Wed, 01 Apr 2026

Package RTMBdist updated to version 1.0.3 with previous version 1.0.2 dated 2026-03-16

Title: Distributions Compatible with Automatic Differentiation by 'RTMB'
Description: Extends the functionality of the 'RTMB' <https://kaskr.r-universe.dev/RTMB> package by providing a collection of non-standard probability distributions compatible with automatic differentiation (AD). While 'RTMB' enables flexible and efficient modelling, including random effects, its built-in support is limited to standard distributions. The package adds additional AD-compatible distributions, broadening the range of models that can be implemented and estimated using 'RTMB'. Automatic differentiation and Laplace approximation are described in Kristensen et al. (2016) <doi:10.18637/jss.v070.i05>.
Author: Jan-Ole Fischer [aut, cre]
Maintainer: Jan-Ole Fischer <jan-ole.fischer@mailbox.org>

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Package posterior updated to version 1.7.0 with previous version 1.6.1 dated 2025-02-27

Title: Tools for Working with Posterior Distributions
Description: Provides useful tools for both users and developers of packages for fitting Bayesian models or working with output from Bayesian models. The primary goals of the package are to: (a) Efficiently convert between many different useful formats of draws (samples) from posterior or prior distributions. (b) Provide consistent methods for operations commonly performed on draws, for example, subsetting, binding, or mutating draws. (c) Provide various summaries of draws in convenient formats. (d) Provide lightweight implementations of state of the art posterior inference diagnostics. References: Vehtari et al. (2021) <doi:10.1214/20-BA1221>.
Author: Paul-Christian Buerkner [aut, cre], Jonah Gabry [aut], Matthew Kay [aut], Aki Vehtari [aut], Mans Magnusson [ctb], Rok Česnovar [ctb], Ben Lambert [ctb], Ozan Adiguezel [ctb], Jacob Socolar [ctb], Noa Kallioinen [ctb], Teemu Saeilynoja [ctb]
Maintainer: Paul-Christian Buerkner <paul.buerkner@gmail.com>

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Package ecoXCorr updated to version 0.2.1 with previous version 0.1.9 dated 2026-03-24

Title: Lagged Cross-Correlation Analysis of Environmental Time Series
Description: Tools for analysing lagged relationships between environmental variables and ecological or epidemiological time series. The package implements a workflow to aggregate meteorological data over multiple lagged intervals, fit regression models, including mixed-effect models using 'glmmTMB', for each lag window, and visualise varied models outcomes (effect strength and direction, model prediction error...) using cross-correlation maps ('CCM').
Author: Nicolas Moiroux [aut, cre] , Colombine Bartholomee [aut] , Paul Taconet [aut]
Maintainer: Nicolas Moiroux <nicolas.moiroux@ird.fr>

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Package uaparserjs updated to version 0.3.7 with previous version 0.3.6 dated 2026-03-23

Title: Parse 'User-Agent' Strings
Description: Despite there being a section in RFC 7231 <https://datatracker.ietf.org/doc/html/rfc7231#section-5.5.3> defining a suggested structure for 'User-Agent' headers this data is notoriously difficult to parse consistently. Tools are provided that will take in user agent strings and return structured R objects. This is a 'V8'-backed package based on the 'ua-parser' project <https://github.com/ua-parser>.
Author: Bob Rudis [aut, cph], Greg Hunt [aut, cre, cph], Lindsey Simon [aut] , Tobie Langel [aut] , Colman Humphrey [ctb]
Maintainer: Greg Hunt <greg@firmansyah.com>

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Package processx updated to version 3.8.7 with previous version 3.8.6 dated 2025-02-21

Title: Execute and Control System Processes
Description: Tools to run system processes in the background. It can check if a background process is running; wait on a background process to finish; get the exit status of finished processes; kill background processes. It can read the standard output and error of the processes, using non-blocking connections. 'processx' can poll a process for standard output or error, with a timeout. It can also poll several processes at once.
Author: Gabor Csardi [aut, cre, cph] , Winston Chang [aut], Posit Software, PBC [cph, fnd] , Ascent Digital Services [cph, fnd]
Maintainer: Gabor Csardi <csardi.gabor@gmail.com>

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Package FAOSTAT updated to version 2.4.2 with previous version 2.4.0 dated 2024-05-22

Title: Download Data from the FAOSTAT Database
Description: Download Data from the FAOSTAT Database of the Food and Agricultural Organization (FAO) of the United Nations. A list of functions to download statistics from FAOSTAT (database of the FAO <https://www.fao.org/faostat/>) and WDI (database of the World Bank <https://data.worldbank.org/>), and to perform some harmonization operations.
Author: Michael C. J. [aut], Markus Gesmann [aut], Filippo Gheri [aut], Paul Rougieux [aut, cre], Sebastian Campbell [aut]
Maintainer: Paul Rougieux <paul.rougieux@gmail.com>

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Package Signac updated to version 1.17.0 with previous version 1.16.0 dated 2025-10-10

Title: Analysis of Single-Cell Chromatin Data
Description: A framework for the analysis and exploration of single-cell chromatin data. The 'Signac' package contains functions for quantifying single-cell chromatin data, computing per-cell quality control metrics, dimension reduction and normalization, visualization, and DNA sequence motif analysis. Reference: Stuart et al. (2021) <doi:10.1038/s41592-021-01282-5>.
Author: Tim Stuart [aut, cre] , Avi Srivastava [aut] , Paul Hoffman [ctb] , Rahul Satija [ctb]
Maintainer: Tim Stuart <stuartt@a-star.edu.sg>

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Package convertid updated to version 0.3.0 with previous version 0.2.1 dated 2026-02-05

Title: Convert Gene IDs Between Each Other and Fetch Annotations from Biomart
Description: Gene Symbols or Ensembl Gene IDs are converted using the Bimap interface in 'AnnotationDbi' in convertId2() but that function is only provided as fallback mechanism for the most common use cases in data analysis. The main function in the package is convert.bm() which queries BioMart using the full capacity of the API provided through the 'biomaRt' package. Presets and defaults are provided for convenience but all "marts", "filters" and "attributes" can be set by the user. Function convert.alias() converts Gene Symbols to Aliases and vice versa and function likely_symbol() attempts to determine the most likely current Gene Symbol.
Author: Vidal Fey [aut, cre], Henrik Edgren [aut]
Maintainer: Vidal Fey <vidal.fey@gmail.com>

Diff between convertid versions 0.2.1 dated 2026-02-05 and 0.3.0 dated 2026-04-01

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 11 files changed, 68 insertions(+), 20 deletions(-)

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New package taxdiv with initial version 0.1.0
Package: taxdiv
Title: Taxonomic Diversity Indices Using Deng Entropy
Version: 0.1.0
Description: Calculates taxonomic diversity indices for ecological community data using Deng entropy framework and classical approaches (Shannon, Simpson, Clarke & Warwick). Provides functions for computing taxonomic distinctness, average taxonomic distinctness (AvTD/Delta+), variation in taxonomic distinctness (VarTD/Lambda+), and Deng entropy-based measures that incorporate taxonomic hierarchy information. Includes tools for constructing taxonomic trees and computing pairwise taxonomic distances.
Imports: stats, rlang
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-US
LazyData: true
Depends: R (>= 4.1.0)
Suggests: testthat (>= 3.0.0), knitr, rmarkdown, ggplot2
VignetteBuilder: knitr
URL: https://github.com/mgorgoz/taxonomic-diversity-r, https://mgorgoz.github.io/taxonomic-diversity-r/
BugReports: https://github.com/mgorgoz/taxonomic-diversity-r/issues
NeedsCompilation: no
Packaged: 2026-03-28 21:33:27 UTC; muratgorgoz
Author: Muhammet Murat Gorgoz [aut, cre] , Kursad Ozkan [aut] , Mehmet Guvenc Negiz [aut]
Maintainer: Muhammet Murat Gorgoz <muratgorgoz350@gmail.com>
Repository: CRAN
Date/Publication: 2026-04-01 08:50:02 UTC

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Package nomine readmission to version 1.0.2 with previous version 1.0.0 dated 2017-11-04

Title: Classify Names by Gender, U.S. Ethnicity, and Leaf Nationality
Description: Functions to use the 'NamePrism' API <https://www.name-prism.com/api> or 'NamSor' API v2 <https://namsor.app/> for classifying names based on gender, 6 U.S. ethnicities, or 39 leaf nationalities. Updated to work with current API endpoints.
Author: Charles Crabtree [aut, cre], Volha Chykina [aut], Micah Gell-Redman [aut], Christian Chacua [aut]
Maintainer: Charles Crabtree <charles.crabtree@monash.edu>

This is a re-admission after prior archival of version 1.0.0 dated 2017-11-04

Diff between nomine versions 1.0.0 dated 2017-11-04 and 1.0.2 dated 2026-04-01

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 README.md                |  143 ++++++++++++++++++++++++++++++++++++++++++-----
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 10 files changed, 315 insertions(+), 132 deletions(-)

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New package mtaOpenData with initial version 0.1.0
Package: mtaOpenData
Title: Convenient Access to MTA Open Data API Endpoints
Version: 0.1.0
Description: Provides helper functions to access datasets from the Metropolitan Transportation Authority (MTA) portion of the New York State Open Data platform <https://data.ny.gov/>. Returns results as tidy tibbles with support for optional filtering, sorting, and row limits through the Socrata API.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: dplyr, tibble, jsonlite, httr, janitor, rlang
Suggests: curl, covr, knitr, testthat (>= 3.0.0), vcr, withr, webmockr, ggplot2
URL: https://martinezc1.github.io/mtaOpenData/, https://github.com/martinezc1/mtaOpenData
BugReports: https://github.com/martinezc1/mtaOpenData/issues
VignetteBuilder: knitr
Depends: R (>= 4.1.0)
NeedsCompilation: no
Packaged: 2026-03-28 03:24:20 UTC; christianmartinez
Author: Christian Martinez [aut, cre]
Maintainer: Christian Martinez <c.martinez0@outlook.com>
Repository: CRAN
Date/Publication: 2026-04-01 08:30:02 UTC

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New package gcpca with initial version 0.0.1
Package: gcpca
Title: Generalized Contrastive Principal Component Analysis
Version: 0.0.1
Description: Implements dense and sparse generalized contrastive principal component analysis (gcPCA) with S3 fit objects and methods for prediction, summaries, and plotting. The gcPCA is a hyperparameter-free method for comparing high-dimensional datasets collected under different experimental conditions to reveal low-dimensional patterns enriched in one condition compared to the other. Method details are described in de Oliveira, Garg, Hjerling-Leffler, Batista-Brito, and Sjulson (2025) <doi:10.1371/journal.pcbi.1012747>.
License: MIT + file LICENSE
Encoding: UTF-8
URL: https://github.com/SjulsonLab/generalized_contrastive_PCA
BugReports: https://github.com/SjulsonLab/generalized_contrastive_PCA/issues
Imports: graphics, stats
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-03-28 01:20:40 UTC; fermi
Author: Eliezyer de Oliveira [aut, cre]
Maintainer: Eliezyer de Oliveira <eliezyer.deoliveira@gmail.com>
Repository: CRAN
Date/Publication: 2026-04-01 08:30:08 UTC

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New package EE.Data with initial version 0.1.1
Package: EE.Data
Title: Objects for Predicting Energy Expenditure
Version: 0.1.1
Description: This is a data-only package containing model objects that predict human energy expenditure from wearable sensor data. Supported methods include the neural networks of Montoye et al. (2017) <doi:10.1080/1091367X.2017.1337638> and the models of Staudenmayer et al. (2015) <doi:10.1152/japplphysiol.00026.2015>, one a linear model and the other a random forest. The package is intended as a spoke for the hub-package 'accelEE', which brings together the above methods and others from packages such as 'Sojourn' and 'TwoRegression.'
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
LazyDataCompression: xz
Suggests: nnet, randomForest
Depends: R (>= 2.10)
NeedsCompilation: no
Packaged: 2026-03-28 11:20:13 UTC; phibbing
Author: Paul R. Hibbing [aut, cre], Alexander H.K. Montoye [ctb], John Staudenmayer [ctb], Children's Mercy Kansas City [cph]
Maintainer: Paul R. Hibbing <paulhibbing@gmail.com>
Repository: CRAN
Date/Publication: 2026-04-01 08:50:16 UTC

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Package dyngen updated to version 1.1.1 with previous version 1.1.0 dated 2026-03-17

Title: A Multi-Modal Simulator for Spearheading Single-Cell Omics Analyses
Description: A novel, multi-modal simulation engine for studying dynamic cellular processes at single-cell resolution. 'dyngen' is more flexible than current single-cell simulation engines. It allows better method development and benchmarking, thereby stimulating development and testing of novel computational methods. Cannoodt et al. (2021) <doi:10.1038/s41467-021-24152-2>.
Author: Robrecht Cannoodt [aut, cre, cph] , Wouter Saelens [aut]
Maintainer: Robrecht Cannoodt <rcannood@gmail.com>

Diff between dyngen versions 1.1.0 dated 2026-03-17 and 1.1.1 dated 2026-04-01

 DESCRIPTION        |    6 +++---
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New package albersdown with initial version 1.0.0
Package: albersdown
Title: Minimalist Theme and Vignette Kit for 'pkgdown' and R Markdown
Version: 1.0.0
Description: Provides a minimalist 'ggplot2' theme, colour scales, and 'pkgdown' template built around a curated colour palette system inspired by Josef Albers' colour theory (Albers (1963, ISBN:978-0-300-17935-4) "Interaction of Color"). Includes helpers to apply consistent theming to 'ggplot2' plots, 'gt' tables, and 'bslib' Bootstrap 5 sites, along with one-command setup functions for adopting the style across an R package.
URL: https://github.com/bbuchsbaum/albersdown, https://bbuchsbaum.github.io/albersdown/
BugReports: https://github.com/bbuchsbaum/albersdown/issues
Depends: R (>= 4.1)
Imports: grDevices, grid, stats, ggplot2
Suggests: gt, bslib, usethis, yaml, cli, testthat, viridisLite, knitr, rmarkdown, pkgdown
Encoding: UTF-8
VignetteBuilder: knitr
License: MIT + file LICENSE
NeedsCompilation: no
Packaged: 2026-03-28 13:04:28 UTC; bbuchsbaum
Author: Bradley R. Buchsbaum [aut, cre]
Maintainer: Bradley R. Buchsbaum <brad.buchsbaum@gmail.com>
Repository: CRAN
Date/Publication: 2026-04-01 08:50:10 UTC

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New package AgriDiversiX with initial version 0.1.0
Package: AgriDiversiX
Title: Agricultural Crop Diversification Indices Analysis
Version: 0.1.0
Depends: R (>= 3.5.0)
Imports: dplyr,DT,MCMCpack,ggplot2,tidyr,viridis
Description: Provides functions to compute agricultural crop diversification indices for crop data across zones and years. The package implements widely used diversification and concentration measures including Herfindahl Index,Simpson Index, Entropy Index, Ogive Index, and Maximum Proportion Index.
Encoding: UTF-8
License: GPL-3
NeedsCompilation: no
Maintainer: Santosha Rathod <santoshagriculture@gmail.com>
Packaged: 2026-03-28 06:18:15 UTC; pc
Author: Santosha Rathod [aut, cre], Mrinmoy Ray [aut, ctb], Prabhat Kumar [aut, ctb], Rahul Patil Kumar [aut, ctb], Anil Kumar [aut, ctb]
Repository: CRAN
Date/Publication: 2026-04-01 08:40:10 UTC

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Package scan updated to version 0.68.0 with previous version 0.67.0 dated 2025-09-11

Title: Single-Case Data Analyses for Single and Multiple Baseline Designs
Description: A collection of procedures for analysing, visualising, and managing single-case data. Multi-phase and multi-baseline designs are supported. Analysing methods include regression models (multilevel, multivariate, bayesian), between case standardised mean difference, overlap indices ('PND', 'PEM', 'PAND', 'NAP', 'PET', 'tau-u', 'IRD', 'baseline corrected tau', 'CDC'), and randomization tests. Data preparation functions support outlier detection, handling missing values, scaling, and custom transformations. An export function helps to generate html, word, and latex tables in a publication friendly style. A shiny app allows to use scan in a graphical user interface. More details can be found in the online book 'Analyzing single-case data with R and scan', Juergen Wilbert (2026) <https://jazznbass.github.io/scan-Book/>.
Author: Juergen Wilbert [cre, aut] , Timo Lueke [aut]
Maintainer: Juergen Wilbert <juergen.wilbert@uni-muenster.de>

Diff between scan versions 0.67.0 dated 2025-09-11 and 0.68.0 dated 2026-04-01

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New package nysOpenData with initial version 0.1.1
Package: nysOpenData
Title: Convenient Access to NYS Open Data API Endpoints
Version: 0.1.1
Description: Provides helper functions to access datasets from the NYS Open Data platform <https://data.ny.gov/>. Functions return results as tidy tibbles and support optional filtering, sorting, and row limits via the Socrata API.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: dplyr, tibble, stringr, jsonlite, httr, janitor, rlang
Suggests: curl, covr, knitr, testthat (>= 3.0.0), vcr, withr, webmockr, ggplot2
URL: https://martinezc1.github.io/nysOpenData/, https://github.com/martinezc1/nysOpenData
BugReports: https://github.com/martinezc1/nysOpenData/issues
VignetteBuilder: knitr
Depends: R (>= 4.1.0)
NeedsCompilation: no
Packaged: 2026-03-27 19:19:58 UTC; christianmartinez
Author: Christian Martinez [aut, cre]
Maintainer: Christian Martinez <c.martinez0@outlook.com>
Repository: CRAN
Date/Publication: 2026-04-01 08:00:14 UTC

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New package catviz with initial version 0.1.1
Package: catviz
Title: Visualizing Causal Assignment Trees for CSDiD and DR-DDD Designs
Version: 0.1.1
Description: Tools for constructing, labeling, and visualizing Causal Assignment Trees (CATs) in settings with staggered adoption. Supports Callaway and Sant'Anna difference-in-differences (CSDiD) and doubly robust difference-in-difference-differences (DR-DDD) designs. The package helps clarify treatment timing, never-treated vs. not-yet-treated composition, and subgroup structure, and produces publication-quality diagrams and summary tables. Current functionality focuses on data-to-node mapping, node counts, cohort-year summaries, and high-quality tree plots suitable for empirical applications prior to estimation. Methods are based on Callaway and Sant'Anna (2021) <doi:10.1016/j.jeconom.2020.12.001>, Sant'Anna and Zhao (2020) <doi:10.1016/j.jeconom.2020.06.003>, and Kilanko (2026) <https://github.com/VictorKilanko/catviz>.
License: MIT + file LICENSE
URL: https://github.com/VictorKilanko/catviz
BugReports: https://github.com/VictorKilanko/catviz/issues
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: dplyr, ggplot2, glue, tidyr, purrr, tibble, grid, rlang
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-03-27 19:13:26 UTC; victo
Author: Victor Kilanko [aut, cre]
Maintainer: Victor Kilanko <victorkilanko@gmail.com>
Repository: CRAN
Date/Publication: 2026-04-01 08:00:20 UTC

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New package bigKNN with initial version 0.3.0
Package: bigKNN
Title: Exact Search and Graph Construction for 'bigmemory' Matrices
Version: 0.3.0
Date: 2026-03-26
Author: Frederic Bertrand [aut, cre]
Maintainer: Frederic Bertrand <frederic.bertrand@lecnam.net>
Description: Exact nearest-neighbour and radius-search routines that operate directly on 'bigmemory::big.matrix' objects. The package streams row blocks through 'BLAS' kernels, supports self-search and external-query search, exposes prepared references for repeated queries, and can build exact k-nearest-neighbour, radius, mutual k-nearest-neighbour, and shared-nearest-neighbour graphs. Version 0.3.0 adds execution plans, serializable prepared caches, resumable streamed graph jobs, coercion helpers, exact candidate reranking, and recall summaries for evaluating approximate neighbours.
License: GPL (>= 2)
Depends: R (>= 3.5.0)
Imports: Matrix, Rcpp (>= 1.0.12), methods
Suggests: bigmemory, knitr, rmarkdown, testthat (>= 3.0.0)
LinkingTo: Rcpp, bigmemory, BH
Encoding: UTF-8
NeedsCompilation: yes
URL: https://fbertran.github.io/bigKNN/, https://github.com/fbertran/bigKNN
BugReports: https://github.com/fbertran/bigKNN/issues
VignetteBuilder: knitr
Packaged: 2026-03-27 01:16:22 UTC; bertran7
Repository: CRAN
Date/Publication: 2026-04-01 08:00:26 UTC

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New package bigANNOY with initial version 0.3.0
Package: bigANNOY
Title: Approximate k-Nearest Neighbour Search for 'bigmemory' Matrices with Annoy
Version: 0.3.0
Date: 2026-03-27
Author: Frederic Bertrand [aut, cre]
Maintainer: Frederic Bertrand <frederic.bertrand@lecnam.net>
Description: Approximate Euclidean k-nearest neighbour search routines that operate on 'bigmemory::big.matrix' data through Annoy indexes created with 'RcppAnnoy'. The package builds persistent on-disk indexes plus sidecar metadata from streamed 'big.matrix' rows, supports euclidean, angular, Manhattan, and dot-product Annoy metrics, and can either return in-memory results or stream neighbour indices and distances into destination 'bigmemory' matrices. Explicit index life cycle helpers, stronger metadata validation, descriptor-aware file-backed workflows, and benchmark helpers are also included.
License: GPL (>= 2)
Depends: R (>= 3.5.0)
Imports: methods, Rcpp, RcppAnnoy
LinkingTo: BH, bigmemory, Rcpp, RcppAnnoy
Suggests: bigmemory, knitr, litedown, testthat (>= 3.0.0)
VignetteBuilder: litedown
Encoding: UTF-8
NeedsCompilation: yes
URL: https://fbertran.github.io/bigANNOY/, https://github.com/fbertran/bigANNOY
BugReports: https://github.com/fbertran/bigANNOY/issues
Packaged: 2026-03-27 20:39:35 UTC; bertran7
Repository: CRAN
Date/Publication: 2026-04-01 08:00:33 UTC

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Package dynamAedes (with last version 2.2.9) was removed from CRAN

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

2024-03-12 2.2.9
2024-01-08 2.2.8
2023-03-30 2.1.2

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Package spanner updated to version 1.0.4 with previous version 1.0.3 dated 2026-03-26

Title: Utilities to Support Lidar Applications at the Landscape, Forest, and Tree Scale
Description: Implements algorithms for terrestrial, mobile, and airborne lidar processing, tree detection, segmentation, and attribute estimation (Donager et al., 2021) <doi:10.3390/rs13122297>, and a hierarchical patch delineation algorithm 'PatchMorph' (Girvetz & Greco, 2007) <doi:10.1007/s10980-007-9104-8>. Tree detection uses rasterized point cloud metrics (relative neighborhood density and verticality) combined with RANSAC cylinder fitting to locate tree boles and estimate diameter at breast height. Tree segmentation applies graph-theory approaches inspired by Tao et al. (2015) <doi:10.1016/j.isprsjprs.2015.08.007> with cylinder fitting methods from de Conto et al. (2017) <doi:10.1016/j.compag.2017.07.019>. PatchMorph delineates habitat patches across spatial scales using organism-specific thresholds. Built on 'lidR' (Roussel et al., 2020) <doi:10.1016/j.rse.2020.112061>.
Author: Andrew Sanchez Meador [aut, cre, ctb] , Jonathon Donager [aut, ctb] , Blackburn Ryan [aut, ctb] , Cannon Jeffery [ctb] , Tiago de Conto [ctb, cph] , Keith O'Hara [ctb, cph]
Maintainer: Andrew Sanchez Meador <Andrew.SanchezMeador@nau.edu>

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Package riskmetric updated to version 0.2.7 with previous version 0.2.6 dated 2026-01-13

Title: Risk Metrics to Evaluating R Packages
Description: Facilities for assessing R packages against a number of metrics to help quantify their robustness.
Author: R Validation Hub [aut], Doug Kelkhoff [aut], Marly Gotti [aut], Eli Miller [cre, aut], Kevin K [aut], Yilong Zhang [aut], Eric Milliman [aut], Juliane Manitz [aut], Mark Padgham [ctb], PSI special interest group Application and Implementation of Meth [...truncated...]
Maintainer: Eli Miller <eli.miller@atorusresearch.com>

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Package quickSentiment updated to version 0.3.3 with previous version 0.3.2 dated 2026-03-20

Title: A Fast and Flexible Pipeline for Text Classification
Description: A high-level pipeline that simplifies text classification into three streamlined steps: preprocessing, model training, and standardized prediction. It unifies the interface for multiple algorithms (including 'glmnet', 'ranger', 'xgboost', and 'naivebayes') and memory-efficient sparse matrix vectorization methods (Bag-of-Words, Term Frequency, TF-IDF, and Binary). Users can go from raw text to a fully evaluated sentiment model, complete with ROC-optimized thresholds, in just a few function calls. The resulting model artifact automatically aligns the vocabulary of new datasets during the prediction phase, safely appending predicted classes and probability matrices directly to the user's original dataframe to preserve metadata.
Author: Alabhya Dahal [aut, cre]
Maintainer: Alabhya Dahal <alabhya.dahal@gmail.com>

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Package pkgload updated to version 1.5.1 with previous version 1.5.0 dated 2026-02-03

Title: Simulate Package Installation and Attach
Description: Simulates the process of installing a package and then attaching it. This is a key part of the 'devtools' package as it allows you to rapidly iterate while developing a package.
Author: Hadley Wickham [aut], Winston Chang [aut], Jim Hester [aut], Lionel Henry [aut, cre], Posit Software, PBC [cph, fnd], R Core team [ctb]
Maintainer: Lionel Henry <lionel@posit.co>

Diff between pkgload versions 1.5.0 dated 2026-02-03 and 1.5.1 dated 2026-04-01

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Package nonnest2 updated to version 0.5-9 with previous version 0.5-8 dated 2024-08-28

Title: Tests of Non-Nested Models
Description: Testing non-nested models via theory supplied by Vuong (1989) <DOI:10.2307/1912557>. Includes tests of model distinguishability and of model fit that can be applied to both nested and non-nested models. Also includes functionality to obtain confidence intervals associated with AIC and BIC. This material is partially based on work supported by the National Science Foundation under Grant Number SES-1061334.
Author: Edgar Merkle [aut, cre], Dongjun You [aut], Lennart Schneider [ctb], Mauricio Garnier-Villarreal [ctb], Seongho Bae [ctb], Phil Chalmers [ctb]
Maintainer: Edgar Merkle <merklee@missouri.edu>

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Package nimble updated to version 1.4.2 with previous version 1.4.1 dated 2026-02-13

Title: MCMC, Particle Filtering, and Programmable Hierarchical Modeling
Description: A system for writing hierarchical statistical models largely compatible with 'BUGS' and 'JAGS', writing nimbleFunctions to operate models and do basic R-style math, and compiling both models and nimbleFunctions via custom-generated C++. 'NIMBLE' includes default methods for MCMC, Laplace Approximation, deterministic nested approximations, Monte Carlo Expectation Maximization, and some other tools. The nimbleFunction system makes it easy to do things like implement new MCMC samplers from R, customize the assignment of samplers to different parts of a model from R, and compile the new samplers automatically via C++ alongside the samplers 'NIMBLE' provides. 'NIMBLE' extends the 'BUGS'/'JAGS' language by making it extensible: New distributions and functions can be added, including as calls to external compiled code. Although most people think of MCMC as the main goal of the 'BUGS'/'JAGS' language for writing models, one can use 'NIMBLE' for writing arbitrary other kinds of model-generic al [...truncated...]
Author: Perry de Valpine [aut], Christopher Paciorek [aut, cre], Daniel Turek [aut], Nick Michaud [aut], Cliff Anderson-Bergman [aut], Fritz Obermeyer [aut], Claudia Wehrhahn Cortes [aut] , Abel Rodriguez [aut] , Duncan Temple Lang [aut] , Wei Zhang [aut] , [...truncated...]
Maintainer: Christopher Paciorek <paciorek@stat.berkeley.edu>

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Package maidr updated to version 0.3.0 with previous version 0.2.0 dated 2026-03-07

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, 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 ICC.Sample.Size updated to version 1.1 with previous version 1.0 dated 2015-09-03

Title: Calculation of Sample Size and Power for ICC
Description: Provides functions to calculate the requisite sample size for studies where ICC is the primary outcome. Can also be used for calculation of power. In both cases it allows the user to test the impact of changing input variables by calculating the outcome for several different values of input variables. Based off the work of Zou. Zou, G. Y. (2012). Sample size formulas for estimating intraclass correlation coefficients with precision and assurance. Statistics in medicine, 31(29), 3972-3981.
Author: Alasdair Rathbone [aut, cre], Saurabh Shaw [aut], Dinesh Kumbhare [aut]
Maintainer: Alasdair Rathbone <alasdair.rathbone@gmail.com>

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Package HonestDiD updated to version 0.2.7 with previous version 0.2.6 dated 2024-07-14

Title: Robust Inference in Difference-in-Differences and Event Study Designs
Description: Provides functions to conduct robust inference in difference-in-differences and event study designs by implementing the methods developed in Rambachan & Roth (2023) <doi:10.1093/restud/rdad018>, "A More Credible Approach to Parallel Trends" [Previously titled "An Honest Approach..."]. Inference is conducted under a weaker version of the parallel trends assumption. Uniformly valid confidence sets are constructed based upon conditional confidence sets, fixed-length confidence sets and hybridized confidence sets.
Author: Ashesh Rambachan [aut, cph, cre], Jonathan Roth [aut, cph]
Maintainer: Ashesh Rambachan <ashesh.a.rambachan@gmail.com>

Diff between HonestDiD versions 0.2.6 dated 2024-07-14 and 0.2.7 dated 2026-04-01

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Package futurize updated to version 0.3.0 with previous version 0.2.0 dated 2026-03-18

Title: Parallelize Common Functions via One Magic Function
Description: The futurize() function transpiles calls to sequential map-reduce functions such as base::lapply(), purrr::map(), 'foreach::foreach() %do% { ... }' into concurrent alternatives, providing you with a simple, straightforward path to scalable parallel computing via the 'future' ecosystem <doi:10.32614/RJ-2021-048>. By combining this function with R's native pipe operator, you have a convenient way for speeding up iterative computations with minimal refactoring, e.g. 'lapply(xs, fcn) |> futurize()', 'purrr::map(xs, fcn) |> futurize()', and 'foreach::foreach(x = xs) %do% { fcn(x) } |> futurize()'. Other map-reduce packages that can be "futurized" are 'BiocParallel', 'plyr', 'crossmap', 'pbapply' packages. There is also support for a growing set of domain-specific packages on CRAN (e.g. 'boot', 'caret', 'fgsea', 'fwb', 'gamlss', 'glmmTMB', 'glmnet', 'kernelshap', 'lme4', 'metafor', 'mgcv', 'partykit', 'riskRegression', 'seriation', 'shapr', 'SimDesign', 'strucchange', 'tm', 'T [...truncated...]
Author: Henrik Bengtsson [aut, cre, cph]
Maintainer: Henrik Bengtsson <henrikb@braju.com>

Diff between futurize versions 0.2.0 dated 2026-03-18 and 0.3.0 dated 2026-04-01

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 futurize-0.3.0/futurize/DESCRIPTION                                                  |    9 
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 futurize-0.3.0/futurize/NAMESPACE                                                    |    1 
 futurize-0.3.0/futurize/NEWS.md                                                      |   20 
 futurize-0.3.0/futurize/R/000.bquote.R                                               |    2 
 futurize-0.3.0/futurize/R/addons-BiocParallel.R                                      |   11 
 futurize-0.3.0/futurize/R/addons-DESeq2.R                                            |    6 
 futurize-0.3.0/futurize/R/addons-GSVA.R                                              |    5 
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 futurize-0.3.0/futurize/R/addons-Rsamtools.R                                         |    5 
 futurize-0.3.0/futurize/R/addons-SimDesign.R                                         |   12 
 futurize-0.3.0/futurize/R/addons-SingleCellExperiment.R                              |    5 
 futurize-0.3.0/futurize/R/addons-TSP.R                                               |    6 
 futurize-0.3.0/futurize/R/addons-boot.R                                              |   12 
 futurize-0.3.0/futurize/R/addons-caret.R                                             |   15 
 futurize-0.3.0/futurize/R/addons-fgsea.R                                             |    5 
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 futurize-0.3.0/futurize/R/addons-gamlss.R                                            |   21 
 futurize-0.3.0/futurize/R/addons-glmmTMB.R                                           |   14 
 futurize-0.3.0/futurize/R/addons-glmnet.R                                            |    5 
 futurize-0.3.0/futurize/R/addons-kernelshap.R                                        |    6 
 futurize-0.3.0/futurize/R/addons-lme4.R                                              |    5 
 futurize-0.3.0/futurize/R/addons-metafor.R                                           |   15 
 futurize-0.3.0/futurize/R/addons-mgcv.R                                              |   11 
 futurize-0.3.0/futurize/R/addons-partykit.R                                          |    3 
 futurize-0.3.0/futurize/R/addons-pbapply.R                                           |   11 
 futurize-0.3.0/futurize/R/addons-plyr.R                                              |    8 
 futurize-0.3.0/futurize/R/addons-riskRegression.R                                    |   10 
 futurize-0.3.0/futurize/R/addons-scater.R                                            |    5 
 futurize-0.3.0/futurize/R/addons-scuttle.R                                           |    5 
 futurize-0.3.0/futurize/R/addons-seriation.R                                         |    6 
 futurize-0.3.0/futurize/R/addons-shapr.R                                             |   10 
 futurize-0.3.0/futurize/R/addons-strucchange.R                                       |    5 
 futurize-0.3.0/futurize/R/addons-sva.R                                               |    5 
 futurize-0.3.0/futurize/R/addons-tm.R                                                |   11 
 futurize-0.3.0/futurize/R/addons-vegan.R                                             |    2 
 futurize-0.3.0/futurize/R/make_addon_transpilers.R                                   |   11 
 futurize-0.3.0/futurize/R/make_options_for_furrr.R                                   |   16 
 futurize-0.3.0/futurize/R/make_options_for_future.apply.R                            |    5 
 futurize-0.3.0/futurize/R/transpile.R                                                |   17 
 futurize-0.3.0/futurize/R/transpiler-unwrap.R                                        |    3 
 futurize-0.3.0/futurize/README.md                                                    |    2 
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 futurize-0.3.0/futurize/inst/testme/run.R                                            |   15 
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 futurize-0.3.0/futurize/inst/testme/test-furrr-future_imap.R                         |    6 
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 futurize-0.3.0/futurize/man/transpile.Rd                                             |    4 
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More information about futurize at CRAN
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Package bfast updated to version 1.7.2 with previous version 1.7.1 dated 2025-08-18

Title: Breaks for Additive Season and Trend
Description: Decomposition of time series into trend, seasonal, and remainder components with methods for detecting and characterizing abrupt changes within the trend and seasonal components. 'BFAST' can be used to analyze different types of satellite image time series and can be applied to other disciplines dealing with seasonal or non-seasonal time series, such as hydrology, climatology, and econometrics. The algorithm can be extended to label detected changes with information on the parameters of the fitted piecewise linear models. 'BFAST' monitoring functionality is described in Verbesselt et al. (2010) <doi:10.1016/j.rse.2009.08.014>. 'BFAST monitor' provides functionality to detect disturbance in near real-time based on 'BFAST'- type models, and is described in Verbesselt et al. (2012) <doi:10.1016/j.rse.2012.02.022>. 'BFAST Lite' approach is a flexible approach that handles missing data without interpolation, and will be described in an upcoming paper. Furthermore, different mode [...truncated...]
Author: Jan Verbesselt [aut], Dainius Masiliūnas [aut, cre] , Achim Zeileis [aut], Rob Hyndman [ctb], Marius Appel [aut], Martin Jung [ctb], Andrei Mîrț [ctb] , Paulo Negri Bernardino [ctb], Dongdong Kong [ctb]
Maintainer: Dainius Masiliūnas <pastas4@gmail.com>

Diff between bfast versions 1.7.1 dated 2025-08-18 and 1.7.2 dated 2026-04-01

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More information about bfast at CRAN
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