Fri, 13 Mar 2026

Package xtdml updated to version 0.1.12 with previous version 0.1.11 dated 2025-12-11

Title: Double Machine Learning for Static Panel Models with Fixed Effects
Description: The 'xtdml' package implements partially linear panel regression (PLPR) models with high-dimensional confounding variables and an exogenous treatment variable within the double machine learning framework. The package is used to estimate the structural parameter (treatment effect) in static panel data models with fixed effects using the approaches established in Clarke and Polselli (2025) <doi:10.1093/ectj/utaf011>. 'xtdml' is built on the object-oriented package 'DoubleML' (Bach et al., 2024) <doi:10.18637/jss.v108.i03> using the 'mlr3' ecosystem.
Author: Annalivia Polselli [aut, cre]
Maintainer: Annalivia Polselli <apolselli.econ@gmail.com>

Diff between xtdml versions 0.1.11 dated 2025-12-11 and 0.1.12 dated 2026-03-13

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Package SlimR updated to version 1.1.2 with previous version 1.1.1 dated 2026-02-05

Title: Adaptive Machine Learning-Powered, Context-Matching Tool for Single-Cell and Spatial Transcriptomics Annotation
Description: Annotates single-cell and spatial-transcriptomic (ST) data using context-matching marker datasets. It creates a unified marker list (`Markers_list`) from multiple sources: built-in curated databases ('Cellmarker2', 'PanglaoDB', 'ScType', 'scIBD', 'TCellSI', 'PCTIT', 'PCTAM'), Seurat objects with cell labels, or user-provided Excel tables. SlimR first uses adaptive machine learning for parameter optimization, and then offers two automated annotation approaches: 'cluster-based' and 'per-cell'. Cluster-based annotation assigns one label per cluster, expression-based probability calculation, and AUC validation. Per-cell annotation assigns labels to individual cells using three scoring methods with adaptive thresholds and ratio-based confidence filtering, plus optional UMAP spatial smoothing, making it ideal for heterogeneous clusters and rare cell types. The package also supports semi-automated workflows with heatmaps, feature plots, and combined visualizations for manual annotation. For m [...truncated...]
Author: Zhaoqing Wang [aut, cre]
Maintainer: Zhaoqing Wang <zhaoqingwang@mail.sdu.edu.cn>

Diff between SlimR versions 1.1.1 dated 2026-02-05 and 1.1.2 dated 2026-03-13

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Package ResIN updated to version 2.3.1 with previous version 2.3.0 dated 2026-03-02

Title: Conduct Response Item Network (ResIN) Analysis with Social Response Data
Description: Contains various tools to estimate, analyze, and visualize Response Item Networks. 'ResIN' dummy-codes ordered and qualitative response choices from (survey) data, calculates pairwise associations and maps the location of each item response as a node in a force-directed network. Please refer to <https://www.resinmethod.net/> for more details.
Author: Philip Warncke [cre, aut], Dino Carpentras [aut], Adrian Lueders [aut]
Maintainer: Philip Warncke <philip.warncke@ul.ie>

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Package SAM updated to version 1.3 with previous version 1.2 dated 2026-02-19

Title: Sparse Additive Modelling
Description: Computationally efficient tools for high dimensional predictive modeling (regression and classification). SAM is short for sparse additive modeling, and adopts the computationally efficient basis spline technique. We solve the optimization problems by various computational algorithms including the block coordinate descent algorithm, fast iterative soft-thresholding algorithm, and newton method. The computation is further accelerated by warm-start and active-set tricks.
Author: Haoming Jiang [aut], Yukun Ma [aut], Han Liu [aut], Kathryn Roeder [aut], Xingguo Li [aut], Tuo Zhao [aut, cre]
Maintainer: Tuo Zhao <tourzhao@gatech.edu>

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Package cffr updated to version 1.3.0 with previous version 1.2.1 dated 2026-01-12

Title: Generate Citation File Format ('cff') Metadata for R Packages
Description: The Citation File Format version 1.2.0 <doi:10.5281/zenodo.5171937> is a human and machine readable file format which provides citation metadata for software. This package provides core utilities to generate and validate this metadata.
Author: Diego Hernangomez [aut, cre, cph] , Joao Martins [rev] , Scott Chamberlain [rev]
Maintainer: Diego Hernangomez <diego.hernangomezherrero@gmail.com>

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Package WaterBalanceR updated to version 0.1.21 with previous version 0.1.20 dated 2026-03-11

Title: Calculate High Resolution Water Balance of Starch Potatoes
Description: Calculates the water balance of starch potatoes from Normalized Distance Vegetation Index (NDVI) images, German Weather Service (DWD) reference evapotranspiration, German Weather Service RADOLAN precipitation data and irrigation information. For more details see Piernicke et al. (2025) <doi:10.3390/rs17183227>.
Author: Thomas Piernicke [aut, cre]
Maintainer: Thomas Piernicke <thomasp@gfz.de>

Diff between WaterBalanceR versions 0.1.20 dated 2026-03-11 and 0.1.21 dated 2026-03-13

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Package samc updated to version 4.2.1 with previous version 4.1.0 dated 2026-02-05

Title: Spatial Absorbing Markov Chains
Description: Implements functions for working with absorbing Markov chains. The implementation is based on the framework described in "Toward a unified framework for connectivity that disentangles movement and mortality in space and time" by Fletcher et al. (2019) <doi:10.1111/ele.13333>, which applies them to spatial ecology. This framework incorporates both resistance and absorption with spatial absorbing Markov chains (SAMC) to provide several short-term and long-term predictions for metrics related to connectivity in landscapes. Despite the ecological context of the framework, this package can be used in any application of absorbing Markov chains.
Author: Andrew Marx [aut, cre, cph] , Robert Fletcher [ctb] , Miguel Acevedo [ctb] , Jorge Sefair [ctb] , Chao Wang [ctb] , Hughes Josie [ctb] , Barrett Griffin [ctb]
Maintainer: Andrew Marx <ajm.rpackages@gmail.com>

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Package rsoi updated to version 0.5.8 with previous version 0.5.7 dated 2026-03-06

Title: Import Various Northern and Southern Hemisphere Climate Indices
Description: Downloads Southern Oscillation Index, Oceanic Nino Index, North Pacific Gyre Oscillation data, North Atlantic Oscillation and Arctic Oscillation. Data sources are described in the help files for each function.
Author: Sam Albers [aut, cre], Elio Campitelli [ctb]
Maintainer: Sam Albers <sam.albers@gmail.com>

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Package poLCAParallel readmission to version 1.2.7 with previous version 1.2.6 dated 2026-02-19

Title: Polytomous Variable Latent Class Analysis Parallel
Description: A 'C++' reimplementation of 'poLCA' - latent class analysis and latent class regression models for polytomous outcome variables, also known as latent structure analysis. It attempts to reproduce results and be as similar as possible to the original code, while running faster, especially with multiple repetitions, by utilising multiple threads. Further reading is available on the Queen Mary, University of London, IT Services Research blog <https://blog.hpc.qmul.ac.uk/speeding_up_r_packages/>.
Author: Sherman Lo [aut, cre], Drew Linzer [aut], Jeffrey Lewis. [aut]
Maintainer: Sherman Lo <s.lo@qmul.ac.uk>

This is a re-admission after prior archival of version 1.2.6 dated 2026-02-19

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Package nda updated to version 0.2.5 with previous version 0.2.4 dated 2025-02-16

Title: Generalized Network-Based Dimensionality Reduction and Analysis
Description: Non-parametric dimensionality reduction function. Reduction with and without feature selection. Plot functions. Automated feature selections. Kosztyan et. al. (2024) <doi:10.1016/j.eswa.2023.121779>.
Author: Zsolt T. Kosztyan [aut, cre], Marcell T. Kurbucz [aut], Attila I. Katona [aut], Zahid Khan [aut]
Maintainer: Zsolt T. Kosztyan <kosztyan.zsolt@gtk.uni-pannon.hu>

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Package LOST updated to version 2.1.3 with previous version 2.1.2 dated 2025-01-27

Title: Missing Morphometric Data Simulation and Estimation
Description: Functions for simulating missing morphometric data randomly, with taxonomic bias and with anatomical bias. LOST also includes functions for estimating linear and geometric morphometric data.
Author: J. Arbour [aut, cre], C. Brown [aut]
Maintainer: J. Arbour <jessica.arbour@mtsu.edu>

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Package ipumsr updated to version 0.10.0 with previous version 0.9.0 dated 2025-06-04

Title: An R Interface for Downloading, Reading, and Handling IPUMS Data
Description: An easy way to work with census, survey, and geographic data provided by IPUMS in R. Generate and download data through the IPUMS API and load IPUMS files into R with their associated metadata to make analysis easier. IPUMS data describing 1.4 billion individuals drawn from over 750 censuses and surveys is available free of charge from the IPUMS website <https://www.ipums.org>.
Author: Greg Freedman Ellis [aut], Derek Burk [aut, cre], Finn Roberts [aut], Joe Grover [ctb], Dan Ehrlich [ctb], Renae Rodgers [ctb], Institute for Social Research and Data Innovation [cph]
Maintainer: Derek Burk <ipums+cran@umn.edu>

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Package haplo.stats updated to version 1.9.8.3 with previous version 1.9.8.2 dated 2026-02-13

Title: Statistical Analysis of Haplotypes with Traits and Covariates when Linkage Phase is Ambiguous
Description: Routines for the analysis of indirectly measured haplotypes. The statistical methods assume that all subjects are unrelated and that haplotypes are ambiguous (due to unknown linkage phase of the genetic markers). The main functions are: haplo.em(), haplo.glm(), haplo.score(), and haplo.power(); all of which have detailed examples in the vignette.
Author: Schaid Daniel [aut], Jason P. Sinnwell [aut, cre]
Maintainer: Jason P. Sinnwell <sinnwell.jason@mayo.edu>

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Package globals updated to version 0.19.1 with previous version 0.19.0 dated 2026-02-02

Title: Identify Global Objects in R Expressions
Description: Identifies global ("unknown" or "free") objects in R expressions by code inspection using various strategies (ordered, liberal, conservative, or deep-first search). The objective of this package is to make it as simple as possible to identify global objects for the purpose of exporting them in parallel, distributed compute environments.
Author: Henrik Bengtsson [aut, cre, cph], Davis Vaughan [ctb]
Maintainer: Henrik Bengtsson <henrikb@braju.com>

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Package fastqq updated to version 0.1.4 with previous version 0.1.3 dated 2022-10-25

Title: Faster Generation of Quantile Quantile Plots with Large Samples
Description: New and faster implementations for quantile quantile plots. The package also includes a function to prune data for quantile quantile plots. This can drastically reduce the running time for large samples, for 100 million samples, you can expect a factor 80X speedup.
Author: Gudmundur Einarsson [aut, cre], Hafsteinn Einarsson [aut]
Maintainer: Gudmundur Einarsson <gudmundur.einarsson.phd@gmail.com>

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Package apollo updated to version 0.3.7 with previous version 0.3.6 dated 2025-09-19

Title: Tools for Choice Model Estimation and Application
Description: Choice models are a widely used technique across numerous scientific disciplines. The Apollo package is a very flexible tool for the estimation and application of choice models in R. Users are able to write their own model functions or use a mix of already available ones. Random heterogeneity, both continuous and discrete and at the level of individuals and choices, can be incorporated for all models. There is support for both standalone models and hybrid model structures. Both classical and Bayesian estimation is available, and multiple discrete continuous models are covered in addition to discrete choice. Multi-threading processing is supported for estimation and a large number of pre and post-estimation routines, including for computing posterior (individual-level) distributions are available. For examples, a manual, and a support forum, visit <https://www.ApolloChoiceModelling.com>. For more information on choice models see Train, K. (2009) <isbn:978-0-521-74738-7> and [...truncated...]
Author: Stephane Hess [aut, cre], David Palma [aut], Thomas Hancock [ctb]
Maintainer: Stephane Hess <S.Hess@leeds.ac.uk>

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Package N2R (with last version 1.0.4) was removed from CRAN

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

2026-03-06 1.0.4
2024-02-26 1.0.2
2024-02-26 1.0.3
2022-01-18 1.0.1
2021-11-19 1.0.0
2020-12-14 0.1.1
2020-09-29 0.1.0

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Package conos (with last version 1.5.2) was removed from CRAN

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

2024-02-26 1.5.2
2024-01-23 1.5.1
2022-10-17 1.5.0
2022-09-30 1.4.9
2022-09-26 1.4.8
2022-09-04 1.4.7
2022-04-11 1.4.6
2022-01-21 1.4.5
2021-11-08 1.4.4
2021-08-07 1.4.3
2021-06-29 1.4.2
2021-05-15 1.4.1
2021-02-23 1.4.0

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Package pagoda2 (with last version 1.0.14) was removed from CRAN

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

2026-03-08 1.0.14
2025-08-18 1.0.13
2024-02-26 1.0.12
2023-08-08 1.0.11
2022-04-19 1.0.10
2022-03-02 1.0.9
2021-12-12 1.0.8
2021-11-15 1.0.7
2021-10-06 1.0.6
2021-08-11 1.0.5
2021-06-29 1.0.4
2021-05-03 1.0.3
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2021-02-23 1.0.1
2021-01-28 1.0.0

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Package orbital updated to version 0.5.1 with previous version 0.5.0 dated 2026-02-27

Title: Predict with 'tidymodels' Workflows in Databases
Description: Turn 'tidymodels' workflows into objects containing the sufficient sequential equations to perform predictions. These smaller objects allow for low dependency prediction locally or directly in databases.
Author: Emil Hvitfeldt [aut, cre], Posit Software, PBC [cph, fnd]
Maintainer: Emil Hvitfeldt <emil.hvitfeldt@posit.co>

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Package multilevel updated to version 2.8 with previous version 2.7.1 dated 2025-09-08

Title: Multilevel Functions
Description: Tools used by organizational researchers for the analysis of multilevel data. Includes four broad sets of tools. First, functions for estimating within-group agreement and reliability indices. Second, functions for manipulating multilevel and longitudinal (panel) data. Third, simulations for estimating power and generating multilevel data. Fourth, miscellaneous functions for estimating reliability and performing simple calculations and data transformations.
Author: Paul Bliese [aut, cre], Gilad Chen [ctb], Patrick Downes [ctb], Patrick Flynn [ctb], Jonas Lang [ctb], Donald Schepker [ctb]
Maintainer: Paul Bliese <pdbliese@gmail.com>

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Package igoR updated to version 1.0.1 with previous version 1.0.0 dated 2026-01-17

Title: Intergovernmental Organizations Database
Description: Tools to extract information from the Intergovernmental Organizations ('IGO') Database (v3), provided by the Correlates of War Project <https://correlatesofwar.org/>. See also Pevehouse, J. C. et al. (2020) <doi:10.1177/0022343319881175>.
Author: Diego Hernangomez [aut, cre, cph] , The Correlates of War Project [cph]
Maintainer: Diego Hernangomez <diego.hernangomezherrero@gmail.com>

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Package gctsc updated to version 0.2.0 with previous version 0.1.3 dated 2025-12-17

Title: Gaussian and Student-t Copula Models for Count Time Series
Description: Provides likelihood-based inference for Gaussian and Student-t copula models for univariate count time series. Supports Poisson, negative binomial, binomial, beta-binomial, and zero-inflated marginals with ARMA dependence structures. Includes simulation, maximum-likelihood estimation, residual diagnostics, and predictive inference. Implements Time Series Minimax Exponential Tilting (TMET) <doi:10.1016/j.csda.2026.108344>, an adaptation of minimax exponential tilting of Botev (2017) <doi:10.1111/rssb.12162>. Also provides a linear-cost implementation of the Geweke–Hajivassiliou–Keane (GHK) simulator following Masarotto and Varin (2012) <doi:10.1214/12-EJS721>, and the Continuous Extension (CE) approximation of Nguyen and De Oliveira (2025) <doi:10.1080/02664763.2025.2498502>. The package follows the S3 design philosophy of 'gcmr' but is developed independently.
Author: Quynh Nguyen [aut, cre], Victor De Oliveira [aut]
Maintainer: Quynh Nguyen <nqnhu2209@gmail.com>

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More information about gctsc at CRAN
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Package DebiasInfer updated to version 0.2.1 with previous version 0.2 dated 2023-10-09

Title: Efficient Inference on High-Dimensional Linear Model with Missing Outcomes
Description: A statistically and computationally efficient debiasing method for conducting valid inference on the high-dimensional linear regression function with missing outcomes. The reference paper is Zhang, Giessing, and Chen (2023) <doi:10.48550/arXiv.2309.06429>.
Author: Yikun Zhang [aut, cre] , Alexander Giessing [aut] , Yen-Chi Chen [aut]
Maintainer: Yikun Zhang <yikunzhang@foxmail.com>

Diff between DebiasInfer versions 0.2 dated 2023-10-09 and 0.2.1 dated 2026-03-13

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 7 files changed, 77 insertions(+), 45 deletions(-)

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