, knitr, mgcv, randomForest, RColorBrewer, rmarkdown, scatterpie
VignetteBuilder: knitr
Language: en-US
NeedsCompilation: no
Packaged: 2026-06-23 20:27:30 UTC; Conno
Author: Connor Hughes [aut, cre] , Mariana Castaneda-Guzman [aut] , Luis E. Escobar [aut]
Maintainer: Connor Hughes <connorhughes926@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-30 10:40:19 UTC

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New package steves with initial version 0.1.1
Package: steves
Title: Rick Steves' Europe Episodes for Teaching Data Analysis
Version: 0.1.1
Description: Tidy snapshot of every episode of the public-television travel series 'Rick Steves' Europe' (2000-2025), enriched with IMDB ratings, geocoded destinations, ISO country codes, episode thumbnails, and descriptive summaries. Designed as a companion dataset for introductory data analysis and visualization in the spirit of the 'moderndive' textbook: every row is an episode, every column is a candidate for a plot or a join. Compiled from public sources for teaching purposes; not an official or verified 'Rick Steves' Europe' dataset, and shared with the permission of the Rick Steves' Europe team.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Depends: R (>= 4.1)
Suggests: dplyr, forcats, ggplot2, knitr, leaflet, maps, rmarkdown, tibble
URL: https://moderndive.github.io/steves/, https://github.com/moderndive/steves
BugReports: https://github.com/moderndive/steves/issues
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-06-23 19:15:21 UTC; chesterismay
Author: Chester Ismay [aut, cre]
Maintainer: Chester Ismay <chester.ismay@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-30 10:40:02 UTC

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New package porter with initial version 0.1.0
Package: porter
Title: Generate Port Files for C Libraries
Version: 0.1.0
Description: Generate port files for foreign function interfaces to C libraries by parsing C-family header files with 'CastXML'.
License: MIT + file LICENSE
URL: https://github.com/hongyuanjia/porter
BugReports: https://github.com/hongyuanjia/porter/issues
SystemRequirements: CastXML
Encoding: UTF-8
Depends: R (>= 3.6.0)
Imports: xml2
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-06-23 18:40:32 UTC; hongyuanjia
Author: Hongyuan Jia [aut, cre, cph]
Maintainer: Hongyuan Jia <hongyuanjia@cqust.edu.cn>
Repository: CRAN
Date/Publication: 2026-06-30 10:30:08 UTC

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New package PITS with initial version 0.1.0
Package: PITS
Title: Power of Interrupted Time Series (ITS) Studies
Version: 0.1.0
Description: Provides tools for estimating the statistical power of Interrupted Time Series (ITS) designs, with a focus on healthcare applications. The package supports prospective power calculations before a study begins, and retrospective assessments of whether a completed study was adequately powered. It includes functions to estimate nuisance parameters (baseline, residual standard deviation, autocorrelation) from data observed before the intervention, and to estimate power via Monte Carlo simulation for single-site and multi-site designs. Utility functions for design optimisation sweeps and publication- ready plots are also provided.
License: MIT + file LICENSE
Language: en-GB
Encoding: UTF-8
Depends: R (>= 4.0.0)
Imports: nlme, stats, graphics, grDevices, utils
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
LazyData: true
URL: https://github.com/drdaviddelorenzo/PITS
BugReports: https://github.com/drdaviddelorenzo/PITS/issues
NeedsCompilation: no
Packaged: 2026-06-23 16:20:24 UTC; daviddelorenzo
Author: David de Lorenzo [aut, cre] )
Maintainer: David de Lorenzo <drdaviddelorenzo@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-30 10:10:02 UTC

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New package okf with initial version 0.5.2
Package: okf
Title: Open Knowledge Format (OKF) Ingestion
Version: 0.5.2
Description: Read, validate, and load Open Knowledge Format (OKF) bundles (a directory of markdown files with YAML frontmatter) into a portable DuckDB catalog, build the concept graph, render to HTML, and optionally embed concept bodies for semantic search. Deterministic and agent-free: the same bundle always yields the same catalog, graph, and render, with no LLM calls in the core. Conformant and permissive per the OKF v0.1 specification.
License: Apache License (>= 2)
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: yaml, DBI, duckdb, digest, jsonlite, utils
Suggests: httr2, commonmark, testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-06-23 21:20:30 UTC; tsj_j
Author: Travis Jakel [aut, cre]
Maintainer: Travis Jakel <travis.s.jakel@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-30 10:40:07 UTC

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New package ernest with initial version 1.2.4
Package: ernest
Title: A Toolkit for Nested Sampling
Version: 1.2.4
Description: Bayesian evidence estimation and posterior inference with the nested sampling algorithm, described in Skilling (2006) <doi:10.1214/06-BA127> and Buchner (2023) <doi:10.1214/23-SS144>, along with S3 methods for simulating uncertainty and creating visualisations.
License: GPL (>= 3)
URL: https://github.com/ropensci/ernest, https://docs.ropensci.org/ernest/
BugReports: https://github.com/ropensci/ernest/issues
Depends: R (>= 4.1.0)
Imports: cli, generics, ggplot2, lifecycle, matrixStats, posterior, rlang (>= 1.1.0), vctrs, withr
Suggests: brms, distributional, extraDistr, ggdist, knitr, mvtnorm, patchwork, rmarkdown, testthat (>= 3.0.0), tidyselect, uniformly, vdiffr, xml2
LinkingTo: cpp11, cpp11eigen, testthat
VignetteBuilder: knitr
Encoding: UTF-8
LazyData: true
NeedsCompilation: yes
Packaged: 2026-06-23 17:42:20 UTC; ksnap
Author: Kyle Dewsnap [aut, cre, cph] , TJ Mahr [rev], Robert Kubinec [rev], Michael Hughes [cph]
Maintainer: Kyle Dewsnap <kyle.dewsnap@ubc.ca>
Repository: CRAN
Date/Publication: 2026-06-30 10:40:12 UTC

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New package BioTooltipR with initial version 0.1.0
Package: BioTooltipR
Title: Add Bio Tooltips to HTML Reports
Version: 0.1.0
Description: Provides lightweight helpers for adding gene and chemical tooltips to R Markdown, Quarto, Shiny, pkgdown, and other HTML outputs. The package emits small HTML spans with module-specific data attributes and attaches the browser-side 'bio-tooltips' JavaScript and CSS assets through 'htmltools'. Entity lookup and rendering are handled in the browser by 'bio-tooltips'; this package does not query biological databases from R during package checks.
Language: en-US
License: MIT + file LICENSE
URL: https://github.com/mattjmeier/BioTooltipR
BugReports: https://github.com/mattjmeier/BioTooltipR/issues
Encoding: UTF-8
Depends: R (>= 4.1)
Imports: htmltools, jsonlite, knitr, utils
Suggests: DT, htmlwidgets, plotly, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-06-23 15:59:26 UTC; matt
Author: Matthew J. Meier [aut, cre]
Maintainer: Matthew J. Meier <matthew.meier@hc-sc.gc.ca>
Repository: CRAN
Date/Publication: 2026-06-30 10:10:09 UTC

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Mon, 29 Jun 2026

New package shinyReports with initial version 1.0.3
Package: shinyReports
Title: R Markdown HTML Tab Rendering for Shiny
Version: 1.0.3
Description: Render R Markdown reports to HTML and display them instantly in a new browser tab from within a 'shiny' application. Replaces file downloads with a seamless in-browser approach.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: rmarkdown, shiny
Suggests: htmltools, knitr, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-06-23 12:53:43 UTC; alexa
Author: Alexander Sadler [aut, cre], Kirsty Twigger [ctb]
Maintainer: Alexander Sadler <alexander@apexomic.com>
Repository: CRAN
Date/Publication: 2026-06-29 14:40:02 UTC

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New package mapsf.gui with initial version 0.1.0
Package: mapsf.gui
Title: Create Thematic Maps Interactively
Version: 0.1.0
Description: A 'Shiny' application to create thematic maps interactively, based on the 'mapsf' package. Features include: a user-friendly interface to create and customize thematic maps without coding, support for various map types (choropleth, proportional symbols, etc.) and customization options (colors, legends, etc.), R code generation to ensure reproducibility and export options to save maps in different formats (PNG, SVG).
License: GPL (>= 3)
URL: https://codeberg.org/riatelab/mapsf.gui, https://riatelab.r-universe.dev/mapsf.gui
BugReports: https://codeberg.org/riatelab/mapsf.gui/issues
Depends: R (>= 4.0.0)
Imports: base64enc, bslib (>= 0.10.0), colourpicker, Ckmeans.1d.dp, DT, formatR, jpeg, graphics, grDevices, htmltools, mapsf (>= 1.2.1), phosphoricons, png, sf, shiny (>= 1.12.0), shinyjs (>= 2.0.0), shiny.i18n, sortable, stats, utils
Language: en-US
Encoding: UTF-8
Suggests: shinytest2, testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-06-23 12:30:09 UTC; mthh
Author: Matthieu Viry [cre, aut] , Timothee Giraud [aut] , Hugues Pecout [aut]
Maintainer: Matthieu Viry <matthieu.viry@cnrs.fr>
Repository: CRAN
Date/Publication: 2026-06-29 14:20:02 UTC

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New package wompwomp with initial version 0.99.0
Package: wompwomp
Version: 0.99.0
Date: 2026-06-23
Title: Optimizing Alluvial Plots
Description: Sort k-partite graphs with node order, layer order, and node grouping optimized with a heuristic to (nearly) minimize edge crossings. Useful for improving visualizations with alluvial plots by "untangling" the graphs.
License: MIT + file LICENSE
Encoding: UTF-8
VignetteBuilder: knitr
Imports: dplyr, igraph, tibble, rlang, tidyr, purrr, TSP, R6, stats, tidyselect, vctrs, utils
Depends: R (>= 4.1.0)
Suggests: testthat, vdiffr, magick, knitr, rmarkdown, gtools, mclust, here, stringr, reticulate, ggplot2, ggalluvial, sessioninfo
URL: https://github.com/pachterlab/wompwomp
BugReports: https://github.com/pachterlab/wompwomp/issues
NeedsCompilation: no
Packaged: 2026-06-23 09:38:00 UTC; joeyrich
Author: Joseph Rich [aut, cre] , Conrad Oakes [aut], Lior Pachter [aut]
Maintainer: Joseph Rich <jmrich@caltech.edu>
Repository: CRAN
Date/Publication: 2026-06-29 13:50:02 UTC

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New package R2camtrapdp with initial version 2.0.0
Package: R2camtrapdp
Title: Convert Camera Trap Dataset to 'Camtrap DP'
Version: 2.0.0
Description: Builds Camera Trap Data Packages ('Camtrap DP') from arbitrary spreadsheets in a schema-driven way: table structure, types, constraints and relations are read from the 'Frictionless' table schemas of the requested 'Camtrap DP' version, so any version and custom columns are handled automatically. Provides validation against the schemas and an optional bridge to the 'frictionless' 'Python' framework. The 'Camtrap DP' standard is described in Bubnicki et al. (2023) <doi:10.1002/rse2.374>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: R6, jsonlite, tibble, magrittr, lubridate, dplyr, tidyr, purrr, readr, httr, taxadb, stats, utils
Suggests: camtrapdp, knitr, rmarkdown, testthat (>= 3.0.0), jsonvalidate, spelling
VignetteBuilder: knitr
Depends: R (>= 3.5.0)
SystemRequirements: Python (>= 3.8) with the 'frictionless' package (optional; only for validate_frictionless()) Config/testthat/edition: 3
URL: https://github.com/kfukasawa37/R2camtrapdp
BugReports: https://github.com/kfukasawa37/R2camtrapdp/issues
Language: en-US
NeedsCompilation: no
Packaged: 2026-06-23 02:23:45 UTC; Kana Terayama
Author: Kana Terayama [aut, cre] , Keita Fukasawa [aut]
Maintainer: Kana Terayama <terayama.kana@nies.go.jp>
Repository: CRAN
Date/Publication: 2026-06-29 13:00:48 UTC

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New package PsychoMatic with initial version 0.3.0
Package: PsychoMatic
Title: Automated Psychometric Workflows and Reporting Tools
Version: 0.3.0
Description: Automates common psychometric workflows for applied researchers, including item descriptives, inter-item correlations, exploratory and confirmatory factor analysis, reliability, multi-group measurement invariance, and alignment optimization. Decision heuristics are informed by procedures such as parallel analysis (Horn, 1965, <doi:10.1007/BF02289447>), multivariate normality diagnostics (Mardia, 1970, <doi:10.1093/biomet/57.3.519>), measurement-invariance fit-change rules (Chen, 2007, <doi:10.1080/10705510701301834>), and alignment optimization (Asparouhov and Muthen, 2014, <doi:10.1080/10705511.2014.919210>), among others. Results can be returned as structured R objects and exported as bilingual reports for transparent analytical documentation.
License: MIT + file LICENSE
URL: https://github.com/gmoncayoj/PsychoMatic
BugReports: https://github.com/gmoncayoj/PsychoMatic/issues
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: GPArotation, lavaan, Matrix, psych, stats, utils
Suggests: flextable, knitr, mirt, MVN, officer, openxlsx, rmarkdown, semTools, sirt, testthat (>= 3.0.0), writexl
VignetteBuilder: knitr
LazyData: true
NeedsCompilation: no
Packaged: 2026-06-23 01:51:06 UTC; JoseGM
Author: Jose Gamarra-Moncayo [aut, cre]
Maintainer: Jose Gamarra-Moncayo <gamarramoncayoj@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-29 13:00:55 UTC

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New package hubEvals with initial version 0.3.0
Package: hubEvals
Title: Tools for Scoring and Evaluating Hubverse Model Outputs
Version: 0.3.0
Description: Provides tools for scoring and evaluating 'hubverse' model outputs against observed data, wrapping scoring workflows from the 'scoringutils' package and bridging hubverse model output formats to 'scoringutils' forecast classes.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: cli, dplyr, hubUtils (>= 1.2.0), purrr, rlang, scoringutils (>= 2.2.0), tibble
URL: https://hubverse-org.github.io/hubEvals/, https://github.com/hubverse-org/hubEvals
BugReports: https://github.com/hubverse-org/hubEvals/issues
Additional_repositories: https://hubverse-org.r-universe.dev
Depends: R (>= 4.1.0)
Suggests: hubExamples, knitr, rmarkdown, testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-06-23 08:28:43 UTC; Anna
Author: Anna Krystalli [aut, cre] , Nicholas Reich [aut] , Evan Ray [aut], Nikos Bosse [aut] , Kimberlyn Roosa [aut], Zhian Kamvar [ctb] , Li Shandross [ctb] , Becky Sweger [ctb], Lucie Contamin [ctb], Consortium of Infectious Disease Modeling Hubs [cph]
Maintainer: Anna Krystalli <annakrystalli@googlemail.com>
Repository: CRAN
Date/Publication: 2026-06-29 13:40:02 UTC

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New package fz with initial version 1.1
Package: fz
Title: R Wrapper for the 'funz-fz' Parametric Simulation Framework
Version: 1.1
Description: Provides R bindings to the 'funz-fz' Python package using 'reticulate'. The 'fz' framework wraps arbitrary simulation codes to run parameter sweeps, design-of-experiments studies, and iterative algorithm-driven analyses by substituting variable placeholders in text input files and collecting outputs into data frames. Calculators can run locally (shell), over SSH, or on 'SLURM' clusters. See <https://github.com/Funz/fz> for the underlying framework.
License: BSD_3_clause + file LICENSE
Encoding: UTF-8
Language: en-US
SystemRequirements: Python (>= 3.8), funz-fz Python package
Imports: reticulate (>= 1.28)
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
URL: https://github.com/Funz/fz.R
BugReports: https://github.com/Funz/fz.R/issues
NeedsCompilation: no
Packaged: 2026-06-22 20:39:38 UTC; richet
Author: Yann Richet [aut, cre]
Maintainer: Yann Richet <yann.richet@asnr.fr>
Repository: CRAN
Date/Publication: 2026-06-29 13:30:02 UTC

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New package ecpromethee with initial version 0.1.0
Package: ecpromethee
Title: EC-PROMETHEE Multi-Criteria Decision Method
Version: 0.1.0
Description: Implements the EC-PROMETHEE multi-criteria decision method described by Basilio, Pereira and Yigit (2023) <doi:10.3390/math11214432>. The method combines objective criteria weights from ENTROPY and CRITIC with optional subjective weights, generates random normalized weights inside criterion-specific ranges, and aggregates repeated PROMETHEE II rankings into a final score.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-06-23 02:01:23 UTC; marci
Author: Marcio Basilio [aut, cre], Valdecy Pereira [aut], Fatih Yigit [aut]
Maintainer: Marcio Basilio <marciopbasilio@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-29 13:00:35 UTC

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New package amorem with initial version 1.0.0
Package: amorem
Title: Augmented Modelling of Relational Events
Version: 1.0.0
Description: Utilities for simulating and prototyping relational event models, including helpers to generate dynamic event sequences and covariate processes for sender and receiver sets. The endogenous-effect and case-control estimation machinery follows Juozaitiene and Wit (2024) <doi:10.1093/jrsssa/qnae132>.
License: MIT + file LICENSE
Depends: R (>= 4.2.0)
URL: https://franciscorichter.github.io/amorem/, https://github.com/franciscorichter/amorem
Imports: splines, stats, Rcpp, survival, withr
LinkingTo: Rcpp
Suggests: torch, testthat (>= 3.1.0), mgcv, coxme, roxygen2 (>= 7.3.0), pkgdown (>= 2.0.0), knitr, rmarkdown
Encoding: UTF-8
LazyData: true
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2026-06-22 19:25:02 UTC; pancho
Author: Francisco Richter [aut, cre], Martina Boschi [aut], Ernst C. Wit [aut], Melania Lembo [aut]
Maintainer: Francisco Richter <richtf@usi.ch>
Repository: CRAN
Date/Publication: 2026-06-29 13:50:12 UTC

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New package gp3tools with initial version 1.0.1
Package: gp3tools
Title: Import, Inspect, Analyse, and Report Gazepoint GP3 Exports
Version: 1.0.1
Description: Imports, inspects, cleans, summarises, models, and reports Gazepoint GP3 and Gazepoint Analysis CSV exports. Supports offline workflows for all-gaze, fixation, pupil, area-of-interest, transition, time-course, quality-audit, and manuscript-reporting analyses.
License: MIT + file LICENSE
LazyData: true
Encoding: UTF-8
Language: en-US
Depends: R (>= 4.1.0)
Imports: dplyr, ggplot2, readr, rlang, stringr, tibble, tidyr, withr
Suggests: DHARMa, emmeans, eyetools, glmmTMB, knitr, lme4, magick, mgcv, pracma, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
URL: https://github.com/stefanosbalaskas/gp3tools
BugReports: https://github.com/stefanosbalaskas/gp3tools/issues
NeedsCompilation: no
Packaged: 2026-06-22 20:33:54 UTC; Stefanos-PC
Author: Stefanos Balaskas [aut, cre]
Maintainer: Stefanos Balaskas <s.balaskas@ac.upatras.gr>
Repository: CRAN
Date/Publication: 2026-06-29 12:50:07 UTC

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New package fibr with initial version 0.1.1
Package: fibr
Title: Prior-Fraction Diagnostics for Hierarchical Models
Version: 0.1.1
Description: Computes the prior fraction, the per-group pooling or shrinkage factor, for hierarchical models, including directly from 'brms' fits. For each group-level coefficient the prior fraction is the share of the posterior precision contributed by the shrinkage prior relative to the likelihood; values near one indicate a coefficient that is prior-dominated (the centring/non-centring funnel regime), values near zero indicate a likelihood-dominated coefficient that is well identified from the data. These quantities are invisible to standard convergence diagnostics such as R-hat and effective sample size, and they indicate where a non-centred reparameterisation is likely to help. A companion advisor reports the same decomposition for changepoint random effects fitted with 'smoothbp'. The underlying geometry (the Fisher-metric connection on the base-fiber split, for which this connection is flat so the obstruction is statistical rather than geometric) is described in Bindoff (2026) <doi:10.528 [...truncated...]
License: MIT + file LICENSE
URL: https://github.com/ABindoff/fibr, https://doi.org/10.5281/zenodo.20724550
BugReports: https://github.com/ABindoff/fibr/issues
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: posterior (>= 1.4.0), ggplot2
Suggests: brms, smoothbp, cmdstanr, testthat (>= 3.0.0)
Additional_repositories: https://stan-dev.r-universe.dev
SystemRequirements: Cargo (Rust's package manager), rustc >= 1.65.0, xz
NeedsCompilation: no
Packaged: 2026-06-22 22:44:16 UTC; bindoffa
Author: Aidan D Bindoff [aut, cre]
Maintainer: Aidan D Bindoff <aidan.bindoff@utas.edu.au>
Repository: CRAN
Date/Publication: 2026-06-29 12:50:19 UTC

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Fri, 26 Jun 2026

New package egfr with initial version 1.1.1
Package: egfr
Title: Estimated Glomerular Filtration Rate (eGFR) Calculators
Version: 1.1.1
Description: A comprehensive, vectorised toolkit for estimating glomerular filtration rate (eGFR) and creatinine clearance from serum creatinine, cystatin C, or both. Implements adult, paediatric, and neonatal equations, including the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equations (2009, 2012, 2021), the Modification of Diet in Renal Disease (MDRD) Study equation, Cockcroft-Gault, the European Kidney Function Consortium (EKFC) equations, the Full Age Spectrum (FAS) equations, the Lund-Malmoe equations, the Berlin Initiative Study (BIS) equations, the Schwartz bedside equation, the Chronic Kidney Disease in Children Under 25 (CKiD U25) equations, the Caucasian, Asian, Paediatric, and Adult (CAPA) cystatin C equation, and a neonatal equation. Helpers for body surface area, chronic kidney disease (CKD) staging following the Kidney Disease: Improving Global Outcomes (KDIGO) guideline, and unit conversions are included. Methods are described in Levey et al. (2009) <doi:10.7326/ [...truncated...]
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.0)
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
URL: https://github.com/mhovd/egfr, https://mhovd.github.io/egfr/
BugReports: https://github.com/mhovd/egfr/issues
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-06-22 18:53:37 UTC; marku
Author: Markus Hovd [aut, cre, cph]
Maintainer: Markus Hovd <markus@hovd.io>
Repository: CRAN
Date/Publication: 2026-06-26 11:20:02 UTC

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New package dwmmlRidge with initial version 0.1.1
Package: dwmmlRidge
Title: Dynamically Weighted Modified Maximum Likelihood (DWMML) Ridge Regression
Version: 0.1.1
Description: Implements the dynamically weighted modified maximum likelihood ridge (DWMMLR) regression estimator, a robust and multicollinearity-aware linear regression estimator that combines the DWMML3 weighting procedure of Sazak (2019) <doi:10.1080/00949655.2019.1571060> with ridge penalization to address both outlier sensitivity and variance inflation due to multicollinearity. The ridge parameter is selected automatically using the approach implemented in the 'ridgregextra' package (Karadag, Sazak, and Aydin, 2023) <https://CRAN.R-project.org/package=ridgregextra>, described further in Karadag, Sazak, and Aydin (2026) <doi:10.1080/02664763.2026.2655681>, which targets a variance inflation factor (VIF) close to but not below 1, removing the need for manual tuning. Returns comprehensive outputs (coefficients, fitted values, residuals, mean squared error (MSE), standard errors, R-squared, and adjusted R-squared) through a simple x/y interface.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.0.0)
Imports: MASS, stats, Styperidge.reg
Suggests: isdals, mctest
Enhances: ridgregextra
URL: https://github.com/filizkrdg/dwmmlRidge
BugReports: https://github.com/filizkrdg/dwmmlRidge/issues
NeedsCompilation: no
Packaged: 2026-06-22 18:02:59 UTC; pc
Author: Filiz Karadag [aut, cre] , Hakan Savas Sazak [aut] , Olgun Aydin [aut]
Maintainer: Filiz Karadag <filiz.karadag@ege.edu.tr>
Repository: CRAN
Date/Publication: 2026-06-26 10:10:02 UTC

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New package SNPkit with initial version 0.1.0
Package: SNPkit
Title: S4 Tools for Reading and Organizing Genetic Data
Version: 0.1.0
Description: Provides an integrated suite of tools for handling single nucleotide polymorphism (SNP) genotype data in large-scale genetic studies. Supports importing and merging genotype files, performing quality control on SNP markers and samples, and preparing data for downstream analyses using popular software such as 'FImpute' and 'PLINK'. Offers S4 classes and methods to efficiently encapsulate SNP data, along with utilities for generating genotype summary statistics and visualization. Additional functionalities include anticlustering approaches for batch effect control, automated script generation for external software, and streamlined workflows for large datasets commonly encountered in animal and plant breeding programs. Designed to facilitate reproducible and scalable SNP data analyses in quantitative and statistical genetics.
Depends: R (>= 4.1.0)
Imports: methods, ggplot2, dplyr, data.table, Rcpp, stringi, anticlust, grDevices, graphics, stats, utils, MASS, snpStats, magrittr, reshape2
LinkingTo: Rcpp
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
Encoding: UTF-8
License: GPL-3
URL: https://viniciusjunqueira.github.io/SNPkit/, https://github.com/viniciusjunqueira/SNPkit
BugReports: https://github.com/viniciusjunqueira/SNPkit/issues
NeedsCompilation: yes
Packaged: 2026-06-22 15:01:21 UTC; viniciusjunqueira
Author: Vinicius Junqueira [aut, cre], Roberto Higa [aut], Fernando Flores Cardoso [aut], Marcos Jun Iti Yokoo [aut]
Maintainer: Vinicius Junqueira <junqueiravinicius@hotmail.com>
Repository: CRAN
Date/Publication: 2026-06-26 09:40:08 UTC

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New package skymodelr with initial version 0.3.1
Package: skymodelr
Title: Generates and Samples Realistic Terrestrial Atmospheres
Version: 0.3.1
Description: Generates physically based sky environment maps and radiance samples using the spectral Hosek-Wilkie and Prague atmosphere models. Functions write high-dynamic-range 'OpenEXR' domes in latitude-longitude projections, compute per-direction RGB or 55-channel values, and optionally composite time-accurate star fields and moon phases. Features include automatic sun and moon positioning from date, time and location, support for sea-level and high-altitude observers, wide-spectrum coefficients, and multithreaded C++ acceleration for fast, high-resolution output. For model details, see Hosek and Wilkie (2012) <doi:10.1145/2185520.2185591>, Hosek and Wilkie (2013) <doi:10.1109/MCG.2013.18>, Wilkie et al. (2021) <doi:10.1145/3450626.3459758>, and Vevoda et al. (2022) <doi:10.1111/cgf.14677>.
License: GPL-3
Copyright: file inst/COPYRIGHTS
Depends: R (>= 4.3.0)
Imports: Rcpp, swephR, rayvertex (>= 0.14.0), rayimage (>= 0.24.1)
LinkingTo: Rcpp, RcppThread, libimath, libopenexr
Encoding: UTF-8
LazyData: true
Suggests: testthat (>= 3.0.0), rayrender (>= 0.40.1)
URL: https://www.skymodelr.com
BugReports: https://github.com/tylermorganwall/skymodelr/issues
NeedsCompilation: yes
Packaged: 2026-06-21 23:38:46 UTC; tyler
Author: Tyler Morgan-Wall [aut, cre, cph], Petr Vevoda [ctb], Charles University [cph], Eric Bruneton [ctb, cph], Lukas Hosek [ctb, cph], Alexander Wilkie [ctb, cph]
Maintainer: Tyler Morgan-Wall <tylermw@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-26 09:20:02 UTC

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New package sceua with initial version 0.1.0
Package: sceua
Title: Shuffled Complex Evolution Algorithm for Optimization
Version: 0.1.0
Description: Provides an 'R' interface to a 'Rust' implementation of the Shuffled Complex Evolution - University of Arizona (SCE-UA) global optimization algorithm (Duan et al., 1992). SCE-UA combines simplex search, competitive evolution, and complex shuffling to solve nonlinear, non-convex, continuous parameter estimation problems. The method is commonly used for calibrating hydrological and environmental models and follows the algorithm proposed by Duan et al. (1992) <doi:10.1029/91WR02985>.
License: MIT + file LICENSE
URL: https://github.com/atsyplenkov/sceua/, https://atsyplenkov.github.io/sceua/
BugReports: https://github.com/atsyplenkov/sceua/issues/
Encoding: UTF-8
Language: en
SystemRequirements: Cargo (Rust's package manager), rustc (>= 1.91.1)
Imports: checkmate
Suggests: testthat (>= 3.0.0)
NeedsCompilation: yes
Packaged: 2026-06-22 07:43:44 UTC; ats
Author: Anatoly Tsyplenkov [aut, cre, cph]
Maintainer: Anatoly Tsyplenkov <atsyplenkov@fastmail.com>
Repository: CRAN
Date/Publication: 2026-06-26 09:20:08 UTC

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New package mpaR with initial version 0.4.0
Package: mpaR
Title: Main Path Analysis for Citation and Directed Networks
Version: 0.4.0
Description: Implements Main Path Analysis (MPA) as introduced by Hummon and Doreian (1989) <doi:10.1016/0378-8733(89)90017-8>. Given a directed acyclic graph (DAG) representing a citation or precedence network, the package computes traversal weights (SPC, SPLC, SPNP) for each edge and extracts the global, local, and key-route main paths. Also provides tools for DAG validation, node role classification (source/terminal/user), per-component path extraction for disconnected networks, and scale-free network testing. Accepts 'igraph' objects or edge-list data frames as input. Includes readers for 'Pajek' (.net) and 'Gephi' export (.gexf, .graphml) files.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: igraph (>= 1.3.0), methods, rlang (>= 1.0.0), tools, xml2
Suggests: testthat (>= 3.0.0)
URL: https://github.com/resendeph/mpaR
BugReports: https://github.com/resendeph/mpaR/issues
NeedsCompilation: no
Packaged: 2026-06-22 17:11:45 UTC; phres
Author: Paulo H Resende [aut, cre]
Maintainer: Paulo H Resende <paulo.resende@ttu.edu>
Repository: CRAN
Date/Publication: 2026-06-26 10:00:02 UTC

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New package diffdriver with initial version 0.1.7
Package: diffdriver
Title: Identify Differential Selection
Version: 0.1.7
Maintainer: Siming Zhao <siming.zhao@dartmouth.edu>
Description: Tests for context-dependent selection on cancer driver genes using somatic mutation data. The package implements the DiffDriver statistical framework to assess whether the strength of positive selection on mutations in a driver gene is associated with tumor- or individual-level context variables, such as clinical traits, genomic features, or immune microenvironment subtypes. DiffDriver estimates individual- and position-specific background mutation rates, models selection as a deviation from the background rate using functional annotations, and tests context effects through a latent-variable logistic model. It provides utilities for preparing mutation and annotation data, fitting differential-selection models, running gene-level association tests, summarizing candidate genes, and visualizing mutation patterns. The method is described in Zhou et al. (2026) "Detecting context-dependent selection on cancer driver genes with DiffDriver" <doi:10.64898/2026.04.06.716771>.
URL: https://szhaolab.github.io/diffdriver/, https://github.com/szhaolab/diffdriver
License: MIT + file LICENSE
Encoding: UTF-8
Imports: Matrix, stats, data.table, brglm, fastTopics, SQUAREM
Suggests: knitr, rmarkdown, logging, testthat (>= 3.0.0)
Depends: R (>= 3.5.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-06-22 16:12:45 UTC; ld-zhangqr
Author: Siming Zhao [aut, cre], Jie Zhou [aut], Qirui Zhang [aut]
Repository: CRAN
Date/Publication: 2026-06-26 09:50:10 UTC

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New package depthR with initial version 0.1.8
Package: depthR
Title: Multivariate Depth Functions for General Dimension
Version: 0.1.8
Date: 2026-06-22
Description: Efficient computation of multivariate statistical depth functions in arbitrary dimension d. Implements Mahalanobis depth, Tukey (halfspace) depth, Liu simplicial depth (via adaptive Monte Carlo), projection depth, and spatial depth. Provides depth-based medians, central regions, outlier detection, and depth-depth plots. 'C++' backends via 'Rcpp' and 'RcppEigen' ensure performance at large n and d. References: Liu (1990) <doi:10.1214/aos/1176347507>, Zuo and Serfling (2000) <doi:10.1214/aos/1016218226>, Vardi and Zhang (2000) <doi:10.1073/pnas.97.4.1423>.
License: GPL (>= 3)
URL: https://github.com/penny4nonsense/depthR
BugReports: https://github.com/penny4nonsense/depthR/issues
Depends: R (>= 3.1.0)
Imports: Rcpp (>= 1.0.0), RcppParallel (>= 5.0.0), stats, graphics
LinkingTo: Rcpp, RcppEigen (>= 0.3.3), RcppParallel (>= 5.0.0)
Suggests: testthat (>= 3.0.0), MASS, knitr, rmarkdown
VignetteBuilder: knitr
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2026-06-22 15:22:33 UTC; e200601
Author: Jason Parker [aut, cre]
Maintainer: Jason Parker <jparker588@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-26 09:40:02 UTC

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New package ClusterRandSSAdj with initial version 1.0.0
Package: ClusterRandSSAdj
Title: Small Sample Adjustment of Cluster Randomized Trial
Version: 1.0.0
Description: A set of functions to apply 'HC3' (FIRORES) and 'HC2' (ROOT) sandwich estimators to make small-sample adjustments to standard errors of Generalized Linear Model statistics used to analyze cluster randomized trial data. The functions in the 'ClusterRandSSAdj' package make small-sample adjustments to Generalized Linear Model parameter estimates, least squares means and pair-wise comparison of least squares means, Type III tests, and estimates from linear combinations of Generalized Linear Model parameters. For more details see Ford (2017) <doi:10.1002/bimj.201600182> and Westgate (2022) <doi:10.1177/17407745211063479>.
License: GPL (>= 3)
Encoding: UTF-8
Imports: dplyr, car, emmeans, lmtest, Matrix, multcomp, sandwich
Depends: R (>= 4.1)
LazyData: true
Suggests: MASS, knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-06-22 17:06:29 UTC; beggleston
Author: Barry Eggleston [aut, cre], Rouba Chahine [aut], Phil Westgate [aut], Nathan Vandergrift [fnd]
Maintainer: Barry Eggleston <beggleston@rti.org>
Repository: CRAN
Date/Publication: 2026-06-26 09:50:15 UTC

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Thu, 25 Jun 2026

New package SIEVEseq with initial version 0.0.0
Package: SIEVEseq
Title: Unified Differential Expression, Variability and Skewness Analysis for RNA-Seq Data
Version: 0.0.0
Date: 2026-06-07
Maintainer: Hongxiang Li <hxli@ynnu.edu.cn>
Description: Provides a unified framework for the simultaneous testing of differential expression, variability, and skewness of genes using RNA-Seq data. The framework adopts a compositional data analysis approach for modelling RNA-Seq count data, applies the centered log-ratio transformation to obtain continuous variables, and uses the skew-normal distribution for statistical inference. Methods are described in Li and Khang (bioRxiv preprint, 2024, version 3) <doi:10.1101/2024.04.09.588804>.
Depends: R (>= 4.1)
Imports: sn, stats, ggplot2
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
URL: https://github.com/Divo-Lee/SIEVEseq
License: GPL (>= 2)
Encoding: UTF-8
LazyData: TRUE
NeedsCompilation: no
Packaged: 2026-06-22 14:21:19 UTC; chels
Author: Hongxiang Li [aut, cre], Tsung Fei Khang [aut]
Repository: CRAN
Date/Publication: 2026-06-25 16:10:09 UTC

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New package mixqr with initial version 0.2.0
Package: mixqr
Title: Extensible Finite Mixtures of Quantile and Expectile Regressions
Version: 0.2.0
Description: An extensible expectation-maximization (EM) framework for finite mixtures of quantile regressions (clusterwise / mixture-of-experts quantile regression). A single EM substrate with an engine/extension contract carries a family of capabilities: the core free-weight mixture of Wu and Yao (2016) <doi:10.1016/j.csda.2014.04.014> -- a fast asymmetric-Laplace path and the nonparametric kernel-density EM with components constrained to have their tau-quantile equal to zero (Hall and Presnell 1999 device); expectile and M-quantile component-loss families (Newey and Powell 1987; Breckling and Chambers 1988); component-specific penalized variable selection (SCAD / adaptive-LASSO, the quantile analogue of Khalili and Chen 2007); and joint multi-quantile estimation with a shared latent classification and non-crossing component curves. Provides classification-aware standard errors (sparsity and stochastic-EM multiple imputation), multi-start estimation, component-count selection, and predictio [...truncated...]
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Depends: R (>= 4.1)
Imports: quantreg, stats, graphics, utils
Suggests: ggplot2, rqPen, testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
URL: https://github.com/kvenkita/mixqr, https://kvenkita.github.io/mixqr/
BugReports: https://github.com/kvenkita/mixqr/issues
NeedsCompilation: no
Packaged: 2026-06-22 11:18:57 UTC; kyle
Author: Kailas Venkitasubramanian [aut, cre, cph]
Maintainer: Kailas Venkitasubramanian <kailasv@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-25 16:10:02 UTC

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New package TCpRepDesigns with initial version 0.0.1
Package: TCpRepDesigns
Title: Partially Replicated Test-Control Designs for Early Generation Varietal Trials
Version: 0.0.1
Description: Provides functions for generating partially replicated (p-rep) test-control designs for early generation varietal trials conducted across multiple environments. The package implements three construction methods for obtaining efficient p-rep test-control designs with one or more control treatments. The package extends the partially replicated design framework of Vinaykumar et al. (2026) <doi:10.1007/s12355-025-01684-1> to accommodate test-control comparisons in breeding trials. Functions are also provided for generating randomized and non-randomized layouts and for evaluating designs using average variance measures for test-versus-test and test-versus-control comparisons, together with canonical efficiency factors. The proposed designs are useful for large-scale varietal evaluation trials where a large number of test lines are assessed under limited experimental resources.
License: GPL (>= 3)
Encoding: UTF-8
Imports: MASS
NeedsCompilation: no
Packaged: 2026-06-22 03:51:26 UTC; admin
Author: Vinaykumar L.N. [aut, cre], Cini Varghese [aut, ctb], Mohd Harun [aut, ctb], Sayantani Karmakar [aut, ctb], Vinayaka [aut, ctb]
Maintainer: Vinaykumar L.N. <vinaymandya123@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-25 15:50:16 UTC

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New package taperNOR with initial version 0.2.1
Package: taperNOR
Title: Taper, Volume and Bark Thickness Models for Spruce, Pine and Birch in Norway
Version: 0.2.1
Description: Stem taper, bark thickness, and volume models for the main Norwegian tree species (Norway spruce, Scots pine, and birch), based on Hansen et al. (2023) <doi:10.1080/02827581.2023.2243821> and the correction <doi:10.1080/02827581.2024.2358467>. Provides functions to predict stem diameter along the bole, bark thickness, and stem volume by numerical integration of the taper curve, and to invert these relationships (e.g. estimating height and diameter at breast height from measured diameters).
License: MIT + file LICENSE
URL: https://github.com/SmartForest-no/taperNOR
BugReports: https://github.com/SmartForest-no/taperNOR/issues
Encoding: UTF-8
Language: en-US
Imports: TapeR
Depends: R (>= 2.10)
Suggests: spelling, testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-06-19 12:41:24 UTC; JoRa
Author: Johannes Rahlf [aut, cre], Endre Hofstad Hansen [aut]
Maintainer: Johannes Rahlf <johannes.rahlf@nibio.no>
Repository: CRAN
Date/Publication: 2026-06-25 16:00:02 UTC

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New package rMosaic with initial version 0.1.3
Package: rMosaic
Title: R Bindings to the 'Mosaic' Visualization Framework
Version: 0.1.3
Description: Provides R bindings for 'Mosaic', a declarative grammar for linked, data-driven visualizations backed by 'DuckDB'. The package supplies 'htmlwidgets' and 'shiny' helpers for rendering 'Mosaic' specifications from R, including optional browser-side 'DuckDB-WASM' execution and selection export helpers for exploratory workflows.
License: MIT + file LICENSE
URL: https://github.com/TiRizvanov/rMosaic
BugReports: https://github.com/TiRizvanov/rMosaic/issues
Encoding: UTF-8
Language: en-US
Depends: R (>= 4.1.0)
Imports: htmlwidgets (>= 1.5.4), shiny (>= 1.7.0), jsonlite (>= 1.8.0), yaml (>= 2.3.0), DBI (>= 1.1.0), duckdb (>= 1.4.0), stats
Suggests: arrow (>= 12.0.0), knitr, rmarkdown, rstudioapi
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-06-09 14:00:38 UTC; timurrizvanov
Author: Timur Rizvanov [aut, cre], Edward C. Ruiz [aut], Ruben Dries [aut, rev], Dries Lab [fnd] , Boston University [fnd] )
Maintainer: Timur Rizvanov <timurr@bu.edu>
Repository: CRAN
Date/Publication: 2026-06-25 15:40:02 UTC

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New package ratecalib with initial version 0.3.0
Package: ratecalib
Title: Calibration Weighting to Multiple Subgroup Pass-Rate Targets
Version: 0.3.0
Description: Calibration weighting for binary-outcome pass rates against multiple overlapping subgroup targets. Adjusts initial positive weights so that the overall pass rate and subgroup pass rates approach (soft mode) or exactly match (exact mode) given targets, while preserving the initial weight structure and population margins. Provides a one-step interface, pre-solve data checks, target-table construction, effective sample size and design-effect diagnostics, and example data. The solver works on a bounded convex quadratic program over demographic-cell-by-outcome aggregates for efficiency on large samples. Methods follow the calibration approach of Deville and Saerndal (1992) <doi:10.1080/01621459.1992.10475217>.
License: MIT + file LICENSE
URL: https://github.com/makunxiang-cmd/ratecalib
BugReports: https://github.com/makunxiang-cmd/ratecalib/issues
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: Matrix, methods, osqp, stats
Suggests: testthat (>= 3.0.0), openxlsx
NeedsCompilation: no
Packaged: 2026-06-21 15:50:54 UTC; makunxiang
Author: Kunxiang Ma [aut, cre]
Maintainer: Kunxiang Ma <mkx07080412@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-25 15:10:02 UTC

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New package ProbSVMs with initial version 0.1.0
Package: ProbSVMs
Title: Probabilistic Support Vector Machines
Version: 0.1.0
Author: A. Pedro Duarte Silva [aut, cre]
Maintainer: A. Pedro Duarte Silva <psilva@ucp.pt>
Description: Implements kernel-based classification Support Vector Machines with reliable estimated probabilities of class membership. Theoretical support for the functions in this package can be found in Duarte Silva (2025) <doi:10.1016/j.cor.2025.107203>.
License: GPL-2
Encoding: UTF-8
Depends: R (>= 3.5.0), Rcpp (>= 1.0.4.6)
LinkingTo: Rcpp, RcppArmadillo (>= 15.2.6-1)
Imports: lpSolveAPI, kernlab, ggplot2, MASS, stats, reshape2
NeedsCompilation: yes
Packaged: 2026-06-22 09:13:01 UTC; antonio
Repository: CRAN
Date/Publication: 2026-06-25 16:00:20 UTC

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New package mixedsubjectsirt with initial version 1.0.0
Package: mixedsubjectsirt
Title: Item Response Theory Calibration with a Mixed Subjects Design
Version: 1.0.0
Description: Integrates large language model generated item responses into psychometric calibration studies through a mixed-subjects design for unidimensional two-parameter and one-parameter logistic item response theory models. Human pilot responses are augmented with model-generated responses using a prediction-powered inference estimator (Angelopoulos, Bates, Fannjiang, Jordan and Zrnic (2023) <doi:10.1126/science.adi6000>; Angelopoulos, Duchi and Zrnic (2023) <doi:10.48550/arXiv.2311.01453>) adapted to marginal maximum-likelihood estimation, following the mixed-subjects design of Broska, Howes and van Loon (2025) <doi:10.1177/00491241251326865>. The estimator is anchored to the human responses and is asymptotically unbiased for the human item parameters at any tuning weight; the weight on the synthetic responses is chosen to minimize propagated ability-score risk, down-weighting uninformative or biased generated responses. Louis-corrected sandwich standard errors, ability scor [...truncated...]
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-US
Imports: mirt, rmutil
Suggests: ggplot2, knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
URL: https://klintkanopka.com/mixedsubjectsirt/, https://github.com/klintkanopka/mixedsubjectsirt
BugReports: https://github.com/klintkanopka/mixedsubjectsirt/issues
NeedsCompilation: no
Packaged: 2026-06-22 02:19:58 UTC; klintkanopka
Author: Klint Kanopka [aut, cre]
Maintainer: Klint Kanopka <klint.kanopka@nyu.edu>
Repository: CRAN
Date/Publication: 2026-06-25 15:50:09 UTC

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New package FragiliTidy with initial version 0.1.0
Package: FragiliTidy
Title: Tidyverse-Compatible Fragility Index Calculations
Version: 0.1.0
Description: Provides optimized, Tidyverse-compatible functions for calculating the Fragility Index and Reverse Fragility Index for 2x2 contingency tables from clinical trials. Uses customized hypergeometric and algebraic calculations along with binary search algorithms to achieve substantial speedups over standard implementations, with seamless integration into 'dplyr' pipelines.
License: GPL-3
Encoding: UTF-8
Imports: dplyr, purrr, rlang, tibble, stats
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
URL: https://github.com/tomdrake/fragilitidy
BugReports: https://github.com/tomdrake/fragilitidy/issues
NeedsCompilation: no
Packaged: 2026-06-22 04:02:09 UTC; tdrake
Author: Tom Drake [aut, cre]
Maintainer: Tom Drake <t.drake@ed.ac.uk>
Repository: CRAN
Date/Publication: 2026-06-25 15:50:21 UTC

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New package DataCraftR with initial version 0.3.2
Package: DataCraftR
Title: Create Datasets Interactively Using 'shiny'
Version: 0.3.2
Description: Set of 'shiny'-based 'RStudio' add-ins for interactively creating datasets through graphical interfaces. Users can adjust graphical elements to define data generation parameters, and the resulting datasets can be saved to temporary RDS files for further analysis or visualization. Methods are described in: Chang et al. (2024) <https://CRAN.R-project.org/package=shiny>; Bostock et al. (2011) <doi:10.1109/TVCG.2011.185>.
License: GPL (>= 3)
URL: https://github.com/CarlosRivera1212/DataCraftR
BugReports: https://github.com/CarlosRivera1212/DataCraftR/issues
Encoding: UTF-8
Imports: bsicons, bslib, RcppColors, rstudioapi, shiny, shinyWidgets
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-06-21 16:09:56 UTC; carlos
Author: Carlos Rivera [aut, cre] , Heidi Renninger [fnd]
Maintainer: Carlos Rivera <riveramo.carlos@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-25 15:10:07 UTC

More information about DataCraftR at CRAN
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New package rsei with initial version 0.1.0
Package: rsei
Title: Client for the 'SEI' Electronic Information System Web Services
Version: 0.1.0
Description: Toolkit to interact with the 'SOAP' web services of the 'SEI' (Sistema Eletronico de Informacoes), the electronic system for document and process management widely used by Brazilian public administration bodies. Provides functions to build the 'SOAP' envelopes, perform the requests, handle 'SOAP' faults, and parse the 'XML' responses into data frames. Covers process and document queries, listing services, write operations (creating processes and documents, sending and signing off processes, blocks, deadlines and markers) and the permission services of the companion 'SIP' system. Note that access to the web services is restricted by the server to previously authorized network addresses. For more information about the 'SEI' system and its web services see <https://www.gov.br/gestao/pt-br/assuntos/processo-eletronico-nacional>.
License: GPL-3
Encoding: UTF-8
Language: pt-BR
Depends: R (>= 4.1.0)
Imports: httr2, xml2, keyring, jsonlite, magrittr, dplyr, tidyr, purrr, tibble
Suggests: testthat (>= 3.0.0), roxygen2, knitr, rmarkdown
VignetteBuilder: knitr
URL: https://github.com/StrategicProjects/rsei, https://strategicprojects.github.io/rsei/
BugReports: https://github.com/StrategicProjects/rsei/issues
NeedsCompilation: no
Packaged: 2026-06-20 20:21:58 UTC; leite
Author: Andre Leite [aut, cre], Marcos Wasilew [aut], Hugo Vasconcelos [aut], Carlos Amorin [aut], Diogo Bezerra [aut], Julia Nascimento Barreto [aut]
Maintainer: Andre Leite <leite@castlab.org>
Repository: CRAN
Date/Publication: 2026-06-25 11:10:02 UTC

More information about rsei at CRAN
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New package ringSeg with initial version 0.1.0
Package: ringSeg
Title: Asymptotic Distribution-Free Change-Point Detection via a New Ranking Scheme (RING)
Version: 0.1.0
Description: Rank-based, asymptotic distribution-free change-point detection for modern (high-dimensional, non-Euclidean) data, based on the graph-induced ranking scheme of Zhou and Chen (2025) <doi:10.1109/TIT.2025.3575858>. Given a rank matrix built from a pairwise similarity, the method scans for a single change-point or a changed interval using three statistics (weighted 'WR', max-type 'MR', and generalized 'TR') and returns analytic distribution-free p-value approximations (with an optional skewness correction) as well as optional permutation p-values.
License: GPL (>= 2)
Encoding: UTF-8
Imports: stats
NeedsCompilation: no
Packaged: 2026-06-21 08:53:55 UTC; hao
Author: Doudou Zhou [aut], Hao Chen [aut, cre]
Maintainer: Hao Chen <hxchen@ucdavis.edu>
Repository: CRAN
Date/Publication: 2026-06-25 11:30:02 UTC

More information about ringSeg at CRAN
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New package QuantileModels with initial version 1.0.0
Package: QuantileModels
Title: Estimation of Different Quantile Related Models
Version: 1.0.0
Description: Estimation of different quantile models, at the moment only Conditional autoregressive value at risk (CAViaR) proposed by Engle & Manganelli (2004) <doi:10.1198/073500104000000370> with also the specification proposed in Huang et al. (2009) <doi:10.1016/j.eneco.2008.12.006> and it's multivariate extension, Multi-variate multi-quantile CAViaR (MVMQ-CAViaR) proposed by White et al. (2015) <doi:10.1016/j.jeconom.2015.02.004> are available, however, in further updates, other models and extensions will be included.
License: GPL (>= 3)
Encoding: UTF-8
LinkingTo: Rcpp, RcppArmadillo
Imports: Rcpp, nloptr, quantreg, numDeriv, xts, zoo, ufRisk, GenSA
Suggests: knitr, rmarkdown,
VignetteBuilder: knitr
Depends: R (>= 3.5)
LazyData: true
Language: en-US
NeedsCompilation: yes
Packaged: 2026-06-21 10:21:56 UTC; Christian
Author: Christian Jorge Carreiro [aut, cre, cph]
Maintainer: Christian Jorge Carreiro <christianjorge59@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-25 11:30:07 UTC

More information about QuantileModels at CRAN
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New package ggbond with initial version 0.0.5
Package: ggbond
Title: Interactive Layout Editor for 'R' Plots
Version: 0.0.5
Description: Provides a 'shiny'-based layout editor for arranging 'R' plot objects on a fixed-size canvas. It supports 'ggplot2' plots, 'graphics' functions and recorded plots, 'pheatmap' objects, 'ComplexHeatmap' objects, 'grid' grobs, 'gtable' objects, and local raster images, with live preview and PDF or PNG export.
License: GPL (>= 3)
Encoding: UTF-8
Imports: ggplot2, graphics, grDevices, grid, gridGraphics, jpeg, jsonlite, png, shiny, stats, tiff, tools, utils
Suggests: ComplexHeatmap, pheatmap
NeedsCompilation: no
Packaged: 2026-06-21 15:43:49 UTC; libeihao
Author: BeiHao Li [aut, cre, cph]
Maintainer: BeiHao Li <szright2000@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-25 11:50:07 UTC

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New package ggalttext with initial version 0.3.0
Package: ggalttext
Title: Make 'ggplot2' Fully Accessible by Generating Alternative Text
Version: 0.3.0
Description: Generates concise alternative text for data visualizations created with 'ggplot2'. Descriptions are produced by inspecting plot layers, labels, scales, and facets, with support for multiple languages and alternative text stored in plot metadata.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: ggplot2, knitr
Suggests: babynames, ggtext, dplyr, patchwork, testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-06-21 14:21:21 UTC; josephbarbier
Author: Joseph Barbier [aut, cre, cph]
Maintainer: Joseph Barbier <joseph@ysunflower.com>
Repository: CRAN
Date/Publication: 2026-06-25 11:50:12 UTC

More information about ggalttext at CRAN
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New package chatterbox with initial version 0.2.1
Package: chatterbox
Title: Text-to-Speech Using the 'Chatterbox' Engine
Version: 0.2.1
Date: 2026-06-21
Description: A native R 'torch' port of the 'Chatterbox' text-to-speech engine <https://github.com/resemble-ai/chatterbox>. Provides speech synthesis with voice cloning; model weights are downloaded from 'HuggingFace' <https://huggingface.co/> via the 'hfhub' package.
License: MIT + file LICENSE
Encoding: UTF-8
URL: https://github.com/cornball-ai/chatterbox
BugReports: https://github.com/cornball-ai/chatterbox/issues
Depends: R (>= 4.0.0)
Imports: torch (>= 0.17.0), tuneR, jsonlite, hfhub, safetensors (>= 0.1.1)
Suggests: tinytest
NeedsCompilation: no
Packaged: 2026-06-21 15:19:20 UTC; troy
Author: Troy Hernandez [aut, cre] , cornball.ai [cph], Resemble AI [cph] )
Maintainer: Troy Hernandez <troy@cornball.ai>
Repository: CRAN
Date/Publication: 2026-06-25 11:50:18 UTC

More information about chatterbox at CRAN
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New package CAFT with initial version 0.1.0
Package: CAFT
Title: Rank-Based Compositional Analysis using Log-Linear Models for Microbiome Data with Zero Cells
Version: 0.1.0
Date: 2026-06-09
Description: Provides rank-based compositional differential abundance analysis for microbiome count data with zero cells using the compositional accelerated failure time model of Satten, Li and Zhao (2025) "CAFT: A Compositional Log-Linear Model for Microbiome Data with Zero Cells" <doi:10.1101/2025.11.26.690468>. Zero counts are treated as censored observations below sample-specific detection limits, avoiding the use of pseudocounts. The package implements estimation and hypothesis testing procedures for assessing associations between microbial taxa and covariates while accounting for the compositional structure of sequencing count data. It supports taxon-level differential abundance analysis, estimation of regression effects under censoring induced by detection limits, and inference based on rank-based methods that remain applicable in the presence of excess zeros. Functions are provided for model fitting, significance testing, extraction of effect estimates, and summarization of results ac [...truncated...]
Imports: doParallel, doRNG, expm, foreach, ggplot2, ggtext, ICSNP, MASS, stats
License: LGPL (>= 2)
Depends: R (>= 4.3.0)
URL: https://github.com/mli171/CAFT
BugReports: https://github.com/mli171/CAFT/issues
Suggests: graphics, knitr, rmarkdown, testthat (>= 3.0.0)
Encoding: UTF-8
LazyData: true
LazyDataCompression: bzip2
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-06-21 06:31:16 UTC; mli171
Author: Glen A. Satten [aut, ctb, cph], Mo Li [aut, ctb, cre, cph], Ni Zhao [aut, ctb, cph]
Maintainer: Mo Li <mo.li@louisiana.edu>
Repository: CRAN
Date/Publication: 2026-06-25 11:20:14 UTC

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New package prepR4pcm with initial version 1.0.0
Package: prepR4pcm
Title: Prepare Data and Trees for Phylogenetic Comparative Methods
Version: 1.0.0
Description: Reconcile species names across datasets and phylogenetic trees for comparative biology workflows. Identifies mismatches due to formatting differences, taxonomic synonymy, and spelling errors. Produces detailed reports documenting how each name was resolved, which taxonomic authority was used, and what remains unresolved. Supports exact matching, name normalisation, synonym resolution via local taxonomic databases, and fuzzy matching for likely typos. Detects taxonomic splits and lumps. For methodological context, see Nakagawa et al. (2026) <doi:10.32942/X2468Z>.
License: MIT + file LICENSE
URL: https://github.com/itchyshin/prepR4pcm, https://itchyshin.github.io/prepR4pcm/
BugReports: https://github.com/itchyshin/prepR4pcm/issues
Date: 2026-06-16
Language: en-GB
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: ape, cli, rlang, tibble
Suggests: caper, clootl, digest, dplyr, fishtree, httr2, knitr, MCMCglmm, phytools, piggyback, pkgdown, readr, rgnparser, rmarkdown, rotl, rtrees, spelling, stringr, taxadb, testthat (>= 3.0.0)
LazyData: true
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-06-20 18:45:02 UTC; z3437171
Author: Shinichi Nakagawa [aut, cre, cph] , Santiago Ortega [aut], Ayumi Mizuno [aut], Eduardo S.A. Santos [aut], Malgorzata Lagisz [aut] , Bhavya Jain [aut], Jimuel Jr Celeste [aut], Sergio Poo Hernandez [aut]
Maintainer: Shinichi Nakagawa <itchyshin@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-25 11:00:13 UTC

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Wed, 24 Jun 2026

New package TwoCutoff with initial version 0.1.0
Package: TwoCutoff
Title: Deriving Clinically Interpretable Cutoffs for Disease Biomarkers
Version: 0.1.0
Maintainer: Bhrigu Kumar Rajbongshi <kumarbhrigu536@gmail.com>
Description: Provides a reproducible pipeline for deriving two clinically meaningful cutoffs for disease biomarkers using a unified two-stage framework. The package integrates finite mixture modeling with risk prediction using biomarker plus clinical features, followed by decision curve analysis to evaluate clinical utility. Outputs include biomarker density plots, risk calibration curves, decision curves, and summary tables of diagnostic performance. Designed for researchers in bio-statistics, neurology, and data science, this package emphasizes reproducibility, transparency, and clear clinical relevance.
Imports: dplyr, mixtools, stats, pROC, xgboost, ggplot2, caret, patchwork, gridExtra
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Depends: R (>= 4.0.0)
NeedsCompilation: no
Suggests: rmarkdown, DiagrammeR, knitr, devtools
VignetteBuilder: knitr
Author: Bhrigu Kumar Rajbongshi [aut, cre, ctb], Seyed Ehsan Saffari [aut, ctb], Nastaran Marzban [aut, ctb]
Packaged: 2026-06-20 14:38:03 UTC; bhrigu
Repository: CRAN
Date/Publication: 2026-06-24 10:00:13 UTC

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New package productshotaiR with initial version 0.1.0
Package: productshotaiR
Title: Product Photo Planning Helpers
Version: 0.1.0
Description: Helpers for preparing ecommerce product photo planning tables, prompt sheets, and public ProductShot AI workflow URLs. The package works offline and focuses on data-frame preparation for product image batches.
License: MIT + file LICENSE
URL: https://productshotai.app, https://github.com/bbwdadfg/productshotai-site-kit
BugReports: https://github.com/bbwdadfg/productshotai-site-kit/issues
Encoding: UTF-8
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-06-20 15:15:42 UTC; baiwei
Author: Baiwei Chu [aut, cre]
Maintainer: Baiwei Chu <baiwei.chu@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-24 10:00:02 UTC

More information about productshotaiR at CRAN
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New package moderncor with initial version 0.2.0
Package: moderncor
Title: Unified Interface for Modern and Classical Correlation Coefficients
Version: 0.2.0
Description: Provides a single unified interface for computing a wide variety of classical and modern correlation and association measures. Continuous methods include classical correlations (Pearson, Spearman, Kendall), modern dependence measures (distance correlation, maximal information coefficient, Hilbert-Schmidt independence criterion, Chatterjee's xi, Hoeffding's D, mutual information), robust correlations (biweight midcorrelation, percentage bend, Winsorized), ordinal correlations (polychoric, tetrachoric), partial and semi-partial correlations, and nonparametric measures (ball correlation, Bergsma-Dassios tau*). Categorical association measures (Cramer's V, phi coefficient, Goodman-Kruskal gamma, Somers' D, contingency coefficient, Tschuprow's T) are available via moderncor_cat().
License: GPL-3
URL: https://github.com/ToshihiroIguchi/moderncor
BugReports: https://github.com/ToshihiroIguchi/moderncor/issues
Encoding: UTF-8
Imports: stats, energy, XICOR
Suggests: minerva, Hmisc, dHSIC, infotheo, WRS2, psych, ppcor, Ball, TauStar, DescTools, testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-06-20 11:46:22 UTC; toshi
Author: Toshihiro Iguchi [aut, cre]
Maintainer: Toshihiro Iguchi <toshihiro.iguchi.github@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-24 09:50:02 UTC

More information about moderncor at CRAN
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New package locdiff with initial version 1.4
Package: locdiff
Title: Local Diffusion Exponent
Version: 1.4
Maintainer: Chun-Xiao Nie <niechunxiao2009@163.com>
Description: The local diffusion exponent for undirected, unweighted networks characterizes the speed of local diffusion from a specified node and depends on the resistance distance.
License: GPL-3
Encoding: UTF-8
Depends: igraph, MASS
NeedsCompilation: no
Packaged: 2026-06-20 10:31:45 UTC; niech
Author: Chun-Xiao Nie [aut, cre]
Repository: CRAN
Date/Publication: 2026-06-24 09:50:07 UTC

More information about locdiff at CRAN
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New package ivgls with initial version 0.1.0
Package: ivgls
Title: Network-Aware IV Regression with Graph-Fused Lasso
Version: 0.1.0
Description: Implements network-aware instrumental variable regression for causal node discovery in high-dimensional settings with graph-structured exposures. Provides IVGL and IVGL-S estimators combining graph-Laplacian penalization with IV-based identification, including correction for invalid instruments via a sisVIVE-style update. Methods are described in Pal and Ghosh (2026) <doi:10.48550/arXiv.2604.24969>. The 'glmgraph' package, required for the main estimators, is available at the additional repository <https://djghosh1123.r-universe.dev>.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: glmnet, MASS, igraph
Suggests: knitr, glmgraph, rmarkdown, testthat (>= 3.0.0), ggplot2, spelling
Additional_repositories: https://djghosh1123.r-universe.dev
VignetteBuilder: knitr
URL: https://github.com/djghosh1123/ivgls
BugReports: https://github.com/djghosh1123/ivgls/issues
Language: en-US
NeedsCompilation: no
Packaged: 2026-06-20 02:10:10 UTC; dghosh3
Author: Dhrubajyoti Ghosh [aut, cre] , Samhita Pal [aut]
Maintainer: Dhrubajyoti Ghosh <dghosh3@kennesaw.edu>
Repository: CRAN
Date/Publication: 2026-06-24 09:30:02 UTC

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New package hypergraph.sizing with initial version 1.0.0
Package: hypergraph.sizing
Title: Hypergraph-Based Sizing Function for Generalised Linear Step-Up Method
Version: 1.0.0
Description: Calculates a sizing function based on the number of independent sets in the rejected hypergraph (Organ, Kenney & Gu, 2026, <doi:10.48550/arXiv.2606.20514>). The sizing function is designed to be used with the 'GLSUP' package.
Depends: R (>= 3.2.3)
License: GPL-3
Encoding: UTF-8
Imports: utils,stats
Enhances: GLSUP
NeedsCompilation: yes
Maintainer: Toby Kenney <tkenney@mathstat.dal.ca>
Packaged: 2026-06-19 20:36:29 UTC; tkenney
Author: Toby Kenney [aut, cre]
Repository: CRAN
Date/Publication: 2026-06-24 09:30:07 UTC

More information about hypergraph.sizing at CRAN
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New package drlate with initial version 0.3.1
Package: drlate
Title: Doubly Robust Estimation of Local Average Treatment Effects
Version: 0.3.1
Description: Estimates the local average treatment effect (LATE) and the local average treatment effect on the treated (LATT) using observational data with a binary instrument, implementing the complete estimator suite of Sloczynski, Uysal, and Wooldridge: the doubly robust estimators of Sloczynski, Uysal, and Wooldridge (2022) <doi:10.48550/arXiv.2208.01300> -- inverse probability weighted regression adjustment (IPWRA), inverse probability weighting (IPW), augmented inverse probability weighting (AIPW), and regression adjustment (RA) -- and the Abadie-kappa weighting estimators of Sloczynski, Uysal, and Wooldridge (2025) <doi:10.1080/07350015.2024.2332763>. Supports linear, logistic, probit, Poisson, and fractional (fractional-logit and fractional-probit) outcome and treatment models, and instrument propensity scores estimated by maximum likelihood, covariate balancing (CBPS), or inverse probability tilting (IPT). Standard errors are computed jointly for all estimation stages by stacki [...truncated...]
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-US
Depends: R (>= 4.1)
Imports: stats, numDeriv
Suggests: ggplot2, testthat (>= 3.0.0), knitr, rmarkdown, haven
VignetteBuilder: knitr
URL: https://github.com/kvenkita/drlate, https://kvenkita.github.io/drlate/
BugReports: https://github.com/kvenkita/drlate/issues
LazyData: true
NeedsCompilation: no
Packaged: 2026-06-20 14:14:49 UTC; kyle
Author: Kailas Venkitasubramanian [aut, cre], S. Derya Uysal [ctb, cph] , Tymon Sloczynski [ctb, cph] , Jeffrey M. Wooldridge [ctb, cph]
Maintainer: Kailas Venkitasubramanian <kailasv@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-24 09:50:12 UTC

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New package CRBHSF with initial version 0.1.0
Package: CRBHSF
Title: Cyber-Resilient Bayesian Healthcare Surveillance Framework
Version: 0.1.0
Description: Provides methods for healthcare performance surveillance using Bayesian risk estimation, latent organisational trust modelling, cyber-resilience assessment, external validation, decision-theoretic optimisation, and digital-twin deployment simulation. The package supports prospective deterioration monitoring, uncertainty-aware risk assessment, intervention prioritisation, ablation analysis, and operational evaluation for healthcare performance management and health system resilience research. The methodological framework is informed by contemporary guidance on prediction model development and validation (Efthimiou et al., 2024 <doi:10.1136/bmj-2023-078276>), transparent reporting of prediction models (Collins et al., 2024 <doi:10.1136/bmj-2023-078378>), and decision-analytic model evaluation (Vickers and Elkin, 2006 <doi:10.1177/0272989X06295361>).
License: MIT + file LICENSE
Encoding: UTF-8
URL: https://github.com/zerish12/CRBHSF
BugReports: https://github.com/zerish12/CRBHSF/issues
Depends: R (>= 4.1.0)
Imports: dplyr, ggplot2, pROC, purrr, tibble
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
NeedsCompilation: no
Packaged: 2026-06-20 14:26:28 UTC; muhammadzahirkhan
Author: Muhammad Zahir Khan [aut, cre], Abdul Wahid Khan [aut]
Maintainer: Muhammad Zahir Khan <zahirstat007@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-24 09:50:27 UTC

More information about CRBHSF at CRAN
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New package bewrs with initial version 0.1.1
Package: bewrs
Title: Bayesian Early-Warning Risk Surveillance for Healthcare Performance Monitoring
Version: 0.1.1
Description: Provides Bayesian early-warning surveillance methods for monitoring healthcare performance and patient safety outcomes. The package draws on risk-adjusted monitoring frameworks developed by Steiner et al. (2000) <doi:10.1093/biostatistics/1.4.441>, Spiegelhalter et al. (2003) <doi:10.1002/sim.1546>, Cook et al. (2011) <doi:10.1136/bmjqs.2008.031831>, and Neuburger et al. (2017) <doi:10.1136/bmjqs-2016-005511>. The package implements Bayesian predictive modelling, risk-adjusted monitoring, early-warning signal detection, and graphical tools for continuous quality improvement and healthcare performance assessment.
License: GPL-3
Encoding: UTF-8
Depends: R (>= 4.2.0)
Imports: ggplot2, pROC
Suggests: testthat (>= 3.0.0)
URL: https://github.com/zerish12/bewrs
BugReports: https://github.com/zerish12/bewrs/issues
NeedsCompilation: no
Packaged: 2026-06-20 15:22:09 UTC; muhammadzahirkhan
Author: Muhammad Zahir Khan [aut, cre]
Maintainer: Muhammad Zahir Khan <zahirstat007@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-24 10:00:07 UTC

More information about bewrs at CRAN
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New package beautils with initial version 0.2.0
Package: beautils
Title: Field Planning and Biostatistics Utilities
Version: 0.2.0
Maintainer: Tiago Olivoto <tiagoolivoto@gmail.com>
Description: Provides a collection of utility functions for biostatistics, agricultural trial planning, and experimental design. Key features include generating experimental designs (like Latin Square, Alpha-Lattice by Patterson and Williams (1976) <doi:10.2307/2335087>, and Factorial), fieldbook creation, layout sketching, QR code-based label generation, and descriptive statistical tools to easily handle most common descriptive statistics for quantitative variables as described by Field, A., Miles, J., & Field, Z. (2012, ISBN:978-1-4462-0045-2).
Encoding: UTF-8
License: MIT + file LICENSE
Depends: R (>= 4.1.0)
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
Imports: cli, dplyr, FielDHub, ggplot2, glue, grid, purrr, qrencoder, rlang, rstudioapi, tidyr, uuid
NeedsCompilation: no
Packaged: 2026-06-19 17:02:00 UTC; tiago
Author: Tiago Olivoto [aut, cre]
Repository: CRAN
Date/Publication: 2026-06-24 09:10:03 UTC

More information about beautils at CRAN
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New package aurora with initial version 0.1.12
Package: aurora
Title: Build Stateless Web Apps with 'plumber2'
Version: 0.1.12
Description: A scaffolding and deployment toolkit for building stateless web applications in R on top of the 'plumber2' web framework (<https://plumber2.posit.co/>). The UI is authored with 'bslib' and compiled to a static HTML asset at build time, while 'plumber2' serves the assets and exposes JSON API routes. Provides functions to scaffold app skeletons, run them locally, and generate Dockerfiles and images suitable for 'ShinyProxy' or plain Docker.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1)
Imports: cli, fs, glue, htmltools, jsonlite, plumber2 (>= 0.2.0), rlang, yaml
Suggests: brand.yml, bslib (>= 0.9.0), callr, config, fiery, geojsonsf, httpuv, httr2, jose, knitr, later, nanoparquet, pak, reqres, rmarkdown, sf, shiny, sodium, testthat (>= 3.0.0), withr
VignetteBuilder: knitr
URL: https://github.com/aurora-govpe/aurora-rpkg, https://aurora-govpe.github.io/aurora-rpkg/
BugReports: https://github.com/aurora-govpe/aurora-rpkg/issues
NeedsCompilation: no
Packaged: 2026-06-19 18:24:46 UTC; leite
Author: Andre Leite [aut, cre], Marcos Wasilew [aut], Hugo Vasconcelos [aut], Carlos Amorin [aut], Diogo Bezerra [aut], Julia Nascimento Barreto [aut]
Maintainer: Andre Leite <leite@castlab.org>
Repository: CRAN
Date/Publication: 2026-06-24 09:10:09 UTC

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New package artoo with initial version 0.1.1
Package: artoo
Title: Lossless CDISC-Native Input and Output for Clinical Datasets
Version: 0.1.1
Description: Reads and writes clinical-trial datasets losslessly across 'SAS' XPORT (XPT), Clinical Data Interchange Standards Consortium (CDISC) Dataset-JSON, and 'Apache Parquet', applying a specification to produce submission-ready Study Data Tabulation Model (SDTM) and Analysis Data Model (ADaM) datasets. A single canonical metadata model carries labels, CDISC data types, lengths, 'SAS' display formats, controlled-terminology references, and sort keys identically across every format, so conversion between any two formats is lossless by construction. Pure 'R' and lightweight, with no external 'SAS' or 'Java' runtime. Implements the published format specifications for CDISC Dataset-JSON (<https://cdisc-org.github.io/DataExchange-DatasetJson/doc/dataset-json1-1.html>) and 'SAS' XPORT (<https://www.loc.gov/preservation/digital/formats/fdd/fdd000466.shtml>).
License: MIT + file LICENSE
URL: https://vthanik.github.io/artoo/, https://github.com/vthanik/artoo
BugReports: https://github.com/vthanik/artoo/issues
Encoding: UTF-8
Language: en-US
Depends: R (>= 4.2)
Imports: cli, hms, jsonlite, nanoparquet (>= 0.3.0), rlang (>= 1.1.0), S7, utf8
Suggests: quarto, readxl, testthat (>= 3.0.0), tibble, withr, writexl, xml2
VignetteBuilder: quarto
LazyData: true
NeedsCompilation: no
Packaged: 2026-06-20 13:56:18 UTC; vignesh
Author: Vignesh Thanikachalam [aut, cre, cph]
Maintainer: Vignesh Thanikachalam <about.vignesh@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-24 09:50:18 UTC

More information about artoo at CRAN
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New package strollur with initial version 0.1.2
Package: strollur
Title: Store and Transfer Amplicon Sequence Data
Version: 0.1.2
Date: 2026-06-09
Maintainer: Pat Schloss <pschloss@umich.edu>
Description: Stores the data associated with your amplicon sequence analysis. This includes nucleotide sequences, abundance, sample and treatment assignments, taxonomic classifications, asv, otu and phylotype clusters, metadata, trees and various reports. It is designed to facilitate data analysis across multiple R packages with utility functions to read / write from 'mothur', 'qiime2', 'dada2', and 'phyloseq'.
URL: https://github.com/mothur/strollur, https://mothur.org/strollur/
BugReports: https://github.com/mothur/strollur/issues
License: GPL (>= 3)
Imports: Rcpp, cli, methods, microseq, R.utils, R6, waldo, readr, ape, dplyr, tidyr, yaml, rbiom (>= 3.1.0), stats, utils
LinkingTo: Rcpp, cli, Rcereal
Depends: R (>= 4.5.0)
Suggests: knitr, rmarkdown, testthat (>= 3.0.0), xml2, phyloseq, ggplot2, phylotypr, rhdf5, h5lite, pak
Encoding: UTF-8
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2026-06-19 14:36:46 UTC; swestcot
Author: Sarah Westcott [aut] , Gregory Johnson [aut] , Pat Schloss [cph, cre]
Repository: CRAN
Date/Publication: 2026-06-24 09:00:02 UTC

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New package selecta with initial version 0.6.0
Package: selecta
Title: Declarative EQUATOR-Style Flow Diagrams for Clinical Studies
Version: 0.6.0
Description: Build EQUATOR-style flowcharts for clinical studies by sequentially defining inclusion and exclusion criteria, study arms, and endpoints. The pipe-friendly API supports CONSORT (randomized trials), STROBE (observational cohorts), STARD (diagnostic accuracy), PRISMA (systematic reviews), and MOOSE (observational meta-analysis) diagram layouts, as well as multi-source convergence, split-and-recombine, factorial, and hybrid topologies. Diagrams are rendered via 'grid' graphics in both data-driven (automatic counting) and manual-count modes, with optional 'DiagrammeR'/'Graphviz' output.
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
URL: https://phmcc.codeberg.page/selecta, https://codeberg.org/phmcc/selecta, https://github.com/phmcc/selecta
BugReports: https://github.com/phmcc/selecta/issues
Depends: R (>= 4.1.0)
Imports: data.table, grid
Suggests: DiagrammeR, knitr, ragg, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-06-19 07:29:36 UTC; paul
Author: Paul Hsin-ti McClelland [aut, cre, cph]
Maintainer: Paul Hsin-ti McClelland <PaulHMcClelland@protonmail.com>
Repository: CRAN
Date/Publication: 2026-06-24 08:40:02 UTC

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New package PONG2 with initial version 1.0.1
Package: PONG2
Title: KIR Genotype Imputation and Model Training from SNP Array Data
Version: 1.0.1
Date: 2026-05-30
Description: A scalable and accurate tool for Killer-cell Immunoglobulin-like Receptor (KIR) genotype imputation directly from SNP array data using supervised machine learning models trained across five continental ancestry groups. Uses attribute bagging and an ensemble classifier method with haplotype inference for SNPs and KIR types. Models are built from global populations in the 1000 Genomes Project and validated across diverse biobank cohorts. Methods are based on Zheng et al. (2014) <doi:10.1016/j.ajhg.2013.12.015> and Sadeeq et al. (2026) <https://github.com/NormanLabUCD/PONG2>.
Maintainer: Suraju A. Sadeeq <suraju.sadeeq@cuanschutz.edu>
License: GPL-3
URL: https://normanlabucd.github.io/PONG2/, https://github.com/NormanLabUCD/PONG2
BugReports: https://github.com/NormanLabUCD/PONG2/issues
Depends: R (>= 4.0.0)
Imports: parallel, graphics, stats, utils, tools
LinkingTo: Rcpp, RcppParallel
Suggests: HIBAG, knitr, rmarkdown, pkgdown, testthat
VignetteBuilder: knitr
Encoding: UTF-8
SystemRequirements: PLINK2 (>= 2.0), minimac4 (>= 4.1.6, optional)
NeedsCompilation: yes
Packaged: 2026-06-18 16:44:28 UTC; suraju
Author: Suraju A. Sadeeq [aut, cre], Laura A. Leaton [aut], Katherine M. Kichula [aut], Paul J. Norman [aut], Xiuwen Zheng [ctb, cph]
Repository: CRAN
Date/Publication: 2026-06-24 08:10:02 UTC

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New package mergeGridR with initial version 0.2.0
Package: mergeGridR
Title: Grid-Based Number Merge Puzzle Simulation
Date: 2026-06-10
Version: 0.2.0
Author: Frederic Bertrand [cre, aut]
Maintainer: Frederic Bertrand <frederic.bertrand@lecnam.net>
Description: Provides tools to simulate, analyse, visualise, and benchmark grid-based number merge puzzles. The package implements generic grid mechanics, tile-spawning rules, merge rules, scoring functions, reproducible simulation utilities, and local 'Shiny' and 'WebGL' interfaces for interactive use. It is intended for teaching, algorithmic experimentation, and game-theoretic examples. The autoplay helpers use standard heuristic search and Monte Carlo simulation ideas described in Russell and Norvig (2021, ISBN:9780134610993) and Robert and Casella (2004, ISBN:9780387212395).
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
Depends: R (>= 4.1.0)
Imports: ggplot2, ggWebGL, parallel, Rcpp, shiny, tools
LinkingTo: Rcpp
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
URL: https://github.com/fbertran/mergeGridR/, https://fbertran.github.io/mergeGridR/
BugReports: https://github.com/fbertran/mergeGridR/issues
NeedsCompilation: yes
Packaged: 2026-06-19 09:00:09 UTC; bertran7
Repository: CRAN
Date/Publication: 2026-06-24 08:50:02 UTC

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New package inatpick with initial version 0.2.2
Package: inatpick
Title: Download Photos and Metadata from 'iNaturalist'
Version: 0.2.2
Description: A lightweight interface to the 'iNaturalist' API (<https://www.inaturalist.org/pages/api+reference>) for downloading observation photos and exporting metadata to CSV. Supports filtering by taxon, place, user, and annotation. Note that downloaded photos retain their original licenses as set by 'iNaturalist' observers; users are responsible for respecting these licenses.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: httr, jsonlite, dplyr, tidyr, purrr, rlang, stats, utils
Suggests: knitr, rmarkdown, testthat (>= 3.0.0), httptest2
URL: https://github.com/andresarb/inatpick, https://andresarb.github.io/inatpick/
BugReports: https://github.com/andresarb/inatpick/issues
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-06-18 18:23:19 UTC; ar696
Author: Andres Romero-Bravo [aut, cre]
Maintainer: Andres Romero-Bravo <aromerobravo@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-24 08:20:02 UTC

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New package HydroPonicsK with initial version 1.0.3
Package: HydroPonicsK
Title: Hydroponic Data Analysis Tools
Version: 1.0.3
Description: Provides statistical and graphical tools for the analysis of hydroponic crop production data. The package includes functions for descriptive statistical analysis, data visualization, correlation analysis, heatmap generation, and graphical summaries of plant growth and nutrient-related variables. These tools support researchers, students, and practitioners in evaluating crop performance and environmental conditions in hydroponic cultivation systems. The package utilizes standard statistical methods implemented in R for data exploration and visualization. Methods are described in James et al. (2021, ISBN:9781071614172) and Wickham (2016, ISBN:9783319242750).
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: ggplot2, pheatmap, stats
Depends: R (>= 3.5)
NeedsCompilation: no
Packaged: 2026-06-19 05:24:11 UTC; Dr. Imtiyaz
Author: Khalid Ul Islam Rather [aut, cre]
Maintainer: Khalid Ul Islam Rather <drkhalidulislam@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-24 08:30:02 UTC

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New package HOIF with initial version 0.2.0
Package: HOIF
Title: Higher-Order Influence Function Estimators for the Average Treatment Effect
Version: 0.2.0
Description: Implements Higher-Order Influence Function (HOIF) estimators of the Average Treatment Effect (ATE), following Robins et al. (2008) <doi:10.1214/193940307000000527>, Liu et al. (2017) <doi:10.48550/arXiv.1705.07577> and Liu and Li (2023) <doi:10.48550/arXiv.2302.08097>. Estimators of any order are supported, with optional covariate basis transformations (B-splines, Fourier) and optional K-fold sample splitting (cross-fitting) for improved finite-sample performance. The core higher-order U-statistics are computed exactly via the 'ustats' package, an R interface to the 'Python' package 'u-stats'; the underlying algorithm and its computational complexity are analyzed in Chen, Zhang and Liu (2025) <doi:10.48550/arXiv.2508.12627>. A pure R implementation (up to order 6) is also provided as a fallback that does not require 'Python'.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.0.0)
Imports: splines, corpcor, SMUT, ustats (>= 0.1.5)
Suggests: MASS, testthat (>= 3.0.0), reticulate, knitr, rmarkdown
URL: https://cxy0714.github.io/HOIF/, https://github.com/cxy0714/HOIF
BugReports: https://github.com/cxy0714/HOIF/issues
SystemRequirements: For the default Python backend: Python (>= 3.11) with the 'u-stats', 'numpy' and 'torch' packages (provisioned automatically on first use via 'reticulate', or via ustats::setup_ustats()). Not needed when pure_R_code = TRUE.
VignetteBuilder: knitr
Language: en-US
NeedsCompilation: no
Packaged: 2026-06-19 07:29:51 UTC; thinkbook-cxy
Author: Xingyu Chen [aut, cre], Lin Liu [aut]
Maintainer: Xingyu Chen <xingyuchen0714@sjtu.edu.cn>
Repository: CRAN
Date/Publication: 2026-06-24 08:40:10 UTC

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New package gaQSAR with initial version 1.2.3
Package: gaQSAR
Title: QSAR Modelling Using Genetic Algorithm Based Variable Selection
Version: 1.2.3
Description: Implements genetic algorithm-based variable selection for building quantitative structure-activity relationship (QSAR) models. The package provides a workflow for selecting optimal predictor subsets from large descriptor spaces using leave-one-out cross-validation (LOOCV) with Q2 as the fitness criterion. Features include automatic handling of multicollinearity via variance inflation factor (VIF) thresholding, customizable genetic algorithm operators, and diagnostic tools for model evaluation. Supports both training set optimization and external validation, plus nested (double) cross-validation for unbiased performance estimation and predictor stability diagnostics. Built-in visualization functions include Q2 curves and Williams plots to assess model applicability domain. The method is demonstrated in papers predicting antibacterial activity by Araya-Cloutier et al. (2018) <doi:10.1038/s41598-018-27545-4> and Kalli et al. (2021) <doi:10.1038/s41598-021-92964-9>.
License: GPL-3
Encoding: UTF-8
Imports: GA, future, future.apply, ggplot2, ggrepel, stats, scales, prospectr, reshape2
Suggests: knitr, rmarkdown, QSARdata
VignetteBuilder: knitr
URL: https://github.com/joshageman/gaQSAR
BugReports: https://github.com/joshageman/gaQSAR/issues
NeedsCompilation: no
Author: Jos Hageman [aut, cre]
Maintainer: Jos Hageman <jos.hageman@wur.nl>
Packaged: 2026-06-18 20:49:14 UTC; josha
Repository: CRAN
Date/Publication: 2026-06-24 08:20:07 UTC

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New package formulaiv with initial version 0.1.0
Package: formulaiv
Title: Sensitivity of Formula Instrument to Shock Design
Version: 0.1.0
Description: Functions to implement the formula instrument method in Borusyak and Hull (2023) <doi:10.3982/ECTA19367> and examine its sensitivity to the assumed distributional of counterfactual shocks.
License: MIT + file LICENSE
URL: https://github.com/peizansheng/formulaiv
BugReports: https://github.com/peizansheng/formulaiv/issues
Encoding: UTF-8
LazyData: true
LazyDataCompression: xz
Imports: stats, lpSolve
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
Depends: R (>= 3.5)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-06-19 15:38:42 UTC; peizan
Author: Peizan Sheng [aut, cre]
Maintainer: Peizan Sheng <peizan@uchicago.edu>
Repository: CRAN
Date/Publication: 2026-06-24 09:00:11 UTC

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New package ExtremeConformal with initial version 0.2.2
Package: ExtremeConformal
Title: Extreme Conformal Prediction Intervals
Version: 0.2.2
Description: This new extreme conformal prediction framework provides informative prediction intervals at the high-confidence levels for which classical conformal methods fail. In applications with potentially high-impact events, a very high level of confidence is often required for predictions. If that level is too large relative to the amount of data used for calibration, classical conformal methods provide infinitely wide, thus, uninformative prediction intervals. Our extreme conformal procedure bridges extreme value statistics and conformal prediction to provide reliable and informative prediction intervals with high-confidence coverage, which can be constructed using any black-box extreme quantile regression method. A weighted version of the approach can account for nonstationary data. The methodology was introduced in Pasche, Lam, and Engelke (2026) <doi:10.1007/s10687-026-00536-9>.
License: GPL (>= 3)
Encoding: UTF-8
Imports: ExtremeCI, extRemes, ismev, stats
URL: https://github.com/opasche/ExtremeConformal, https://opasche.github.io/ExtremeConformal/
BugReports: https://github.com/opasche/ExtremeConformal/issues
NeedsCompilation: no
Packaged: 2026-06-18 16:41:44 UTC; pascheo
Author: Olivier C. Pasche [aut, cre, cph]
Maintainer: Olivier C. Pasche <olivier_pasche@alumni.epfl.ch>
Repository: CRAN
Date/Publication: 2026-06-24 08:10:07 UTC

More information about ExtremeConformal at CRAN
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New package dqcheckrGUI with initial version 0.1.0
Package: dqcheckrGUI
Title: Point-and-Click GUI Client for 'dqcheckr'
Version: 0.1.0
Date: 2026-06-18
Description: A graphical user interface for the 'dqcheckr' package. Provides a point-and-click 'shiny' application for configuring dataset quality checks, running them against recurring file deliveries, and browsing historical check results — without writing any R code.
License: MIT + file LICENSE
URL: https://github.com/mickmioduszewski/dqcheckrGUI
BugReports: https://github.com/mickmioduszewski/dqcheckrGUI/issues
Encoding: UTF-8
Language: en-GB
Depends: R (>= 4.2)
Imports: dqcheckr (>= 0.2.2), shiny, bslib, shinyvalidate, shinyFiles, shinyAce, reactable, DT, callr, yaml, readr, DBI, RSQLite, stats, tools
Suggests: testthat (>= 3.1.0), knitr, rmarkdown, shinytest2, withr
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-06-18 20:36:58 UTC; mick
Author: Mick Mioduszewski [aut, cre]
Maintainer: Mick Mioduszewski <mick@mioduszewski.net>
Repository: CRAN
Date/Publication: 2026-06-24 08:20:13 UTC

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New package dataProfilerR with initial version 0.2.1
Package: dataProfilerR
Title: Automated Exploratory Data Analysis and Dataset Profiling
Version: 0.2.1
Description: Profiles a data frame with minimal input: column type inference, missing-value analysis, distributional summary statistics (including skewness and kurtosis), normality tests, outlier detection, correlation and categorical-association analysis, date-column profiling, grouped comparisons and an overall data-quality score, alongside a set of 'ggplot2' visualisations. A single entry point, profile_data(), returns a structured S3 object holding metadata, statistics, diagnostics and plots, with print(), summary() and plot() methods, and report() renders the whole profile to a self-contained HTML file. Statistical methods include the Shapiro-Wilk normality test as implemented by Royston (1995) <doi:10.2307/2986146> and the Anderson-Darling test following Stephens (1974) <doi:10.1080/01621459.1974.10480196>, with power comparisons of these tests in Yap and Sim (2011) <doi:10.1080/00949655.2010.520163>, and the categorical association measure of Cramer (1946, ISBN:978069108004 [...truncated...]
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-GB
Depends: R (>= 4.1.0)
Imports: ggplot2, stats, utils
Suggests: testthat (>= 3.0.0), knitr, rmarkdown, nortest, spelling
VignetteBuilder: knitr
URL: https://github.com/mqfarooqi1/dataProfilerR
BugReports: https://github.com/mqfarooqi1/dataProfilerR/issues
NeedsCompilation: no
Packaged: 2026-06-18 22:53:01 UTC; faroo
Author: Muhammad Farooqi [aut, cre]
Maintainer: Muhammad Farooqi <mqfarooqi@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-24 08:20:18 UTC

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New package countryatlas with initial version 1.0.0
Package: countryatlas
Title: Join World Bank Data, Country Codes and Maps on the ISO Spine
Version: 1.0.0
Description: A complete toolkit for getting country data onto honest maps. Country names rarely line up across data sources ("US", "U.S.", "United States", "United States of America" are one country, but a naive join treats them as four), so 'countryatlas' makes ISO codes the universal join key. It generalises a one-call, map-ready table that stitches together 'ggplot2' map geometry, 'WDI' World Bank indicators and the 'countrycode' Rosetta stone; exposes the join machinery for the user's own data; ships curated reference data (metadata, group memberships, an indicator catalogue, flags and currencies); adds analysis helpers (per-capita, regional roll-ups, ranking); and turns one hand-drawn choropleth into a full vocabulary of projected, area-honest maps (binned and quantile choropleths, proportional-symbol, bivariate, cartogram, tile-grid, flow, animated and interactive). Heavy spatial dependencies stay optional, and a bundled offline snapshot lets every example, test and vignette run without the n [...truncated...]
License: GPL (>= 3)
URL: https://pursuitofdatascience.github.io/countryatlas/, https://github.com/PursuitOfDataScience/countryatlas
BugReports: https://github.com/PursuitOfDataScience/countryatlas/issues
Encoding: UTF-8
LazyData: true
Depends: R (>= 4.1.0)
Imports: cli, countrycode, dplyr, ggplot2, memoise, rlang, tibble, tidyr, WDI
Suggests: biscale, cartogram, classInt, covr, gganimate, geofacet, ggiraph, ggrepel, knitr, leaflet, maps, plotly, rmapshaper, rmarkdown, rnaturalearth, rnaturalearthdata, scales, sf, stringdist, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-06-19 14:28:17 UTC; youzhi
Author: Youzhi Yu [aut, cre]
Maintainer: Youzhi Yu <yuyouzhi666@icloud.com>
Repository: CRAN
Date/Publication: 2026-06-24 09:00:17 UTC

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New package BIGpopA with initial version 1.0.5
Package: BIGpopA
Title: Pedigree Validation Genetic Composition of Diploids & Polyploids
Version: 1.0.5
Maintainer: Josue Chinchilla-Vargas <josue.chinchilla@ufl.edu>
Description: Tools for pedigree quality control and genomic breed/line composition estimation in diploid and polyploid breeding populations. 'BIGpopA' provides functions to check and correct common pedigree errors, assign parentage from SNP genotype data using Mendelian error rates, validate parent-offspring trios, and estimate genome-wide breed or line composition using quadratic programming. Supports both diploid and polyploid species. For more details about the included 'breedTools' functions, see Funkhouser et al. (2017) <doi:10.2527/tas2016.0003>.
License: Apache License (>= 2)
URL: https://github.com/Breeding-Insight/BIGpopA
BugReports: https://github.com/Breeding-Insight/BIGpopA/issues
Encoding: UTF-8
Depends: R (>= 4.4.0)
Imports: dplyr, janitor, quadprog, data.table, ggplot2
Suggests: covr, knitr (>= 1.10), rmarkdown, testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-06-18 20:36:44 UTC; josue.chinchilla
Author: Josue Chinchilla-Vargas [cre, aut], Alexander Sandercock [aut], University of Florida [cph]
Repository: CRAN
Date/Publication: 2026-06-24 08:20:24 UTC

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New package sentixr with initial version 0.2.0
Package: sentixr
Title: Lexicons and Tools for Italian Sentiment Analysis
Version: 0.2.0
Description: Lexicons and tools to perform sentiment analysis on Italian texts. Lexicons included: Sentix 3.0, MAL, ElIta VAD and basic emotions (Plutchik's wheel of emotions). For more details about the lexicons, see Basile & Nissim (2013), "Sentiment Analysis on Italian Tweets", <https://aclanthology.org/W13-1614/>; Vassallo et al. (2019), "The Tenuousness of Lemmatization in Lexicon-based Sentiment Analysis", <https://aclanthology.org/2019.clicit-1.79/>; Di Palma (2024), "ELIta: A New Italian Language Resource for Emotion Analysis", <https://aclanthology.org/2024.clicit-1.36/>.
Language: en, it
Depends: R (>= 4.1), dplyr, tidyselect, rlang
Imports: udpipe
Suggests: knitr, rmarkdown, tidytext, spacyr, readtext, tibble, testthat (>= 3.0.0), remotes, quanteda, mockery
VignetteBuilder: knitr
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
URL: https://github.com/valeriobasile/sentixr
Packaged: 2026-06-18 14:40:30 UTC; avard
Author: Agnese Vardanega [aut, cre] , Valerio Basile [aut] , Eliana Di Palma [aut] , Giuliano Gabrieli [aut] , Marco Vassallo [aut]
Maintainer: Agnese Vardanega <avardanega@unite.it>
Repository: CRAN
Date/Publication: 2026-06-24 07:50:02 UTC

More information about sentixr at CRAN
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New package rCoros with initial version 0.1.0
Package: rCoros
Title: Access COROS Training Hub Fitness Data
Version: 0.1.0
Date: 2026-06-07
Description: Provides a tidy interface to the 'COROS' Training Hub API (<https://coros.com/traininghub>), the web platform that accompanies 'COROS' GPS sports watches. Retrieves activities, daily wellness metrics (heart rate variability, resting heart rate, VO2 max and training load), workout programmes and training calendars. All results are returned as tibbles, ready for analysis with 'dplyr' and 'ggplot2'. Both the US and EU regional endpoints are supported.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: digest (>= 0.6.30), dplyr (>= 1.1.0), httr2 (>= 1.0.0), purrr (>= 1.0.0), tibble (>= 3.2.0)
Suggests: ggplot2 (>= 3.4.0), knitr (>= 1.40), rmarkdown (>= 2.20), testthat (>= 3.0.0), withr (>= 2.5.0)
VignetteBuilder: knitr
URL: https://github.com/mattyoreilly/rCoros, https://mattyoreilly.github.io/rCoros/
BugReports: https://github.com/mattyoreilly/rCoros/issues
NeedsCompilation: no
Packaged: 2026-06-08 07:03:30 UTC; mattoreilly
Author: Matt O'Reilly [aut, cre]
Maintainer: Matt O'Reilly <fermoymatt@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-24 08:00:02 UTC

More information about rCoros at CRAN
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New package hydrochem with initial version 0.1.0
Package: hydrochem
Title: Analysis and Visualization Tools for Hydrochemical Analysis
Version: 0.1.0
Description: Provides a comprehensive suite of tools for processing, analyzing, and visualizing hydrochemical data in a reproducible and programmatic workflow. Implements unit conversion, censored data management, ionic balance calculation, water type classification, and a range of hydrochemical indices relevant to water quality assessment. Offers advanced visualization functions for generating Piper (Piper, 1944, <doi:10.1029/TR025i006p00914>), Durov (Durov, 1948), Stiff (Stiff, 1951, <doi:10.2118/951376-G>), Collins (Collins, 1923, <doi:10.1021/ie50160a030>), Schoeller (Schoeller, 1935), Gibbs (Gibbs, 1970, <doi:10.1126/science.170.3962.1088>), and ternary diagrams — the standard graphical tools used in hydrochemical interpretation. Unlike existing solutions that rely on spreadsheets or proprietary graphical software, 'hydrochem' is designed for scalability and reproducibility, lowering the technical barrier for hydrochemists working with datasets of varying complexity. I [...truncated...]
License: GPL-2
Depends: R (>= 4.1.0)
Imports: cowplot (>= 1.2.0), data.table (>= 1.16.2), ggplot2 (>= 3.5.1), grDevices, scales (>= 1.4.0), stats
Suggests: spelling
Encoding: UTF-8
Language: en-US
LazyData: true
NeedsCompilation: no
Packaged: 2026-06-18 16:10:27 UTC; busemorose
Author: Guillaume Cinkus [aut, cre] , Raphael Bondu [aut]
Maintainer: Guillaume Cinkus <guillaume.cinkus@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-24 08:00:16 UTC

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New package ggtaichi with initial version 0.1.0
Package: ggtaichi
Title: Taichi-Diagram Visualization for Two Data Sources
Version: 0.1.0
Description: A data visualization design that compares two (usually on a par with each other) data sources on one grid of taichi (yin-yang) diagrams, where the two interlocking fish of every symbol are filled by the two sources, while inheriting 'ggplot2' features.
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
URL: https://github.com/PursuitOfDataScience/ggtaichi
BugReports: https://github.com/PursuitOfDataScience/ggtaichi/issues
Depends: R (>= 3.5.0)
Imports: rlang, grid, ggplot2 (>= 3.0.0), ggnewscale (>= 0.4.5)
Suggests: rmarkdown, knitr, dplyr, scales, tidyr
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-06-18 16:09:09 UTC; youzhi
Author: Youzhi Yu [aut, cre]
Maintainer: Youzhi Yu <yuyouzhi666@icloud.com>
Repository: CRAN
Date/Publication: 2026-06-24 08:00:22 UTC

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New package geovizr with initial version 1.0.0
Package: geovizr
Title: Interactive Cartography
Version: 1.0.0
Description: Create a wide range of interactive, zoomable vector maps. This package is an 'R' binding for the 'geoviz' 'JavaScript' library <https://github.com/riatelab/geoviz/>, itself based on the 'd3.js' ecosystem <doi:10.1109/TVCG.2011.185>. Like the original 'JavaScript' library, the package takes advantage of the many features provided by 'd3.js': proportional symbols, pictograms, typologies, choropleth maps, spikes, tiles, Dorling cartograms, and more. It can also be used to create pretty static vectorial maps in 'svg' format, suitable for editorial cartography.
License: GPL (>= 3)
URL: https://riatelab.github.io/geovizr/
BugReports: https://github.com/riatelab/geovizr/issues/
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: htmlwidgets, geojsonsf, jsonlite, sf
Language: en-US
NeedsCompilation: no
Packaged: 2026-06-18 14:19:51 UTC; nlambert
Author: Nicolas Lambert [aut, cre] , Timothee Giraud [ctb]
Maintainer: Nicolas Lambert <nicolas.lambert@cnrs.fr>
Repository: CRAN
Date/Publication: 2026-06-24 07:40:37 UTC

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New package blockwise with initial version 0.1.2
Package: blockwise
Title: Reduced Modeling for Tabular Data with Blockwise Missingness
Version: 0.1.2
Description: Supervised learning on tabular data with blockwise missing patterns, using the Blockwise Reduced Modeling (BRM) method of Srinivasan, Currim, and Ram (2025) <doi:10.1287/ijds.2022.9016>. BRM partitions the training data into overlapping subsets based on per-row feature-missing patterns, fits one user-supplied learner per subset with minimal imputation, and at prediction time routes each test instance to the best-matching subset model. The interface is learner-agnostic: any fit-and-predict pair can be plugged in, and convenience specifications are provided for linear models, tree models, random forests, and gradient boosting.
License: GPL-3
Language: en-US
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.6.0)
Imports: stats, VIM, withr
Suggests: testthat (>= 3.0.0), knitr, rmarkdown, rpart, ranger, gbm, ggplot2
VignetteBuilder: knitr
URL: https://github.com/KarAnalytics/blockwise
BugReports: https://github.com/KarAnalytics/blockwise/issues
NeedsCompilation: no
Packaged: 2026-06-18 16:03:18 UTC; k639s258
Author: Karthik Srinivasan [aut, cre] , Faiz Currim [aut], Sudha Ram [aut]
Maintainer: Karthik Srinivasan <karthiks@ku.edu>
Repository: CRAN
Date/Publication: 2026-06-24 08:00:27 UTC

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Tue, 23 Jun 2026

New package msprog with initial version 1.0.0
Package: msprog
Title: Reproducible Assessment of Disability Course in Multiple Sclerosis
Version: 1.0.0
Description: Analyse disability course in multiple sclerosis (MS) from longitudinal data. The package provides a flexible framework for identifying disability events under user-specified criteria, allowing adaptation to different study designs and endpoints. Tools are included to facilitate transparent and reproducible reporting of the settings used in the analysis. For an introduction to the package and illustrative applications, see Montobbio et al. (2024) <doi:10.1177/13524585241243157>.
Encoding: UTF-8
LazyData: true
Imports: stats, dplyr, rlang
Depends: R (>= 4.1.0)
VignetteBuilder: knitr
Suggests: knitr, rmarkdown, xfun, DT
License: MIT + file LICENSE
NeedsCompilation: no
Packaged: 2026-06-18 13:56:40 UTC; nmontobbio
Author: Noemi Montobbio [aut, cre] , Francesca Bovis [rev], Luca Carmisciano [rev]
Maintainer: Noemi Montobbio <noemi.montobbio@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-23 16:00:02 UTC

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New package geer with initial version 0.1.0
Package: geer
Title: Bias-Reduced and Penalized Generalized Estimating Equations
Version: 0.1.0
Description: Fits marginal regression models for repeated or clustered responses using generalized estimating equations (GEE). Provides ordinary GEE estimators, bias-reduced and bias-corrected GEE estimators, and Jeffreys-type penalized GEE estimators for binary, count and continuous responses. Methods are described in Touloumis (2026a) <doi:10.48550/arXiv.2606.16043> and Touloumis (2026b) <doi:10.48550/arXiv.2606.16058>.
License: GPL-3
URL: https://github.com/AnestisTouloumis/geer
BugReports: https://github.com/AnestisTouloumis/geer/issues
Depends: R (>= 4.0.0)
Imports: brglm2, generics, Rcpp (>= 1.0.9)
LinkingTo: Rcpp, RcppArmadillo
Suggests: covr, emmeans (>= 2.0.0), estimability, testthat (>= 3.0.0), tibble
Encoding: UTF-8
LazyData: true
NeedsCompilation: yes
Packaged: 2026-06-18 12:42:46 UTC; Anestis
Author: Anestis Touloumis [aut, cre]
Maintainer: Anestis Touloumis <A.Touloumis@brighton.ac.uk>
Repository: CRAN
Date/Publication: 2026-06-23 14:50:02 UTC

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New package BayesFR with initial version 1.0.1
Package: BayesFR
Title: Fitting Functional Responses in 1- and 2-Prey Systems
Version: 1.0.1
Description: Easy application of Bayesian inference for functional responses via 'brms'. This package allows to fit various FR models for single- and multi-prey experiments by providing nonlinear prediction functions for 'brms'. It uses dynamical prediction models to correct for prey depletion. The 'brms' framework facilitates statistical modeling and enables users to conveniently incorporate covariates such as temperature gradients, experimental treatment variables, or random effects that account for grouping in experimental units. Default 'brms' functions make it easy to perform model checking, model comparison and hypothesis testing. Potential statistical issues with data from feeding trials, such as overdispersion, can be resolved by effortlessly switching between likelihood functions. This package, together with its tutorials, should provide students and researchers with a comprehensive and integrated statistical framework for easily testing their hypotheses on trophic interactions. References [...truncated...]
License: GPL (>= 3)
Encoding: UTF-8
URL: https://github.com/benjamin-rosenbaum/BayesFR
BugReports: https://github.com/benjamin-rosenbaum/BayesFR/issues
LazyData: TRUE
Imports: brms, ggplot2, tidyr
Depends: R (>= 3.5)
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-06-18 12:25:07 UTC; br86redu
Author: Benjamin Rosenbaum [aut, cre]
Maintainer: Benjamin Rosenbaum <benjamin.rosenbaum@idiv.de>
Repository: CRAN
Date/Publication: 2026-06-23 14:50:08 UTC

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New package srr with initial version 1.0.0
Package: srr
Title: 'rOpenSci' Software Review 'Roclets'
Version: 1.0.0
Description: Companion package to 'rOpenSci' statistical software review project ('rOpenSci' authors, 2021; <doi:10.5281/zenodo.5556756>), to facilitate documenting software compliance with statistical standards using 'Roxygen2' 'roclets'.
License: MIT + file LICENSE
URL: https://docs.ropensci.org/srr/, https://github.com/ropensci-review-tools/srr
BugReports: https://github.com/ropensci-review-tools/srr/issues
Imports: cli, clipr, fs, gert, here, methods, Rcpp, roxygen2, rprojroot
Suggests: jsonlite, knitr, pkgbuild, rmarkdown, testthat (>= 3.0.0), toml
LinkingTo: Rcpp
VignetteBuilder: knitr
Encoding: UTF-8
Language: en-GB
NeedsCompilation: yes
Packaged: 2026-06-18 09:45:06 UTC; smexus
Author: Mark Padgham [aut, cre]
Maintainer: Mark Padgham <mark@ropensci.org>
Repository: CRAN
Date/Publication: 2026-06-23 14:00:02 UTC

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New package rphylo with initial version 0.1.1
Package: rphylo
Title: Phylogenetic Analysis with Dependent Discrete Models
Version: 0.1.1
Description: Implementation of dependent discrete models (with reversible jump MCMC) derived from 'BayesTraits' V5.0.3 <https://github.com/AndrewPMeade/BayesTraits-Release/tree/Release>. Original software copyright Andrew Meade and contributors, distributed under GPL-3. Modifications for this package by Vivian G. Li <liguo.vivian@gmail.com>. The following articles should be referenced when using this package: Pagel, M., A. Meade and D. Barker (2004) "Bayesian estimation of ancestral character states on phylogenies" <doi:10.1080/10635150490522232>; Pagel, M. (1994) "Detecting correlated evolution on phylogenies: a general method for the comparative analysis of discrete characters" <doi:10.1098/rspb.1994.0006>; Pagel, M. and A. Meade (2006) "Bayesian analysis of correlated evolution of discrete characters by reversible-jump Markov chain Monte Carlo" <doi:10.1086/503444>.
License: GPL-3
Encoding: UTF-8
Imports: ape, phangorn, expm, stats
LazyData: true
Depends: R (>= 3.5)
NeedsCompilation: no
Packaged: 2026-06-18 03:16:46 UTC; v
Author: Vivian G. Li [aut, cre], Andrew Meade [ctb] , Mark Pagel [ctb]
Maintainer: Vivian G. Li <liguo.vivian@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-23 13:30:02 UTC

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New package llmimpute with initial version 0.1.0
Package: llmimpute
Title: Missing Data Imputation via Language Models and Statistics
Version: 0.1.0
Description: Provides missing data imputation through two complementary engines: a large language model engine that communicates with the 'Anthropic' 'Claude' application programming interface for context-aware semantic imputation, and a fully self-contained offline engine implementing nineteen statistical and machine learning algorithms entirely in base R with no additional package dependencies. Offline methods include mean, median, mode, last observation carried forward, next observation carried backward, hot-deck, predictive mean matching, k-nearest neighbours, ordinary least-squares regression, Lasso with coordinate descent, Ridge with closed-form solution, Bayesian Ridge regression with evidence approximation following MacKay (1992), support vector regression with a radial basis function kernel, classification and regression trees, random forests, gradient boosting, iterative random forest imputation, principal component analysis imputation via iterative singular value decomposition, and nucle [...truncated...]
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-US
Depends: R (>= 4.1.0)
Imports: httr2 (>= 1.0.0), methods, jsonlite (>= 1.8.0), cli (>= 3.6.0),
Suggests: testthat (>= 3.0.0), knitr (>= 1.40), rmarkdown (>= 2.14), withr (>= 2.5.0)
VignetteBuilder: knitr
BugReports: https://cran.r-project.org/submit.html
NeedsCompilation: no
Packaged: 2026-06-18 06:25:03 UTC; acer
Maintainer: Sadikul Islam <sadikul.islamiasri@gmail.com>
Author: Sadikul Islam [aut, cre] , Rajesh Kaushal [aut]
Repository: CRAN
Date/Publication: 2026-06-23 13:40:02 UTC

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New package LatSquare with initial version 0.4.1
Package: LatSquare
Title: Analysis of Latin Square and Semi-Latin Square Designs
Version: 0.4.1
Description: Provides functions for the analysis of Latin Square and Semi-Latin Square (Latin Rectangle) experimental designs, including analysis of variance (ANOVA), least significant difference (LSD) tests, and calculation of summary statistics. The implemented methods follow Munzert (1992, ISBN: 3-489-53410-7).
Depends: R (>= 4.0.0)
Imports: openxlsx
License: GPL-3
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-06-18 09:18:46 UTC; Heinrich.Holzner
Author: Heinrich Holzner [aut, cre]
Maintainer: Heinrich Holzner <heholzner@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-23 14:00:09 UTC

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New package imdR with initial version 0.1.1
Package: imdR
Title: Download, Process and Visualize IMD Gridded Meteorological Data
Version: 0.1.1
Description: Interface to India Meteorological Department (IMD) gridded daily rainfall (0.25 degree, 1901-present) and temperature (1.0 degree, 1951-present) binary data. Provides functions to download, read, extract by point or boundary, compute climate indices, perform trend analysis, and produce publication-quality maps with Survey of India approved boundaries.
License: MIT + file LICENSE
URL: https://github.com/Subhradip25/imdR
BugReports: https://github.com/Subhradip25/imdR/issues
Encoding: UTF-8
Language: en-US
Depends: R (>= 4.1.0)
Imports: ggplot2, httr2, Kendall, ncdf4, rlang, sf, terra, tidyterra, zoo
LazyData: true
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-06-18 08:44:32 UTC; subhradip
Author: Subhradip Bhattacharjee [aut, cre], Amitava Panja [aut], Ankita Chakraborty [aut], Basavareddy [aut]
Maintainer: Subhradip Bhattacharjee <subhradip25@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-23 13:50:02 UTC

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New package BsplineQuantReg with initial version 0.1.0
Package: BsplineQuantReg
Title: 'Constrained Quantile Regression with Cubic B-Splines'
Version: 0.1.0
Date: 2026-06-01
Description: Quantile regression with cubic B-splines under monotonicity and convexity constraints using the Karlin-Studden SOCP formulation. The method is described in Abbes (2026) <doi:10.5281/zenodo.17427913>. This R implementation is intended for demonstration and prototyping; all B-spline and polynomial functions have been rewritten for consistency. A faster version written in 'Python' is available at <https://github.com/alexandreabbes/Constrained-Quantile-Regression-with-cubic-splines>.
License: GPL-3
URL: https://github.com/alexandreabbes/BsplineQuantReg, https://doi.org/10.5281/zenodo.17427913
BugReports: https://github.com/alexandreabbes/BsplineQuantReg/issues
Depends: R (>= 3.5.0)
Imports: CVXR
Suggests: cobs,quantreg,pracma
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-06-18 08:24:17 UTC; Abbes
Author: Alexandre Abbes [aut, cre]
Maintainer: Alexandre Abbes <alexandre.abbes@proton.me>
Repository: CRAN
Date/Publication: 2026-06-23 13:50:08 UTC

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Mon, 22 Jun 2026

New package rolescry with initial version 0.1.0
Package: rolescry
Title: Name-Blind Variable-Role Detection by Data Signature
Version: 0.1.0
Description: Deterministic, name-blind detection of variable roles (group, outcome, survival time and event, paired and agreement measurements, repeated measures, scale items, subject identifier, covariate) in tabular data. Roles are assigned from each column's information-theoretic signature -- Shannon entropy, normalized mutual information, and distributional shape -- rather than from column names, so renaming columns to 'col_1', 'col_2', ... does not change the result ("Data inspice, non nomen"). An optional, capped name-based hint and automatic header-row detection are also provided. No large language models and no external data transmission. Extracted from the 'MDStatR' biostatistics engine; see Boynukara (2026) <doi:10.5281/zenodo.20707791>.
License: Apache License (== 2.0)
Encoding: UTF-8
Depends: R (>= 4.0.0)
Imports: stats, utils
Suggests: moments, diptest, stringdist, readxl, openxlsx, haven, testthat (>= 3.0.0), knitr, rmarkdown, spelling
VignetteBuilder: knitr
URL: https://github.com/canboynukara/rolescry
BugReports: https://github.com/canboynukara/rolescry/issues
Language: en-US
NeedsCompilation: no
Packaged: 2026-06-17 20:27:43 UTC; cboyn
Author: Can Boynukara [aut, cre, cph] , M. Yasir Ceyhan [ctb]
Maintainer: Can Boynukara <canboynukara1@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-22 16:20:02 UTC

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New package redeem with initial version 1.0.0
Package: redeem
Title: Relational Event and Durational Event Models
Version: 1.0.0
Date: 2026-06-18
Author: Cornelius Fritz [aut, cre]
Maintainer: Cornelius Fritz <corneliusfritz2010@gmail.com>
Description: Model relational and durational events in a counting process framework, with functions for estimating and simulating Relational Event Models (REM) and Durational Event Models (DEM). Includes support for time-varying covariates, windowed statistics, and high-dimensional node-level fixed effects. References include Fritz et al. (2026) "Scalable Durational Event Models: Application to Physical and Digital Interactions" <doi:10.48550/arXiv.2504.00049>.
License: GPL-3
Depends: R (>= 4.0.0)
Imports: Rcpp (>= 1.0.12), data.table, MASS, survival, stats, grDevices, graphics, utils, digest
LinkingTo: Rcpp, RcppProgress, RcppArmadillo
Suggests: testthat (>= 3.0.0), network, knitr, rmarkdown
VignetteBuilder: knitr
Encoding: UTF-8
URL: https://corneliusfritz.github.io/redeem/
BugReports: https://github.com/corneliusfritz/redeem/issues
NeedsCompilation: yes
Packaged: 2026-06-17 21:52:02 UTC; corneliusfritz
Repository: CRAN
Date/Publication: 2026-06-22 16:20:07 UTC

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New package geokmeans with initial version 0.1.0
Package: geokmeans
Title: A Collection of Fast, Exact and Eco-Friendly k-Means Clustering Algorithms
Version: 0.1.0
Description: A collection of fast k-means clustering algorithms under a single, uniform interface. The core method is Geometric-k-means, a bound-free algorithm of Sharma et al. (2026) <doi:10.1007/s10994-025-06891-1> that uses geometry to restrict computation to the data points able to change clusters, substantially reducing distance computations and runtime while returning the same result as standard k-means. Also included are Lloyd's algorithm, Elkan, Hamerly, Annulus, Exponion, and Ball k-means. All algorithms are implemented in 'C++' via 'Rcpp' and 'RcppEigen' and return the final centroids, optional per-point cluster assignments, and computational statistics.
License: GPL-3
Encoding: UTF-8
Imports: Rcpp
LinkingTo: Rcpp, RcppEigen
SystemRequirements: C++17
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
URL: https://github.com/parichit/Geometric-k-means
BugReports: https://github.com/parichit/Geometric-k-means/issues
NeedsCompilation: yes
Packaged: 2026-06-17 16:23:38 UTC; parichit
Author: Parichit Sharma [aut, cre, cph], Hasan Kurban [aut]
Maintainer: Parichit Sharma <parishar@iu.edu>
Repository: CRAN
Date/Publication: 2026-06-22 16:10:02 UTC

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New package riskutility with initial version 0.1.0
Package: riskutility
Title: Disclosure Risk and Data Utility Metrics for Synthetic and Anonymized Data
Version: 0.1.0
Description: Provides comprehensive methods to measure disclosure risk and data utility for anonymized and synthetic data. Implements attribution-based risk metrics including Correct Attribution Probability (CAP), Targeted CAP (TCAP), Within Equivalence Class Attribution Probability (WEAP), and RAPID (Risk of Attribute Prediction-Induced Disclosure). Also provides distance-based privacy metrics such as Distance to Closest Record (DCR), Nearest Neighbor Distance Ratio (NNDR), and Identical Match Share (IMS). Utility assessment includes propensity score analysis, distribution comparisons, and various statistical tests. Methods are based on Taub et al. (2018) <doi:10.1007/978-3-319-99771-1_9> and related literature. Designed for integration with 'simPop' S4 classes.
Depends: R (>= 4.1.0)
Imports: ggplot2, data.table, MASS, VIM, randomForest, ranger, reshape2, stats, graphics, utils
Suggests: simPop, synthpop, caretEnsemble, kernelshap, uwot, Rtsne, dbscan, vip, rpart, xgboost, partykit, testthat (>= 3.0.0), torch, knitr, rmarkdown, plotly, misc3d, sdcMicro, caret, robustbase, gridExtra, Hmisc, robCompositions, clue
License: GPL-3
URL: https://github.com/matthias-da/riskutility
BugReports: https://github.com/matthias-da/riskutility/issues
Encoding: UTF-8
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-06-17 11:54:46 UTC; matthias
Author: Matthias Templ [aut, cre] , Oscar Thees [ctb]
Maintainer: Matthias Templ <matthias.templ@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-22 15:40:09 UTC

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New package nocturn with initial version 1.1.3
Package: nocturn
Title: Sleep Data Filtering and Visualisation
Version: 1.1.3
Description: An online app and command-line utility to import, filter and visualise sleep data. Can be used with sleep data collected from any type of device (e.g. radar, sleep diary,...) as long as the data contains sleep onset and wake-up times for each sleep session.
License: MIT + file LICENSE
Encoding: UTF-8
Suggests: bslib, devtools, DT, markdown, readr, shinyjs, shinyWidgets, svglite, testthat
Imports: circular, cli, dplyr, edfReader, ggnewscale, ggplot2, lubridate, readxl, rlang, scales, shiny, shinyalert, stringr, tibble, tidyr, rsvg, svgedit, qpdf
Depends: R (>= 4.3)
LazyData: true
URL: https://github.com/chronopsychiatry/AMBIENT-BD-nocturn
BugReports: https://github.com/chronopsychiatry/AMBIENT-BD-nocturn/issues
NeedsCompilation: no
Packaged: 2026-06-17 15:35:11 UTC; dthedie
Author: Daniel Thedie [aut, cre, cph]
Maintainer: Daniel Thedie <daniel.thedie@ed.ac.uk>
Repository: CRAN
Date/Publication: 2026-06-22 16:00:02 UTC

More information about nocturn at CRAN
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New package nfcore.utils with initial version 0.0.4
Package: nfcore.utils
Version: 0.0.4
Date: 2026-06-17
Title: Utilities for 'nf-core' Modules
Depends: R (>= 4.4.0),
Imports: utils
Description: Provides utility functions to facilitate the use of R within nf-core modules. The package helps parse 'Nextflow' inputs and perform validation checks to ensure correct parameter handling and reproducible execution. For more details see Ewels (2020) <doi:10.1038/s41587-020-0439-x>.
License: MIT + file LICENSE
Encoding: UTF-8
VignetteBuilder: knitr
Suggests: testthat (>= 3.0.0), rmarkdown, BiocStyle, knitr, withr, yaml
BugReports: https://github.com/nf-core/r-nf-core-utils/issues
URL: https://github.com/nf-core/r-nf-core-utils
NeedsCompilation: no
Packaged: 2026-06-17 10:25:41 UTC; llenezet
Author: nf-core Community [aut], Louis Le Nezet [aut, cre, cph]
Maintainer: Louis Le Nezet <louislenezet@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-22 15:10:02 UTC

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New package lzrq with initial version 0.1.0
Package: lzrq
Title: Quantile Regression for Logarithmic Relationships with Non-Positive Outcome Values
Version: 0.1.0
Maintainer: Jack Fitzgerald <jackfitzgeraldresearch@gmail.com>
Description: Provides the lzrq() function for estimating logarithmic regression slopes in quantile regression models, permitting the outcome variable to take on non-positive values. lzrq() conducts regression after replacing non-positive values with a sufficiently negative value. If the fitted values of a quantile regression on this transformed outcome are all greater than the negative value, then results are displayed. The resulting coefficients can be meaningfully interpreted as logarithmic intensive-margin relationships between the outcome variable and the independent variables, even with non-positive values in the outcome variable. If the condition does not hold for the specified quantile, then the command iteratively makes the value larger and checks again. After ten iterations where the condition does not hold, the functions return an error and suppress results. This is an automated adaptation of the algorithm described by Liu & Kaplan (2025) <https://drive.google.com/file/d/1F3dnhm8Mr [...truncated...]
License: CC BY 4.0
Encoding: UTF-8
URL: https://github.com/jack-fitzgerald/lzrq
BugReports: https://github.com/jack-fitzgerald/lzrq/issues
Imports: MASS, quantreg, stats
NeedsCompilation: no
Packaged: 2026-06-17 10:30:09 UTC; jackfitzgerald
Author: David Valenta [aut], Jack Fitzgerald [aut, cre]
Repository: CRAN
Date/Publication: 2026-06-22 15:10:08 UTC

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New package lstar with initial version 0.1.0
Package: lstar
Title: Uniform Data Model and 'Zarr' Interchange for Single-Cell Omics
Version: 0.1.0
Description: A lightweight interchange layer for single-cell and spatial omics data, built on the L-star model of labelled axes and typed fields over them, serialized to the 'Zarr' format. Provides bidirectional converters ("profiles") for 'Seurat', 'SingleCellExperiment', 'Conos', and 'pagoda2' objects, including collections of heterogeneous samples, via a shared C++ core ('libstar') so the same store is readable from R, 'Python', and C++.
License: MIT + file LICENSE
Encoding: UTF-8
URL: https://github.com/kharchenkolab/lstar
BugReports: https://github.com/kharchenkolab/lstar/issues
LinkingTo: cpp11
Imports: Matrix, methods, stats, utils
Suggests: SeuratObject, Seurat, SingleCellExperiment, SummarizedExperiment, S4Vectors, GenomicRanges, igraph, conos, pagoda2, BPCells, HDF5Array, testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
Additional_repositories: https://bnprks.r-universe.dev
SystemRequirements: C++17, zlib
NeedsCompilation: yes
Packaged: 2026-06-17 13:55:54 UTC; pkharchenko
Author: Peter Kharchenko [aut, cre]
Maintainer: Peter Kharchenko <pk.restricted@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-22 15:50:07 UTC

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New package dragmapr with initial version 0.2.0
Package: dragmapr
Title: Create Draggable Plots from Projected Geometry
Version: 0.2.0
Description: Creates interactive draggable plots from grouped projected 'sf' geometry. The primary deliverable is a browser-based 'D3' helper where regions and labels can be moved freely; users drag, then copy or download the resulting offset tables. Labels can be derived automatically with make_region_labels(), supplied directly with as_drag_labels(), and their moved positions saved and restored with read_label_state() and apply_label_state(). Hierarchical spatial datasets are supported via hierarchy detection, upload profiling, make_hierarchy_key(), and inherit_layout(), which recommend parent-child groupings and propagate parent-level drag offsets to finer child groupings. Automatic starting layouts are provided by suggest_offsets() using radial, grid, or directional algorithms. Spatial file diagnostics are available through dragmapr_diagnostics(). When a reproducible static image is also needed, render_dragged_map() reconstructs the layout as a 'ggplot2' plot from the source geometry plus the e [...truncated...]
License: MIT + file LICENSE
URL: https://prigasg.github.io/dragmapr/
BugReports: https://github.com/PrigasG/dragmapr/issues
Imports: ggplot2, grid, jsonlite, rlang, sf, stats, tools, utils
Suggests: glasstabs, knitr, miniUI, pkgdown, rmarkdown, shiny, shinyWidgets (>= 0.8.6), spelling, testthat (>= 3.0.0)
VignetteBuilder: knitr
Encoding: UTF-8
Language: en-US
NeedsCompilation: no
Packaged: 2026-06-17 13:23:32 UTC; priga
Author: George Arthur [aut, cre]
Maintainer: George Arthur <prigasgenthian48@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-22 15:40:29 UTC

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New package tsqr with initial version 0.1.2
Package: tsqr
Title: Sequential Threshold-Spatial-Quantile Panel Estimation
Version: 0.1.2
Description: Implements a sequential panel estimation protocol for regional economic panels that combines three estimation layers in a fixed order. The first layer applies a two-way fixed effects baseline. The second layer applies the panel threshold regression method of Hansen (1999) <doi:10.1016/S0304-4076(99)00025-1> to identify structural breaks at an unknown threshold of a moderating variable, with bootstrap inference following Hansen (2000) <doi:10.1111/1468-0262.00124>. The third layer applies a spatial Durbin model with an impact decomposition following LeSage and Pace (2009, ISBN:978-1-4200-6424-7) to quantify direct and indirect spillover effects. The fourth layer applies the two-step panel quantile estimator of Canay (2011) <doi:10.1111/j.1368-423X.2011.00349.x> to document distributional heterogeneity in the outcome. The threshold identified in the second layer defines a subsample used as structured input to the fourth layer, and a consistency check evaluates whether t [...truncated...]
License: GPL-3
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: plm (>= 2.6-0), spdep (>= 1.2-0), spatialreg (>= 1.2-0), quantreg (>= 5.90), ggplot2 (>= 3.4.0), stats, utils
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-06-16 15:36:46 UTC; nehadhanawade
Author: Prakash Vhankade [aut, cre]
Maintainer: Prakash Vhankade <prakash.vhankade@gipe.ac.in>
Repository: CRAN
Date/Publication: 2026-06-22 15:00:02 UTC

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New package tl with initial version 0.0.1
Package: tl
Title: Tiny Logging Interface to 'rspdlite' Wrapping 'spdlite' C++20 Logging
Version: 0.0.1
Date: 2026-05-31
Description: Just how 'spdl' provides a nice and consistent interface to 'spdlog' (via 'RcppSpdlog'), this package does so for 'spdlite', the lightweight header-only C++-20 logging library that provides a lighter version of 'spdlog'. This package is essentially a thin shim around it for a more compact interface from both R and C++.
URL: https://github.com/eddelbuettel/tl
BugReports: https://github.com/eddelbuettel/tl/issues
License: GPL (>= 2)
Imports: rspdlite
Suggests: tinytest
NeedsCompilation: no
Packaged: 2026-06-17 12:54:00 UTC; edd
Author: Dirk Eddelbuettel [aut, cre]
Maintainer: Dirk Eddelbuettel <edd@debian.org>
Repository: CRAN
Date/Publication: 2026-06-22 15:00:07 UTC

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New package Rfuzzydid with initial version 1.1.2
Package: Rfuzzydid
Title: Fuzzy Difference in Differences
Description: Differences in differences is a methodology to measure the impact of a treatment by comparing a control group, which remains untreated at two different time periods, with a treatment group, which receives the treatment at the later date. In many cases, this approach is used in situations where the intervention doesn't fully apply the treatment to the entire treatment group but rather increases the treatment rate. In response to such fuzzy scenarios, de Chaisemartin and D'Haultfoeuille (2018) <doi:10.1093/restud/rdx049> introduce estimands capable of identifying local average and quantile treatment effects under various assumptions. This R package computes the estimators they are proposing.
Version: 1.1.2
Author: Kevin Michael Frick [aut, cre]
Maintainer: Kevin Michael Frick <kmfrick@proton.me>
License: AGPL-3
Depends: R (>= 3.6.0)
Encoding: UTF-8
Imports: generics, knitr, rmarkdown
Suggests: broom, foreign, haven, modelsummary, pkgload, testthat (>= 3.0.0)
VignetteBuilder: knitr
URL: https://kmfrick.github.io/Rfuzzydid/, https://github.com/kmfrick/Rfuzzydid
BugReports: https://github.com/kmfrick/Rfuzzydid/issues
NeedsCompilation: no
Packaged: 2026-06-16 14:15:34 UTC; kmfrick
Repository: CRAN
Date/Publication: 2026-06-22 14:50:02 UTC

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New package pslr with initial version 1.0.1
Package: pslr
Title: Public Suffix List Engine
Version: 1.0.1
Description: A focused implementation of the Public Suffix List (PSL). Bundles a reproducible, pinned PSL snapshot and implements the official prevailing-rule algorithm to answer public-suffix (eTLD) and registrable-domain (eTLD+1) queries. Distinguishes ICANN and PRIVATE rule sections, accepts Unicode and ASCII hostnames via 'punycoder' canonicalization, and supports an explicit, validated offline refresh path. The matcher is compiled with 'cpp11' and requires no external system library.
License: MIT + file LICENSE
Language: en-US
URL: https://github.com/bart-turczynski/pslr
BugReports: https://github.com/bart-turczynski/pslr/issues
Encoding: UTF-8
Depends: R (>= 4.0.0)
Imports: punycoder (>= 1.1.0), tools, utils
LinkingTo: cpp11
Suggests: cucumber (>= 2.0.0), curl, digest, knitr, rmarkdown, testthat (>= 3.0.0), withr
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2026-06-16 11:31:10 UTC; bartturczynski
Author: Bart Turczynski [aut, cre]
Maintainer: Bart Turczynski <bartek+pslr@turczynski.pl>
Repository: CRAN
Date/Publication: 2026-06-22 14:40:02 UTC

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New package NeutroSplitStripAnalysis with initial version 0.0.1
Package: NeutroSplitStripAnalysis
Title: Neutrosophic Analysis of Split-Plot and Strip-Plot Designs
Version: 0.0.1
Maintainer: Vinaykumar L.N. <vinaymandya123@gmail.com>
Description: Provides methods for Neutrosophic Analysis of Variance (NANOVA) for split-plot and strip-plot experimental designs using interval-valued observations. The package computes neutrosophic sums of squares, mean squares, interval-valued F-statistics, significance tests, and Least Significant Difference (LSD) based multiple comparisons for main plot, sub plot, horizontal factor, vertical factor, and interaction effects. For crisp data, users may provide identical lower and upper response values to obtain results equivalent to classical analysis of variance. The basic idea of neutrosophic statistics is obtained from Smarandache (2014) <https://fs.unm.edu/NeutrosophicStatistics.pdf>, while the analysis procedures implemented in this package are newly developed.
License: GPL-3
Encoding: UTF-8
Imports: MASS, stats
Depends: R (>= 4.1.0)
NeedsCompilation: no
Packaged: 2026-06-17 12:09:46 UTC; admin
Author: Boyina Devi Priyanka [aut, ctb], Neethu R.S [aut, ctb], Cini Varghese [aut, ctb], Mohd Harun [aut, ctb], Anindita Datta [aut, ctb], Susheel kumar [aut, ctb], Vinaykumar L.N. [aut, cre]
Repository: CRAN
Date/Publication: 2026-06-22 15:00:28 UTC

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New package momst with initial version 0.1.1
Package: momst
Title: Multi-Objective Minimum Spanning Tree via NSGA-II with Local Search
Version: 0.1.1
Description: Solves the Multi-Criteria Minimum Spanning Tree (mc-MST) problem on complete weighted graphs by combining the Non-dominated Sorting Genetic Algorithm II (NSGA-II) with optional Pareto local search operators. Chromosomes are represented as Prufer sequences so that every random individual decodes to a valid spanning tree (Cayley's theorem), avoiding repair operators. Four solver variants are provided: pure NSGA-II ("base"), Path Relinking ("PR"), Pareto Local Search ("PLS"), and Tabu Search ("TS"). The package supports 2 and 3 objective formulations and provides convenience functions to plot Pareto fronts and best-compromise spanning trees. This package is the reference implementation of the method described in Parraga-Alava, Inostroza-Ponta and Dorn (2017) <doi:10.1109/CEC.2017.7969432>.
License: GPL (>= 3)
URL: https://github.com/jorgeklz/momst, https://jorgeklz.github.io/momst/
BugReports: https://github.com/jorgeklz/momst/issues
Encoding: UTF-8
Depends: R (>= 4.0)
Imports: stats, utils, graphics
Suggests: igraph, knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-06-16 23:17:12 UTC; jorge
Author: Jorge A. Parraga-Alava [aut, cre]
Maintainer: Jorge A. Parraga-Alava <jorge.parraga@utm.edu.ec>
Repository: CRAN
Date/Publication: 2026-06-22 14:40:15 UTC

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New package lyubishchev with initial version 0.1.0
Package: lyubishchev
Title: Quantitative Taxonomy Methods of A.A. Lyubishchev (1943)
Version: 0.1.0
Description: Implements the multivariate classification methods of Alexander Alexandrovich Lyubishchev (1890-1972), as described in his 1943 manuscript 'Programma obshchey sistematiki' Lyubishchev (1943) <https://www.zin.ru/animalia/coleoptera/rus/lyubis05.htm> and published in Lubischew (1962) <https://www.jstor.org/stable/2527894>. Provides divergence_coefficient() for measuring separation between groups on continuous features, scatter_ellipse() for fitting covariance ellipses per class, transgression() for detecting ellipse overlap, and classify() for Bayesian posterior classification. These methods predate and are more general than the binary-character similarity coefficients of Sokal and Sneath (1963) that appear in other R packages.
License: MIT + file LICENSE
Encoding: UTF-8
Suggests: testthat (>= 3.0.0), knitr, rmarkdown, ggplot2
VignetteBuilder: knitr
URL: https://github.com/AkzhanBerdi/lyubishchev-r
BugReports: https://github.com/AkzhanBerdi/lyubishchev-r/issues
NeedsCompilation: no
Packaged: 2026-06-17 09:23:26 UTC; aki_berdi
Author: Akzhan Berdeyev [aut, cre]
Maintainer: Akzhan Berdeyev <akzhan.berdeyev@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-22 15:00:12 UTC

More information about lyubishchev at CRAN
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New package levelSets with initial version 0.8.2
Package: levelSets
Version: 0.8.2
Date: 2026-06-15
Title: Ray-Based Mapping and Visualization of Level Sets (Excursion Sets)
Author: Richard Raubertas [aut, cre]
Maintainer: Richard Raubertas <rrprf@emvt.net>
License: GPL (>= 3)
Depends: R (>= 3.5.0)
Imports: graphics, stats, tools, utils, proxy, withr
Suggests: ggplot2, randomForest, palmerpenguins, knitr, rmarkdown
Description: An (upper) level set of a function is the set of inputs for which the function value is at or above a specified threshold. (Also called an excursion set). Applications of level sets include confidence or credible regions for parameters of statistical models, where the function is the likelihood or posterior density; regions where classification rules assign high probability to a given class; and scientific or engineering models where one is interested in input regions for which model output is above a threshold. This package maps out the boundary of a level set by finding its intersections with collections of 1-dimensional rays, generalizing a proposal by Kim and Lindsay (Statistica Sinica 21:923-948, 2011). Tools are provided to generate rays, find intersections, and visualize results. The package makes few assumptions about the studied function: it may be discontinuous, it may have a complicated feasible region, and the target level set may be non-convex or have multiple, disco [...truncated...]
LazyData: yes
VignetteBuilder: knitr, rmarkdown
NeedsCompilation: no
Packaged: 2026-06-16 03:31:07 UTC; rfr
Repository: CRAN
Date/Publication: 2026-06-22 14:30:02 UTC

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New package kumquat with initial version 1.1.0
Package: kumquat
Title: A Smaller Version of LIME
Version: 1.1.0
Description: The existing implementation of 'lime' can be quite limiting in understanding the underlying components that make Local Local interpretable model-agnostic explanations (LIME) work. 'kumquat' is a simpler implementation of 'lime' that is easier to understand and is more transparent on the pieces that come together to make LIME work. For more details on LIME, see Ribeiro, Singh, and Guestrin (2016) <doi:10.1145/2939672.2939778>.
License: MIT + file LICENSE
Encoding: UTF-8
Suggests: colorspace, knitr, patchwork, randomForest, RColorBrewer, rmarkdown, testthat (>= 3.0.0), tidyverse
Imports: bundle, dplyr, ggplot2, glmnet, glue, logger, rlang, tidyr
Depends: R (>= 4.1.0)
LazyData: true
VignetteBuilder: knitr
URL: https://janithwanni.github.io/kumquat/, https://github.com/janithwanni/kumquat
BugReports: https://github.com/janithwanni/kumquat/issues
NeedsCompilation: no
Packaged: 2026-06-16 04:22:34 UTC; jwan0443
Author: Janith Wanniarachchi [aut, cre, cph]
Maintainer: Janith Wanniarachchi <janithcwanni@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-22 14:40:20 UTC

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New package jirar with initial version 0.1.0
Package: jirar
Title: Modern R Client for the Jira REST API
Version: 0.1.0
Description: A modern, tidy interface to the Jira REST API for both Jira Cloud and Jira Server / Data Center. Authenticate once, query issues with the Jira Query Language (JQL), and retrieve projects, fields, dashboards and more as tibbles. Built on 'httr2' with automatic pagination, informative errors and support for API tokens and personal access tokens.
License: MIT + file LICENSE
URL: https://github.com/JanWein/jirar
BugReports: https://github.com/JanWein/jirar/issues
Encoding: UTF-8
Language: en-US
Suggests: dplyr, jsonlite, knitr, rmarkdown, spelling, testthat (>= 3.0.0), withr
Imports: cli, httr2 (>= 1.0.0), rlang, tibble, vctrs
Depends: R (>= 4.1)
NeedsCompilation: no
Packaged: 2026-06-17 08:37:04 UTC; 1003177
Author: Jan-Hendrik Weinert [aut, cre]
Maintainer: Jan-Hendrik Weinert <janhendrikweinert@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-22 15:00:17 UTC

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New package imuGAP with initial version 0.1.0
Package: imuGAP
Title: Immunity: Geographic and Age-Based Projection
Version: 0.1.0
Description: Fits Bayesian hierarchical models of vaccine coverage by location, birth cohort, and age. Observations of vaccination status (which may span cohorts, ages, and doses) are used to fit a latent survival-style process model that decomposes coverage into a lifetime propensity to vaccinate and a time-varying force of vaccination. Hierarchical spatial structure (e.g., state, county, school) supports partial pooling via random effects. Models are implemented in 'Stan' and fit via 'rstan'. Provides helpers to validate user-supplied input data, and to predict coverage from fitted models.
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-US
Biarch: true
Depends: R (>= 4.1.0)
Imports: data.table, methods, Rcpp (>= 0.12.0), RcppParallel (>= 5.0.1), rstan (>= 2.18.1), rstantools (>= 2.5.0)
LinkingTo: BH (>= 1.66.0), Rcpp (>= 0.12.0), RcppEigen (>= 0.3.3.3.0), RcppParallel (>= 5.0.1), rstan (>= 2.18.1), StanHeaders (>= 2.18.0)
SystemRequirements: GNU make
Suggests: knitr, rmarkdown, testthat (>= 3.0.0), roxygen2, roxyglobals, lintr, spelling, bayesplot, ggplot2
VignetteBuilder: knitr
URL: https://accidda.github.io/imuGAP/, https://github.com/ACCIDDA/imuGAP
BugReports: https://github.com/ACCIDDA/imuGAP/issues
LazyData: true
LazyDataCompression: xz
NeedsCompilation: yes
Packaged: 2026-06-16 20:36:29 UTC; runner
Author: Carl Pearson [aut, cre] , Claire Perrin Smith [aut] , Kelly Zhen [ctb], Weston Voglesonger [ctb], Joshua Chen [ctb], Minjae Kung [ctb]
Maintainer: Carl Pearson <carl.ab.pearson@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-22 14:40:26 UTC

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New package fbrglm with initial version 0.0.1
Package: fbrglm
Title: Safe Formula-Based Regularized Generalized Linear Models
Version: 0.0.1
Description: A formula-based wrapper around 'glmnet' that brings the 'glm()'-compatible modeling workflow to regularized generalized linear models. Training-time 'terms', 'xlevels', and 'contrasts' are stored on the fit object and reused at predict time, so the design matrix is reconstructed consistently across sessions. Complete-case bookkeeping is exposed via 'nobs_info', and linearly dependent columns are detected by a QR pivot and reported as 'NA' in 'coef()' and 'summary()' (the 'stats::glm()' convention), distinguishing "not identifiable" from "shrunk to zero by the penalty". Novel factor levels at predict time raise the same error 'stats::predict.glm()' does by default, with 'on_new_levels = "na"' as a production-style opt-in. Accepts character family strings ('gaussian', 'binomial', 'poisson', 'cox', 'multinomial', 'mgaussian') and any 'glm' family object the underlying 'glmnet' itself accepts, including 'Gamma' and fixed-theta negative binomial via 'MASS::negative.binomial'.
URL: https://github.com/dsc-chiba-u/fbrglm
BugReports: https://github.com/dsc-chiba-u/fbrglm/issues
License: MIT + file LICENSE
Encoding: UTF-8
Imports: glmnet, stats, graphics
Suggests: testthat (>= 3.0.0), knitr, rmarkdown, survival, MASS
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-06-17 12:12:59 UTC; koki
Author: Koki Tsuyuzaki [aut, cre]
Maintainer: Koki Tsuyuzaki <k.t.the-answer@hotmail.co.jp>
Repository: CRAN
Date/Publication: 2026-06-22 15:00:23 UTC

More information about fbrglm at CRAN
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New package AGBQR with initial version 0.1.0
Package: AGBQR
Title: Adaptive Generalized Bayesian Quantile Regression
Version: 0.1.0
Date: 2026-06-16
Description: Implements adaptive generalized Bayesian quantile regression with quantile-specific learning rates, HAC-based calibration, Gibbs posterior simulation, posterior summaries, predictive evaluation, and visualization tools. The package builds on the generalized Bayesian composite quantile regression framework of Hardy and Korobilis (2026) <doi:10.2139/ssrn.6618603> by allowing learning rates to vary across quantile levels. The implementation is designed for empirical work with small and moderate time-series samples where posterior calibration and tail-specific inference are important.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: quantreg, MASS, stats
Suggests: testthat
NeedsCompilation: no
Packaged: 2026-06-16 14:02:46 UTC; khder
Author: Khder Alakkari [aut, cre]
Maintainer: Khder Alakkari <khderalakkari1990@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-22 15:00:38 UTC

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Sun, 21 Jun 2026

New package pdfsigner with initial version 0.2.2
Package: pdfsigner
Title: Digitally Sign and Verify PDF Documents
Version: 0.2.2
Description: Digitally sign PDF documents with a 'PKCS#12' keystore and verify their signatures. Signing produces a detached 'PKCS#7' / 'CMS' signature ('adbe.pkcs7.detached') over the document and is applied as an incremental update, so existing signatures remain valid. The cryptography and PDF manipulation are performed by a bundled, pure-'Rust' backend (the 'pdf_signer' crate); no Java runtime, 'OpenSSL', or external command-line tools are required. Visible signature appearances with custom text are supported.
Depends: R (>= 4.2)
Suggests: testthat (>= 3.0.0)
License: GPL-3
Copyright: The pdfsigner package and its bundled 'pdf_signer' Rust backend are released under GPL-3. The build vendors the source of third-party Rust crates (src/rust/vendor.tar.xz) that remain under the copyright of their respective authors and are licensed under permissive terms (MIT, Apache-2.0, BSD, ISC, Zlib, Unicode-3.0, 0BSD, Unlicense or CDLA-Permissive-2.0); see the inst/AUTHORS file for the full list.
Encoding: UTF-8
URL: https://github.com/StrategicProjects/pdfsigner
BugReports: https://github.com/StrategicProjects/pdfsigner/issues
SystemRequirements: Cargo (Rust's package manager), rustc
NeedsCompilation: yes
Packaged: 2026-06-15 14:05:24 UTC; leite
Author: Andre Leite [aut, cre], Hugo Vasconcelos [aut], Diogo Bezerra [aut], Authors of the vendored Rust crates [ctb, cph]
Maintainer: Andre Leite <leite@castlab.org>
Repository: CRAN
Date/Publication: 2026-06-21 15:20:02 UTC

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New package nmathopencl with initial version 0.8.2
Package: nmathopencl
Title: 'OpenCL'-Ported R 'Mathlib' for GPU-Accelerated Packages
Version: 0.8.2
Date: 2026-06-11
Description: Ships statistical and mathematical routines from R internal 'nmath' ('Mathlib') as 'OpenCL' C sources under directory 'inst/cl/', with R wrappers that use the GPU when 'OpenCL' is available at compile time and fall back to 'stats' equivalents otherwise. Aimed at package developers building custom kernels (for example Bayesian GLMs via suggested package 'glmbayes') using 'opencltools' kernel loaders and related helpers. Contains translated shims, an illustrative GLM-related kernel subsystem, vignettes, and optional GPU acceleration. The ported routines are translated from the 'nmath' ('Mathlib') and 'Rmath' sources of R Core Team (2026) "R: A Language and Environment for Statistical Computing" <doi:10.32614/R.manuals>. 'OpenCL' GPU execution follows the standard described in Stone, Gohara, and Shi (2010) <doi:10.1109/MCSE.2010.69>. The likelihood subgradient simulation methodology implemented by the illustrative GLM kernel subsystem is described in Nygren and Nygren (2006) & [...truncated...]
License: GPL (>= 2)
URL: https://github.com/knygren/nmathopencl, https://knygren.r-universe.dev/nmathopencl
BugReports: https://github.com/knygren/nmathopencl/issues
Imports: stats, Rcpp (>= 1.1.1), RcppParallel, Rdpack (>= 0.11-0), opencltools (>= 0.8.1)
LinkingTo: Rcpp, RcppArmadillo, RcppParallel, opencltools
Depends: MASS, R (>= 3.5.0)
Suggests: glmbayes (>= 0.9.3), knitr, rmarkdown, testthat (>= 3.0.0), spelling
SystemRequirements: Optional 'OpenCL' support. If available, GPU acceleration will be used; otherwise, computation runs on CPU.
Encoding: UTF-8
VignetteBuilder: knitr
Language: en-US
NeedsCompilation: yes
Packaged: 2026-06-12 00:12:40 UTC; kjell
Author: Kjell Nygren [aut, cre], The R Core Team [ctb, cph] , The R Foundation [cph] , Ross Ihaka [ctb, cph] , Robert Gentleman [ctb, cph] , Morten Welinder [ctb, cph] ), Martin Maechler [ctb] , Catherine Loader [ctb] , Claus Ekstroem [ctb] in R 'Mathlib' po [...truncated...]
Maintainer: Kjell Nygren <kjell.a.nygren@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-21 15:20:08 UTC

More information about nmathopencl at CRAN
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Sat, 20 Jun 2026

New package reproducr with initial version 0.2.0
Package: reproducr
Title: Behavioural Reproducibility Auditing for R Projects
Version: 0.2.0
Description: Audits R scripts for behavioural reproducibility risk. Scans scripts for qualified package::function calls and checks them against a curated database of known silent breaking changes across popular CRAN packages. Flags stochastic calls lacking set.seed() and detects locale-sensitive operations that may produce different results across systems. Supports baseline certification of analytical outputs so that silent numerical drift can be detected across package upgrades or platform changes. Generates human-readable audit reports suitable for academic submission or pharmaceutical QC workflows. For more details see <https://github.com/repro-stats/reproducr>.
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-GB
Depends: R (>= 4.0.0)
Imports: utils
Suggests: digest (>= 0.6.0), jsonlite, commonmark, testthat (>= 3.0.0), knitr, rmarkdown, covr
VignetteBuilder: knitr
URL: https://github.com/repro-stats/reproducr
BugReports: https://github.com/repro-stats/reproducr/issues
NeedsCompilation: no
Packaged: 2026-06-15 15:03:22 UTC; ndohpenn
Author: Ndoh Penn [aut, cre]
Maintainer: Ndoh Penn <ndohpenn9@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-20 14:10:02 UTC

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New package neuralnetwork with initial version 0.1.0
Package: neuralnetwork
Title: Fast Compact Multilayer Perceptrons
Version: 0.1.0
Description: A small multilayer perceptron implementation for 'R'. It supports regression and classification, multiple hidden layers, mini-batch training, Adam, SGD, momentum, Nesterov, RPROP, GRPROP and L-BFGS optimizers, dropout, L2 regularization, early stopping, convergence thresholds, gradient clipping, sample and class weights, callback hooks, target scaling and robust Huber loss for regression, 'Rcpp' forward-pass kernels, formula interfaces, model evaluation with balanced classification metrics, cross-validation, compact tuning, permutation importance, model persistence helpers, and 'S3' prediction methods. Methods follow Rumelhart, Hinton and Williams (1986) <doi:10.1038/323533a0>, with optimizers including Riedmiller and Braun (1993) <doi:10.1109/ICNN.1993.298623>, Nocedal (1980) <doi:10.1090/S0025-5718-1980-0572855-7>, and Kingma and Ba (2014) <doi:10.48550/arXiv.1412.6980>.
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-US
Depends: R (>= 4.1.0)
Imports: Rcpp
LinkingTo: Rcpp
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2026-06-15 13:25:04 UTC; jifeng3
Author: Feng Ji [aut, cre]
Maintainer: Feng Ji <f.ji@utoronto.ca>
Repository: CRAN
Date/Publication: 2026-06-20 14:10:08 UTC

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New package ggkodom with initial version 1.0.3
Package: ggkodom
Title: Visualize Individual Longitudinal Trajectories
Version: 1.0.3
Description: A 'ggplot2'-based toolkit for visualizing individual-level longitudinal trajectories. Creates linear kodom plots, circular kodom plots, heatmaps, and state-ribbon charts for repeated-measures data. Each subject gets its own visual lane with measurements colored by value, revealing patterns across subjects and time. The circular variant resembles the Kodom flower.
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-US
Imports: ggplot2 (>= 3.4.0), rlang, scales
Suggests: testthat (>= 3.0.0), lme4, mgcv, refund, fdapace, patchwork, knitr, rmarkdown, spelling
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-06-15 21:05:23 UTC; subroy13
Author: Ayoushman Bhattacharya [aut], Sayan Das [aut], Subrata Pal [aut], Subhrajyoty Roy [aut, cre]
Maintainer: Subhrajyoty Roy <subhrajyotyroy@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-20 14:30:02 UTC

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New package fda.vi with initial version 1.0.0
Package: fda.vi
Title: Functional Data Analysis using Variational Inference
Version: 1.0.0
Maintainer: Camila de Souza <camila.souza@uwo.ca>
Description: Implements a variational Expectation-Maximization (VEM) algorithm for smoothing one or multiple functional observations via basis function selection. The algorithm estimates all model parameters simultaneously and automatically, while accounting for within-curve correlation. The approach provides a flexible and computationally efficient framework for smoothing correlated functional data. The algorithm is described in da Cruz, A. C., de Souza, C. P., and Sousa, P. H. (2024). 'Fast Bayesian basis selection for functional data representation with correlated errors.' <doi:10.48550/arXiv.2405.20758>.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1)
Imports: stats, graphics, fda, MASS, scales
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
LazyData: true
VignetteBuilder: knitr
URL: https://github.com/desouzalab/fda.vi
BugReports: https://github.com/desouzalab/fda.vi/issues
NeedsCompilation: no
Packaged: 2026-05-26 15:06:52 UTC; carol
Author: Camila de Souza [cre], Stephen Kinsey [aut], Ana Carolina da Cruz [aut], Pedro Henrique Toledo Oliveira Sousa [aut]
Repository: CRAN
Date/Publication: 2026-06-20 14:10:14 UTC

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New package survSampleSize with initial version 0.1.1
Package: survSampleSize
Title: Sample Size Calculator for Survival Endpoint Clinical Trials
Version: 0.1.1
Description: An interactive 'shiny' application for sample size and power calculation under general conditions for clinical trials with survival endpoints. Implements the weighted log-rank method of Lu (2021) <doi:10.1002/pst.2069> via the 'lrstat' package, supporting non-proportional hazards, delayed treatment effects, unequal allocation and dropout, as well as the classic method of Freedman (1982) <doi:10.1002/sim.4780010204> via the 'powerSurvEpi' package. Results are presented interactively with survival curves and event-prediction timelines.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: lrstat, powerSurvEpi, shiny, stats
Suggests: bslib, DT, ggplot2, knitr, plotly, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-06-15 13:44:10 UTC; lenovo
Author: Huai Jiang [aut, cre]
Maintainer: Huai Jiang <13661928191@163.com>
Repository: CRAN
Date/Publication: 2026-06-20 14:00:02 UTC

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New package spacc with initial version 0.8.3
Package: spacc
Title: Fast Spatial Species Accumulation Curves
Version: 0.8.3
Description: High-performance spatial species accumulation curves using nearest-neighbor algorithms. Implements 'kNN' and 'kNCN' sampling methods with a 'C++' backend for speed. Supports Hill numbers (q=0,1,2), beta diversity partitioning (turnover/nestedness), coverage-based rarefaction and extrapolation, phylogenetic diversity (Faith's PD, mean pairwise distance, mean nearest taxon distance), functional diversity accumulation, diversity-area relationships (DAR), endemism-area curves, sampling-effort correction and fragmentation analysis, and species-area relationship (SAR) models based on extreme value theory (EVT). Multiple starting points (seeds) provide uncertainty quantification. Methods are described in 'Chao' et al. (2014) <doi:10.1890/13-0133.1>, 'Baselga' (2010) <doi:10.1111/j.1466-8238.2009.00490.x>, 'Chao' and 'Jost' (2012) <doi:10.1890/11-1952.1>, 'Faith' (1992) <doi:10.1016/0006-3207(92)91201-3>, 'Ma' (2018) <doi:10.1002/ece3.4526>, 'Borda-de-Agua' et al. [...truncated...]
License: MIT + file LICENSE
Language: en-US
Encoding: UTF-8
Depends: R (>= 3.5)
LinkingTo: Rcpp, RcppParallel
Imports: Rcpp, RcppParallel, stats, parallel
Suggests: testthat (>= 3.0.0), knitr, rmarkdown, svglite, ggplot2, cli, sf, areaOfEffect, ape, iNEXT, betapart, cluster
VignetteBuilder: knitr
SystemRequirements: GNU make
URL: https://gillescolling.com/spacc/, https://github.com/gcol33/spacc
BugReports: https://github.com/gcol33/spacc/issues
NeedsCompilation: yes
Packaged: 2026-06-14 13:19:29 UTC; Gilles Colling
Author: Gilles Colling [aut, cre, cph]
Maintainer: Gilles Colling <gilles.colling051@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-20 13:40:02 UTC

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New package scopusflow with initial version 0.1.0
Package: scopusflow
Title: A Reproducible Workflow Layer for 'Scopus' Bibliographic Searches
Version: 0.1.0
Description: A coherent, quota-aware workflow layer over the Elsevier 'Scopus' Search 'API' <https://dev.elsevier.com/sc_apis.html>. It builds reproducible search plans, retrieves records with rate-limit handling, retry with back-off and optional resumable caching, normalises results to a stable tidy schema, extracts and tracks changes in Digital Object Identifiers (DOIs), compares publication trends across topics and exports to formats compatible with downstream bibliometric tools. Network and 'API' errors are surfaced as typed conditions so that callers can respond to them programmatically. 'Scopus' is a trademark of Elsevier. This package is an independent client and is not affiliated with or endorsed by Elsevier.
License: MIT + file LICENSE
URL: https://github.com/pablobernabeu/scopusflow, https://pablobernabeu.github.io/scopusflow/
BugReports: https://github.com/pablobernabeu/scopusflow/issues
Depends: R (>= 4.1.0)
Imports: cli, httr2 (>= 1.0.0), jsonlite, rlang (>= 1.0.0), stats, tibble, tools, utils
Suggests: ggplot2, knitr, rmarkdown, spelling, testthat (>= 3.0.0), withr
VignetteBuilder: knitr
Encoding: UTF-8
LazyData: true
Language: en-GB
NeedsCompilation: no
Packaged: 2026-06-14 22:23:30 UTC; PabloB
Author: Pablo Bernabeu [aut, cre, cph]
Maintainer: Pablo Bernabeu <pcbernabeu@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-20 13:50:02 UTC

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New package muiDataGrid with initial version 0.1.2
Package: muiDataGrid
Title: 'MUI X Data Grid' for 'shiny' Apps and 'Quarto'
Version: 0.1.2
Maintainer: Felix Luginbuhl <felix.luginbuhl@protonmail.ch>
Description: Provides access to 'MUI X Data Grid', a fast and extensible React data table and React data grid, with filtering, sorting, pagination, and more. Bundles the MIT-licensed community edition of the '@mui/x-data-grid' JavaScript library (the commercial 'Pro' and 'Premium' tiers are not included).
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-US
Depends: R (>= 3.4)
Imports: htmltools, shiny, shiny.react (>= 0.4.0), muiMaterial (>= 0.2.0), utils
Suggests: knitr, rmarkdown, dplyr, testthat (>= 3.0.0)
URL: https://felixluginbuhl.com/muiDataGrid/
BugReports: https://github.com/lgnbhl/muiDataGrid/issues
NeedsCompilation: no
Packaged: 2026-06-14 10:48:41 UTC; felix
Author: Felix Luginbuhl [aut, cre, cph] , MUI [cph] , Meta Platforms, Inc. and affiliates [cph]
Repository: CRAN
Date/Publication: 2026-06-20 13:30:02 UTC

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New package gleifr with initial version 0.1.0
Package: gleifr
Title: Client for the 'GLEIF' API
Version: 0.1.0
Description: Download legal entity reference data from the 'Global Legal Entity Identifier Foundation' ('GLEIF') API. Retrieve Legal Entity Identifier ('LEI') records, their direct and ultimate parent and child relationships, accredited issuers ('Local Operating Units'), and mappings from 'LEI' codes to other identifiers such as 'ISIN', 'BIC', and 'MIC'. See <https://www.gleif.org/en/lei-data/gleif-api> for further details.
License: MIT + file LICENSE
URL: https://m-muecke.github.io/gleifr/, https://github.com/m-muecke/gleifr
BugReports: https://github.com/m-muecke/gleifr/issues
Depends: R (>= 4.1.0)
Imports: curl, httr2, rvest, stats, utils
Suggests: testthat (>= 3.0.0)
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-06-15 13:51:00 UTC; mmuecke
Author: Maximilian Muecke [aut, cre]
Maintainer: Maximilian Muecke <muecke.maximilian@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-20 14:00:07 UTC

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New package coxstream with initial version 0.1.0
Package: coxstream
Title: Memory-Efficient Cox Proportional Hazards via Streaming Newton-Raphson
Version: 0.1.0
Description: Fits the Cox proportional hazards model using a single descending-order pass per Newton-Raphson iteration. Peak RAM is O(p^2) regardless of the number of rows, making it suitable for datasets that do not fit in memory. Produces identical coefficients to survival::coxph() with Efron tie correction.
URL: https://github.com/tommycarstensen/coxstream-r
BugReports: https://github.com/tommycarstensen/coxstream-r/issues
License: MIT + file LICENSE
Encoding: UTF-8
Imports: Rcpp, survival
LinkingTo: Rcpp
Suggests: arrow, testthat (>= 3.0.0)
NeedsCompilation: yes
Packaged: 2026-06-14 21:24:20 UTC; tommy
Author: Tommy Carstensen [aut, cre] , Apache Software Foundation [cph, ctb] , Apache-2.0)
Maintainer: Tommy Carstensen <cran@tommycarstensen.com>
Repository: CRAN
Date/Publication: 2026-06-20 13:40:11 UTC

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New package CamelRatiosIndex with initial version 1.0.0
Package: CamelRatiosIndex
Title: Multivariate-Weighted Indexing of CAMEL Ratios for Bank Performance
Version: 1.0.0
Description: Computes a composite year-on-year index for bank performance assessment using the CAMEL framework (Capital Adequacy, Asset Quality, Management Efficiency, Earnings, Liquidity). The multivariate weighting scheme employs factor analysis with robust covariance estimation to derive communality-based weights from the correlation matrix of CAMEL ratios. Provides functions for index computation, visualization, and comparison across banks and time periods.The methodology is described in Ayimah et al. (2023a) <doi:10.9734/bpi/mono/978-81-19315-32-1> and Ayimah et al. (2023b) <https://ajtem.com/index.php/ajtem/article/view/53>.
License: MIT + file LICENSE
URL: https://github.com/JC-Ayimah/CamelRatiosIndex, https://JC-Ayimah.github.io/CamelRatiosIndex/
BugReports: https://github.com/JC-Ayimah/CamelRatiosIndex/issues
Depends: R (>= 3.5)
Imports: cli (>= 3.6.0), dplyr (>= 1.1.0), ggplot2 (>= 3.4.0), robustfa, rrcov, stats, tibble (>= 3.2.0), utils
Suggests: knitr, rmarkdown, testthat (>= 3.0.0), vdiffr
VignetteBuilder: knitr
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2026-06-15 08:25:35 UTC; JC-AYIMAH
Author: John Coker Ayimah [aut, cph, cre], George Kyei Agyen [aut, cph], Raymond Achiyaale [aut, cph]
Maintainer: John Coker Ayimah <jayimah@htu.edu.gh>
Repository: CRAN
Date/Publication: 2026-06-20 13:50:08 UTC

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