Tue, 08 Sep 2026

Package tidyllm updated to version 0.6.0 with previous version 0.5.2 dated 2026-07-30

Title: Tidy Integration of Large Language Models
Description: A tidy interface for integrating large language model (LLM) APIs such as 'Claude', 'OpenAI', 'Gemini', 'Mistral', and local models via 'Ollama' into R workflows. The package supports text, image, audio, video, and document interactions; a unified media interface for attaching inline files or uploading to provider file stores; batch request APIs for cost-efficient large-scale processing; and a pipeline-oriented interface for seamless integration into data workflows. Web services are available at <https://www.anthropic.com>, <https://openai.com>, <https://aistudio.google.com/>, <https://mistral.ai/> and <https://ollama.com>.
Author: Eduard Bruell [aut, cre], Jia Zhang [ctb]
Maintainer: Eduard Bruell <eduard.bruell@zew.de>

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Package TestDesign updated to version 1.7.1 with previous version 1.7.0 dated 2024-08-22

Title: Optimal Test Design Approach to Fixed and Adaptive Test Construction
Description: Uses the optimal test design approach by Birnbaum (1968, ISBN:9781593119348) and van der Linden (2018) <doi:10.1201/9781315117430> to construct fixed, adaptive, and parallel tests. Supports the following mixed-integer programming (MIP) solver packages: 'Rsymphony', 'highs', 'gurobi', 'lpSolve', and 'Rglpk'. The 'gurobi' package is not available from CRAN; see <https://www.gurobi.com/downloads/>.
Author: Seung W. Choi [aut, cre] , Sangdon Lim [aut]
Maintainer: Seung W. Choi <schoi@austin.utexas.edu>

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Package predictset updated to version 0.4.0 with previous version 0.3.0 dated 2026-03-19

Title: Conformal Prediction and Uncertainty Quantification
Description: Implements conformal prediction methods for constructing prediction intervals (regression) and prediction sets (classification) with finite-sample coverage guarantees. Methods include split conformal, 'CV+' and 'Jackknife+' (Barber et al. 2021) <doi:10.1214/20-AOS1965>, 'Conformalized Quantile Regression' (Romano et al. 2019) <doi:10.48550/arXiv.1905.03222>, 'Adaptive Prediction Sets' (Romano, Sesia, Candes 2020) <doi:10.48550/arXiv.2006.02544>, 'Regularized Adaptive Prediction Sets' (Angelopoulos et al. 2021) <doi:10.48550/arXiv.2009.14193>, Mondrian conformal prediction for group-conditional coverage (Vovk, Gammerman, and Shafer 2005) <doi:10.1007/b106715>, weighted conformal prediction for covariate shift (Tibshirani et al. 2019) <doi:10.48550/arXiv.1904.06019>, and adaptive conformal inference for sequential prediction (Gibbs and Candes 2021) <doi:10.48550/arXiv.2106.00170>. All methods are distribution-free and provide calibrated uncertain [...truncated...]
Author: Charles Coverdale [aut, cre, cph]
Maintainer: Charles Coverdale <charlesfcoverdale@gmail.com>

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Package magentabook updated to version 0.1.1 with previous version 0.1.0 dated 2026-04-29

Title: HM Treasury Magenta Book Policy Evaluation Primitives
Description: Implements policy evaluation primitives from HM Treasury Magenta Book guidance (HM Treasury, 2026): theory of change and log-frame construction, evaluation planning and stakeholder mapping, power and minimum-detectable-effect calculations for randomised designs (including cluster and stepped-wedge designs following Hussey and Hughes (2007) <doi:10.1016/j.cct.2006.05.007> and Hemming et al. (2015) <doi:10.1136/bmj.h391>), Maryland Scientific Methods Scale ratings, structured confidence ratings, light-weight difference-in-differences and interrupted-time-series estimators (Bernal et al. (2017) <doi:10.1093/ije/dyw098>) with cluster-robust standard errors (Cameron and Miller (2015) <doi:10.3368/jhr.50.2.317>), pre-treatment balance checks (Stuart (2010) <doi:10.1214/09-STS313>), and cost-effectiveness analysis (cost per outcome, incremental cost-effectiveness ratio, acceptability curves, incremental net benefit, quality-adjusted and disability-adjusted life y [...truncated...]
Author: Charles Coverdale [aut, cre]
Maintainer: Charles Coverdale <charlesfcoverdale@gmail.com>

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Package inequality updated to version 0.2.0 with previous version 0.1.0 dated 2026-04-20

Title: Inequality Measurement, Decomposition, and Poverty Analysis
Description: Tools for measuring income and wealth inequality. Computes the Gini coefficient with bootstrap or asymptotic confidence intervals following Davidson (2009) <doi:10.1016/j.jeconom.2008.11.004>, the extended S-Gini family, Theil T and L indices (generalised entropy family), the Atkinson index, the Kolm absolute inequality index, Palma ratio, Hoover index, percentile ratios, and Lorenz curves. Supports between-within group decomposition following Bourguignon (1979) <doi:10.2307/1914138>, income share tabulation, concentration indices for health inequality with Erreygers (2009) correction, Kakwani tax progressivity and Reynolds-Smolensky redistribution indices, Foster-Greer-Thorbecke poverty measures including the Sen index, growth incidence curves following Ravallion and Chen (2003) <doi:10.1016/S0165-1765(02)00205-7>, and Wolfson polarisation. All functions accept optional survey weights and work with data from any source.
Author: Charles Coverdale [aut, cre]
Maintainer: Charles Coverdale <charlesfcoverdale@gmail.com>

Diff between inequality versions 0.1.0 dated 2026-04-20 and 0.2.0 dated 2026-09-08

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Package debtkit updated to version 0.1.3 with previous version 0.1.2 dated 2026-03-31

Title: Debt Sustainability Analysis and Fiscal Risk Assessment
Description: Analyses government debt sustainability using the standard debt dynamics framework from Blanchard (1990) <doi:10.1787/budget-v2-art12-en> and the IMF Debt Sustainability Analysis methodology (IMF, 2013) and the Sovereign Risk and Debt Sustainability Framework (IMF, 2022). Projects debt-to-GDP paths, decomposes historical debt changes into interest, growth, and primary balance contributions, and estimates fiscal reaction functions following Bohn (1998) <doi:10.1162/003355398555793>. Produces stochastic fan charts via Monte Carlo simulation, standardised stress tests, and IMF- style heat map risk assessments. Computes S1/S2 sustainability gap indicators used by the European Commission. All methods are pure computation with no external dependencies beyond base R; works with fiscal data from any source.
Author: Charles Coverdale [aut, cre]
Maintainer: Charles Coverdale <charlesfcoverdale@gmail.com>

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Package tidySEM updated to version 0.2.12 with previous version 0.2.11 dated 2026-08-20

Title: Tidy Structural Equation Modeling
Description: A tidy workflow for generating, estimating, reporting, and plotting structural equation models using 'lavaan', 'OpenMx', or 'Mplus'. Throughout this workflow, elements of syntax, results, and graphs are represented as 'tidy' data, making them easy to customize. Includes functionality to estimate latent class analyses, and to plot 'dagitty' and 'igraph' objects.
Author: Caspar J. van Lissa [aut, cre] , Mauricio Garnier-Villarreal [ctb] , Frank C Gootjes [ctb]
Maintainer: Caspar J. van Lissa <c.j.vanlissa@tilburguniversity.edu>

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Package groupTesting readmission to version 1.3.1 with previous version 1.3.0 dated 2024-08-17

Title: Simulating and Modeling Group (Pooled) Testing Data
Description: Provides an expectation-maximization (EM) algorithm using the approach introduced in Warasi (2023) <doi:10.1080/03610918.2021.2009867>. The EM algorithm can be used to estimate the prevalence (overall proportion) of a disease and to estimate a binary regression model from among the class of generalized linear models based on group testing data. The estimation framework we consider offers a flexible and general approach; i.e., its application is not limited to any specific group testing protocol. Consequently, the EM algorithm can model data arising from simple pooling as well as advanced pooling such as hierarchical testing, array testing, and quality control pooling. Also, provided are functions that can be used to conduct the Wald tests described in Buse (1982) <doi:10.1080/00031305.1982.10482817> and to simulate the group testing data described in Kim et al. (2007) <doi:10.1111/j.1541-0420.2007.00817.x>. We offer a function to compute relative efficiency measures, [...truncated...]
Author: Md S. Warasi [aut, cre]
Maintainer: Md S. Warasi <msarker@radford.edu>

This is a re-admission after prior archival of version 1.3.0 dated 2024-08-17

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Package fable.intermittent updated to version 0.3.0 with previous version 0.2.0 dated 2026-07-27

Title: Forecasting Models for Intermittent Time Series
Description: Extends the 'fable' framework to support forecasting methods specifically designed for intermittent time series data, where demand occurs sporadically with many zero values. All methods produce probabilistic forecasts returned as 'distributional' objects. The returned forecasts can be used to evaluate accuracy, plot and print the results seamlessly with 'fable'. The methods include: Harvey, Fernandes (1989) <doi:10.1080/07350015.1989.10509750>, Willemain, Smart, Schwarz (2004) <doi:10.1016/S0169-2070(03)00013-X>, Zhou, Viswanathan (2011) <doi:10.1016/j.ijpe.2010.09.021>, Snyder, Ord, Beaumont (2012) <doi:10.1016/j.ijforecast.2011.03.009>, Kolassa (2016) <doi:10.1016/j.ijforecast.2015.12.004>, Hasni, Aguir, Babai, Jemai (2019) <doi:10.1080/00207543.2018.1424375>, Damato, Azzimonti, Corani (2025) <doi:10.1016/j.ijforecast.2025.10.001>, Sbrana (2025) <doi:10.1080/01605682.2025.2569661>, Sbrana, Babai (2026) <doi:10.1016/j.ejor.2026.06.009 [...truncated...]
Author: Stefano Damato [aut, cre, cph] , Lorenzo Zambon [aut] , Dario Azzimonti [aut]
Maintainer: Stefano Damato <stefanodamato128@gmail.com>

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Package carat readmission to version 2.3.0 with previous version 2.2.1 dated 2023-09-05

Title: Covariate-Adaptive Randomization for Clinical Trials
Description: Provides functions and command-line user interface to generate allocation sequence by covariate-adaptive randomization for clinical trials. The package currently supports six covariate-adaptive randomization procedures. Three hypothesis testing methods that are valid and robust under covariate-adaptive randomization are also available in the package to facilitate the inference for treatment effect under the included randomization procedures. Additionally, the package provides comprehensive and efficient tools to allow one to evaluate and compare the performance of randomization procedures and tests based on various criteria. See Ma W, Ye X, Tu F, and Hu F (2023) <doi: 10.18637/jss.v107.i02> for details.
Author: Fuyi Tu [aut, cre], Xiaoqing Ye [aut], Wei Ma [aut, ths], Feifang Hu [aut, ths]
Maintainer: Fuyi Tu <tufy@cqupt.edu.cn>

This is a re-admission after prior archival of version 2.2.1 dated 2023-09-05

Diff between carat versions 2.2.1 dated 2023-09-05 and 2.3.0 dated 2026-09-08

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Package Sequential updated to version 4.6.2 with previous version 4.6.1 dated 2026-07-05

Title: Exact Sequential Analysis for Poisson and Binomial Data
Description: Functions to calculate exact critical values, statistical power, expected time to signal, and required sample sizes for performing exact sequential analysis. All these calculations can be done for either Poisson or binomial data, for continuous or group sequential analyses, and for different types of rejection boundaries. In case of group sequential analyses, the group sizes do not have to be specified in advance and the alpha spending can be arbitrarily settled. For regression versions of the methods, Monte Carlo and asymptotic methods are used.
Author: Ivair Ramos Silva [aut, cre], Martin Kulldorff [aut]
Maintainer: Ivair Ramos Silva <ivair@ufop.edu.br>

Diff between Sequential versions 4.6.1 dated 2026-07-05 and 4.6.2 dated 2026-09-08

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Package sense updated to version 1.2.0 with previous version 1.1.0 dated 2024-06-19

Title: Automatic Stacked Ensemble for Regression Tasks
Description: Stacked ensembles for regression tasks using the 'mlr3' framework, internal preprocessing and out-of-fold stacking, and hyperparameter tuning using grid or random search. Supports numeric and categorical predictors.
Author: Giancarlo Vercellino [aut, cre]
Maintainer: Giancarlo Vercellino <giancarlo.vercellino@gmail.com>

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Package rintcal updated to version 1.4.2 with previous version 1.4.1 dated 2026-06-23

Title: Radiocarbon Calibration Curves
Description: The IntCal20 radiocarbon calibration curves (Reimer et al. 2020 <doi:10.1017/RDC.2020.68>) are provided as a data package, together with previous IntCal curves (IntCal13, IntCal09, IntCal04, IntCal98), other curves (e.g., NOTCal04 [van der Plicht et al. 2004], Arnold & Libby 1951, Stuiver & Suess 1966, Pearson & Stuiver 1986) and postbomb curves. Also provided are functions to copy the curves into memory, and to read, query and plot the data underlying the IntCal20 curves.
Author: Maarten Blaauw [aut, cre] , Christopher Bronk Ramsey [ctb]
Maintainer: Maarten Blaauw <maarten.blaauw@qub.ac.uk>

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Package RcppArmadillo updated to version 15.6.0-1 with previous version 15.4.2-1 dated 2026-07-25

Title: 'Rcpp' Integration for the 'Armadillo' Templated Linear Algebra Library
Description: 'Armadillo' is a templated C++ linear algebra library aiming towards a good balance between speed and ease of use. It provides high-level syntax and functionality deliberately similar to Matlab. It is useful for algorithm development directly in C++, or quick conversion of research code into production environments. It provides efficient classes for vectors, matrices and cubes where dense and sparse matrices are supported. Integer, floating point and complex numbers are supported. A sophisticated expression evaluator (based on template meta-programming) automatically combines several operations to increase speed and efficiency. Dynamic evaluation automatically chooses optimal code paths based on detected matrix structures. Matrix decompositions are provided through integration with LAPACK, or one of its high performance drop-in replacements (such as 'MKL' or 'OpenBLAS'). It can automatically use 'OpenMP' multi-threading (parallelisation) to speed up computationally expensive operations [...truncated...]
Author: Dirk Eddelbuettel [aut, cre] , Romain Francois [aut] , Doug Bates [aut] , Binxiang Ni [aut], Conrad Sanderson [aut]
Maintainer: Dirk Eddelbuettel <edd@debian.org>

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Package omopgenerics updated to version 1.4.2 with previous version 1.4.1 dated 2026-07-23

Title: Methods and Classes for the OMOP Common Data Model
Description: Provides definitions of core classes and methods used by analytic pipelines that query the OMOP (Observational Medical Outcomes Partnership) common data model.
Author: Marti Catala [aut, cre] , Edward Burn [aut] , Mike Du [ctb] , Yuchen Guo [ctb] , Adam Black [ctb] , Marta Alcalde-Herraiz [ctb]
Maintainer: Marti Catala <marti.catalasabate@ndorms.ox.ac.uk>

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Package kfda updated to version 1.0.1 with previous version 1.0.0 dated 2017-09-27

Title: Kernel Fisher Discriminant Analysis
Description: Kernel Fisher Discriminant Analysis (KFDA) is performed using Kernel Principal Component Analysis (KPCA) and Fisher Discriminant Analysis (FDA). There are some similar packages. First, 'lfda' is a package that performs Local Fisher Discriminant Analysis (LFDA) and performs other functions. In particular, 'lfda' seems to be impossible to test because it needs the label information of the data in the function argument. Also, the 'ks' package has a limited dimension, which makes it difficult to analyze properly. This package is a simple and practical package for KFDA based on the paper of Yang, J., Jin, Z., Yang, J. Y., Zhang, D., and Frangi, A. F. (2004) <DOI:10.1016/j.patcog.2003.10.015>.
Author: Donghwan Kim [aut, cre]
Maintainer: Donghwan Kim <donhkim9714@korea.ac.kr>

Diff between kfda versions 1.0.0 dated 2017-09-27 and 1.0.1 dated 2026-09-08

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Package FactoMineR updated to version 2.17 with previous version 2.16 dated 2026-07-02

Title: Multivariate Exploratory Data Analysis and Data Mining
Description: Exploratory data analysis methods to summarize, visualize and describe datasets. The main principal component methods are available, those with the largest potential in terms of applications: principal component analysis (PCA) when variables are quantitative, correspondence analysis (CA) and multiple correspondence analysis (MCA) when variables are categorical, Multiple Factor Analysis when variables are structured in groups, etc. and hierarchical cluster analysis. F. Husson, S. Le and J. Pages (2017).
Author: Francois Husson [aut, cre] , Julie Josse [aut], Sebastien Le [aut], Jeremy Mazet [aut]
Maintainer: Francois Husson <francois.husson@institut-agro.fr>

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Package ECGofTestDx updated to version 0.6 with previous version 0.5 dated 2024-10-11

Title: A Goodness-of-Fit Test for Elliptical Distributions with Diagnostic Capabilities
Description: A goodness-of-fit test for elliptical distributions with diagnostic capabilities. Gilles R. Ducharme, Pierre Lafaye de Micheaux (2020) <doi:10.1016/j.jmva.2020.104602>.
Author: Gilles R Ducharme [aut], Pierre Lafaye De Micheaux [aut, cre]
Maintainer: Pierre Lafaye De Micheaux <lafaye@unsw.edu.au>

Diff between ECGofTestDx versions 0.5 dated 2024-10-11 and 0.6 dated 2026-09-08

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Package distributional updated to version 0.9.0 with previous version 0.8.1 dated 2026-06-27

Title: Vectorised Probability Distributions
Description: Vectorised distribution objects with tools for manipulating, visualising, and using probability distributions. Designed to allow model prediction outputs to return distributions rather than their parameters, allowing users to directly interact with predictive distributions in a data-oriented workflow. In addition to providing generic replacements for p/d/q/r functions, other useful statistics can be computed including means, variances, intervals, and highest density regions.
Author: Mitchell O'Hara-Wild [aut, cre] , Matthew Kay [aut] , Alex Hayes [aut] , Rob Hyndman [aut] , Earo Wang [ctb] , Vencislav Popov [ctb] , Stefano Damato [ctb]
Maintainer: Mitchell O'Hara-Wild <mail@mitchelloharawild.com>

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Package censored updated to version 0.3.5 with previous version 0.3.4 dated 2026-04-04

Title: 'parsnip' Engines for Survival Models
Description: Engines for survival models from the 'parsnip' package. These include parametric models (e.g., Jackson (2016) <doi:10.18637/jss.v070.i08>), semi-parametric (e.g., Simon et al (2011) <doi:10.18637/jss.v039.i05>), and tree-based models (e.g., Buehlmann and Hothorn (2007) <doi:10.1214/07-STS242>).
Author: Emil Hvitfeldt [aut] , Hannah Frick [aut, cre] , Posit Software, PBC [cph, fnd]
Maintainer: Hannah Frick <hannah@posit.co>

Diff between censored versions 0.3.4 dated 2026-04-04 and 0.3.5 dated 2026-09-08

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Package datom updated to version 0.1.2 with previous version 0.1.1 dated 2026-09-01

Title: A Unified Framework for Versioned, Traceable Tabular Data
Description: Provides versioned storage for tabular data without a database or a server. Each table is written as an immutable, content-addressed version -- identical content is detected and stored only once -- while its version history and metadata are kept as code in a 'git' repository and the data itself in a local filesystem or cloud object storage ('S3'). Any past version can be read back exactly by its identifier, and each table records the sources it was derived from, so a project carries full data lineage. A lightweight reader role retrieves current or historical data from storage alone, without 'git' or write access, giving downstream analyses and pipelines a single versioned source of truth. It targets analytical and scientific data management, such as preparing clinical study datasets, and is designed as a foundation for higher-level governance tooling.
Author: Afshin Mashadi-Hossein [aut, cre, cph]
Maintainer: Afshin Mashadi-Hossein <amashadihossein@gmail.com>

Diff between datom versions 0.1.1 dated 2026-09-01 and 0.1.2 dated 2026-09-08

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