Fri, 10 Jul 2026

Package vasicekfit updated to version 0.2.0 with previous version 0.1.0 dated 2026-04-28

Title: Extended Vasicek Credit Loss Model with Macroeconomic Factors
Description: Fits the extended Vasicek single-factor credit loss model where the probability of default depends on macroeconomic covariates. Maximum likelihood estimates of all parameters, including asset value correlation, are obtained via closed-form probit-transformed OLS regression; see Mayorov (2026) <doi:10.2139/ssrn.6506378> for derivation.
Author: Dmitriy Mayorov [aut, cre]
Maintainer: Dmitriy Mayorov <cran@dimview.org>

Diff between vasicekfit versions 0.1.0 dated 2026-04-28 and 0.2.0 dated 2026-07-10

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New package truchet with initial version 0.0.1.1
Package: truchet
Title: Tiles and Random Mosaics Truchet Style Using the 'sf' Framework
Version: 0.0.1.1
Description: Functions to create Truchet tiles, so called after Sébastien Truchet who was the first to describe the patterns obtained by rotating tiles with respect to each other. This form of tiling is described by Smith and Boucher (1987) <https://muse.jhu.edu/article/600574>.
License: MIT + file LICENSE
Encoding: UTF-8
URL: https://paezha.github.io/truchet/, https://github.com/paezha/truchet
BugReports: https://github.com/paezha/truchet/issues
Imports: bezier, checkmate, dplyr, lwgeom, magrittr, methods, purrr, rlang, sf, tidyr
Suggests: rmarkdown, gganimate, ggplot2, knitr, imager
NeedsCompilation: no
Packaged: 2026-07-03 16:26:07 UTC; antonio-paez
Author: Antonio Paez [aut, cre]
Maintainer: Antonio Paez <paezha@mcmaster.ca>
Repository: CRAN
Date/Publication: 2026-07-10 20:30:02 UTC

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New package svySE with initial version 0.1.0
Package: svySE
Title: Sampling Error Estimation for Complex Surveys
Version: 0.1.0
Description: Tools for estimating sampling errors of indicators from complex survey designs. The package supports weighted totals, proportions, standard errors, confidence intervals, coefficients of variation, design effects, unweighted counts, grouped estimates, domain estimates, configurable survey settings, and customizable Excel exports.
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-US
Depends: R (>= 4.2.0)
Imports: survey, openxlsx, stats
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
URL: https://github.com/lburgoss/svySE
BugReports: https://github.com/lburgoss/svySE/issues
NeedsCompilation: no
Packaged: 2026-07-03 19:32:32 UTC; encal154
Author: Luis Burgos [aut, cre]
Maintainer: Luis Burgos <lburgoss1996@gmail.com>
Repository: CRAN
Date/Publication: 2026-07-10 20:50:02 UTC

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New package stepwedgepower with initial version 0.1.0
Package: stepwedgepower
Title: Tools for Stepped-Wedge Clinical Trial Analysis and Power Simulation
Version: 0.1.0
Maintainer: Lin (Amanda) Li <amandali14124277@gmail.com>
Description: Refactors an academic stepped-wedge clinical trial analysis script into reusable functions for physician-level data preparation, specialty-level rate modeling, and simulation-based power calculations with a random provider effects. The package was designed to support Eli Lilly Lp(a) grant support and more general stepped-wedge planning workflows.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: lme4
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
NeedsCompilation: no
Packaged: 2026-07-03 21:33:04 UTC; amandalinli
Author: Lin Li [aut, cre], Florin Vaida [aut]
Repository: CRAN
Date/Publication: 2026-07-10 20:50:08 UTC

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Package spca readmission to version 1.1.1 with previous version 0.6.0 dated 2014-12-16

Title: Least Squares Sparse Principal Components Analysis
Description: Implements least-squares sparse principal component analysis (LS-SPCA). The approach follows Merola (2015) <doi:10.1111/anzs.12128> and Merola and Chen (2019) <doi:10.1016/j.jmva.2019.04.001>.
Author: Giovanni Maria Merola [aut, cre]
Maintainer: Giovanni Maria Merola <merolagio@gmail.com>

This is a re-admission after prior archival of version 0.6.0 dated 2014-12-16

Diff between spca versions 0.6.0 dated 2014-12-16 and 1.1.1 dated 2026-07-10

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New package sealeveltools with initial version 0.3.0
Package: sealeveltools
Title: Sea Level Adjustment and Coastal Terrain Modeling
Version: 0.3.0
Date: 2026-07-03
Imports: grDevices, terra
Maintainer: Jovan Kovacevic <jkovacevic@grf.bg.ac.rs>
Description: Simulates sea-level rise and fall from raster-based elevation models through functions for relative vertical datum transformation of Digital Terrain Models (DTMs) and integration with bathymetric data to produce continuous terrestrial–marine Digital Elevation Models (DEMs). Supports coastal exposure modeling, paleogeographic reconstruction, submerged landscape analysis, and climate change impact assessment. Optional gap-filling and threshold-based terrain filtering facilitate reconstruction of incomplete elevation surfaces and scenario-based landscape simulation. Applications span coastal engineering, geomorphology, archaeology, environmental modeling, and geospatial analysis.
License: GPL (>= 3)
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-07-03 20:28:40 UTC; Administrator
Author: Jovan Kovacevic [aut, cre] , Christopher Nuttall [aut]
Repository: CRAN
Date/Publication: 2026-07-10 20:50:12 UTC

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New package safuzzy with initial version 0.1.1
Package: safuzzy
Title: Stability Analysis with Fuzzy Logic
Version: 0.1.1
Description: It integrates 'fuzzy logic' into the analysis of genotype adaptability and stability. By classifying genotypes based on degrees of belonging, the package provides a detailed assessment of their behavior in different environmental groups.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Date: 2026-07-02
Imports: dplyr, purrr, tidyr
Depends: R (>= 3.5)
NeedsCompilation: no
Packaged: 2026-07-03 16:52:05 UTC; dougl
Author: Maciel Douglas, O. [aut, cre]
Maintainer: "Maciel Douglas, O." <douglasmaciel@discente.ufg.br>
Repository: CRAN
Date/Publication: 2026-07-10 20:30:08 UTC

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New package retraction with initial version 0.1.0
Package: retraction
Title: Detect Retracted References in Documents and Bibliographies
Version: 0.1.0
Description: Scans manuscripts, bibliographies, and reference lists for citations to retracted publications so that authors can avoid citing retracted work. 'retraction' reads bibliographic formats (BibTeX, BibLaTeX, CSL-JSON, RIS, EndNote XML) and document formats (R Markdown, Quarto, 'LaTeX', Markdown, HTML, JATS XML, Word, and PDF), extracts and normalizes identifiers, and checks them against retraction data. The default data source is the Retraction Watch database served through the 'XeraRetractionTracker' API; 'Crossref', 'OpenAlex', 'Europe PMC', 'PubMed', 'DataCite', and a preprint source ('arXiv' and 'bioRxiv' withdrawals) are available as additional sources ('OpenAlex' retraction data is itself derived from Retraction Watch). Within each source, matching proceeds from exact Digital Object Identifier (DOI) and 'PubMed' identifier lookups to fuzzy title matching, and results are returned as a tidy table with a match-quality score and an optional self-contained HTML report.
License: GPL-3
URL: https://github.com/choxos/retraction, https://choxos.github.io/retraction/
BugReports: https://github.com/choxos/retraction/issues
Depends: R (>= 4.0)
Imports: cli (>= 3.0.0), httr2, jsonlite, stringdist, tibble, tools, utils, xml2
Suggests: arrow, covr, DBI, DT, furrr, future, httptest2, knitr, pdftools, rmarkdown, RSQLite, rstudioapi, shiny, stringi (>= 1.5.3), testthat (>= 3.0.0), withr, writexl
VignetteBuilder: knitr
Encoding: UTF-8
Language: en-US
LazyData: true
NeedsCompilation: no
Packaged: 2026-07-03 13:24:43 UTC; choxos
Author: Ahmad Sofi-Mahmudi [aut, cre]
Maintainer: Ahmad Sofi-Mahmudi <a.sofimahmudi@gmail.com>
Repository: CRAN
Date/Publication: 2026-07-10 20:20:08 UTC

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New package pycnogrid with initial version 0.2.0
Package: pycnogrid
Title: Flexible Pycnophylactic Interpolation to Discrete Global and Local Grid Systems
Version: 0.2.0
Description: Provides tools for pycnophylactic interpolation of polygon totals to discrete global and local grid systems. The method follows Tobler (1979) <doi:10.1080/01621459.1979.10481647>, preserving source-zone totals while smoothing values across neighboring target cells.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1)
Imports: a5R, dplyr, h3o, hexify, Matrix, rlang, s2, sf, sfdep, terra, tibble
Suggests: forcats, gt, knitr, purrr, quarto, testthat (>= 3.0.0), tidyr, tmap
VignetteBuilder: quarto
LazyData: true
URL: https://higgicd.github.io/pycnogrid/, https://github.com/higgicd/pycnogrid
BugReports: https://github.com/higgicd/pycnogrid/issues
NeedsCompilation: no
Packaged: 2026-07-03 15:46:12 UTC; chris
Author: Christopher Higgins [aut, cre, cph]
Maintainer: Christopher Higgins <cd.higgins@utoronto.ca>
Repository: CRAN
Date/Publication: 2026-07-10 20:30:13 UTC

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New package OORRT with initial version 0.1.0
Package: OORRT
Title: Estimator for Optimised Optional Randomised Response Technique
Version: 0.1.0
Description: Provides functions for estimation under the Randomised Response Technique for sensitive survey data, including Warner's estimator, Optional Randomised Response Technique estimator proposed by Chaudhuri and Mukerjee,and the Optimized Optional Randomised Response Technique estimator proposed by Pushadapu et al. The package also includes Monte Carlo simulation tools for evaluating estimator performance. The implemented methods are based on Warner (1965) <doi:10.1080/01621459.1965.10480775>, Chaudhuri and Mukerjee (1985),and Pushadapu et al. (2025) <doi: 10.1111/insr.12581>.
License: GPL-3
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-07-03 08:01:06 UTC; hp
Author: Safeela Nasrin [aut, cre], Kaustav Aditya [aut], Ritwika Das [aut]
Maintainer: Safeela Nasrin <nasrinkareem315@gmail.com>
Repository: CRAN
Date/Publication: 2026-07-10 20:10:22 UTC

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New package jpmapdata with initial version 0.1.0
Package: jpmapdata
Title: Boundary Data for Japan Maps
Version: 0.1.0
URL: https://github.com/yhoriuchi/jpmapdata
BugReports: https://github.com/yhoriuchi/jpmapdata/issues
Description: Provides boundary 'GeoPackage' files used by the 'jpmap' package, including Japan prefecture example boundaries and official MLIT N03 administrative area data converted for 'jpmap'. Keeping these data in a separate package lets 'jpmap' update its functionality without repeatedly redistributing large boundary files on CRAN mirrors.
License: CC BY 4.0
Copyright: See inst/COPYRIGHTS.
Encoding: UTF-8
Depends: R (>= 4.1.0)
Suggests: sf
NeedsCompilation: no
Packaged: 2026-07-03 13:48:32 UTC; yh25m
Author: Yusaku Horiuchi [aut, cre]
Maintainer: Yusaku Horiuchi <yusaku.horiuchi@gmail.com>
Repository: CRAN
Date/Publication: 2026-07-10 20:30:20 UTC

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New package isoreader2 with initial version 0.6.1
Package: isoreader2
Title: Read Stable Isotope Data Files
Version: 0.6.1
Description: Interface to the raw data and metadata stored in the file formats commonly encountered in scientific disciplines that make use of stable isotopes. Supports Isodat (.dxf, .cf, .did, .caf, .scn), IonOS (.iarc), LyticOS (.larc), Callisto (.bch), and Qtegra (.imexp) file formats. Provides a consistent data structure together with tools to aggregate, convert signal units, filter, and visualize the extracted data. The approach is described in Kopf et al. (2021) <doi:10.21105/joss.02878>.
License: AGPL (>= 3)
Encoding: UTF-8
URL: https://isoreader2.isoverse.org/, https://github.com/isoverse/isoreader2
BugReports: https://github.com/isoverse/isoreader2/issues
Depends: R (>= 4.5.0)
Imports: ggplot2, tools, utils, methods, stats, rlang (>= 1.1.0), cli (>= 3.6.0), processx, readr, tibble, dplyr, tidyr, purrr, withr, RcppSimdJson, scales, fansi, knitr
Suggests: testthat (>= 3.0.0), vdiffr, arrow, openxlsx, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-07-03 17:58:55 UTC; seko0922
Author: Sebastian Kopf [aut, cre]
Maintainer: Sebastian Kopf <sebastian.kopf@colorado.edu>
Repository: CRAN
Date/Publication: 2026-07-10 20:40:02 UTC

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New package inferencer with initial version 0.1.4.5
Package: inferencer
Title: Simple Unified Wrappers for Hosted Foundation Model Inference APIs
Version: 0.1.4.5
Author: Oliver Zhou [aut, cre]
Maintainer: Oliver Zhou <oliver.yxzhou@gmail.com>
Description: Provides lightweight R wrappers for querying and listing models from several hosted foundation model inference platforms, currently including Google Gemini, Groq, OpenRouter, Cerebras, and Ollama Cloud. The package is designed for simple inference workflows and quick experimentation, with minimal abstraction and a consistent interface across providers. It includes helper functions for model discovery, text generation, embeddings, image generation, and multimodal inputs, while leaving room for future support of provider-specific parameters and advanced options.
License: MIT + file LICENSE
URL: https://github.com/OliverLDS/inferencer
BugReports: https://github.com/OliverLDS/inferencer/issues
Depends: R (>= 4.1.0)
Encoding: UTF-8
Imports: data.table, httr2, jsonlite
Suggests: knitr, rmarkdown, testthat
NeedsCompilation: no
Packaged: 2026-07-03 06:42:35 UTC; oliver
Repository: CRAN
Date/Publication: 2026-07-10 20:10:09 UTC

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New package ggpower with initial version 0.1.2
Package: ggpower
Title: Publication-Ready Power Analysis and Visualization
Version: 0.1.2
Author: Yaoxiang Li [aut, cre]
Maintainer: Yaoxiang Li <liyaoxiang@outlook.com>
Description: Provides statistical power analysis and sample size calculations for t-tests, ANOVA, regression, chi-square, proportion, correlation, nonparametric, biomarker, and clinical trial designs. Includes a scriptable API via power_compute(), publication-ready 'ggplot2' visualizations, and an optional 'Shiny' application.
URL: https://github.com/YaoxiangLi/ggpower, https://yaoxiangli.github.io/ggpower/
BugReports: https://github.com/YaoxiangLi/ggpower/issues
License: GPL (>= 3)
Imports: bs4Dash, config, ggplot2, golem, shiny
Encoding: UTF-8
Suggests: knitr, pkgdown, rmarkdown, spelling, testthat (>= 3.0.0)
VignetteBuilder: knitr
Language: en-US
NeedsCompilation: no
Packaged: 2026-07-03 19:58:15 UTC; Li
Repository: CRAN
Date/Publication: 2026-07-10 20:50:17 UTC

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New package doclingr with initial version 0.1.0
Package: doclingr
Title: Document Intelligence via 'Docling'
Version: 0.1.0
Description: An interface to 'Docling', a document-understanding library that converts 'PDF', 'DOCX', 'PPTX', 'HTML' and image documents into structured, AI-ready data. The package wraps the 'Docling' 'Python' package through 'reticulate' to extract layout-aware text, tables and metadata, export to 'Markdown' or 'JSON', and split documents into context-rich chunks suitable for retrieval-augmented generation (RAG) and embedding pipelines.
License: MIT + file LICENSE
Language: en-US
Encoding: UTF-8
URL: https://github.com/StrategicProjects/doclingr, https://strategicprojects.github.io/doclingr/
BugReports: https://github.com/StrategicProjects/doclingr/issues
SystemRequirements: Python (>= 3.9), docling (>= 2.20.0; tested with 2.107.0)
Imports: reticulate (>= 1.34.0), cli, rlang, stats, tibble
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-07-03 14:46:50 UTC; leite
Author: Andre Leite [aut, cre], Marcos Wasilew [aut], Hugo Vasconcelos [aut], Carlos Amorim [aut], Diogo Bezerra [aut]
Maintainer: Andre Leite <leite@castlab.org>
Repository: CRAN
Date/Publication: 2026-07-10 20:30:26 UTC

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New package derrick with initial version 0.1.1
Package: derrick
Title: Export 'gtsummary' Tables with 'reporter'
Version: 0.1.1
Date: 2026-06-26
Maintainer: Xiecheng Gu <guxc0405med@163.com>
Description: Convert 'gtsummary' tables and plain data frames into clinical-style Rich Text Format, plain text, Word, PDF, and HTML outputs using 'reporter', with managed widths, pagination, indentation, spanning headers, and optional intermediate data exports.
License: Apache License 2.0
URL: https://github.com/openpharma/derrick/
BugReports: https://github.com/openpharma/derrick/issues
Depends: R (>= 4.4)
Imports: dplyr, purrr, reporter (>= 1.4.7), rlang, stringi, tibble
Suggests: cards (>= 0.8.0), gtsummary (>= 2.5.1), knitr, rmarkdown, testthat (>= 3.3.0)
VignetteBuilder: knitr
Encoding: UTF-8
Language: en-US
NeedsCompilation: no
Packaged: 2026-07-03 11:03:37 UTC; Kathy Zhang
Author: Xiecheng Gu [aut, cre], Joe Zhu [aut], Bill Huang [aut]
Repository: CRAN
Date/Publication: 2026-07-10 20:30:31 UTC

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New package conflibertR with initial version 0.5.3
Package: conflibertR
Title: Inference and Fine-Tuning with 'ConfliBERT' Conflict Text Models
Version: 0.5.3
Description: An interface to 'ConfliBERT', a pretrained language model for analyzing text about conflict and political violence (Hu et al. (2022) <doi:10.18653/v1/2022.naacl-main.400>). Provides functions for named entity recognition, binary and multilabel classification, and question answering, plus tools to fine-tune custom classifiers, compare several base model architectures, and run an interactive active-learning loop for efficiently labeling new data. Models are downloaded from 'Hugging Face' and run through the 'transformers' library for 'Python' via the 'reticulate' package.
License: MIT + file LICENSE
URL: https://github.com/shreyasmeher/conflibertR
BugReports: https://github.com/shreyasmeher/conflibertR/issues
Encoding: UTF-8
Language: en
SystemRequirements: Python (>= 3.8); the Python modules 'torch', 'transformers' (>= 4.40), 'accelerate', 'peft', 'scikit-learn' and 'numpy', installable via conflibert_install()
Imports: cli, reticulate (>= 1.34), tibble
Suggests: ggplot2, knitr, miniUI, rmarkdown, rstudioapi, shiny, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-07-03 19:19:22 UTC; apple
Author: Shreyas Meher [aut, cre]
Maintainer: Shreyas Meher <shreyasmeher@gmail.com>
Repository: CRAN
Date/Publication: 2026-07-10 20:40:09 UTC

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New package CDSimX with initial version 1.1.2
Package: CDSimX
Title: Simulating Climate Data for Research and Modelling
Version: 1.1.2
Date: 2026-06-25
Maintainer: Isaac Osei <ikemillar65@gmail.com>
Description: Advanced climate simulation, forecasting, visualization, export, and machine learning tools. Generates synthetic climate datasets for single or multiple weather stations using stochastic weather generation techniques. 'CDSimX' simulates daily climate variables including minimum and maximum temperature, rainfall, relative humidity, solar radiation, wind speed, wind direction, dew point temperature, and potential evapotranspiration. The package incorporates seasonal harmonic models, Markov chain rainfall occurrence processes, Gamma-distributed rainfall amounts, copula-based dependence structures, bias-correction procedures, and physical consistency constraints. 'CDSimX' supports climate data generation, environmental modeling, machine learning benchmarking, sensitivity analysis, and educational applications. Methods are based on established stochastic weather generation approaches described in Richardson (1981) <doi:10.1029/WR017i001p00182>, Wilks (1999) <doi:10.1016/S0168-1923( [...truncated...]
License: MIT + file LICENSE
Encoding: UTF-8
Imports: copula, ggplot2, dplyr, tidyr, lubridate, randomForest, gbm, forecast, xgboost, nnet, ncdf4, rlang, readr, scales, stats
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
URL: https://ikemillar.github.io/CDSimX/
BugReports: https://github.com/ikemillar/CDSimX/issues
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-07-03 06:25:47 UTC; isaacosei
Author: Isaac Osei [aut, cre], Acheampong Baafi-Adomako [aut], Jayanti Maji [aut]
Repository: CRAN
Date/Publication: 2026-07-10 20:10:26 UTC

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New package BSCB with initial version 1.0.0
Package: BSCB
Title: Bayesian Simultaneous Credible Bands for Polynomial Regression
Version: 1.0.0
Description: Provides functions to construct two-sided Bayesian simultaneous credible bands (BSCBs) for the regression curve in univariate polynomial regression over a finite covariate interval. Six methods are implemented, including Normal-Gamma conjugate priors (with empirical Bayes, unit-information, and g-prior hyperparameter specifications), non-conjugate priors fitted via Hamiltonian Monte Carlo (HMC) using 'cmdstanr', and a non-informative independent Jeffreys prior approach. Also includes functions for computing the empirical simultaneous coverage rate (ESCR) and posterior simultaneous coverage probability (PSCP), enabling performance comparison across methods. The methodology is described in: Yang, F., Han, Y., Liu, W., & Hall, I. (2026). "Bayesian simultaneous credible bands for polynomial regression" <doi:10.48550/arXiv.2606.28015>.
License: MIT + file LICENSE
Encoding: UTF-8
Suggests: DEoptim, testthat (>= 3.0.0), cmdstanr, knitr, rmarkdown, ggplot2
VignetteBuilder: knitr
Additional_repositories: https://stan-dev.r-universe.dev
Imports: mvtnorm, MASS, OptimalDesign, instantiate, posterior
Depends: R (>= 4.0)
Date: 2026-07-02
URL: https://github.com/fannyyang73/BSCB
BugReports: https://github.com/fannyyang73/BSCB/issues
NeedsCompilation: yes
Packaged: 2026-07-02 16:51:49 UTC; fei
Author: Fei Yang [aut, cre]
Maintainer: Fei Yang <fei.yang@manchester.ac.uk>
Repository: CRAN
Date/Publication: 2026-07-10 20:10:32 UTC

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Package arcgislayers updated to version 0.6.1 with previous version 0.6.0 dated 2026-03-04

Title: Harness ArcGIS Data Services
Description: Enables users of 'ArcGIS Enterprise', 'ArcGIS Online', or 'ArcGIS Platform' to read, write, publish, or manage vector and raster data via ArcGIS location services REST API endpoints <https://developers.arcgis.com/rest/>.
Author: Josiah Parry [aut, cre] , Eli Pousson [ctb] , Kenneth Vernon [ctb] , Martha Bass [ctb] , Antony Barja [ctb]
Maintainer: Josiah Parry <josiah.parry@gmail.com>

Diff between arcgislayers versions 0.6.0 dated 2026-03-04 and 0.6.1 dated 2026-07-10

 DESCRIPTION                               |    8 ++++----
 MD5                                       |   10 ++++++----
 NEWS.md                                   |    8 ++++++--
 R/add_item.R                              |   27 +++++++++++++++++++++++++--
 R/arc-add-delete.R                        |    8 +++++---
 tests/testthat/_snaps/json-correctness.md |only
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 7 files changed, 46 insertions(+), 15 deletions(-)

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New package psAve with initial version 1.0.1
Package: psAve
Title: Model-Averaged Propensity Scores Selected by Prognostic-Score Balance
Version: 1.0.1
Description: Constructs a model-averaged propensity score as a convex combination of candidate propensity score models, with mixing weights selected on a simplex grid to optimize covariate or prognostic-score balance, implementing the method of Kabata, Stuart and Shintani (2024) <doi:10.1186/s12874-024-02350-y>. Prognostic scores follow Hansen (2008) <doi:10.1093/biomet/asn004>: outcome models are fit on untreated units only. The resulting score is designed to be supplied directly to the matchit() function of 'MatchIt' as a distance measure or to the weightit() function of 'WeightIt' as a propensity score, with balance assessment via 'cobalt'.
Depends: R (>= 4.1)
Imports: cobalt (>= 4.6.0), stats, utils, graphics
Suggests: MatchIt, WeightIt, SuperLearner, rpart, ranger, xgboost, survey, testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
License: GPL (>= 2)
URL: https://kabajiro.github.io/psAve/, https://github.com/kabajiro/psAve
BugReports: https://github.com/kabajiro/psAve/issues
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-07-02 21:56:07 UTC; kabajiro
Author: Daijiro Kabata [aut, cre, cph]
Maintainer: Daijiro Kabata <daijiro.kabata@port.kobe-u.ac.jp>
Repository: CRAN
Date/Publication: 2026-07-10 19:10:02 UTC

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Package neurohcp updated to version 0.12.0 with previous version 0.11.0 dated 2025-04-01

Title: Human 'Connectome' Project Interface
Description: Downloads and reads data from Human 'Connectome' Project <https://balsa.wustl.edu/> using Amazon Web Services ('AWS') 'S3' buckets.
Author: John Muschelli [aut, cre], Adi Gherman [ctb]
Maintainer: John Muschelli <muschellij2@gmail.com>

Diff between neurohcp versions 0.11.0 dated 2025-04-01 and 0.12.0 dated 2026-07-10

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 MD5                      |   52 +++++++++++++++++++-----------------
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 R/hcp_aws_url.R          |    4 ++
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 27 files changed, 213 insertions(+), 188 deletions(-)

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New package DSDRM with initial version 0.1.3
Package: DSDRM
Title: Distributed Sampling for Dynamic Regression Models
Version: 0.1.3
Depends: R (>= 4.1.0)
Description: A toolbox for distributed dynamic regression modeling, parallel estimation, multiple distributed sampling algorithms (Metropolis-Hastings, block bootstrap, adaptive, hypergeometric), sparse matrix optimization, model visualization, prediction and performance evaluation. The philosophy of the package is described in Guo (2025) <doi:10.1038/s41598-025-93333-6>.
License: Apache License 2.0
Encoding: UTF-8
Imports: parallel, Matrix
Author: Guangbao Guo [aut, cre]
Maintainer: Guangbao Guo <ggb11111111@163.com>
NeedsCompilation: no
Language: en-US
Suggests: testthat
Packaged: 2026-06-27 09:28:12 UTC; admin
Repository: CRAN
Date/Publication: 2026-07-10 19:30:02 UTC

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New package bqmm with initial version 0.1.0
Package: bqmm
Title: Bayesian Multilevel Quantile Regression
Version: 0.1.0
Description: Fits Bayesian mixed-effects (multilevel) quantile regression models using the asymmetric Laplace working likelihood and Stan. Supports an 'lme4'-style formula interface with nested and crossed random effects, fitting one or several quantiles, post-hoc non-crossing rearrangement of fitted quantiles, and the Yang, Wang and He (2016) posterior-variance correction for valid frequentist inference from the (misspecified) asymmetric Laplace posterior.
License: MIT + file LICENSE
Encoding: UTF-8
Biarch: true
Depends: R (>= 4.0.0)
Imports: methods, stats, graphics, grDevices, lme4, Matrix, Rcpp (>= 0.12.0), RcppParallel (>= 5.0.1), rstan (>= 2.26.0), rstantools (>= 2.4.0), posterior
LinkingTo: BH (>= 1.66.0), Rcpp (>= 0.12.0), RcppEigen (>= 0.3.3.3.0), RcppParallel (>= 5.0.1), rstan (>= 2.26.0), StanHeaders (>= 2.26.0)
Suggests: bayesplot, ggplot2, lqmm, MASS, nlme, quantreg, testthat (>= 3.0.0), knitr, rmarkdown
SystemRequirements: GNU make
VignetteBuilder: knitr
URL: https://github.com/kvenkita/bqmm, https://kvenkita.github.io/bqmm/
BugReports: https://github.com/kvenkita/bqmm/issues
NeedsCompilation: yes
Packaged: 2026-06-29 11:45:38 UTC; kyle
Author: Kailas Venkitasubramanian [aut, cre, cph]
Maintainer: Kailas Venkitasubramanian <kailasv@gmail.com>
Repository: CRAN
Date/Publication: 2026-07-10 20:00:02 UTC

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New package MBGapp with initial version 0.1.0
Package: MBGapp
Title: Interactive 'shiny' Application for Model-Based Geostatistics
Version: 0.1.0
Description: Provides an interactive 'shiny' application for teaching and applied analysis of geostatistical data. Users can explore spatial data, assess spatial correlation through the empirical variogram, fit model-based geostatistical models for continuous, prevalence and count outcomes, produce spatial predictions, and download reports. The methodology follows the model-based geostatistics framework of Diggle and Giorgi (2019, ISBN:9781138732353).
License: MIT + file LICENSE
URL: https://github.com/olatunjijohnson/MBGapp
BugReports: https://github.com/olatunjijohnson/MBGapp/issues
Encoding: UTF-8
Imports: geoR, ggplot2, shiny, sf, dplyr, readr, tidyr, magrittr, leaflet, leafem, tidyterra, stars, RiskMap, terra, grDevices, shinyjs, splines, httr2, rmarkdown
Suggests: INLA, covr, testthat (>= 3.0.0)
Additional_repositories: https://inla.r-inla-download.org/R/stable
NeedsCompilation: no
Packaged: 2026-07-02 20:59:52 UTC; olatunji-johnson
Author: Olatunji Johnson [cre, aut] , Claudio Fronterre [aut], Emanuele Giorgi [aut]
Maintainer: Olatunji Johnson <olatunjijohnson21111@gmail.com>
Repository: CRAN
Date/Publication: 2026-07-10 19:00:08 UTC

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New package IMR with initial version 1.0.0
Package: IMR
Title: Incomplete Matrix Regression
Version: 1.0.0
Description: A framework for matrix completion and regression on response matrices with missing values. The model estimates missing entries using any combination of intercepts, row and column covariates, and a low-rank matrix approximation. It applies Lasso penalties on the covariates and a nuclear norm penalty on the low-rank component. It also adjusts for correlation within the rows and columns of the target matrix using similarity matrices. The framework is described in Fouda, Labbe and Oualkacha (2026) <doi:10.48550/arXiv.2606.26325>.
License: GPL (>= 3)
URL: https://github.com/khaledfouda/IMR
BugReports: https://github.com/khaledfouda/IMR/issues
Depends: R (>= 3.5)
Imports: fields, irlba, MASS, Matrix, methods, parallel, Rcpp, RSpectra, stats, utils
Suggests: knitr, rmarkdown, spelling, testthat (>= 3.0.0)
LinkingTo: Rcpp, RcppArmadillo
VignetteBuilder: knitr
Encoding: UTF-8
Language: en-US
LazyData: true
SystemRequirements: C++17
NeedsCompilation: yes
Packaged: 2026-07-02 16:16:40 UTC; khaledfouda
Author: Khaled Fouda [aut, cre] , Aurelie Labbe [ths, ctb], Karim Oualkacha [ths, ctb], Korbinian Strimmer [cph, ctb]
Maintainer: Khaled Fouda <khaled.fouda@hec.ca>
Repository: CRAN
Date/Publication: 2026-07-10 18:20:02 UTC

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New package ctreeMI with initial version 0.1.0
Package: ctreeMI
Title: Conditional Inference Trees with Stacked Multiple Imputation
Version: 0.1.0
Description: Implements the stacked-imputation workflow for conditional inference trees ('ctree') described in Sherlock et al. (2026) <doi:10.1080/00273171.2026.2661244>. When data contain missing values, multiply imputed datasets (e.g., from 'mice') are stacked vertically and a single 'ctree' is fit on the combined data. To correct for the artificially inflated sample size introduced by stacking, the pruning significance threshold is divided by the number of imputations M (the Stack/M correction), producing a conservative but interpretable single tree that incorporates imputation uncertainty without requiring pooling of structurally different trees. Also exports stack_imputations() and rescale_alpha() as standalone utilities. The underlying 'ctree' algorithm is provided by 'partykit' (Hothorn & Zeileis, 2015; Hothorn, Hornik & Zeileis, 2006 <doi:10.1198/106186006X133933>).
License: GPL (>= 3)
Encoding: UTF-8
Imports: partykit (>= 1.2-0), mice (>= 3.0.0), methods
Suggests: testthat (>= 3.0.0)
Depends: R (>= 4.0.0)
URL: https://github.com/Phillip-Sherlock/ctreeMI
BugReports: https://github.com/Phillip-Sherlock/ctreeMI/issues
NeedsCompilation: no
Packaged: 2026-07-02 21:17:52 UTC; coe-phillip.sherlock
Author: Phillip Sherlock [aut, cre]
Maintainer: Phillip Sherlock <phillip.sherlock@ufl.edu>
Repository: CRAN
Date/Publication: 2026-07-10 19:00:02 UTC

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Package CohortGenerator updated to version 1.1.1 with previous version 1.1.0 dated 2026-03-03

Title: Cohort Generation for the OMOP Common Data Model
Description: Generate cohorts and subsets using an Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) Database. Cohorts are defined using 'CIRCE' (<https://github.com/ohdsi/circe-be>) or SQL compatible with 'SqlRender' (<https://github.com/OHDSI/SqlRender>).
Author: Anthony Sena [aut, cre], Jamie Gilbert [aut], Gowtham Rao [aut], Freddy Avila Cruz [aut], Martijn Schuemie [aut], Observational Health Data Science and Informatics [cph]
Maintainer: Anthony Sena <sena@ohdsi.org>

Diff between CohortGenerator versions 1.1.0 dated 2026-03-03 and 1.1.1 dated 2026-07-10

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 23 files changed, 859 insertions(+), 689 deletions(-)

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Package animl updated to version 3.3.1 with previous version 3.3.0 dated 2026-06-16

Title: A Collection of ML Tools for Species Detection and Classification in Camera Trap Images and Videos
Description: Functions required to classify subjects within camera trap field data. The package can handle both images and videos. The authors recommend a two-step approach using Microsoft's 'MegaDector' model and then a second model trained on the classes of interest.
Author: Kyra Swanson [aut, cre] , Mathias Tobler [aut]
Maintainer: Kyra Swanson <tswanson@sdzwa.org>

Diff between animl versions 3.3.0 dated 2026-06-16 and 3.3.1 dated 2026-07-10

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 NAMESPACE                                     |  112 ++--
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 tests/testthat/helper-animl.R                 |    6 
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 tests/testthat/test-file_management.R         |  406 +++++++-------
 tests/testthat/test-reid.R                    |  240 ++++----
 tests/testthat/test-sequence_classification.R |  160 ++---
 tests/testthat/test-split.R                   |  234 ++++----
 tests/testthat/test-visualization.R           |   80 +-
 83 files changed, 4884 insertions(+), 4855 deletions(-)

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Package nVennR2 updated to version 2.0.2 with previous version 2.0.1 dated 2026-06-01

Title: An Interface to 'nVenn2'
Description: Creates quasi-proportional Venn diagrams with an arbitrary number of sets. It is related to the old 'nVennR' package, but the algorithm and use have been reworked.
Author: Victor Quesada [aut, cre, cph]
Maintainer: Victor Quesada <quesadavictor@uniovi.es>

Diff between nVennR2 versions 2.0.1 dated 2026-06-01 and 2.0.2 dated 2026-07-10

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 12 files changed, 1819 insertions(+), 2038 deletions(-)

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Package LLMR updated to version 0.8.10 with previous version 0.8.6 dated 2026-06-17

Title: Interface for Large Language Model APIs in R
Description: Provides a unified interface to large language models across multiple providers. Supports text generation, tidy data workflows, structured output with optional JSON Schema validation, XML-like tag extraction, and embeddings. Includes chat sessions, consistent error handling, and parallel batch tools.
Author: Ali Sanaei [aut, cre]
Maintainer: Ali Sanaei <sanaei@uchicago.edu>

Diff between LLMR versions 0.8.6 dated 2026-06-17 and 0.8.10 dated 2026-07-10

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 R/LLMR_tidy.R                             |  134 +++++--
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 R/LLM_robust_utils.R                      |    4 
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More information about LLMR at CRAN
Permanent link

Package aridagri updated to version 2.0.4 with previous version 2.0.3 dated 2026-02-24

Title: Comprehensive Statistical Tools for Agricultural Research
Description: A comprehensive suite of statistical and analytical tools for agricultural research. Includes complete analysis of variance (ANOVA) functions for all experimental designs: Completely Randomized Design (CRD), Randomized Block Design (RBD), Pooled RBD, Split Plot with all variations, Split-Split Plot, Strip Plot, Latin Square, Factorial, Augmented, and Alpha Lattice, with proper error terms and comprehensive Standard Error (SE) and Critical Difference (CD) calculations. Features multiple post-hoc tests: Least Significant Difference (LSD), Duncan Multiple Range Test (DMRT), Tukey Honestly Significant Difference (HSD), Student-Newman-Keuls (SNK), Scheffe, Bonferroni, and Dunnett, along with assumption checking and publication-ready output. Advanced methods include stability analysis using Eberhart-Russell regression, Additive Main Effects and Multiplicative Interaction (AMMI), Finlay-Wilkinson regression, Shukla stability variance, Wricke ecovalence, Coefficient of Variation (CV), and Cult [...truncated...]
Author: Lalit Kumar Rolaniya [aut, cre] , Ram Lal Jat [aut] , Monika Punia [aut] , Raja Ram Choudhary [aut]
Maintainer: Lalit Kumar Rolaniya <lalitrolaniya@gmail.com>

Diff between aridagri versions 2.0.3 dated 2026-02-24 and 2.0.4 dated 2026-07-10

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Package rotations updated to version 1.6.7 with previous version 1.6.6 dated 2025-09-28

Title: Working with Rotation Data
Description: Tools for working with rotational data, including simulation from the most commonly used distributions on SO(3), methods for different Bayes, mean and median type estimators for the central orientation of a sample, confidence/credible regions for the central orientation based on those estimators and a novel visualization technique for rotation data. Most recently, functions to identify potentially discordant (outlying) values have been added. References: Bingham, Melissa A. and Nordman, Dan J. and Vardeman, Steve B. (2009), Bingham, Melissa A and Vardeman, Stephen B and Nordman, Daniel J (2009), Bingham, Melissa A and Nordman, Daniel J and Vardeman, Stephen B (2010), Leon, C.A. and Masse, J.C. and Rivest, L.P. (2006), Hartley, R and Aftab, K and Trumpf, J. (2011), Stanfill, Bryan and Genschel, Ulrike and Hofmann, Heike (2013), Maonton, Jonathan (2004), Mardia, KV and Jupp, PE (2000, ISBN:9780471953333), Rancourt, D. and Rivest, L.P. and Asselin, J. (2000), Chang, Ted and Rivest, Loui [...truncated...]
Author: Bryan Stanfill [aut, cre], Heike Hofmann [aut], Ulrike Genschel [aut], Aymeric Stamm [ctb] , Luciano Selzer [ctb]
Maintainer: Bryan Stanfill <bstanfill2003@gmail.com>

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Package nlmixr2data updated to version 2.0.10 with previous version 2.0.9 dated 2024-01-31

Title: Nonlinear Mixed Effects Models in Population PK/PD, Data
Description: Datasets for 'nlmixr2' and 'rxode2'. 'nlmixr2' is used for fitting and comparing nonlinear mixed-effects models in differential equations with flexible dosing information commonly seen in pharmacokinetics and pharmacodynamics (Almquist, Leander, and Jirstrand 2015 <doi:10.1007/s10928-015-9409-1>). Differential equation solving is by compiled C code provided in the 'rxode2' package (Wang, Hallow, and James 2015 <doi:10.1002/psp4.12052>).
Author: Matthew Fidler [aut, cre] , Rik Schoemaker [ctb] , Kyle Baron [ctb], Thierry Wendling [ctb], Ted Grasella [ctb], C Weil [ctb], Yaning Wang [ctb], R O'Reilly [ctb], David D'Argenio [ctb], Rodriguez-Vera [ctb], D Gaver [ctb], Yuan Xiong [ctb], Jan Rohl [...truncated...]
Maintainer: Matthew Fidler <matthew.fidler@gmail.com>

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Package mlr3cluster updated to version 0.4.1 with previous version 0.4.0 dated 2026-06-11

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

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Package cograph updated to version 2.4.4 with previous version 2.3.6 dated 2026-05-31

Title: Analysis and Visualization of Complex Networks
Description: Provides tools for the analysis, visualization, and manipulation of dynamical, social (Saqr et al. (2024) <doi:10.1007/978-3-031-54464-4_10>) and complex networks (Saqr et al. (2025) <doi:10.1145/3706468.3706513>). The package supports multiple network formats and offers flexible tools for heterogeneous, multi-layer, and hierarchical network analysis with simple syntax and extensive toolset.
Author: Mohammed Saqr [aut, cph], Sonsoles Lopez-Pernas [aut, cre, cph]
Maintainer: Sonsoles Lopez-Pernas <sonsoles.lopez@uef.fi>

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Package vectra updated to version 0.11.1 with previous version 0.9.8 dated 2026-07-01

Title: Columnar Query Engine for Larger-than-RAM Data
Description: A minimal columnar query engine with lazy execution on datasets larger than RAM. Provides 'dplyr'-like verbs (filter(), select(), mutate(), group_by(), summarise(), joins, window functions) and common aggregations (n(), sum(), mean(), min(), max(), sd(), first(), last()) backed by a pure C11 pull-based execution engine and a custom on-disk format ('.vtr'). Reads and writes 'GeoTIFF' (including tiled and 'BigTIFF' layouts) and a tiled raster format ('.vec') with overview pyramids and time cubes for larger-than-RAM raster data. Streams vector operations (spatial transforms, point-in-polygon and nearest-feature joins including a two-sided grid-partitioned join, select-by-location, clip, erase, dissolve, 'rasterization', 'polygonization', and contouring) through 'sf', and runs raster operations (zonal statistics, focal windows, terrain derivatives, resample or 'reproject' warp, polygon masking, map algebra, and 'mosaicking') in native C or over the tiled '.vec' format, one batch or tile at [...truncated...]
Author: Gilles Colling [aut, cre, cph]
Maintainer: Gilles Colling <gilles.colling051@gmail.com>

Diff between vectra versions 0.9.8 dated 2026-07-01 and 0.11.1 dated 2026-07-10

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More information about vectra at CRAN
Permanent link

Package FPDclustering updated to version 2.3.6 with previous version 2.3.5 dated 2025-03-05

Title: PD-Clustering and Related Methods
Description: Probabilistic distance clustering (PD-clustering) is an iterative, distribution-free, probabilistic clustering method. PD-clustering assigns units to a cluster according to their probability of membership under the constraint that the product of the probability and the distance of each point to any cluster center is a constant. PD-clustering is a flexible method that can be used with elliptical clusters, outliers, or noisy data. PDQ is an extension of the algorithm for clusters of different sizes. GPDC and TPDC use a dissimilarity measure based on densities. Factor PD-clustering (FPDC) is a factor clustering method that involves a linear transformation of variables and a cluster optimizing the PD-clustering criterion. It works on high-dimensional data sets.
Author: Cristina Tortora [aut, cre, cph], Noe Vidales [aut], Francesco Palumbo [aut], Tina Kalra [aut], Paul D. McNicholas [fnd]
Maintainer: Cristina Tortora <grikris1@gmail.com>

Diff between FPDclustering versions 2.3.5 dated 2025-03-05 and 2.3.6 dated 2026-07-10

 DESCRIPTION |    8 ++++----
 MD5         |   14 +++++++-------
 R/GPDC.R    |    8 ++++----
 R/PDQ.R     |    9 ++++-----
 R/TPDC.R    |    8 ++++----
 man/GPDC.Rd |    4 +++-
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More information about FPDclustering at CRAN
Permanent link

Package gsearly updated to version 1.1.0 with previous version 1.0.0 dated 2026-01-23

Title: Creates Group Sequential Trial Designs when Early Outcomes are Available
Description: Methods to construct and power group sequential clinical trial designs for outcomes at multiple times. Outcomes at earlier times provide information on the final (primary) outcome. A range of recruitment and correlation models are available as are methods to simulate data in order to explore design operating characteristics. For more details see Parsons (2024) <doi:10.1186/s12874-024-02174-w>.
Author: Nick Parsons [aut, cre]
Maintainer: Nick Parsons <nick.parsons@warwick.ac.uk>

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Package robustlmm updated to version 3.5.0-1 with previous version 3.4-5 dated 2026-06-21

Title: Robust Linear Mixed Effects Models
Description: Implements the Robust Scoring Equations estimator to fit linear mixed effects models robustly. Robustness is achieved by modification of the scoring equations combined with the Design Adaptive Scale approach.
Author: Manuel Koller [aut, cre]
Maintainer: Manuel Koller <kollerma@proton.me>

Diff between robustlmm versions 3.4-5 dated 2026-06-21 and 3.5.0-1 dated 2026-07-10

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Package KPC updated to version 0.1.4 with previous version 0.1.3 dated 2026-05-02

Title: Kernel Partial Correlation Coefficient
Description: Implementations of two empirical versions the kernel partial correlation (KPC) coefficient and the associated variable selection algorithms. KPC is a measure of the strength of conditional association between Y and Z given X, with X, Y, Z being random variables taking values in general topological spaces. As the name suggests, KPC is defined in terms of kernels on reproducing kernel Hilbert spaces (RKHSs). The population KPC is a deterministic number between 0 and 1; it is 0 if and only if Y is conditionally independent of Z given X, and it is 1 if and only if Y is a measurable function of Z and X. One empirical KPC estimator is based on geometric graphs, such as K-nearest neighbor graphs and minimum spanning trees, and is consistent under very weak conditions. The other empirical estimator, defined using conditional mean embeddings (CMEs) as used in the RKHS literature, is also consistent under suitable conditions. Using KPC, a stepwise forward variable selection algorithm KFOCI (usin [...truncated...]
Author: Zhen Huang [aut, cre], Nabarun Deb [ctb], Bodhisattva Sen [ctb], Benjamin Lang [ctb]
Maintainer: Zhen Huang <zh2395@columbia.edu>

Diff between KPC versions 0.1.3 dated 2026-05-02 and 0.1.4 dated 2026-07-10

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Package harbinger updated to version 2.1.707 with previous version 2.0.757 dated 2026-05-22

Title: A Unified Time Series Event Detection Framework
Description: By analyzing time series, it is possible to observe significant changes in the behavior of observations that frequently characterize events. Events present themselves as anomalies, change points, or motifs. In the literature, there are several methods for detecting events. However, searching for a suitable time series method is a complex task, especially considering that the nature of events is often unknown. This work presents Harbinger, a framework for integrating and analyzing event detection methods. Harbinger contains several state-of-the-art methods described in Salles et al. (2020) <doi:10.5753/sbbd.2020.13626>.
Author: Eduardo Ogasawara [aut, ths, cre] , Anthony Heimlich [aut], Antonio Castro [aut], Antonio Mello [aut], Diego Carvalho [ctb], Eduardo Bezerra [ctb], Ellen Paixao [aut], Fernando Fraga [aut], Gabriel Giuliano [aut], Heraldo Borges [aut], Igor Andrade [ [...truncated...]
Maintainer: Eduardo Ogasawara <eogasawara@ieee.org>

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Package daltoolboxdp updated to version 1.3.767 with previous version 1.3.757 dated 2026-06-26

Title: Deep Python Extensions for 'daltoolbox'
Description: Extends 'daltoolbox' with Python-backed components for deep learning, scikit-learn classification, and time-series forecasting through 'reticulate'. The package provides objects that follow the 'daltoolbox' architecture while delegating model creation, fitting, encoding, and prediction to Python libraries such as 'torch' and 'scikit-learn'. In the package name, 'dp' stands for 'Deep Python'. The overall workflow is inspired by the Experiment Lines approach described in Ogasawara et al. (2009) <doi:10.1007/978-3-642-02279-1_20>.
Author: Eduardo Ogasawara [aut, ths, cre] , Diego Salles [aut], Erich Carvalho [aut], Janio Lima [aut], Joao Kongevold [aut], Lucas Tavares [aut], Eduardo Bezerra [ctb], CEFET/RJ [cph]
Maintainer: Eduardo Ogasawara <eogasawara@ieee.org>

Diff between daltoolboxdp versions 1.3.757 dated 2026-06-26 and 1.3.767 dated 2026-07-10

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Package reproj updated to version 0.8.0 with previous version 0.7.0 dated 2024-06-11

Title: Coordinate System Transformations for Generic Map Data
Description: Transform coordinates from a specified source to a specified target map projection. This uses the 'PROJ' library directly, via the 'PROJ' package. The 'reproj()' function is generic, methods may be added to remove the need for an explicit source definition. This is for use primarily to transform generic data formats and direct leverage of the underlying 'PROJ' library. (There are transformations that aren't possible with 'PROJ' and that are provided by the 'GDAL' library, a limitation which users of this package should be aware of.) The 'PROJ' library is available at <https://proj.org/>.
Author: Michael D. Sumner [aut, cre]
Maintainer: Michael D. Sumner <mdsumner@gmail.com>

Diff between reproj versions 0.7.0 dated 2024-06-11 and 0.8.0 dated 2026-07-10

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Package duckdb updated to version 1.5.4.3 with previous version 1.5.4.2 dated 2026-06-29

Title: DBI Package for the DuckDB Database Management System
Description: The DuckDB project is an embedded analytical data management system with support for the Structured Query Language (SQL). This package includes all of DuckDB and an R Database Interface (DBI) connector.
Author: Hannes Muehleisen [aut] , Mark Raasveldt [aut] , Kirill Mueller [cre] , Stichting DuckDB Foundation [cph], Apache Software Foundation [cph], PostgreSQL Global Development Group [cph], The Regents of the University of California [cph], Cameron Desrocher [...truncated...]
Maintainer: Kirill Mueller <kirill@cynkra.com>

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Package coin updated to version 1.4-5 with previous version 1.4-4 dated 2026-06-30

Title: Conditional Inference Procedures in a Permutation Test Framework
Description: Conditional inference procedures for the general independence problem including two-sample, K-sample (non-parametric ANOVA), correlation, censored, ordered and multivariate problems described in <doi:10.18637/jss.v028.i08>.
Author: Torsten Hothorn [aut, cre] , Henric Winell [aut] , Kurt Hornik [aut] , Mark A. van de Wiel [aut] , Achim Zeileis [aut]
Maintainer: Torsten Hothorn <Torsten.Hothorn@R-project.org>

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Package CKNNRLD updated to version 0.2.0 with previous version 0.1.4 dated 2026-06-09

Title: Clustering-Based K-Nearest Neighbor Regression for Longitudinal Data
Description: Implements the 'CKNNRLD' algorithm (Clustering-Based K-Nearest Neighbor Regression for Longitudinal Data) for improving K-Nearest Neighbor ('KNN') regression on longitudinal data through cluster-based partitioning and localized prediction. Offers enhanced computational efficiency and accuracy for high-volume longitudinal datasets. The acronym 'KNN' stands for K-Nearest Neighbor. References: Loeloe MS, Tabatabaei SM, Sefidkar R, Mehrparvar AH, Jambarsang S (2025). "Boosting K-nearest neighbor regression performance for longitudinal data through a novel learning approach." BMC Bioinformatics, 26, 232. <doi:10.1186/s12859-025-06205-1>.
Author: Mohammad Sadegh Loeloe [aut, cre], Seyyed Mohammad Tabatabaei [aut], Reyhane Sefidkar [aut], Amir Houshang Mehrparvar [aut], Sara Jambarsang [aut, ths]
Maintainer: Mohammad Sadegh Loeloe <mslbiostat@gmail.com>

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Package AIGRA updated to version 0.2.0 with previous version 0.1.2 dated 2026-06-05

Title: Agentic Item Generation, Review, and Analysis
Description: Provides tools for validating, generating, reviewing, reporting, and visualising assessment item generation workflows. The package supports tabular item-bank templates, item-bank validation, 'Python'-backed agentic generation workflows, multimodal diagram generation, quality summaries, and 'HTML' reporting. External artificial intelligence services and related 'API' calls require user-supplied credentials and are not called during package checks. The workflow is informed by automatic item generation methods described by Gierl and Haladyna (2013, ISBN:9780415897518) and evidence-centered assessment design described by Mislevy et al. (2003) <doi:10.1002/j.2333-8504.2003.tb01908.x>.
Author: Moses O. Omopekunola [aut, cre]
Maintainer: Moses O. Omopekunola <omopekunola.m@hse.ru>

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2019-08-08 0.2-13
2018-03-03 0.2-12
2017-06-12 0.2-8

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2021-02-26 1.2
2020-02-22 1.1
2019-09-20 1.0

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Package gpboost updated to version 1.7.0 with previous version 1.6.8 dated 2026-06-24

Title: Combining Tree-Boosting with Gaussian Process and Mixed Effects Models
Description: An R package that allows for combining tree-boosting with Gaussian process and mixed effects models. It also allows for independently doing tree-boosting as well as inference and prediction for Gaussian process and mixed effects models. See <https://github.com/fabsig/GPBoost> for more information on the software and Sigrist (2022, JMLR) <https://www.jmlr.org/papers/v23/20-322.html> and Sigrist (2023, TPAMI) <doi:10.1109/TPAMI.2022.3168152> for more information on the methodology.
Author: Fabio Sigrist [aut, cre], Tim Gyger [aut], Pascal Kuendig [aut], Benoit Jacob [cph], Gael Guennebaud [cph], Nicolas Carre [cph], Pierre Zoppitelli [cph], Gauthier Brun [cph], Jean Ceccato [cph], Jitse Niesen [cph], Other authors of Eigen for the incl [...truncated...]
Maintainer: Fabio Sigrist <fabiosigrist@gmail.com>

Diff between gpboost versions 1.6.8 dated 2026-06-24 and 1.7.0 dated 2026-07-10

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Package GISSB updated to version 1.1.1 with previous version 1.1 dated 2023-01-10

Title: Network Analysis on the Norwegian Road Network
Description: A collection of GIS (Geographic Information System) functions in R, created for use in Statistics Norway. The functions are primarily related to network analysis on the Norwegian road network.
Author: Sindre Mikael Haugen [aut, cre]
Maintainer: Sindre Mikael Haugen <sindre.haugen@ssb.no>

Diff between GISSB versions 1.1 dated 2023-01-10 and 1.1.1 dated 2026-07-10

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Package BFpack updated to version 1.6.1 with previous version 1.6.0 dated 2026-04-13

Title: Flexible Bayes Factor Testing of Scientific Expectations
Description: Implementation of default Bayes factors for testing statistical hypotheses under various statistical models. The package is intended for applied quantitative researchers in the social and behavioral sciences, medical research, and related fields. The Bayes factor tests can be executed for statistical models such as univariate and multivariate normal linear models, correlation analysis, generalized linear models, special cases of linear mixed models, survival models, relational event models. Parameters that can be tested are location parameters (e.g., group means, regression coefficients), variances (e.g., group variances), and measures of association (e.g,. polychoric/polyserial/biserial/tetrachoric/product moments correlations), among others. Relevant references on the methodology The statistical underpinnings are described in O'Hagan (1995) <DOI:10.1111/j.2517-6161.1995.tb02017.x>, Mulder and Xin (2022) <DOI:10.1080/00273171.2021.1904809>, Mulder and Gelissen (2019) <D [...truncated...]
Author: Joris Mulder [aut, cre], Caspar van Lissa [aut, ctb], Donald R. Williams [aut, ctb], Xin Gu [aut, ctb], Anton Olsson-Collentine [aut, ctb], Florian Boeing-Messing [aut, ctb], Jean-Paul Fox [aut, ctb], Janosch Menke [ctb], Robbie van Aert [ctb], Barry [...truncated...]
Maintainer: Joris Mulder <j.mulder3@tilburguniversity.edu>

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Package tfrmt updated to version 0.4.0 with previous version 0.3.0 dated 2026-01-24

Title: Applies Display Metadata to Analysis Results Datasets
Description: Creates a framework to store and apply display metadata to Analysis Results Datasets (ARDs). The use of 'tfrmt' allows users to define table format and styling without the data, and later apply the format to the data.
Author: Alanah Jonas [aut, cre], Becca Krouse [aut], Christina Fillmore [aut] , Ellis Hughes [aut] , Karima Ahmad [aut] , Shannon Haughton [aut], DragoÈ™ Moldovan-Gruenfeld [aut], GlaxoSmithKline Research & Development Limited [cph, fnd], Atorus Research LLC [ [...truncated...]
Maintainer: Alanah Jonas <alanah.x.jonas@gsk.com>

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Package RALSA updated to version 1.7.0 with previous version 1.6.6 dated 2026-04-16

Title: R Analyzer for Large-Scale Assessments
Description: Download, prepare and analyze data from large-scale assessments and surveys with complex sampling and assessment design (see 'Rutkowski', 2010 <doi:10.3102/0013189X10363170>). Such studies are, for example, international assessments like 'TIMSS', 'PIRLS' and 'PISA'. A graphical interface is available for the non-technical user.The package includes functions to covert the original data from 'SPSS' into 'R' data sets keeping the user-defined missing values, merge data from different respondents and/or countries, generate variable dictionaries, modify data, produce descriptive statistics (percentages, means, percentiles, benchmarks) and multivariate statistics (correlations, linear regression, binary logistic regression). The number of supported studies and analysis types increases with every next release. For a general presentation of the package, see 'Mirazchiyski', 2021a (<doi:10.1186/s40536-021-00114-4>). For detailed technical aspects of the package, see 'Mirazchiyski', 2 [...truncated...]
Author: Plamen V. Mirazchiyski [aut, cre]
Maintainer: Plamen V. Mirazchiyski <plamen.mirazchiyski@gmail.com>

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Package mdbplyr updated to version 0.4.1 with previous version 0.4.0 dated 2026-06-25

Title: A Native Lazy Analytical Backend for MongoDB
Description: Provides a disciplined, lazy subset of 'dplyr' semantics for MongoDB aggregation pipelines. Queries remain lazy until collect() and compile into MongoDB-native aggregation stages.
Author: Paolo Bosetti [aut, cre]
Maintainer: Paolo Bosetti <paolo.bosetti@unitn.it>

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Package Compind updated to version 3.6 with previous version 3.5 dated 2026-07-02

Title: Composite Indicators Functions
Description: A collection of functions to calculate Composite Indicators methods, focusing, in particular, on the normalisation and weighting-aggregation steps, as described in OECD Handbook on constructing composite indicators: methodology and user guide, 2008, 'Vidoli' and 'Fusco' and 'Mazziotta' <doi:10.1007/s11205-014-0710-y>, 'Mazziotta' and 'Pareto' (2016) <doi:10.1007/s11205-015-0998-2>, 'Van Puyenbroeck and 'Rogge' <doi:10.1016/j.ejor.2016.07.038> and other authors.
Author: Francesco Vidoli [aut, cre], Elisa Fusco [aut]
Maintainer: Francesco Vidoli <fvidoli@gmail.com>

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Package asremlPlus updated to version 4.4.63 with previous version 4.4.58 dated 2026-04-12

Title: Augments 'ASReml-R' in Fitting Mixed Models and Packages Generally in Exploring Prediction Differences
Description: Assists in automating the selection of terms to include in mixed models when 'asreml' is used to fit the models. Procedures are available for choosing models that conform to the hierarchy or marginality principle, for fitting and choosing between two-dimensional spatial models using correlation, natural cubic smoothing spline and P-spline models. A history of the fitting of a sequence of models is kept in a data frame. Also used to compute functions and contrasts of, to investigate differences between and to plot predictions obtained using any model fitting function. The content falls into the following natural groupings: (i) Data, (ii) Model modification functions, (iii) Model selection and description functions, (iv) Model diagnostics and simulation functions, (v) Prediction production and presentation functions, (vi) Response transformation functions, (vii) Object manipulation functions, and (viii) Miscellaneous functions (for further details see 'asremlPlus-package' in help). The [...truncated...]
Author: Chris Brien [aut, cre]
Maintainer: Chris Brien <chris.brien@adelaide.edu.au>

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Package starling updated to version 1.1.0 with previous version 0.6.5 dated 2026-01-26

Title: Record Linkage for Public Health Surveillance
Description: Record linkage for public health surveillance datasets using either the Fellegi-Sunter probabilistic framework (via reclin2) or deterministic exact-key matching. Provides pre-linkage data quality auditing (preflight()), Medicare number checksum validation (check_medicare()), blocking variable construction (flock()), and the murmuration() linkage engine. murmuration() expresses linkage as a single cohort-to-event concept (linking a linelist of people to a dated stream of vaccination, hospitalisation, or case events within a before/during/after time window), with the historical four-code taxonomy (case-to-hospitalisation, vaccination-to-case, vaccination-to-hospitalisation, vaccination-to-event) retained as deprecated aliases. Also provides linkage weight distribution visualisation (murmuration_plot()) and threshold sensitivity analysis (perch()) with annotated AIHW, WA Data Linkage Unit, and PHRN reference benchmarks. perch() can be called standalone or triggered automatically mid-linka [...truncated...]
Author: Nicolas Smoll [aut, cre]
Maintainer: Nicolas Smoll <nicolas.smoll@health.qld.gov.au>

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Package rjd3x13 updated to version 3.8.0 with previous version 3.7.1 dated 2026-03-11

Title: Seasonal Adjustment with 'X-13' in 'JDemetra+' 3.x
Description: R Interface to 'JDemetra+' 3.x (<https://github.com/jdemetra>) time series analysis software. It offers full access to options and outputs of 'X-13', including Reg-ARIMA modelling (automatic AutoRegressive Integrated Moving Average (ARIMA) model with outlier detection and trading days adjustment) and X-11 decomposition.
Author: Jean Palate [aut], Alain Quartier-la-Tente [aut] , Tanguy Barthelemy [aut, cre, art], Anna Smyk [aut]
Maintainer: Tanguy Barthelemy <timeserieswithjdemetraandr@gmail.com>

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Package rjd3tramoseats updated to version 3.8.0 with previous version 3.7.1 dated 2026-03-11

Title: Seasonal Adjustment with TRAMO-SEATS in 'JDemetra+' 3.x
Description: Interface to 'JDemetra+' 3.x (<https://github.com/jdemetra>) time series analysis software. It offers full access to options and outputs of 'TRAMO-SEATS' (Time series Regression with ARIMA noise, Missing values and Outliers - Signal Extraction in ARIMA Time Series), including 'TRAMO' modelling (ARIMA model with outlier detection and trading days adjustment). ARIMA = AutoRegressive Integrated Moving Average.
Author: Jean Palate [aut], Alain Quartier-la-Tente [aut] , Tanguy Barthelemy [aut, cre, art], Anna Smyk [aut]
Maintainer: Tanguy Barthelemy <timeserieswithjdemetraandr@gmail.com>

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Package PROJ updated to version 0.7.0 with previous version 0.6.0 dated 2025-04-02

Title: Generic Coordinate System Transformations Using 'PROJ'
Description: A wrapper around the generic coordinate transformation software 'PROJ' that transforms coordinates from one coordinate reference system ('CRS') to another. This includes cartographic projections as well as geodetic transformations. The intention is for this package to be used by user-packages such as 'reproj', and that the older 'PROJ.4' and version 5 pathways be provided by the 'proj4' package.
Author: Michael D. Sumner [aut, cre] , Jeroen Ooms [ctb] , Simon Urbanek [cph, ctb] , Dewey Dunnington [ctb] , Anthony North [ctb]
Maintainer: Michael D. Sumner <mdsumner@gmail.com>

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Package maidr updated to version 0.4.0 with previous version 0.3.0 dated 2026-04-01

Title: Multimodal Access and Interactive Data Representation
Description: Provides accessible, interactive visualizations through the 'MAIDR' (Multimodal Access and Interactive Data Representation) system. Converts 'ggplot2' and Base R plots into accessible HTML/SVG formats with keyboard navigation, screen reader support, and 'sonification' capabilities. Supports bar charts (simple, grouped, stacked), histograms, line plots, scatter plots, box plots, violin plots, candlestick (OHLC) charts, heat maps, density/smooth curves, faceted plots, multi-panel layouts (including patchwork), and multi-layered plot combinations. Enables data exploration for users with visual impairments through multiple sensory modalities. For more details see the 'MAIDR' project <https://maidr.ai/>.
Author: JooYoung Seo [aut, cph], Niranjan Kalaiselvan [aut, cre]
Maintainer: Niranjan Kalaiselvan <nk46@illinois.edu>

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Package edr4r updated to version 0.1.1 with previous version 0.1.0 dated 2026-06-18

Title: Client for OGC API - Environmental Data Retrieval (EDR)
Description: A tidy R client for services implementing the OGC API - Environmental Data Retrieval ('EDR') standard with JSON discovery and 'GeoJSON' or 'CoverageJSON' query responses. General purpose, but most of its real-world use is against in-situ monitoring networks (stream gauges, weather stations, snow and reservoir telemetry) that expose their stations and time series as EDR collections. Known working endpoints include the USGS waterdata OGC API and the Western Water Datahub. Provides discovery, query, and parsing helpers for the locations, items, position, area, cube, radius, trajectory, and corridor query types. Returns 'CoverageJSON' as tidy 'tibble' rows and 'GeoJSON' as 'sf' objects.
Author: Kyle Onda [aut, cre, cph]
Maintainer: Kyle Onda <konda@lincolninst.edu>

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Package dobin updated to version 1.0.5 with previous version 1.0.4 dated 2022-08-25

Title: Dimension Reduction for Outlier Detection
Description: A dimension reduction technique for outlier detection. DOBIN: a Distance based Outlier BasIs using Neighbours, constructs a set of basis vectors for outlier detection. This is not an outlier detection method; rather it is a pre-processing method for outlier detection. It brings outliers to the fore-front using fewer basis vectors (Kandanaarachchi, Hyndman 2020) <doi:10.1080/10618600.2020.1807353>.
Author: Sevvandi Kandanaarachchi [aut, cre]
Maintainer: Sevvandi Kandanaarachchi <sevvandik@gmail.com>

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Package sumup updated to version 1.0.3 with previous version 1.0.2 dated 2026-02-24

Title: Utilizing Automated Text Analysis to Support Interpretation of Narrative Feedback
Description: Combine topic modeling and sentiment analysis to identify individual students' gaps, and highlight their strengths and weaknesses across predefined competency domains and professional activities.
Author: Joyce Moonen - van Loon [aut, cre]
Maintainer: Joyce Moonen - van Loon <j.moonen@maastrichtuniversity.nl>

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Package OpenLand updated to version 1.0.5 with previous version 1.0.4 dated 2026-07-01

Title: Quantitative Analysis and Visualization of LUCC
Description: Tools for the analysis of land use and cover (LUC) time series. It includes support for loading spatiotemporal raster data and synthesized spatial plotting. Several LUC change (LUCC) metrics in regular or irregular time intervals can be extracted and visualized through one- and multistep sankey and chord diagrams. A complete intensity analysis according to Aldwaik and Pontius (2012) <doi:10.1016/j.landurbplan.2012.02.010> is implemented, including tools for the generation of standardized multilevel output graphics.
Author: Reginal Exavier [aut, cre] , Peter Zeilhofer [aut]
Maintainer: Reginal Exavier <reginalexavier@rocketmail.com>

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Package deeptime updated to version 2.4.0 with previous version 2.3.1 dated 2025-11-26

Title: Plotting Tools for Anyone Working in Deep Time
Description: Extends the functionality of other plotting packages (notably 'ggplot2') to help facilitate the plotting of data over long time intervals, including, but not limited to, geological, evolutionary, and ecological data. The primary goal of 'deeptime' is to enable users to add highly customizable timescales to their visualizations. Other functions are also included to assist with other areas of deep time visualization.
Author: William Gearty [aut, cre]
Maintainer: William Gearty <willgearty@gmail.com>

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Package ciuupi updated to version 1.2.4 with previous version 1.2.3 dated 2024-06-18

Title: Confidence Intervals Utilizing Uncertain Prior Information
Description: Computes a confidence interval for a specified linear combination of the regression parameters in a linear regression model with iid normal errors with known variance when there is uncertain prior information that a distinct specified linear combination of the regression parameters takes a given value. This confidence interval, found by numerical nonlinear constrained optimization, has the required minimum coverage and utilizes this uncertain prior information through desirable expected length properties. This confidence interval has the following three practical applications. Firstly, if the error variance has been accurately estimated from previous data then it may be treated as being effectively known. Secondly, for sufficiently large (dimension of the response vector) minus (dimension of regression parameter vector), greater than or equal to 30 (say), if we replace the assumed known value of the error variance by its usual estimator in the formula for the confidence interval then [...truncated...]
Author: Paul Kabaila [aut, cre], Rheanna Mainzer [aut], Ayesha Perera [ctb]
Maintainer: Paul Kabaila <P.Kabaila@latrobe.edu.au>

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Package spada updated to version 0.1.7 with previous version 0.1.6 dated 2026-06-11

Title: A 'shiny' Package for Data Analysis
Description: Provides a 'shiny' application with a user-friendly interface for interactive data analysis. It supports exploratory data analysis through descriptive statistics, data visualization, statistical tests (e.g., normality assessment), linear modeling, data import, transformation and reporting. For more details see Shapiro and Wilk (1965) <doi:10.2307/2333709>.
Author: Luis Gustavo Schuck [aut, cre]
Maintainer: Luis Gustavo Schuck <luisgustavoschuck@yahoo.com.br>

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Package sgolay updated to version 1.0.4 with previous version 1.0.3 dated 2023-04-05

Title: Efficient Savitzky-Golay Filtering
Description: Smoothing signals and computing their derivatives is a common requirement in signal processing workflows. Savitzky-Golay filters are a established method able to do both (Savitzky and Golay, 1964 <doi:10.1021/ac60214a047>). This package implements one dimensional Savitzky-Golay filters that can be applied to vectors and matrices (either row-wise or column-wise). Vectorization and memory allocations have been profiled to reduce computational fingerprint. Short filter lengths are implemented in the direct space, while longer filters are implemented in frequency space, using a Fast Fourier Transform (FFT).
Author: Sergio Oller Moreno [aut, cre] , Robert Gentleman [ctb, cph] ), Ross Ihaka [ctb, cph] ), Brian Ripley [ctb, cph] ), Martin Maechler [ctb, cph] ), Duncan Murdoch [ctb, cph] ), Institute for Bioengineering of Catalonia [cph]
Maintainer: Sergio Oller Moreno <sergioller@gmail.com>

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Package Rduckhts updated to version 1.4.0-0.1.0 with previous version 1.3.0-0.1.0 dated 2026-05-29

Title: 'DuckDB' High Throughput Sequencing File Formats Reader Extension
Description: Bundles the 'duckhts' 'DuckDB' extension for reading High Throughput Sequencing file formats with 'DuckDB'. The 'DuckDB' C extension API <https://duckdb.org/docs/stable/clients/c/api> and its 'htslib' dependency are compiled from vendored sources during package installation. James K Bonfield and co-authors (2021) <doi:10.1093/gigascience/giab007>. VariantKey / RegionKey support follows Nicola Asuni (2018) <doi:10.1101/473744>.
Author: Sounkou Mahamane Toure [aut, cre], James K Bonfield, John Marshall,Petr Danecek ,Heng Li , Valeriu Ohan, Andrew Whitwham,Thomas Keane , Robert M Davies [ctb] , Brent Pedersen [cph] , Giulio Genovese [cph] , Nicola Asuni [cph] , DuckDB C Extension API [...truncated...]
Maintainer: Sounkou Mahamane Toure <sounkoutoure@gmail.com>

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Package kindling updated to version 0.3.2 with previous version 0.3.1 dated 2026-07-02

Title: Higher-Level Interface of 'torch' Package to Auto-Train Neural Networks
Description: Provides a higher-level interface to the 'torch' package for defining, training, and fine-tuning neural networks through code generation. The package supports several architectures, including feedforward (multi-layer perceptron) and recurrent neural networks (RNN, LSTM, GRU), while reducing boilerplate 'torch' code. Model training methods also bridge to machine learning frameworks in R, particularly the 'tidymodels' ecosystem, including 'parsnip' model specifications, workflows, recipes, and tuning tools.
Author: Joshua Marie [aut, cre], Antoine Soetewey [aut]
Maintainer: Joshua Marie <joshua.marie.k@gmail.com>

Diff between kindling versions 0.3.1 dated 2026-07-02 and 0.3.2 dated 2026-07-10

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Package blisa updated to version 1.0.0 with previous version 0.2.0 dated 2026-06-02

Title: Infer Cell-Cell Communication from Spatial Transcriptomics
Description: Identifies cell-cell communication hotspots in spatial transcriptomics data using bivariate Local Moran's I statistics on hexagonally binned cells. Provides functions for spatial weighting, ligand-receptor pair filtering, hotspot detection, and visualisation of sender-receiver cell-type interactions.
Author: Yunshun Chen [aut, cre], Lei Qin [aut], Lizhong Chen [aut]
Maintainer: Yunshun Chen <yuchen@wehi.edu.au>

Diff between blisa versions 0.2.0 dated 2026-06-02 and 1.0.0 dated 2026-07-10

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Package BEND updated to version 2.1.0 with previous version 2.0.1 dated 2026-04-18

Title: Bayesian Estimation of Nonlinear Data (BEND)
Description: Provides a set of models to estimate nonlinear longitudinal data using Bayesian estimation methods. These models include the: 1) Bayesian Piecewise Random Effects Model (Bayes_PREM()) which estimates a piecewise random effects (mixture) model for a given number of latent classes and a latent number of possible changepoints in each class, and can incorporate class and outcome predictive covariates (see Lamm (2022) <https://hdl.handle.net/11299/252533> and Lock et al., (2018) <doi:10.1007/s11336-017-9594-5>), 2) Bayesian Crossed Random Effects Model (Bayes_CREM()) which estimates a linear, quadratic, exponential, or piecewise crossed random effects models where individuals are changing groups over time (e.g., students and schools; see Rohloff et al., (2024) <doi:10.1111/bmsp.12334>), and 3) Bayesian Bivariate Piecewise Random Effects Model (Bayes_BPREM()) which estimates a bivariate piecewise random effects model to jointly model two related outcomes (e.g., reading and [...truncated...]
Author: Corissa T. Rohloff [aut, cre] , Rik Lamm [aut] , Yadira Peralta [aut] , Nidhi Kohli [aut] , Eric F. Lock [aut]
Maintainer: Corissa T. Rohloff <corissa.wurth@gmail.com>

Diff between BEND versions 2.0.1 dated 2026-04-18 and 2.1.0 dated 2026-07-10

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