Thu, 24 Sep 2026

Package ggExametrika updated to version 1.2.0 with previous version 1.1.2 dated 2026-08-21

Title: Visualization of 'exametrika' Output Using 'ggplot2'
Description: Provides 'ggplot2'-based visualization functions for output objects from the 'exametrika' package, which implements test data engineering methods described in Shojima (2022, ISBN:978-981-16-9547-1). Supports a wide range of psychometric models including Item Response Theory, Latent Class Analysis, Latent Rank Analysis, Biclustering (binary, ordinal, and nominal), Bayesian Network Models, and related network models. All plot functions return 'ggplot2' objects that can be further customized by the user.
Author: Koji Kosugi [aut, cre] , Daichi Kamimura [aut]
Maintainer: Koji Kosugi <kosugitti@gmail.com>

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Package fillpattern updated to version 1.0.4 with previous version 1.0.3 dated 2026-02-13

Title: Patterned Fills for 'ggplot2' and 'grid' Graphics
Description: Provides geometric patterns to replace solid color fills in statistical graphics. These patterns ensure figures remain distinguishable when viewed by colorblind readers or when printed in black and white. The included patterns can be customized in terms of scale, rotation, color, fill, line type, and line width. Compatible with the 'ggplot2' package as well as 'grid' graphics.
Author: Daniel P. Smith [aut, cre] , Alkek Center for Metagenomics and Microbiome Research [cph, fnd]
Maintainer: Daniel P. Smith <dansmith01@gmail.com>

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Package canpumf updated to version 0.6.0 with previous version 0.5.2 dated 2026-07-03

Title: Parse StatCan PUMF Files
Description: Facilitate working with Statistics Canada (StatCan) Public Use Microdata Files (PUMF). Enables downloading of available PUMF data, parsing of metadata from command files or other sources to infer the layout structure, variable labels and value labels as well as missing data values, and returns a connection to a 'DuckDB' database with the labelled data. Data and documentation come from Statistics Canada's Public Use Microdata Files <https://www.statcan.gc.ca/en/microdata/pumf>, distributed under the Statistics Canada Open Licence <https://www.statcan.gc.ca/en/terms-conditions/open-licence>.
Author: Jens von Bergmann [aut, cre]
Maintainer: Jens von Bergmann <jens@mountainmath.ca>

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Package BJM updated to version 0.2.0 with previous version 0.1.0 dated 2026-07-04

Title: Backward Joint Model for the Dynamic Prediction of Both Time-to-Event and Longitudinal Outcomes
Description: Provides tools to fit joint models of multivariate longitudinal data and time-to-event data for dynamic prediction. It allows the joint prediction of both future time-to-event outcomes and future longitudinal outcomes conditional on survival. The models accommodate irregularly measured longitudinal data and competing risks outcomes. The use of the backward joint model enables fast and efficient computation, especially for applications with large sample sizes and many longitudinal variables.
Author: Wenhao Li [aut, cre], Liang Li [aut]
Maintainer: Wenhao Li <wenhaoli.jlu@gmail.com>

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Package exametrika updated to version 2.1.0 with previous version 2.0.0 dated 2026-08-20

Title: Test Data Engineering
Description: Implements comprehensive test data engineering methods as described in Shojima (2022, ISBN:978-9811699856). Provides statistical techniques for engineering and processing test data: Classical Test Theory (CTT) with reliability coefficients for continuous ability assessment; Item Response Theory (IRT) including Rasch, 2PL, and 3PL models with item/test information functions; Latent Class Analysis (LCA) for nominal clustering; Latent Rank Analysis (LRA) for ordinal clustering with automatic determination of cluster numbers; Biclustering methods including infinite relational models for simultaneous clustering of examinees and items without predefined cluster numbers; and Bayesian Network Models (BNM) for visualizing inter-item dependencies. Features local dependence analysis through LRA and biclustering, parameter estimation, dimensionality assessment, and network structure visualization for educational, psychological, and social science research.
Author: Koji Kosugi [aut, cre]
Maintainer: Koji Kosugi <kosugitti@gmail.com>

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Package salso updated to version 0.3.79 with previous version 0.3.78 dated 2026-04-16

Title: Search Algorithms and Loss Functions for Bayesian Clustering
Description: The SALSO algorithm is an efficient randomized greedy search method to find a point estimate for a random partition based on a loss function and posterior Monte Carlo samples. The algorithm is implemented for many loss functions, including the Binder loss and a generalization of the variation of information loss, both of which allow for unequal weights on the two types of clustering mistakes. Efficient implementations are also provided for Monte Carlo estimation of the posterior expected loss of a given clustering estimate. See Dahl, Johnson, Müller (2022) <doi:10.1080/10618600.2022.2069779>.
Author: David B. Dahl [aut, cre] , Devin J. Johnson [aut] , Peter Mueller [aut], Andres Felipe Barrientos [aut], Garritt Page [aut], David Dunson [aut], Authors of the dependency Rust crates [ctb]
Maintainer: David B. Dahl <dahl@stat.byu.edu>

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Package fangs updated to version 0.2.25 with previous version 0.2.22 dated 2026-03-07

Title: Feature Allocation Neighborhood Greedy Search Algorithm
Description: A neighborhood-based, greedy search algorithm is performed to estimate a feature allocation by minimizing the expected loss based on posterior samples from the feature allocation distribution. The method is described in Dahl, Johnson, and Andros (2023) "Comparison and Bayesian Estimation of Feature Allocations" <doi:10.1080/10618600.2023.2204136>.
Author: David B. Dahl [aut, cre] , R. Jacob Andros [aut] , Devin J. Johnson [aut] , Authors of the dependency Rust crates [ctb]
Maintainer: David B. Dahl <dahl@stat.byu.edu>

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Package Umpire updated to version 2.0.12 with previous version 2.0.11 dated 2025-02-04

Title: Simulating Realistic Gene Expression and Clinical Data
Description: The Ultimate Microrray Prediction, Reality and Inference Engine (UMPIRE) is a package to facilitate the simulation of realistic microarray data sets with links to associated outcomes. See Zhang and Coombes (2012) <doi:10.1186/1471-2105-13-S13-S1>. Version 2.0 adds the ability to simulate realistic mixed-typed clinical data.
Author: Kevin R. Coombes [aut, cre], Jiexin Zhang [aut], Caitlin E. Coombes [aut]
Maintainer: Kevin R. Coombes <krc@silicovore.com>

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Package SIBERG updated to version 2.0.5 with previous version 2.0.4 dated 2025-04-08

Title: Systematic Identification of Bimodally Expressed Genes Using RNAseq Data
Description: Provides models to identify bimodally expressed genes from RNAseq data based on the Bimodality Index. SIBERG models the RNAseq data in the finite mixture modeling framework and incorporates mechanisms for dealing with RNAseq normalization. Three types of mixture models are implemented, namely, the mixture of log normal, negative binomial, or generalized Poisson distribution. See Tong et al. (2013) <doi:10.1093/bioinformatics/bts713>.
Author: Pan Tong [aut], Kevin R. Coombes [aut, cre]
Maintainer: Kevin R. Coombes <krc@silicovore.com>

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Package NewmanOmics updated to version 1.1.4 with previous version 1.1.3 dated 2026-07-06

Title: Extending the Newman Studentized Range Statistic to Transcriptomics
Description: Extends the classical Newman studentized range statistic in various ways that can be applied to genome-scale transcriptomic or other expression data.
Author: Zachary B. Abrams [aut], Greg Gershkowitz [aut], Anoushka Joglekar [aut], Chao Liu [aut], Kevin R. Coombes [aut, cre]
Maintainer: Kevin R. Coombes <krc@silicovore.com>

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Package NameNeedle updated to version 1.2.11 with previous version 1.2.10 dated 2026-03-14

Title: Using Needleman-Wunsch to Match Sample Names
Description: The Needleman-Wunsch global alignment algorithm can be used to find approximate matches between sample names in different data sets. See Wang et al. (2010) <doi:10.4137/CIN.S5613>.
Author: Kevin R. Coombes [aut, cre]
Maintainer: Kevin R. Coombes <krc@silicovore.com>

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Package integIRTy updated to version 1.0.9 with previous version 1.0.8 dated 2025-04-08

Title: Integrating Multiple Modalities of High Throughput Assays Using Item Response Theory
Description: Provides a systematic framework for integrating multiple modalities of assays profiled on the same set of samples. The goal is to identify genes that are altered in cancer either marginally or consistently across different assays. The heterogeneity among different platforms and different samples are automatically adjusted so that the overall alteration magnitude can be accurately inferred. See Tong and Coombes (2012) <doi:10.1093/bioinformatics/bts561>.
Author: Pan Tong [aut], Kevin R. Coombes [aut, cre]
Maintainer: Kevin R. Coombes <krc@silicovore.com>

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Package Modeler updated to version 3.4.11 with previous version 3.4.10 dated 2026-08-21

Title: Classes and Methods for Training and Using Binary Prediction Models
Description: Defines classes and methods to learn models and use them to predict binary outcomes. These are generic tools, but we also include specific examples for many common classifiers.
Author: Kevin R. Coombes [aut, cre]
Maintainer: Kevin R. Coombes <krc@silicovore.com>

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Package GenAlgo updated to version 2.2.2 with previous version 2.2.1 dated 2025-04-07

Title: Classes and Methods to Use Genetic Algorithms for Feature Selection
Description: Defines classes and methods that can be used to implement genetic algorithms for feature selection. The idea is that we want to select a fixed number of features to combine into a linear classifier that can predict a binary outcome, and can use a genetic algorithm heuristically to select an optimal set of features.
Author: Kevin R. Coombes [aut, cre]
Maintainer: Kevin R. Coombes <krc@silicovore.com>

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Package CrossValidate updated to version 2.3.6 with previous version 2.3.5 dated 2025-04-07

Title: Classes and Methods for Cross Validation of "Class Prediction" Algorithms
Description: Defines classes and methods to cross-validate various binary classification algorithms used for "class prediction" problems.
Author: Kevin R. Coombes [aut, cre]
Maintainer: Kevin R. Coombes <krc@silicovore.com>

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Package BimodalIndex updated to version 1.1.13 with previous version 1.1.11 dated 2025-04-07

Title: The Bimodality Index
Description: Defines the functions used to compute the bimodal index as defined by Wang et al. (2009) <https://pmc.ncbi.nlm.nih.gov/articles/PMC2730180/>, <doi:10.4137/CIN.S2846>.
Author: Kevin R. Coombes [aut, cre]
Maintainer: Kevin R. Coombes <krc@silicovore.com>

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Package angstromATE updated to version 0.2.3 with previous version 0.1.3 dated 2024-10-20

Title: Imports Recipe and Log Files from Angstrom Engineering Thermal Evaporator
Description: Imports and parses recipe and log files generated by Angstrom Engineering thermal evaporation systems. These files contain time-series measurements and process metadata, including chamber pressure, source activity, deposition rate, film thickness, tooling parameters, substrate conditions, and related deposition variables. The package provides functions to extract, organize, and summarize process information in a compact format suitable for data analysis, visualization, and quality control workflows.
Author: Thomas Gredig [aut, cre, cph]
Maintainer: Thomas Gredig <tgredig@csulb.edu>

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Package cpfa updated to version 1.3.3 with previous version 1.3.2 dated 2026-08-01

Title: Classification with Parallel Factor Analysis
Description: Classification using Richard A. Harshman's Parallel Factor Analysis-1 (Parafac) model or Parallel Factor Analysis-2 (Parafac2) model fit to a three-way or four-way data array. See Harshman and Lundy (1994): <doi:10.1016/0167-9473(94)90132-5>. Classification using principal component analysis (PCA) fit to a two-way data matrix is also supported. Uses component weights from one mode of a Parafac, Parafac2, or PCA model as features to tune parameters for one or more classification methods via a k-fold cross-validation procedure. Allows for constraints on different tensor modes. Allows for inclusion of additional features alongside features generated by the component model. Supports penalized logistic regression, support vector machine, random forest, feed-forward neural network, regularized discriminant analysis, and gradient boosting machine. Supports binary and multiclass classification. Predicts class labels or class probabilities and calculates multiple classification performanc [...truncated...]
Author: Matthew A. Asisgress [aut, cre]
Maintainer: Matthew A. Asisgress <mattgress@protonmail.ch>

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Package rdborrow updated to version 0.0.4.1 with previous version 0.0.4.0 dated 2026-08-31

Title: External Control Borrowing for Rare Disease Trials
Description: Implements causal inference methods for incorporating external control data into randomized controlled trials (RCTs) with longitudinal outcomes. Provides an analysis module supporting weighting-based methods such as inverse probability weighting (IPW) and augmented inverse probability weighting (AIPW), difference-in-differences (DID), and synthetic control approaches for borrowing external control information, as well as a simulation module for generating trial and external control data, evaluating estimator performance via Monte Carlo studies, and conducting power analyses for sample size determination. Methods are based on Zhou et al. (2024) <doi:10.1093/jrsssa/qnae075> and Zhou et al. (2024) <doi:10.1080/10543406.2024.2330209>.
Author: Lei Shi [aut], Matt Secrest [cre, aut] , Herbert Pang [aut], Chen Chen [aut], Jiawen Zhu [aut], Genentech, Inc. [cph]
Maintainer: Matt Secrest <secrmatt@gmail.com>

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Package oompaData updated to version 3.1.7 with previous version 3.1.5 dated 2025-04-06

Title: Data to Illustrate OOMPA Algorithms
Description: This is a data-only package to provide example data for other packages that are part of the "Object-Oriented Microrray and Proteomics Analysis" suite of packages. These are described in more detail at the package URL.
Author: Kevin R. Coombes [aut, cre]
Maintainer: Kevin R. Coombes <krc@silicovore.com>

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Package dynamicmultiplex updated to version 1.3.1 with previous version 1.1.0 dated 2026-08-07

Title: Community Detection for Evolving Multiplex Networks
Description: Multiplex temporal community detection with customizable interlayer coupling. Runs Louvain or Leiden community detection on each network layer and constructs interlayer ties using Jaccard similarity, overlap coefficient, node-strength weighted variants, or direct node identity links, and also provides a two-stage snapshot-and-match tracker that aligns independently detected per-layer communities across time with the Hungarian assignment algorithm. Supports user-specified layer connectivity via the layer_links argument, enabling adjacent-only temporal coupling that avoids the long-range pooling problem in standard multislice approaches.
Author: Jared Edgerton [aut, cre]
Maintainer: Jared Edgerton <jared.edgerton@gmail.com>

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Package freesurferformats updated to version 1.1.0 with previous version 1.0.2 dated 2026-09-08

Title: Read and Write 'FreeSurfer' Neuroimaging File Formats
Description: Provides functions to read and write neuroimaging data in various file formats, with a focus on 'FreeSurfer' formats. This includes, but is not limited to, the following file formats: 1) MGH/MGZ/NIFTI format files, which can contain multi-dimensional images or other data. Typically they contain time-series of three-dimensional brain scans acquired by magnetic resonance imaging (MRI). They can also contain vertex-wise measures of surface morphometry data. The MGH format is named after the Massachusetts General Hospital, and the MGZ format is a compressed version of the same format. 2) 'FreeSurfer' morphometry data files in binary 'curv' format. These contain vertex-wise surface measures, i.e., one scalar value for each vertex of a brain surface mesh. These are typically values like the cortical thickness or brain surface area at each vertex. 3) Annotation file format. This contains a brain surface parcellation derived from a cortical atlas. 4) Surface file format. Contains a brain surfa [...truncated...]
Author: Tim Schaefer [aut, cre] , Van Essen Lab [cph] .), Montreal Neurological Institute [cph] .)
Maintainer: Tim Schaefer <ts+code@rcmd.org>

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Package ClassDiscovery updated to version 3.4.11 with previous version 3.4.10 dated 2026-07-27

Title: Classes and Methods for "Class Discovery" with Microarrays or Proteomics
Description: Defines the classes used for "class discovery" problems in the OOMPA project (<http://silicovore.com/OOMPA/index.html>). Class discovery primarily consists of unsupervised clustering methods with attempts to assess their statistical significance.
Author: Kevin R. Coombes [aut, cre]
Maintainer: Kevin R. Coombes <krc@silicovore.com>

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Package ClassComparison updated to version 3.3.6 with previous version 3.3.5 dated 2025-02-05

Title: Classes and Methods for "Class Comparison" Problems on Microarrays
Description: Defines the classes used for "class comparison" problems in the OOMPA project (<http://silicovore.com/OOMPA/index.html>). Class comparison includes tests for differential expression; see Simon's book for details on typical problem types.
Author: Kevin R. Coombes [aut, cre]
Maintainer: Kevin R. Coombes <krc@silicovore.com>

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Package tinyshinyserver updated to version 0.2.1 with previous version 0.2.0 dated 2026-09-17

Title: Tiny 'shiny' Server - Lightweight Multi-App 'shiny' Proxy
Description: A lightweight, 'WebSocket'-enabled proxy server for hosting multiple 'shiny' applications with automatic health monitoring, session management, and resource cleanup. Provides a simple entry point to run the server using a JSON configuration file.
Author: Lars Bernhardsson [aut, cre]
Maintainer: Lars Bernhardsson <cran.sherry228@passinbox.com>

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Package Polychrome updated to version 1.6.2 with previous version 1.6.1 dated 2026-07-06

Title: Qualitative Palettes with Many Colors
Description: Tools for creating, viewing, and assessing qualitative palettes with many (20-30 or more) colors. See Coombes and colleagues (2019) <doi:10.18637/jss.v090.c01>.
Author: Guy Brock [aut], Kevin R. Coombes [aut, cre]
Maintainer: Kevin R. Coombes <krc@silicovore.com>

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Package plasma updated to version 1.1.6 with previous version 1.1.5 dated 2025-05-27

Title: Partial LeAst Squares for Multiomic Analysis
Description: Contains tools for supervised analyses of incomplete, overlapping multiomics datasets. Applies partial least squares in multiple steps to find models that predict survival outcomes. See Yamaguchi et al. (2023) <doi:10.1101/2023.03.10.532096>.
Author: Kevin R. Coombes [cre, aut], Kyoko Yamaguchi [aut], Salma Abdelbaky [aut]
Maintainer: Kevin R. Coombes <krc@silicovore.com>

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Package oompaBase updated to version 3.2.12 with previous version 3.2.11 dated 2026-01-11

Title: Class Unions, Matrix Operations, and Color Schemes for OOMPA
Description: Provides the class unions that must be preloaded in order for the basic tools in the OOMPA (Object-Oriented Microarray and Proteomics Analysis) project to be defined and loaded. It also includes vectorized operations for row-by-row means, variances, and t-tests. Finally, it provides new color schemes. Details on the packages in the OOMPA project can be found at <http://silicovore.com/OOMPA/index.html>.
Author: Kevin R. Coombes [aut, cre]
Maintainer: Kevin R. Coombes <krc@silicovore.com>

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Package mlr3resampling updated to version 2026.9.24 with previous version 2026.5.19 dated 2026-05-19

Title: Resampling Algorithms for 'mlr3' Framework
Description: A supervised learning algorithm inputs a train set, and outputs a prediction function, which can be used on a test set. If each data point belongs to a subset (such as geographic region, year, etc), then how do we know if subsets are similar enough so that we can get accurate predictions on one subset, after training on Other subsets? And how do we know if training on All subsets would improve prediction accuracy, relative to training on the Same subset? SOAK, Same/Other/All K-fold cross-validation, <doi:10.1002/sam.70055> can be used to answer these questions, by fixing a test subset, training models on Same/Other/All subsets, and then comparing test error rates (Same versus Other and Same versus All). Also provides code for estimating how many train samples are required to get accurate predictions on a test set.
Author: Toby Hocking [aut, cre] , Daniel Agyapong [ctb] , Michel Lang [ctb] , Bernd Bischl [ctb] , Jakob Richter [ctb] , Patrick Schratz [ctb] , Giuseppe Casalicchio [ctb] , Stefan Coors [ctb] , Quay Au [ctb] , Martin Binder [ctb], Florian Pfisterer [ctb] , [...truncated...]
Maintainer: Toby Hocking <toby.hocking@r-project.org>

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Package magp updated to version 0.12.0 with previous version 0.8.0 dated 2026-09-03

Title: Mapping-Based Additive Gaussian Process Models
Description: Fits mapping-based additive Gaussian process models for experiments in which each component has both a quantitative level and a position in an ordered sequence. Two model structures are available: a compact two-dimensional mapping and a full mapping with one fewer dimension than the number of components. Both models support parameter estimation, point prediction, and plug-in predictive uncertainty. Input checks validate the sequence data and apply consistent scaling to the quantitative inputs. Computationally intensive covariance and gradient calculations are implemented in C++ with 'Rcpp'. Initial-design functions combine a space-filling Latin hypercube with sequence permutations. The sequence portion can be generated randomly or optimized with simulated annealing or space-filling threshold accepting. Expected improvement can be optimized over both parts of the input, and a sequential interface supports Bayesian optimization of an expensive user-supplied objective. An integrated workf [...truncated...]
Author: Tony Wang [aut, cre, cph], Qian Xiao [aut, cph], Yaping Wang [cph], Abhyuday Mandal [cph], Xinwei Deng [cph]
Maintainer: Tony Wang <wangtony883@gmail.com>

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Package dsROCrate updated to version 0.2.3 with previous version 0.2.2 dated 2026-08-21

Title: 'DataSHIELD' RO-Crate Governance Functions
Description: Tools for wrapping 'DataSHIELD' analyses into RO-Crate (Research Object Crate) objects. Provides functions to create structured metadata for federated data analysis projects, enabling governance tracking of data access, project membership, analysis execution and output validation across distributed data sources.
Author: Roberto Villegas-Diaz [aut, cre] , Becca Wilson [aut] , Olly Butters [aut] , Stuart Wheater [aut] , University of Liverpool [cph]
Maintainer: Roberto Villegas-Diaz <r.villegas-diaz@outlook.com>

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Package CoxBoost updated to version 1.5.2 with previous version 1.5.1 dated 2025-12-11

Title: Cox Models by Likelihood Based Boosting for a Single Survival Endpoint or Competing Risks
Description: Provides routines for fitting Cox models by likelihood based boosting for single event survival data with right censoring or in the presence of competing risks. The methodology is described in Binder and Schumacher (2008) <doi:10.1186/1471-2105-9-14> and Binder et al. (2009) <doi:10.1093/bioinformatics/btp088>.
Author: John Zobolas [cre, aut] , Harald Binder [aut]
Maintainer: John Zobolas <bblodfon@gmail.com>

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Package ThSQCA updated to version 2.0.7 with previous version 2.0.6 dated 2026-07-31

Title: Threshold-Sweep QCA
Description: Provides threshold sweep methods for Qualitative Comparative Analysis (QCA). Implements Condition Threshold Sweep (CTS, for one or several conditions), Outcome Threshold Sweep (OTS), and Dual Threshold Sweep (DTS) for systematic exploration of threshold calibration effects on crisp-set QCA results. These methods extend traditional robustness approaches by treating threshold variation as an explicit analytical dimension and recording the sufficiency solution obtained at each threshold setting. Also provides Fiss (2011) <doi:10.5465/amj.2011.60263120> core/peripheral condition classification via compute_fiss_core() and generate_fiss_chart(), enabling four-symbol configuration charts that distinguish core conditions (present in both parsimonious and intermediate solutions) from peripheral conditions (intermediate only). Built on top of the 'QCA' package by Dusa (2019) <doi:10.1007/978-3-319-75668-4>, with function arguments following 'QCA' conventions. Based on set-theoretic m [...truncated...]
Author: Yuki Toyoda [aut, cre], Japan Society for the Promotion of Science [fnd]
Maintainer: Yuki Toyoda <yuki.toyoda.ds@hosei.ac.jp>

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Package PreProcess updated to version 3.1.10 with previous version 3.1.9 dated 2025-04-06

Title: Basic Functions for Pre-Processing Microarrays
Description: Provides classes to pre-process microarray gene expression data as part of the OOMPA collection of packages described at <http://silicovore.com/OOMPA/index.html>.
Author: Kevin R. Coombes [aut, cre]
Maintainer: Kevin R. Coombes <krc@silicovore.com>

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Package pharmaverseadamjnj updated to version 0.0.6 with previous version 0.0.5 dated 2026-05-08

Title: J&J Innovative Medicine ADaM Test Data
Description: A set of Analysis Data Model (ADaM) datasets constructed by modifying the ADaM datasets in the 'pharmaverseadam' package to meet J&J Innovative Medicine's standard data structure for Clinical and Statistical Programming.
Author: David Munoz Tord [aut, cre], Nicholas Masel [aut], Joe Kovach [aut], Mahesh Divakaran [ctb], Renfei Mao [ctb], J&J Innovative Medicine [cph, fnd]
Maintainer: David Munoz Tord <david.munoztord@mailbox.org>

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Package PatientGenerator updated to version 0.2.5 with previous version 0.2.4 dated 2026-09-15

Title: Generator of Synthetic Patient Data for the OMOP Common Data Model
Description: Tools to generate synthetic patient-level test datasets in the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM). Includes a chat-driven generator backed by large language models and an interactive 'shiny' designer for editing CDM test sets.
Author: Cesar Barboza [aut, cre] , Ger Inberg [aut] , Adam Black [aut]
Maintainer: Cesar Barboza <c.barboza@mi-erasmusmc.nl>

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Package LiblineaR updated to version 2.10-26 with previous version 2.10-25 dated 2026-09-11

Title: Linear Predictive Models Based on the LIBLINEAR C/C++ Library
Description: A wrapper around the LIBLINEAR C/C++ library for machine learning (available at <https://www.csie.ntu.edu.tw/~cjlin/liblinear/>). LIBLINEAR is a simple library for solving large-scale regularized linear classification and regression. It currently supports L2-regularized classification (such as logistic regression, L2-loss linear SVM and L1-loss linear SVM) as well as L1-regularized classification (such as L2-loss linear SVM and logistic regression) and L2-regularized support vector regression (with L1- or L2-loss). The main features of LiblineaR include multi-class classification (one-vs-the rest, and Crammer & Singer method), cross validation for model selection, probability estimates (logistic regression only) or weights for unbalanced data. The estimation of the models is particularly fast as compared to other libraries.
Author: Thibault Helleputte [cre, aut, cph], Jerome Paul [aut], Pierre Gramme [aut], Chih-Jen Lin [cph] ; see LICENSE.note)
Maintainer: Thibault Helleputte <thibault.helleputte@dnalytics.com>

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Package evolqg updated to version 0.4-3 with previous version 0.3-6 dated 2025-09-05

Title: Evolutionary Quantitative Genetics
Description: Provides functions for covariance matrix comparisons, estimation of repeatabilities in measurements and matrices, and general evolutionary quantitative genetics tools. Melo D, Garcia G, Hubbe A, Assis A P, Marroig G. (2016) <doi:10.12688/f1000research.7082.3>.
Author: Diogo Melo [aut, cre] , Ana Paula Assis [aut] , Edgar Zanella [ctb], Fabio Andrade Machado [aut] , Guilherme Garcia [aut], Alex Hubbe [rev] , Gabriel Marroig [ths]
Maintainer: Diogo Melo <diogro@gmail.com>

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 15 files changed, 237 insertions(+), 135 deletions(-)

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Package SSBtools updated to version 1.8.9 with previous version 1.8.8 dated 2026-08-21

Title: Algorithms and Tools for Tabular Statistics and Hierarchical Computations
Description: Includes general data manipulation functions, algorithms for statistical disclosure control (Langsrud, 2024) <doi:10.1007/978-3-031-69651-0_6> and functions for hierarchical computations by sparse model matrices (Langsrud, 2023) <doi:10.32614/RJ-2023-088>.
Author: Oeyvind Langsrud [aut, cre] , Daniel Lupp [aut] , Bjoern-Helge Mevik [ctb], Vidar Norstein Klungre [rev] , Statistics Norway [cph]
Maintainer: Oeyvind Langsrud <oyl@ssb.no>

Diff between SSBtools versions 1.8.8 dated 2026-08-21 and 1.8.9 dated 2026-09-24

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 NEWS.md                     |    6 +
 R/Extend0.R                 |    6 +
 R/Extend0rnd1.R             |  183 +++++++++++++++++++++++++++++++++++++++++---
 man/Extend0_n_rnd_groups.Rd |only
 man/Extend0rnd1.Rd          |    2 
 8 files changed, 199 insertions(+), 21 deletions(-)

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New package screenllm with initial version 0.1.0
Package: screenllm
Title: LLM-Assisted Title/Abstract Screening for Systematic Reviews
Version: 0.1.0
Description: A turn-key workflow for LLM-assisted systematic-review screening. The package ranks a corpus of titles and abstracts with an ensemble of open-source large language models served locally by 'Ollama', then applies the SAFE stopping rule to identify the records a human should screen. Defaults match the four-LLM mean ensemble and the SAFE configuration recommended by Spillias et al. (2026). A companion 'Shiny' app walks the human reviewer through the records above the stopping point. Complementary to the 'AIscreenR' package of Vembye et al. (2025) <doi:10.1037/met0000769>, which targets cloud-hosted 'GPT' models via the 'OpenAI' API; 'screenllm' targets locally-served open-weights ensembles with an integrated stopping rule.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: cli, digest, fs, jsonlite, tibble, dplyr, rlang, httr2, glue
Suggests: shiny, bslib, DT, callr, later, writexl, readxl, testthat (>= 3.0.0), knitr, rmarkdown, readr, withr, mockery, stringdist
VignetteBuilder: knitr
URL: https://github.com/s-spillias/screenllm
BugReports: https://github.com/s-spillias/screenllm/issues
NeedsCompilation: no
Packaged: 2026-09-15 05:47:11 UTC; spi085
Author: Scott Spillias [aut, cre], Laura Avila Turriago [aut], Christopher Brown [aut], Ariane Easton [aut], Jack Roberts [aut], Michael Sievers [aut], Steve Swearer [aut], Andrew Taylor [aut], Brigette Wright [aut], Valeriya Komyakova [aut]
Maintainer: Scott Spillias <scott.spillias@csiro.au>
Repository: CRAN
Date/Publication: 2026-09-24 15:00:02 UTC

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New package rxode2lincmt with initial version 0.1.0
Package: rxode2lincmt
Version: 0.1.0
Title: Linear Compartment Model Solutions and Gradients for 'rxode2'
Maintainer: Matthew L. Fidler <matthew.fidler@gmail.com>
Depends: R (>= 4.1.0)
Imports: Rcpp (>= 1.0.8), checkmate
Suggests: covr, testthat (>= 3.0.0)
Description: Analytic one, two and three compartment linear pharmacokinetic solutions with their parameter gradients from 'stan' automatic differentiation (Carpenter et al (2015) <doi:10.48550/arXiv.1509.07164>), eigen decompositions and derived-parameter conversions used by 'rxode2' (Wang, Hallow and James (2016) <doi:10.1002/psp4.12052>). Split out of 'rxode2' so its installation does not compile 'stan' AD items which made it take too long to compile by itself. The closed-form solutions follow the idea of the 'wnl' package (Bae, <https://CRAN.R-project.org/package=wnl>), though the implementation here is different.
BugReports: https://github.com/nlmixr2/rxode2lincmt/issues/
NeedsCompilation: yes
License: GPL (>= 3)
URL: https://nlmixr2.github.io/rxode2lincmt/, https://github.com/nlmixr2/rxode2lincmt/
Biarch: true
LinkingTo: Rcpp (>= 1.0.8), RcppEigen (>= 0.3.3.9.2), StanHeaders (>= 2.21.0.7), BH, RcppParallel
Encoding: UTF-8
Language: en-US
Packaged: 2026-09-14 19:46:27 UTC; matt-fidler
Author: Matthew L. Fidler [aut, cre] , Richard Upton [ctb]
Repository: CRAN
Date/Publication: 2026-09-24 14:40:02 UTC

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New package RobustVis with initial version 0.1.2
Package: RobustVis
Title: Visualize ROBUST-RCT Risk of Bias Assessments
Version: 0.1.2
Description: Provides functions to visualize ROBUST-RCT assessments, as introduced by Wang et al. (2025) <doi:10.1136/bmj-2024-081199>. Through a two-step workflow (step 1 and step 2), the package generates bar plots and traffic-light plots that match standard Cochrane styles.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Depends: R (>= 4.1.0)
Imports: dplyr (>= 1.2.0), ggplot2 (>= 4.0.2), scales (>= 1.4.0), tidyr (>= 1.3.1)
NeedsCompilation: no
Packaged: 2026-09-14 21:20:09 UTC; xiaobanxia
Author: Guang Chen [aut, cre], Fanrong Liang [aut]
Maintainer: Guang Chen <tcm_chen7410@163.com>
Repository: CRAN
Date/Publication: 2026-09-24 14:50:06 UTC

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New package RCTCovAdj with initial version 0.1.0
Package: RCTCovAdj
Title: Covariate Adjustment for Randomized Controlled Trials
Version: 0.1.0
Description: Implements covariate-adjusted estimation and inference for marginal mean differences in two-arm randomized controlled trials with continuous outcomes. Methods include the unadjusted difference in means, common-slope analysis of covariance, interacted standardization with joint influence-function inference, and cross-fitted augmentation. The package also provides analytic power and sample-size calculations, reproducible simulation designs, and article replication workflows, including tools for verifying and analyzing an authorized local trial-data file. The adjustment methods build on Tsiatis et al. (2008) <doi:10.1002/sim.3113> and Lin (2013) <doi:10.1214/12-AOAS583>.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: digest, graphics, grDevices, parallel, stats, tools, utils
Suggests: knitr, medicaldata (>= 0.2.0), rmarkdown, testthat (>= 3.0.0), withr
VignetteBuilder: knitr
LazyData: true
LazyDataCompression: xz
NeedsCompilation: no
Packaged: 2026-09-14 20:26:11 UTC; seyoo
Author: Se Yoon Lee [aut, cre, cph]
Maintainer: Se Yoon Lee <seyoonlee.stat.math@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-24 14:50:11 UTC

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New package psvr with initial version 0.1.0
Package: psvr
Title: Percentage-Error Support Vector Regression
Version: 0.1.0
Description: Implements four support vector regression (SVR) models derived from a unified mathematical framework for percentage-error loss functions: epsilon-SVR minimizing the mean absolute percentage error (MAPE), its symmetric kernel extension, least-squares SVR (LS-SVR) minimizing the root mean square percentage error (RMSPE), and its symmetric counterpart. All models require strictly positive targets. The epsilon-SVR models are solved via a built-in sequential minimal optimization (SMO) algorithm (with 'osqp' available as an optional alternative backend) and the LS-SVR models via a linear system (base R). See Benavides-Herrera et al. (2026) <doi:10.3390/math14101679> for the mathematical derivations.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1)
Imports: dials, Matrix, parsnip, Rcpp (>= 1.0.10), rlang, scales, stats, tune, utils, workflowsets
LinkingTo: Rcpp
Suggests: dplyr, ggplot2, knitr, osqp, recipes, rmarkdown, rsample, testthat (>= 3.0.0), tibble, workflows, yardstick
VignetteBuilder: knitr
URL: https://pbenavidesh.github.io/psvr/
NeedsCompilation: yes
Packaged: 2026-09-14 19:56:47 UTC; behep
Author: Pablo Benavides-Herrera [aut, cre]
Maintainer: Pablo Benavides-Herrera <pbenavides@iteso.mx>
Repository: CRAN
Date/Publication: 2026-09-24 14:40:08 UTC

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Package PReMiuM updated to version 3.2.14 with previous version 3.2.13 dated 2024-01-09

Title: Dirichlet Process Bayesian Clustering, Profile Regression
Description: Bayesian clustering using a Dirichlet process mixture model. This model is an alternative to regression models, non-parametrically linking a response vector to covariate data through cluster membership. The package allows Bernoulli, Binomial, Poisson, Normal, survival and categorical response, as well as Normal and discrete covariates. It also allows for fixed effects in the response model, where a spatial CAR (conditional autoregressive) term can be also included. Additionally, predictions may be made for the response, and missing values for the covariates are handled. Several samplers and label switching moves are implemented along with diagnostic tools to assess convergence. A number of R functions for post-processing of the output are also provided. In addition to fitting mixtures, it may additionally be of interest to determine which covariates actively drive the mixture components. This is implemented in the package as variable selection. The main reference for the package is Liv [...truncated...]
Author: David I. Hastie [aut], Silvia Liverani [aut, cre], Sylvia Richardson [aut], Aurore J. Lavigne [aut], Lucy Leigh [aut], Lamiae Azizi [aut], Xi Liu [aut], Ruizhu Huang [aut], Austin Gratton [aut], Wei Jing [aut]
Maintainer: Silvia Liverani <liveranis@gmail.com>

Diff between PReMiuM versions 3.2.13 dated 2024-01-09 and 3.2.14 dated 2026-09-24

 ChangeLog         |    5 ++++
 DESCRIPTION       |   56 +++++++++++++++++++++++++++++++++++++++++++++++-------
 MD5               |   10 ++++-----
 NAMESPACE         |    2 -
 R/generateData.R  |    3 +-
 build/partial.rdb |binary
 6 files changed, 62 insertions(+), 14 deletions(-)

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New package funresMech with initial version 1.0.4
Package: funresMech
Title: Mechanistic Functional Response Analysis
Version: 1.0.4
Description: Implements the mechanistic functional response model proposed by Okuyama (2012) <doi:10.1016/j.biocontrol.2011.10.008> for host-parasitoid systems. Provides tools for model fitting, likelihood profiling, stochastic simulation, and visualization of parasitism distributions. Includes an interactive 'shiny' application for complete analysis workflows, built with 'plotly' for interactive graphics and 'rmarkdown' for reproducible reports.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: DEoptim, dplyr, future, ggplot2 (>= 3.4.0), magrittr, parallel, plotly, rlang, rmarkdown, shiny, shinyBS, shinythemes, stats, utils
Suggests: kableExtra, knitr, testthat (>= 3.0.0)
URL: https://github.com/Segon03/funresMech
BugReports: https://github.com/Segon03/funresMech/issues
NeedsCompilation: no
Packaged: 2026-09-15 03:38:09 UTC; Equipo
Author: Segundo Nunez-Campero [aut, cre]
Maintainer: Segundo Nunez-Campero <segundo.nc@conicet.gov.ar>
Repository: CRAN
Date/Publication: 2026-09-24 14:50:02 UTC

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New package foundryR with initial version 0.1.0
Package: foundryR
Title: Data Frame Workflows for 'Microsoft Foundry'
Version: 0.1.0
Description: Work with 'Microsoft Azure AI Foundry' from data-frame-oriented 'R' workflows. Provides data-frame-returning helpers for 'Azure AI Content Safety', 'Azure OpenAI' Responses API calls, strict structured extraction, vector representations, files, batch jobs, audio, media, and chat completions. Supports research annotation, safety gates, semantic search, and 'tidymodels' recipes. Helps teams keep model workflows inside their 'Azure' environment while preserving analyzable outputs. See the Microsoft Foundry REST API documentation <https://learn.microsoft.com/rest/api/microsoft-foundry/> and Azure AI Content Safety documentation <https://learn.microsoft.com/azure/ai-services/content-safety/>.
License: MIT + file LICENSE
Depends: R (>= 4.1.0)
URL: https://github.com/farach/foundryR, https://farach.github.io/foundryR/
BugReports: https://github.com/farach/foundryR/issues
Encoding: UTF-8
Imports: cli, curl, digest, dplyr, generics, httr2 (>= 1.0.0), jsonlite, lifecycle, magrittr, purrr, rlang, tibble
Suggests: AzureAuth, base64enc, ellmer, ggplot2, gt, httptest2, irlba, irr, janeaustenr, knitr, recipes, rmarkdown, S7, testthat (>= 3.0.0), tidymodels, tidyr, withr, yardstick
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-09-14 01:20:09 UTC; runner
Author: Alex Farach [aut, cre, cph]
Maintainer: Alex Farach <alexfarach@microsoft.com>
Repository: CRAN
Date/Publication: 2026-09-24 14:40:16 UTC

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New package CAbiplot with initial version 0.1.0
Package: CAbiplot
Title: Correspondence Analysis Biplots and Diagnostic Reports
Version: 0.1.0
Description: A convenience wrapper around 'FactoMineR' and 'factoextra' for running Correspondence Analysis (CA) on a numeric data table (e.g. a genotype-by-trait or contingency-style matrix) and producing a full set of publication-ready diagnostic plots: scree plot, symmetric biplot, row-only and column-only plots, row/column contribution plots, and row/column cos2 (quality-of-representation) plots. A single top-level function runs the whole pipeline, prints formatted result tables, and optionally saves every plot as a high-resolution image, mirroring a typical CA reporting workflow used in agronomy and plant-breeding studies. An example genotype-by-trait data set is included.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 3.5.0)
Imports: FactoMineR, factoextra, ggplot2, gridExtra, utils
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-09-15 07:00:02 UTC; iasri
Author: Prakash Kumar [aut, cre], Himadri Sekhar Roy [aut], Ranjit Kumar Paul [aut], Md. Yeasin [aut], Sunil Kumar Yadav [aut], Amrit Kumar Paul [aut]
Maintainer: Prakash Kumar <prakash289111@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-24 15:00:08 UTC

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New package blueycolors with initial version 0.2.2
Package: blueycolors
Title: Provides 'Bluey' Inspired Color Palettes
Version: 0.2.2
Description: Provides 'Bluey'-inspired color palettes and 'ggplot2' scales.
License: MIT + file LICENSE
URL: https://github.com/ekholme/blueycolors, https://ekholme.github.io/blueycolors/
BugReports: https://github.com/ekholme/blueycolors/issues
Encoding: UTF-8
Imports: ggplot2, grDevices
Suggests: scales, testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-09-14 17:34:43 UTC; ekholme
Author: Eric Ekholm [aut, cre, cph]
Maintainer: Eric Ekholm <eric.ekholm@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-24 14:40:26 UTC

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New package ZooRisk with initial version 1.0.0
Package: ZooRisk
Title: Quantitative Assessment of Zoonotic Disease Risk
Version: 1.0.0
Description: Provides quantitative tools for assessing zoonotic disease risk across animal, human, environmental, and transmission interfaces. The package supports exposure and transmission risk estimation, spillover risk assessment, risk scoring, cross-species comparison, transmission-network analysis, Monte Carlo uncertainty simulation, and sensitivity analysis. The One Health framework underlying these assessments is described by World Health Organization, Food and Agriculture Organization of the United Nations, United Nations Environment Programme, and World Organisation for Animal Health (2022) <doi:10.4060/cc2289en>.
License: MIT + file LICENSE
URL: https://github.com/vinodhpmd/ZooRisk
BugReports: https://github.com/vinodhpmd/ZooRisk/issues
Encoding: UTF-8
Suggests: igraph, knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-09-14 16:48:26 UTC; m
Author: Vinodhkumar Obli Rajendran [aut, cre], Keerthi Aaradhana [aut]
Maintainer: Vinodhkumar Obli Rajendran <vinodhkumar.rajendran@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-24 13:50:18 UTC

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New package xaiHydro with initial version 0.1.0
Package: xaiHydro
Title: Explainable AI Tools for Hydro-Climate Modelling
Version: 0.1.0
Date: 2026-09-09
Description: Provides a unified workflow for applying Explainable Artificial Intelligence (XAI) methods to hydro-climate predictive models. Functions implement a permutation-based Monte Carlo SHAP estimator (Strumbelj and Kononenko (2014) <doi:10.1007/s10115-013-0679-x>; Lundberg and Lee (2017) <doi:10.48550/arXiv.1705.07874>), a self-contained locally weighted linear surrogate LIME (Ribeiro et al. (2016) <doi:10.1145/2939672.2939778>), and Partial Dependence Plots with Accumulated Local Effects (Friedman (2001) <doi:10.1214/aos/1013203451>; Apley and Zhu (2020) <doi:10.1111/rssb.12377>) with hydrology-specific visualisations and interpretation utilities. Supports any model object compatible with the 'DALEX' explainer interface (Biecek (2018) <doi:10.18637/jss.v097.i01>), including random forests, gradient boosting, and neural networks trained on streamflow, drought indices, flood risk, or evapotranspiration data. Hydrology-standard performance metrics Nash-Sutcl [...truncated...]
License: GPL-3
Encoding: UTF-8
NeedsCompilation: no
Depends: R (>= 4.1.0)
Imports: DALEX (>= 2.4.0), ggplot2 (>= 3.4.0), dplyr (>= 1.1.0), tidyr (>= 1.3.0), patchwork (>= 1.2.0), cli (>= 3.6.0), rlang (>= 1.1.0)
Suggests: randomForest (>= 4.7.0), xgboost (>= 1.7.0), ranger (>= 0.16.0), testthat (>= 3.0.0), knitr (>= 1.45), rmarkdown (>= 2.25)
VignetteBuilder: knitr
Packaged: 2026-09-13 10:09:33 UTC; Admin
Author: Sadikul Islam [aut, cre] , Shakir Ali [aut], Rajesh Kaushal [aut]
Maintainer: Sadikul Islam <sadikul.islamiasri@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-24 13:30:02 UTC

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New package uqsa with initial version 0.8.0
Package: uqsa
Title: Uncertainty Quantification and Global Sensitivity Analysis
Version: 0.8.0
Description: In the field of systems biology, chemical reaction networks are modeled in various ways, two of those are: (i) stochastic simulations (e.g. Gillespie algorithm) and (ii) ordinary differential equations. In this package we use a simple tabular model description of reaction systems and automatically generate C code for either solver type. We use the ordinary differential equation solvers from the GNU Scientific Library and provide an interface that deals with lists of simulation experiments. Each simulation experiment contains both the data, and instructions for the model to replicate the data. We use approximate Bayesian computation methods (combined with Markov chain Monte Carlo and sequential Monte Carlo, particle filters) as well as classic methods such as Random Walk Metropolis (Gaussian transition kernel) and Simplified Manifold Metropolis adjusted Langevin algorithm for a Bayesian investigation of the model´s parameter space. Experiments can be evaluated in a sequence; intermediat [...truncated...]
Language: en-US
License: GPL (>= 3)
Encoding: UTF-8
Depends: R (>= 4.1)
Imports: stats, methods, parallel, Ryacas, VineCopula, MASS, errors, mvtnorm, digest, colorspace, pracma, cli
Suggests: ks, remotes, pbdMPI, ggplot2, testthat (>= 3.0.0), knitr, rmarkdown, hexbin
SystemRequirements: GSL (>= 2.7)
VignetteBuilder: knitr
URL: https://icpm-kth.github.io/uqsa/
NeedsCompilation: yes
Packaged: 2026-09-14 16:44:28 UTC; andreikr
Author: Alexandra Jauhiainen [aut], Olivia Eriksson [aut, ctb, cph], Federica Milinanni [aut], Andrei Kramer [cre]
Maintainer: Andrei Kramer <andreikr@kth.se>
Repository: CRAN
Date/Publication: 2026-09-24 13:50:02 UTC

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Package tReeTraits readmission to version 0.1.3 with previous version 0.1.2 dated 2026-02-25

Title: Calculate Tree Traits from Terrestrial Lidar
Description: Measuring tree architecture from terrestrial lidar data, including tree-level properties, crown characteristics, and structural attributes derived from quantitative structure models (QSMs).
Author: Jeffery B. Cannon [aut, cre]
Maintainer: Jeffery B. Cannon <jeffery.cannon@jonesctr.org>

This is a re-admission after prior archival of version 0.1.2 dated 2026-02-25

Diff between tReeTraits versions 0.1.2 dated 2026-02-25 and 0.1.3 dated 2026-09-24

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 README.md                 |   19 +++++--
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 man/fit_taper_Kozak.Rd    |   42 ++++++++++++-----
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 11 files changed, 171 insertions(+), 96 deletions(-)

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Package SLGP updated to version 2.0.0 with previous version 1.1.1 dated 2026-09-07

Title: Spatial Logistic Gaussian Process for Field Density Estimation
Description: Provides tools for conditional and spatially dependent density estimation using Spatial Logistic Gaussian Processes (SLGPs). The approach represents probability densities through finite-rank Gaussian process priors transformed via a spatial logistic density transformation, enabling flexible non-parametric modeling of heterogeneous data. Functionality includes density prediction, quantile and moment estimation, sampling methods, and preprocessing routines for basis functions. Applications arise in spatial statistics, machine learning, and uncertainty quantification. The methodology builds on the framework of Leonard (1978) <doi:10.1111/j.2517-6161.1978.tb01655.x>, Lenk (1988) <doi:10.1080/01621459.1988.10478625>, Tokdar (2007) <doi:10.1198/106186007X210206>, Tokdar (2010) <doi:10.1214/10-BA605>, and is further aligned with recent developments in Bayesian non-parametric modelling: see Gautier (2023) <https://boristheses.unibe.ch/4377/>, and Gautier (2025) &l [...truncated...]
Author: Athenais Gautier [aut, cre]
Maintainer: Athenais Gautier <athenais.gautier@onera.fr>

Diff between SLGP versions 1.1.1 dated 2026-09-07 and 2.0.0 dated 2026-09-24

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 src/stanExports_likelihoodSimple.h   |  189 +---
 vignettes/IntroductionSLGP.Rmd       |   23 
 vignettes/SLGPdiscrete.Rmd           |   12 
 31 files changed, 2511 insertions(+), 2199 deletions(-)

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New package rsmart with initial version 0.1.0
Package: rsmart
Title: Sequential Multiple Assignment Randomized Trials Design and Analyses
Version: 0.1.0
Description: Implements the interim augmented inverse probability weighted estimator (IAIPWE) for estimating the value of treatment regimes embedded in sequential multiple assignment randomized trials (SMARTs). The IAIPWE subsumes both the inverse probability weighted estimator (IPWE) and the augmented inverse probability weighted estimator (AIPWE), enabling inference at interim and final analyses. The package provides functions for value estimation, sandwich variance computation, group sequential stopping boundaries, and sample size determination for multi-stage SMARTs with up to two treatment options at each stage. See Manschot, Laber, and Davidian (2023) <doi:10.1111/biom.13854> for additional details.
License: GPL (>= 3)
URL: https://MSDLLCpapers.github.io/rsmart/, https://github.com/MSDLLCpapers/rsmart, https://msdllcpapers.github.io/rsmart/
BugReports: https://github.com/MSDLLCpapers/rsmart/issues
Encoding: UTF-8
Suggests: dplyr, knitr, pkgdown, rmarkdown, testthat (>= 3.0.0)
Depends: R (>= 3.5)
Imports: data.table, doFuture, foreach, Matrix, MASS, modelObj, mvtnorm, stats
LazyData: true
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-09-14 14:37:41 UTC; manschoc
Author: Cole Manschot [aut, cre], Tabitha Peter [ctb], Gabriela Piasecki [ctb], Laura Frederick [ctb]
Maintainer: Cole Manschot <cole.manschot@msd.com>
Repository: CRAN
Date/Publication: 2026-09-24 13:40:02 UTC

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New package riskweightedassets with initial version 1.1.1
Package: riskweightedassets
Title: Reproducible Risk-Weighted Asset Calculations
Version: 1.1.1
Description: Provides transparent, deterministic and auditable calculations of risk-weighted assets, own-funds requirements, interest-rate risk in the banking book and related capital metrics. It supports canonical in-memory tables and versioned spreadsheet datasets, strict validation, synthetic reference profiles, bitemporal snapshots, calculation controls and traceable regulatory source metadata. Methods are parameterised against the European Parliament and Council (2013) Capital Requirements Regulation <https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:32013R0575> and its amending Regulation (EU) 2024/1623 <https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:32024R1623>. A granular analyst API exposes individual formulae, domain views, controls, schemas and auditable parameter overrides. The implementation is intended for analytical, educational and model-validation use and does not constitute legal or supervisory advice.
License: GPL-3
Copyright: 2026 RiskDataScience GmbH
URL: https://github.com/rds0001/risk-weighted-assets-r
BugReports: https://github.com/rds0001/risk-weighted-assets-r/issues
Encoding: UTF-8
Date: 2026-09-14
Depends: R (>= 4.1.0)
Imports: digest, jsonlite, openxlsx, readxl, utils, yaml
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-09-14 16:20:54 UTC; qwert123
Author: Dimitrios Geromichalos [cre], RiskDataScience GmbH [aut, cph]
Maintainer: Dimitrios Geromichalos <riskdatascience@web.de>
Repository: CRAN
Date/Publication: 2026-09-24 13:50:10 UTC

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New package regstat with initial version 0.1.0
Package: regstat
Title: An Exact Test for a Change in Covariance (Dependence) Structure
Version: 0.1.0
Description: An exact finite-sample test for whether two groups share a covariance matrix, the omnibus form of the differential-network question. Under the Gaussian null the likelihood-ratio statistic has a distribution given by the real Jacobi ensemble that is free of the unknown common covariance, so a single Monte-Carlo calibration at the identity serves every covariance with no estimate of the nuisance covariance; this is the property that survives the dimension barrier, where estimating the covariance is hardest. The max-type high-dimensional test of Cai, Liu and Xia (2013) <doi:10.1080/01621459.2012.758041> is provided for comparison. A pure-C back-end does the numerics and also backs the 'Python' package 'regstat'.
URL: https://github.com/mtloots/regstat
BugReports: https://github.com/mtloots/regstat/issues
License: GPL-3
Encoding: UTF-8
Imports: stats
NeedsCompilation: yes
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
Packaged: 2026-09-14 15:44:51 UTC; home
Author: M. Theodor Loots [aut, cre]
Maintainer: M. Theodor Loots <theo.loots@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-24 13:40:09 UTC

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New package plasmidplot with initial version 0.1.0
Package: plasmidplot
Title: Publication-Quality Circular and Linear Plasmid Maps
Version: 0.1.0
Description: Draws circular and linear plasmid maps with 'grid' graphics. Features are shown as colored arcs with optional arrowheads, callout labels that are laid out to avoid overlap, an automatic base-pair scale, and the plasmid name and size. A style is built from a handful of shape parameters, with presets as named combinations of them, and the layout follows the molecule's topology. Maps can be built up feature by feature or imported from 'GenBank', 'EMBL', 'FASTA' and 'SnapGene' files, whose format is detected from content rather than file extension. Restriction sites can be located in the sequence and labeled. Ships eight visual styles, including one inspired by the 'AngularPlasmid' JavaScript library, and seven categorical palettes checked for colorblind safety. Palettes from other packages can be used directly, as a color vector or as a palette function, and checked against the same criteria.
License: MIT + file LICENSE
URL: https://github.com/dkturingfz/plasmidplot
BugReports: https://github.com/dkturingfz/plasmidplot/issues
Encoding: UTF-8
Imports: grDevices, grid, tools, utils
Suggests: knitr, rmarkdown, testthat (>= 3.0.0), xml2
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-09-14 09:44:14 UTC; church
Author: Qiyou Pan [aut, cre]
Maintainer: Qiyou Pan <dkturingfz@outlook.com>
Depends: R (>= 4.1.0)
Repository: CRAN
Date/Publication: 2026-09-24 13:30:09 UTC

More information about plasmidplot at CRAN
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New package pacha with initial version 0.1.1
Package: pacha
Title: Reproducible Reporting for ChecklistBank Ethnobotanical Data
Version: 0.1.1
Description: Provides programmatic access to the 'Listado de plantas de uso y aprovechamiento sostenible en Ecuador' <doi:10.48580/dgvrn>. Acts as a client for the 'ChecklistBank' API and for processing 'ColDP' (Catalogue of Life Data Package) files. Supports data retrieval for ethnobotanical records and includes built-in Markdown report generation for reproducible workflows.
License: GPL (>= 3)
Language: en-US
URL: https://github.com/envinatu/pacha
BugReports: https://github.com/envinatu/pacha/issues
Imports: httr2, stats, tools, utils, yaml
Suggests: knitr, quarto, rmarkdown, testthat (>= 3.0.0)
Encoding: UTF-8
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-09-14 17:26:51 UTC; PC
Author: Marcelo F. Amores-Palma [aut, cre, cph]
Maintainer: Marcelo F. Amores-Palma <contacto.envinatu@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-24 14:00:02 UTC

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New package nlmixr2scm with initial version 0.4
Package: nlmixr2scm
Title: Stepwise Covariate Modeling for 'nlmixr2' Models
Version: 0.4
Description: Stepwise covariate modeling (SCM) for nonlinear mixed-effects models fitted with 'nlmixr2'. Forward inclusion and backward elimination are driven by likelihood-ratio tests, and the covariate terms are generated inside the model body, so continuous covariates are centered and categorical covariates expanded into indicator columns without editing the model by hand. Candidate fits can be cached and resumed, fitted in parallel, and reviewed through per-step and all-candidate summary tables. The approach follows Jonsson and Karlsson (1998) <doi:10.1023/A:1011970125687>, and the implementation in 'Perl-speaks-NONMEM' described by Lindbom, Ribbing and Jonsson (2004) <doi:10.1016/j.cmpb.2003.11.003>.
Depends: R (>= 4.1)
License: GPL (>= 3)
URL: https://github.com/nlmixr2/nlmixr2scm
BugReports: https://github.com/nlmixr2/nlmixr2scm/issues
Imports: checkmate, cli (>= 3.4.0), data.table, lotri, nlme, nlmixr2est (>= 7.0.0), nlmixr2utils (>= 0.3), rxode2 (>= 5.0.0), stats, tools, utils
Suggests: future, knitr, nlmixr2data, pkgload, rmarkdown, testthat (>= 3.0.0), withr
VignetteBuilder: knitr
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-09-14 09:38:51 UTC; justin
Author: Justin Wilkins [aut, cre, cph] , Matthew Fidler [aut] , Yaping Liu [aut] , Bill Denney [aut] , Vipul Mann [aut], Vishal Sarsani [aut] , Christian Bartels [ctb]
Maintainer: Justin Wilkins <justin.wilkins@occams.com>
Repository: CRAN
Date/Publication: 2026-09-24 13:30:14 UTC

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Package gggenomes updated to version 1.2.0 with previous version 1.1.3 dated 2026-02-23

Title: A Grammar of Graphics for Comparative Genomics
Description: An extension of 'ggplot2' for creating complex genomic maps. It builds on the power of 'ggplot2' and 'tidyverse' adding new 'ggplot2'-style geoms & positions and 'dplyr'-style verbs to manipulate the underlying data. It implements a layout concept inspired by 'ggraph' and introduces tracks to bring tidiness to the mess that is genomics data.
Author: Thomas Hackl [aut, cre], Markus J. Ankenbrand [aut], Bart van Adrichem [aut], Kristina Haslinger [ctb, sad]
Maintainer: Thomas Hackl <t.hackl@rug.nl>

Diff between gggenomes versions 1.1.3 dated 2026-02-23 and 1.2.0 dated 2026-09-24

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New package gdam with initial version 0.0.1
Package: gdam
Title: Fast Robust Additive Models using Gamma Divergence
Version: 0.0.1
Date: 2026-09-10
Description: Provides a computationally efficient method (at least at the time of development!) for robust additive modeling based on the gamma divergence, implementing the methodology of Hui, Ding, and Sugasawa (2026) <doi:10.1007/s11222-026-10960-3>. The method assumes an identity link and normally distributed errors, and applies the gamma divergence to the resulting restricted maximum likelihood function so as to obtain a loss function that is less sensitive to outlying responses. Because 'gdam' uses a model fitted via the 'mgcv' package as the starting point for optimization, and leverages many of its existing techniques for estimation and inference, users can take advantage of many of the smoothing options available in the 'mgcv' package for constructing additive models.
Maintainer: Francis KC Hui <fhui28@gmail.com>
License: GPL (>= 3)
Encoding: UTF-8
Imports: colorspace, ggplot2, gratia, Matrix, mgcv, stats
Suggests: spelling, tidyverse
Language: en-US
URL: https://github.com/fhui28/gdam
BugReports: https://github.com/fhui28/gdam/issues
NeedsCompilation: no
Packaged: 2026-09-14 09:46:04 UTC; fkch
Author: Francis KC Hui [aut, cre] , Shonosuke Sugasawa [ctb]
Repository: CRAN
Date/Publication: 2026-09-24 13:30:20 UTC

More information about gdam at CRAN
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New package FIAstemmap with initial version 2.0.0
Package: FIAstemmap
Title: Tree Canopy Modeling for USDA Forest Inventory and Analysis Plots
Version: 2.0.0
Description: Maps individual tree stem locations on field plots of the Forest Inventory and Analysis Program of USDA Forest Service (<https://research.fs.usda.gov/programs/nfi>). Stem locations are mapped in cartesian coordinate space based on field-measured distance and azimuth from subplot and microplot centers. Per-tree crown widths are estimated using a curated set of allometric equations with coverage for the conterminous US. Spatial descriptors of tree point pattern are computed at the whole plot level. Several stand height metrics are also computed and provided in the output. The spatial representation of modeled tree crowns is used to generate estimates of fractional tree canopy cover at the microplot, subplot and whole plot levels. Convenience functions are provided for efficient data processing. Exploratory data analysis is also facilitated via integration with the 'spatstat' packages.
License: MIT + file LICENSE
Depends: R (>= 4.1.0)
Imports: bit64, cli, gdalraster (>= 2.5.0), grDevices, methods, spatstat.explore, spatstat.geom, stats
Suggests: glue (>= 1.6.0), spelling, testthat (>= 3.0.0), vctrs (>= 0.3.0)
URL: https://firelab.github.io/FIAstemmap/, https://github.com/firelab/FIAstemmap
BugReports: https://github.com/firelab/FIAstemmap/issues
Encoding: UTF-8
LazyData: true
Language: en-US
NeedsCompilation: no
Packaged: 2026-09-14 18:04:43 UTC; ctoney
Author: Chris Toney [aut, cre]
Maintainer: Chris Toney <jctoney@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-24 14:00:15 UTC

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New package bioIOT with initial version 0.2.2
Package: bioIOT
Title: Inverse Optimal Transport for Single-Cell Trajectory Analysis
Version: 0.2.2
Description: Semi-relaxed inverse optimal transport (IOT) for single-cell state-transition and pseudotime analysis: a self-contained R solver (Anderson-accelerated soft Sinkhorn with exact implicit gradients), feature-weight fitting with a two-stage bias-corrected refit and multi-restart, state transition matrices, random-walk pseudotime, 'ggplot2' visualisation, soft-gated 'Seurat' and 'SingleCellExperiment' interfaces, reproducible simulated demo data, and bulk-cohort pathway scoring utilities.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.0.0)
Imports: utils, ggplot2
Suggests: testthat (>= 3.0.0), knitr, rmarkdown, SingleCellExperiment, Seurat, SummarizedExperiment, S4Vectors
URL: https://github.com/XTSgreen/bioIOT-R
BugReports: https://github.com/XTSgreen/bioIOT-R/issues
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-09-14 15:40:40 UTC; XTS-green
Author: Han Dong [aut, cre]
Maintainer: Han Dong <dh411424@163.com>
Repository: CRAN
Date/Publication: 2026-09-24 13:40:24 UTC

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Package typedjson updated to version 0.1.1 with previous version 0.1.0 dated 2026-09-18

Title: Type-Faithful and Human-Readable JSON for R Values
Description: Writing an R value as JSON that a human can read, and reading it back unchanged. The 'jsonlite' package offers either a readable but lossy pair of functions or a faithful but verbose one; this package emits ordinary JSON for ordinary values and annotates only what JSON cannot express, namely the distinction between integer and double, typed missing values, non-finite numbers, attributes, and objects from the S3, S4 and S7 systems.
Author: Nicolas Bennett [aut, cre, cph], YaoYuan [ctb, cph]
Maintainer: Nicolas Bennett <nicolas@cynkra.com>

Diff between typedjson versions 0.1.0 dated 2026-09-18 and 0.1.1 dated 2026-09-24

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Package statAfrikR updated to version 0.2.1 with previous version 0.2.0 dated 2026-09-20

Title: Statistical Tools for African National Statistics Institutes
Description: A comprehensive statistical toolbox for National Statistics Institutes (INS) in Africa. Provides functions for survey data import ('KoboToolbox', 'ODK', 'CSPro', 'Excel', 'Stata', 'SPSS'), data processing and validation, weighted statistical analysis (descriptive statistics, cross-tabulations, regression, Human Development Index (HDI), Multidimensional Poverty Index (MPI) following Alkire and Foster (2011) <doi:10.1093/oep/gpr051>, inequalities), visualization (age pyramids, thematic maps, official charts) and dissemination ('SDMX' export, 'DDI' metadata, anonymization, Word/PDF reports). Designed to work in resource-constrained environments, offline and in French.
Author: Dikers Amoko [aut, cre, ctb], Josue Honore Dasse [ctb]
Maintainer: Dikers Amoko <diamoko@gmail.com>

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Package spconform updated to version 0.1.1 with previous version 0.1.0 dated 2026-09-12

Title: Conformal Prediction for Spatially and Spatio-Temporally Dependent Data
Description: Provides distribution-free, model-agnostic prediction intervals for spatially and spatio-temporally dependent data using localized conformal calibration. Implements locally weighted split conformal prediction for geostatistical (point-referenced) data based on spatial-distance kernels, and a neighbourhood-weighted conformal procedure for areal (lattice) data based on graph adjacency structures. Relaxes the standard exchangeability assumption using spatial proximity, following the localized conformal framework of Mao, Martin and Reich (2024) <doi:10.1080/01621459.2022.2147531>. Includes comprehensive spatial diagnostic tools to audit empirical coverage, conditional spatial strata, and boundary proximity effects.
Author: Ahmed Sattar Jabbar [aut, cre]
Maintainer: Ahmed Sattar Jabbar <ahmed.state.me@gmail.com>

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Package rtemis.llm updated to version 0.8.7 with previous version 0.8.1 dated 2026-05-04

Title: Large Language Models and Agentic AI
Description: Unified interface for creating LLM and Agent objects, generating responses and performing batch inference based on a type-checked and validated 'S7' backend. Features reasoning, structured output, memory management, and tool use. Supports 'Ollama' <https://docs.ollama.com/api>, 'OpenAI'-compatible <https://developers.openai.com/api/reference/overview>, and 'Anthropic'-compatible <https://platform.claude.com/docs/en/api/getting-started> endpoints. Runs Apple's on-device 'Foundation Models' through the 'rtemis-afm' bridge <https://github.com/rtemis-org/rtemis-afm>.
Author: E.D. Gennatas [aut, cre, cph]
Maintainer: E.D. Gennatas <gennatas@gmail.com>

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Package netmem updated to version 1.1-0 with previous version 1.0-3 dated 2026-04-16

Title: Social Network Measures using Matrices
Description: Provides measures to describe and manipulate one-mode, two-mode, multiplex, and multilevel networks using matrix algebra. Implements functions for network centrality, cohesive subgroups, communities, structural holes, roles and positions, similarity measures, path distances, signed networks, segregation, social influence, and random network generation. Supports ego-centric and whole-network analyses, including dyadic and triadic censuses, structural balance, bipartite projections, measures with overlapping group memberships, Q-analysis, neighbourhood-inclusion dominance, main path analysis of citation networks, and permutation tests for networks. Key references: Bonacich (1972) <doi:10.1080/0022250X.1972.9989806>, Breiger (1974) <doi:10.2307/2576011>, Kivela et al. (2014) <doi:10.1093/comnet/cnu016>, Espinosa-Rada et al. (2024) <doi:10.1016/j.socnet.2023.11.008>, Schoch and Brandes (2016) <doi:10.1017/S0956792516000401>, Traag et al. (2019) <doi:10.1038 [...truncated...]
Author: Alejandro Espinosa-Rada [cre, aut]
Maintainer: Alejandro Espinosa-Rada <anespinosa@uc.cl>

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Package mvMORPH updated to version 1.2.2 with previous version 1.2.1 dated 2024-08-28

Title: Multivariate Comparative Tools for Fitting Evolutionary Models to Morphometric Data
Description: Fits multivariate (Brownian Motion, Early Burst, ACDC, Ornstein-Uhlenbeck and Shifts) models of continuous traits evolution on trees and time series. 'mvMORPH' also proposes high-dimensional multivariate comparative tools (linear models using Generalized Least Squares and multivariate tests) based on penalized likelihood and Empirical Bayes approaches. See Clavel et al. (2015) <DOI:10.1111/2041-210X.12420>, Clavel et al. (2019) <DOI:10.1093/sysbio/syy045>, Clavel & Morlon (2020) <DOI:10.1093/sysbio/syaa010>, and Montoya et al. (2026) <DOI:10.1093/sysbio/syag051>.
Author: Julien Clavel [aut, cre], with contributions from Aaron King [aut], Emmanuel Paradis [aut]
Maintainer: Julien Clavel <julien.clavel@hotmail.fr>

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Package LMMsolver updated to version 1.0.14 with previous version 1.0.13 dated 2026-05-29

Title: Linear Mixed Models with Sparse Matrix Methods and Smoothing
Description: Provides tools for fitting linear mixed models using sparse matrix methods and variance component estimation. Applications include spline-based modeling of spatial and temporal trends using penalized splines (Boer, 2023) <doi:10.1177/1471082X231178591>.
Author: Martin Boer [aut] , Bart-Jan van Rossum [aut, cre]
Maintainer: Bart-Jan van Rossum <bart-jan.vanrossum@wur.nl>

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Package kza updated to version 4.2.1 with previous version 4.2.0 dated 2026-09-14

Title: Kolmogorov-Zurbenko Adaptive Filters
Description: Time series analysis including break detection, spectral analysis, and Kolmogorov-Zurbenko Fourier transforms, following Zurbenko et al. (1996) <doi:10.1175/1520-0442(1996)009%3C3548:DDITSO%3E2.0.CO;2> and Yang and Zurbenko (2010) <doi:10.1002/wics.71>.
Author: Brian Close [aut, cre], Igor Zurbenko [aut], Mingzeng Sun [aut]
Maintainer: Brian Close <brian.close@gmail.com>

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Package eurostat updated to version 4.1.1 with previous version 4.0.0 dated 2023-12-19

Title: Tools for Eurostat Open Data
Description: Tools to download data from the Eurostat database <https://ec.europa.eu/eurostat> together with search and manipulation utilities.
Author: Leo Lahti [aut, cre] , Janne Huovari [aut], Markus Kainu [aut], Przemyslaw Biecek [aut], Daniel Antal [ctb], Daniel Loos [ctb] , Diego Hernangomez [ctb] , Joona Lehtomaki [ctb], Francois Briatte [ctb], Reto Stauffer [ctb], Paul Rougieux [ctb], Anna V [...truncated...]
Maintainer: Leo Lahti <leo.lahti@iki.fi>

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Package campsisnca updated to version 1.7.2 with previous version 1.7.1 dated 2026-09-15

Title: Non-Compartmental Analysis for Campsis Simulation Platform
Description: A flexible and user-friendly non-compartmental analysis (NCA) toolkit designed to work seamlessly with simulated pharmacokinetic data generated using the 'campsis' ecosystem. The package provides a comprehensive framework to compute standard and custom NCA metrics, including exposure (AUC), peak/trough concentrations, half-life and time-above/below thresholds, with support for configurable time windows and summary statistics. 'campsisnca' integrates tightly with 'campsis' and 'campsismod', enabling streamlined workflows from simulation to analysis. In addition, the package provides a JSON-based interface to define NCA analyses, metrics and options using formal schemas, allowing analyses to be created, validated and executed outside of R and facilitating reproducibility, automation and system integration. The package also includes utilities for generating formatted summary tables and exporting results in multiple formats suitable for reporting. Trapezoidal rule implementation for AUC ca [...truncated...]
Author: Nicolas Luyckx [aut, cre], Calvagone [cph]
Maintainer: Nicolas Luyckx <nicolas.luyckx@lynxsoft.be>

Diff between campsisnca versions 1.7.1 dated 2026-09-15 and 1.7.2 dated 2026-09-24

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Package autotestR updated to version 1.2.17 with previous version 1.2.16 dated 2026-08-21

Title: Automated Functions for Basic Statistical Tests
Description: Provides simple and intuitive functions for basic statistical analyses. Methods include the t-test (Student 1908 <doi:10.1093/biomet/6.1.1>), the Mann-Whitney U test (Mann and Whitney 1947 <doi:10.1214/aoms/1177730491>), Pearson's correlation (Pearson 1895 <doi:10.1098/rspl.1895.0041>), and analysis of variance (Fisher 1925, <doi:10.1007/978-1-4612-4380-9_5>). Functions are compatible with 'ggplot2' and 'dplyr'.
Author: Luiz Garcia [aut, cre]
Maintainer: Luiz Garcia <luiz.cardoso@ufpr.br>

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Package visPedigree updated to version 1.10.1 with previous version 1.9.0 dated 2026-07-15

Title: Tidying, Analysis, and Fast Visualization of Animal and Plant Pedigrees
Description: Provides tools for the analysis and visualization of animal and plant pedigrees. Analytical methods include equivalent complete generations, generation intervals, effective population size (via inbreeding, coancestry, and demographic approaches), founder and ancestor contributions, partial inbreeding, genetic diversity indices, and additive (A), dominance (D), and epistatic (AA) relationship matrices. Core algorithms — ancestry tracing, topological sorting, inbreeding coefficients, and matrix construction — are implemented in C++ ('Rcpp', 'RcppArmadillo') and 'data.table', scaling to pedigrees with over one million individuals. Matrix-free pedigree traversals apply additive relationship matrices or their inverses to vectors and matrices without materializing dense square matrices. Pedigree graphs are rendered via 'igraph' with support for compact full-sib family display; relationship matrices can be visualized as heatmaps. Supports complex mating systems, including selfing and pedigree [...truncated...]
Author: Sheng Luan [aut, cre]
Maintainer: Sheng Luan <luansheng@gmail.com>

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Package tidyweather updated to version 0.3.2 with previous version 0.3.0 dated 2026-08-20

Title: Analysis the Weather Data for Agriculture
Description: Functions are collected to analyse weather data for agriculture purposes including to read weather records in multiple formats, calculate extreme climate index. Demonstration data are included the SILO daily climate data (licensed under CC BY 4.0, <https://www.longpaddock.qld.gov.au/silo/>).
Author: Bangou Zheng [aut, cre]
Maintainer: Bangou Zheng <zheng.bangyou@gmail.com>

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Package statgenHTP updated to version 1.0.9.5 with previous version 1.0.9.4 dated 2026-07-06

Title: High Throughput Phenotyping (HTP) Data Analysis
Description: Phenotypic analysis of data coming from high throughput phenotyping (HTP) platforms, including different types of outlier detection, spatial analysis, and parameter estimation. The package is being developed within the EPPN2020 project (<https://cordis.europa.eu/project/id/731013>). Some functions have been created to be used in conjunction with the R package 'asreml' for the 'ASReml' software, which can be obtained upon purchase from 'VSN' international (<https://vsni.co.uk/software/asreml-r/>).
Author: Emilie J Millet [aut] , Maria Xose Rodriguez Alvarez [aut] , Diana Marcela Perez Valencia [aut] , Isabelle Sanchez [aut], Nadine Hilgert [aut], Bart-Jan van Rossum [aut, cre] , Fred van Eeuwijk [aut] , Martin Boer [aut]
Maintainer: Bart-Jan van Rossum <bart-jan.vanrossum@wur.nl>

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Package shinyds updated to version 0.6.0 with previous version 0.5.0 dated 2026-08-22

Title: 'Shiny' Bindings for Designsystemet Components
Description: Provides 'R' wrappers for the Designsystemet component library <https://designsystemet.no>, enabling use of Norwegian government design system components in 'Shiny' applications. Includes web components and CSS-based HTML components with full 'Shiny' input binding support.
Author: Novica Nakov [aut, cre, cph]
Maintainer: Novica Nakov <nnovica@gmail.com>

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Package rmoriedata updated to version 0.3.3 with previous version 0.3.2 dated 2026-09-17

Title: Integrated Datasets for the 'rmorie' Package
Description: Integrated open data fixtures used by the 'rmorie' package for examples, vignettes, and tests. Contains snapshots of publicly available datasets from open-data portals built on the Comprehensive Knowledge Archive Network ('CKAN', <https://ckan.org/>), 'Socrata' (<https://dev.socrata.com/>), and 'Opendatasoft' (<https://www.huwise.com/>) (Chicago, New York City, Toronto, Vancouver, and others), Statistics Canada Canadian Centre for Justice and Community Safety Statistics ('CCJS') tables, a multi-agent-reviewed corpus of Ontario Special Investigations Unit ('SIU', <https://www.siu.on.ca/>) director's reports, and synthetic fixtures for unit tests. Also ships a small set of analyst-facing helpers for releasing aggregate statistics without re-identification risk: Laplace and Gaussian differential privacy mechanisms and k-anonymity, l-diversity, and cell suppression verifiers.
Author: Vansh Singh Ruhela [aut, cre]
Maintainer: Vansh Singh Ruhela <vsruhela@proton.me>

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 rmoriedata-0.3.3/rmoriedata/NAMESPACE                                                                                |    3 
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 rmoriedata-0.3.3/rmoriedata/R/ask.R                                                                                  |   22 
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Package RcppFastAD updated to version 0.0.5 with previous version 0.0.4 dated 2024-09-24

Title: 'Rcpp' Bindings to 'FastAD' Auto-Differentiation
Description: The header-only 'C++' template library 'FastAD' for automatic differentiation <https://github.com/JamesYang007/FastAD> is provided by this package, along with a few illustrative examples that can all be called from R.
Author: Dirk Eddelbuettel [aut, cre] , James Yang [aut]
Maintainer: Dirk Eddelbuettel <edd@debian.org>

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Package mirai updated to version 2.7.3 with previous version 2.7.2 dated 2026-07-20

Title: Minimalist Async Evaluation Framework for R
Description: Evaluates R expressions asynchronously and in parallel, locally or distributed across networks. An official parallel cluster type for R. Built on 'nanonext' and 'NNG', its non-polling, event-driven architecture scales from a laptop to thousands of processes across high-performance computing clusters and cloud platforms. Features FIFO scheduling with task cancellation and bounded queues, promises for reactive programming, 'OpenTelemetry' distributed tracing, and custom serialization for cross-language data types.
Author: Charlie Gao [aut, cre] , Joe Cheng [ctb], Posit Software, PBC [cph, fnd] , Hibiki AI Limited [cph]
Maintainer: Charlie Gao <charlie.gao@posit.co>

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Package compareGroups updated to version 4.10.4 with previous version 4.10.3 dated 2026-08-28

Title: Descriptive Analysis by Groups
Description: Create data summaries for quality control, extensive reports for exploring data, as well as publication-ready univariate or bivariate tables in several formats (plain text, HTML,LaTeX, PDF, Word or Excel. Create figures to quickly visualise the distribution of your data (boxplots, barplots, normality-plots, etc.). Display statistics (mean, median, frequencies, incidences, etc.). Perform the appropriate tests (t-test, Analysis of variance, Kruskal-Wallis, Fisher, log-rank, ...) depending on the nature of the described variable (normal, non-normal or qualitative). Summarize genetic data (Single Nucleotide Polymorphisms) data displaying Allele Frequencies and performing Hardy-Weinberg Equilibrium tests among other typical statistics and tests for these kind of data.
Author: Isaac Subirana [aut, cre] , Joan Salvador [ctb]
Maintainer: Isaac Subirana <isubirana@imim.es>

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Package campsis updated to version 1.9.2 with previous version 1.9.1 dated 2026-09-17

Title: Generic PK/PD Simulation Platform Campsis
Description: A generic, easy-to-use and intuitive pharmacokinetic/pharmacodynamic (PK/PD) simulation platform based on the R packages 'rxode2' and 'mrgsolve'. Campsis provides an abstraction layer over the underlying processes of defining a PK/PD model, assembling a custom dataset and running a simulation. The package has a strong dependency on the R package 'campsismod', which allows models to be read from and written to files, including through a JSON-based interface, and to be adapted further on the fly in the R environment. In addition, 'campsis' allows users to assemble datasets in an intuitive manner, including via a JSON-based interface to import Campsis datasets defined using formal JSON schemas distributed with the package. Once the dataset is ready, the package prepares the simulation, calls 'rxode2' or 'mrgsolve' (at the user's choice), and returns the results for the given model, dataset and desired simulation settings. The package itself is licensed under the GPL (>= 3); the JSON sc [...truncated...]
Author: Nicolas Luyckx [aut, cre], Calvagone [cph]
Maintainer: Nicolas Luyckx <nicolas.luyckx@lynxsoft.be>

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Package sfclust updated to version 1.1.1 with previous version 1.1.0 dated 2026-07-28

Title: Bayesian Spatial Functional Clustering
Description: Bayesian clustering of spatial regions with similar functional shapes using spanning trees and latent Gaussian models. The method enforces spatial contiguity within clusters and supports a wide range of latent Gaussian models, including non-Gaussian likelihoods, via the R-INLA framework. The algorithm is based on Zhong, R., Chacón-Montalván, E. A., and Moraga, P. (2026) <doi:10.1002/sim.70597>, extending the approach of Zhang, B., Sang, H., Luo, Z. T., and Huang, H. (2023) <doi:10.1214/22-AOAS1643>. The package includes tools for model fitting, convergence diagnostics, visualization, and summarization of clustering results.
Author: Erick A. Chacon-Montalvan [aut, cre] , Ruiman Zhong [aut] , Paula Moraga [aut]
Maintainer: Erick A. Chacon-Montalvan <erick.chaconmontalvan@wur.nl>

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Package prioritizr updated to version 9.0.1 with previous version 8.1.0 dated 2025-11-10

Title: Systematic Conservation Prioritization in R
Description: Systematic conservation prioritization using mixed integer linear programming (MILP). It provides a flexible interface for building and solving conservation planning problems. Once built, conservation planning problems can be solved using a variety of commercial and open-source exact algorithm solvers. By using exact algorithm solvers, solutions can be generated that are guaranteed to be optimal (or within a pre-specified optimality gap). Furthermore, conservation problems can be constructed to optimize the spatial allocation of different management actions or zones, meaning that conservation practitioners can identify solutions that benefit multiple stakeholders. To solve large-scale or complex conservation planning problems, users should install the Gurobi optimization software (available from <https://www.gurobi.com/>) and the 'gurobi' R package (see Gurobi Installation Guide vignette for details). Users can also install the IBM CPLEX software (<https://www.ibm.com/products [...truncated...]
Author: Jeffrey O Hanson [aut] , Richard Schuster [aut, cre] , Nina Morrell [aut], Matthew Strimas-Mackey [aut] , Sandra Neubert [aut] , Brandon P M Edwards [aut] , Matthew E Watts [aut], Peter Arcese [aut] , Joseph R Bennett [aut] , Hugh P Possingham [aut]
Maintainer: Richard Schuster <richard.schuster@glel.carleton.ca>

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Package LightLogR updated to version 0.10.6 with previous version 0.10.3 dated 2026-04-28

Title: Process Data from Wearable Light Loggers and Optical Radiation Dosimeters
Description: Import, processing, validation, and visualization of personal light exposure measurement data from wearable devices. The package implements features such as the import of data and metadata files, conversion of common file formats, validation of light logging data, verification of crucial metadata, calculation of common parameters, and semi-automated analysis and visualization.
Author: Johannes Zauner [aut, cre] , Manuel Spitschan [aut] , Steffen Hartmeyer [aut] , European Partnership on Metrology [fnd] has received funding from the European Partnership on Metrology, co-financed by the European Union's Horizon Europe Research and [...truncated...]
Maintainer: Johannes Zauner <johannes.zauner@tum.de>

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Package graph4lg updated to version 2.0.0 with previous version 1.8.0 dated 2023-01-30

Title: Build Graphs for Landscape Genetics Analysis
Description: Build graphs for landscape genetics analysis. This set of functions can be used to import and convert spatial and genetic data initially in different formats, import landscape graphs created with 'Graphab' software (Foltete et al., 2021) <doi:10.1016/j.simpa.2021.100065>, make diagnosis plots of isolation by distance relationships in order to choose how to build genetic graphs, create graphs with a large range of pruning methods, weight their links with several genetic distances, plot and analyse graphs, compare them with other graphs. It uses functions from other packages such as 'adegenet' (Jombart, 2008) <doi:10.1093/bioinformatics/btn129> and 'igraph' (Csardi et Nepusz, 2006) <https://igraph.org/>. It also implements methods commonly used in landscape genetics to create graphs, described by Dyer et Nason (2004) <doi:10.1111/j.1365-294X.2004.02177.x> and Greenbaum et Fefferman (2017) <doi:10.1111/mec.14059>, and to analyse distance data (van Strien et a [...truncated...]
Author: Paul Savary [aut, cre] , Gilles Vuidel [ctb] , Tyler Rudolph [ctb], Alexandrine Daniel [ctb] , Jong Yoon Jeon [ctb]
Maintainer: Paul Savary <psavary@protonmail.com>

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Package future updated to version 1.76.0 with previous version 1.75.0 dated 2026-07-20

Title: Unified Parallel and Distributed Processing in R for Everyone
Description: The purpose of this package is to provide a lightweight and unified Future API for sequential and parallel processing of R expression via futures. The simplest way to evaluate an expression in parallel is to use `x %<-% { expression }` with `plan(multisession)`. This package implements sequential, multicore, multisession, and cluster futures. With these, R expressions can be evaluated on the local machine, in parallel a set of local machines, or distributed on a mix of local and remote machines. Extensions to this package implement additional backends for processing futures via compute cluster schedulers, etc. Because of its unified API, there is no need to modify any code in order switch from sequential on the local machine to, say, distributed processing on a remote compute cluster. Another strength of this package is that global variables and functions are automatically identified and exported as needed, making it straightforward to tweak existing code to make use of futures.
Author: Henrik Bengtsson [aut, cre, cph]
Maintainer: Henrik Bengtsson <henrikb@braju.com>

Diff between future versions 1.75.0 dated 2026-07-20 and 1.76.0 dated 2026-09-24

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Package ThomasJeffersonUniv (with last version 0.1.3) was removed from CRAN

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

2024-07-01 0.1.3
2024-04-30 0.1.2
2024-04-21 0.1.1
2022-05-18 0.1.0

Permanent link
Package tulpa updated to version 0.6.0 with previous version 0.5.0 dated 2026-09-21

Title: Templated Unified Library for Posterior Approximation in Bayesian Hierarchical Models
Description: A general-purpose engine for fitting Bayesian hierarchical models with spatial fields, temporal effects, spatially varying coefficients, and multiple inference backends. Scalable spatial structure includes Hilbert space approximate Gaussian processes (HSGP; Riutort-Mayol et al. 2023 <doi:10.1007/s11222-022-10167-2>), nearest-neighbor Gaussian processes (NNGP; Datta et al. 2016 <doi:10.1080/01621459.2015.1044091>), intrinsic conditional autoregressive models (ICAR; Besag, York, and Mollie 1991 <doi:10.1007/BF00116466>), the reparameterized Besag-York-Mollie model (BYM2; Riebler et al. 2016 <doi:10.1177/0962280216660421>), and stochastic partial differential equation fields (SPDE; Lindgren, Rue, and Lindstrom 2011 <doi:10.1111/j.1467-9868.2011.00777.x>). Temporal structure covers random walks, autoregressive processes, and Gaussian processes. Inference is tiered by correctness guarantee: exact Hamiltonian Monte Carlo with the No-U-Turn sampler, Laplace and n [...truncated...]
Author: Gilles Colling [aut, cre, cph] , Frances Y. Kuo [ctb, cph] , Stephen Joe [ctb, cph]
Maintainer: Gilles Colling <gilles.colling051@gmail.com>

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Package egfr updated to version 2.0.0 with previous version 1.1.1 dated 2026-06-26

Title: Estimated Glomerular Filtration Rate (eGFR) Calculators
Description: A comprehensive, vectorised toolkit for estimating glomerular filtration rate (eGFR) and creatinine clearance from serum creatinine, cystatin C, or both. Implements adult, paediatric, and neonatal equations, including the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equations (2009, 2012, 2021), the Modification of Diet in Renal Disease (MDRD) Study equation, Cockcroft-Gault, the European Kidney Function Consortium (EKFC) equations, the Full Age Spectrum (FAS) equations, the Lund-Malmoe equations, the Berlin Initiative Study (BIS) equations, the Schwartz bedside equation, the Chronic Kidney Disease in Children Under 25 (CKiD U25) equations, the Caucasian, Asian, Paediatric, and Adult (CAPA) cystatin C equation, and a neonatal equation. Helpers for body surface area, chronic kidney disease (CKD) staging following the Kidney Disease: Improving Global Outcomes (KDIGO) guideline, and unit conversions are included. Methods are described in Levey et al. (2009) <doi:10.7326/ [...truncated...]
Author: Markus Hovd [aut, cre, cph]
Maintainer: Markus Hovd <markus@hovd.io>

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Package AI4OfficialStats updated to version 0.2.0 with previous version 0.1.0 dated 2026-09-22

Title: Audit Statistical Fidelity of AI-Mediated Official Statistics
Description: Provides deterministic tools for auditing whether artificial intelligence systems preserve the numerical, semantic, contextual, temporal, geographic, unit, provenance, revision, transformation, and uncertainty properties of official statistics. Structured reference statistics and machine-generated claims can be compared using non-compensatory critical-error rules, weakest-link and geometric fidelity summaries, provenance graphs, and portable SHA-256 proof bundles. The package provides bounded connectors for official statistical services, an easy schema-detection and file-import layer for arbitrary official organisations, extensible provider registries, and a search-first natural- language verification layer that classifies statistical claims, selects suitable official sources, retrieves candidate evidence, matches statistical dimensions, and compares claimed values. If no reference year is stated, verification uses the latest available matching official observation and discloses the re [...truncated...]
Author: Hossein Hassani [aut], Steve MacFeely [aut], Leila Marvian Mashhad [aut, cre]
Maintainer: Leila Marvian Mashhad <leila.marveian@gmail.com>

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Package taxodist updated to version 0.8.0 with previous version 0.7.0 dated 2026-08-28

Title: Taxonomic Hierarchy Distances and Lineage Analysis
Description: Computes distances between taxonomic hierarchy nodes using lineage data retrieved from The Taxonomicon <http://taxonomicon.taxonomy.nl>. For distinct nodes, distance is defined as the reciprocal of the depth of their most recent common ancestor; identical nodes have distance zero. This definition yields an ultrametric within each connected hierarchy. Functions are provided for auditable name resolution, online or user-supplied lineage analysis, clade membership, pairwise and matrix distance calculation, hierarchical clustering, principal coordinates analysis, portable JSON analysis bundles, and cache management. Distance matrices are returned as base R 'dist' objects. The distances represent classification depth rather than evolutionary time or phylogenetic branch length.
Author: Rodrigo Fonseca Villa [aut, cre]
Maintainer: Rodrigo Fonseca Villa <rodrigo03.villa@gmail.com>

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Package NeutroCODsAnalysis updated to version 0.2.1 with previous version 0.2.0 dated 2026-08-21

Title: Neutrosophic Analysis Crossover Designs
Description: Provides methods for Neutrosophic Analysis of Variance (NANOVA) and Neutrosophic Analysis of Covariance (NANCOVA) for crossover designs, as well as NANOVA for multi-session designs with direct and residual effects using interval-valued observations. For crisp data, users can enter identical lower and upper values for the response and covariate variables to obtain results equivalent to classical Analysis of Variance (ANOVA) and Analysis of Covariance (ANCOVA), respectively. The basic concepts of neutrosophic statistics are based on Smarandache (2014) <https://fs.unm.edu/NeutrosophicStatistics.pdf>, while the analysis procedures implemented in this package are newly developed.
Author: Boyina Devi Priyanka [aut, ctb], Neethu R.S [aut, ctb], Cini Varghese [aut, ctb], Mohd Harun [aut, ctb], Anindita Datta [aut, ctb], Vinaykumar L.N. [aut, cre]
Maintainer: Vinaykumar L.N. <vinaymandya123@gmail.com>

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Package lglasso updated to version 2.0.0 with previous version 0.1.0 dated 2022-01-15

Title: Graphical Lasso for Longitudinal Data
Description: Estimate treatment-specific precision matrices (networks) from longitudinal high-dimensional normal data. The corresponding random effects are also estimated. It is motivated by the analysis of omics data in clinical trials where the longitudinal omics data becomes increasingly common. It includes both one-stage models (without treatment) and two-stage models (with one treatment). For details of the algorithms, please check the materials on its GitHub repo. If you have any questions, feel free to contact the maintainers through the email below.
Author: Jie Zhou [aut, cre, cph], Jiang Gui [aut], Weston Viles [aut], Anne Hoen [aut]
Maintainer: Jie Zhou <chowstat@gmail.com>

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Package languageserver updated to version 0.3.20 with previous version 0.3.19 dated 2026-09-13

Title: Language Server Protocol
Description: An implementation of the Language Server Protocol for R. The Language Server protocol is used by an editor client to integrate features like auto completion. See <https://microsoft.github.io/language-server-protocol/> for details.
Author: Randy Lai [aut, cre], Kun Ren [ctb]
Maintainer: Randy Lai <randy.cs.lai@gmail.com>

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Package glmnet updated to version 5.1 with previous version 5.0 dated 2026-05-04

Title: Lasso and Elastic-Net Regularized Generalized Linear Models
Description: Extremely efficient procedures for fitting the entire lasso or elastic-net regularization path for linear regression, logistic and multinomial regression models, Poisson regression, Cox model, multiple-response Gaussian, and the grouped multinomial regression; see <doi:10.18637/jss.v033.i01> and <doi:10.18637/jss.v039.i05>. There are two new and important additions. The family argument can be a GLM family object, which opens the door to any programmed family (<doi:10.18637/jss.v106.i01>). This comes with a modest computational cost, so when the built-in families suffice, they should be used instead. The other novelty is the relax option, which refits each of the active sets in the path unpenalized. The algorithm uses cyclical coordinate descent in a path-wise fashion, as described in the papers cited.
Author: Jerome Friedman [aut], Trevor Hastie [aut, cre], Rob Tibshirani [aut], Balasubramanian Narasimhan [aut], Kenneth Tay [aut], Noah Simon [aut], Junyang Qian [ctb], James Yang [aut], Jonathan Taylor [aut]
Maintainer: Trevor Hastie <hastie@stanford.edu>

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Package fabricQueryR updated to version 1.0.0 with previous version 0.2.1 dated 2026-04-03

Title: Access and Manage 'Microsoft Fabric'
Description: Access 'Microsoft Fabric' workspaces, items, and workload endpoints through its web application programming interfaces (APIs). Connect to data in 'OneLake', 'Lakehouse', 'Warehouse', semantic model, and 'Eventhouse' items, with support for 'DBI', 'Arrow', 'GraphQL', and 'Spark'. Manage files, tables, refreshes, jobs, schedules, ingestion, and long-running operations.
Author: Luka Koning [aut, cre, cph], Kennispunt Twente [fnd]
Maintainer: Luka Koning <koningluka@gmail.com>

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Package microeco updated to version 2.4.0 with previous version 2.3.0 dated 2026-07-07

Title: Microbial Community Ecology Data Analysis
Description: A series of data analysis approaches for microbiome data based on the R6 class. The classes are designed for data preprocessing, niche analysis, taxonomic abundance plot, alpha diversity analysis, beta diversity analysis, differential abundance test, null model analysis, network analysis, machine learning, environmental data analysis, functional redundancy analysis, metabolites analysis, etc.
Author: Chi Liu [aut, cre], Felipe R. P. Mansoldo [ctb], Minjie Yao [ctb], Xiangzhen Li [ctb]
Maintainer: Chi Liu <liuchi0426@126.com>

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Package jmvcore updated to version 28.3 with previous version 2.7.38 dated 2026-07-18

Title: Dependencies for the 'jamovi' Framework
Description: A framework for creating rich interactive analyses for the jamovi platform (see <https://www.jamovi.org> for more information).
Author: Jonathon Love [aut, cre, cph]
Maintainer: Jonathon Love <jon@thon.cc>

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Package ggtangle updated to version 0.1.3 with previous version 0.1.2 dated 2026-04-22

Title: Draw Network with Data
Description: Extends the 'ggplot2' plotting system to support network visualization. Inspired by the 'Method 1' in 'ggtree' (G Yu (2018) <doi:10.1093/molbev/msy194>), 'ggtangle' is designed to work with network associated data.
Author: Guangchuang Yu [aut, cre]
Maintainer: Guangchuang Yu <guangchuangyu@gmail.com>

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Package BGGM updated to version 2.2.0 with previous version 2.1.6 dated 2025-12-02

Title: Bayesian Gaussian Graphical Models
Description: Fit Bayesian Gaussian graphical models. The methods are separated into two Bayesian approaches for inference: hypothesis testing and estimation. There are extensions for confirmatory hypothesis testing, comparing Gaussian graphical models, and node wise predictability. These methods were recently introduced in the Gaussian graphical model literature, including Williams (2019) <doi:10.31234/osf.io/x8dpr>, Williams and Mulder (2019) <doi:10.31234/osf.io/ypxd8>, Williams, Rast, Pericchi, and Mulder (2019) <doi:10.31234/osf.io/yt386>.
Author: Donald Williams [aut], Joris Mulder [aut], Philippe Rast [aut, cre]
Maintainer: Philippe Rast <rast.ph@gmail.com>

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Package BarcodingR updated to version 1.0-4 with previous version 1.0-3 dated 2020-04-14

Title: Species Identification using DNA Barcodes
Description: To perform species identification using DNA barcodes.
Author: Ai-bing ZHANG [aut, cre], Meng-di HAO [aut], Cai-qing YANG [aut], Zhi-yong SHI [aut]
Maintainer: Ai-bing ZHANG <Zhangab2008@mail.cnu.edu.cn>

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Package iCAMP updated to version 1.9.1 with previous version 1.8.6 dated 2026-08-25

Title: Infer Community Assembly Mechanisms by Phylogenetic-Bin-Based Null Model Analysis
Description: To implement a general framework to quantitatively infer Community Assembly Mechanisms by Phylogenetic-bin-based null model analysis, abbreviated as 'iCAMP' (Ning et al 2020) <doi:10.1038/s41467-020-18560-z>. It can quantitatively assess the relative importance of different community assembly processes, such as selection, dispersal, and drift, for both communities and each phylogenetic group ('bin'). Each bin usually consists of different taxa from a family or an order. The package also provides functions to implement some other published methods, including neutral taxa percentage (Burns et al 2016) <doi:10.1038/ismej.2015.142> based on neutral theory model and quantifying assembly processes based on entire-community null models ('QPEN', Stegen et al 2013) <doi:10.1038/ismej.2013.93>. It also includes some handy functions, particularly for big datasets, such as phylogenetic and taxonomic null model analysis at both community and bin levels, between-taxa niche differen [...truncated...]
Author: Daliang Ning [aut, cre]
Maintainer: Daliang Ning <ningdaliang@ou.edu>

Diff between iCAMP versions 1.8.6 dated 2026-08-25 and 1.9.1 dated 2026-09-24

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Package enrichit updated to version 0.2.5 with previous version 0.2.4 dated 2026-09-17

Title: 'C++' Implementations of Functional Enrichment Analysis
Description: Fast implementations of functional enrichment analysis methods using 'C++' via 'Rcpp'. Currently provides Over-Representation Analysis (ORA), Gene Set Enrichment Analysis (GSEA), Weighted Enrichment Analysis for ORA and GSEA, Network-based Set Enrichment Analysis (NSEA), multi-layer network-based enrichment, and multi-omics integration workflows. Additional features include early fusion at the feature level, late fusion at the pathway level, multi-omics contribution tracing, topology-aware explanation helpers, Bayesian term selection, and extremely fast Random Walk with Restart (RWR) using 'RcppEigen'. The enrichment methods build on GSEA by Subramanian et al. (2005) <doi:10.1073/pnas.0506580102>, the multilevel strategy derived from 'fgsea' by Korotkevich et al. (2021) <doi:10.1101/060012>, and network-based enrichment ideas described by Glaab et al. (2012) <doi:10.1093/bioinformatics/bts389>.
Author: Guangchuang Yu [aut, cre]
Maintainer: Guangchuang Yu <guangchuangyu@gmail.com>

Diff between enrichit versions 0.2.4 dated 2026-09-17 and 0.2.5 dated 2026-09-24

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New package rapsimng.lupin with initial version 0.1.0
Package: rapsimng.lupin
Title: Crop-Specific Functions and Parameters for APSIM Next Generation Lupin Model
Version: 0.1.0
Description: Provides lupin-specific functions, processes and parameter sets used by lupin model in the Agricultural Production Systems sIMulator ('APSIM') Next Generation. Includes tools for crop process calculations, parameter management and customisation, enabling users to explore, modify and apply lupin model components.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: optree (>= 0.1.1), tidyweather (>= 0.3.0)
Suggests: testthat (>= 3.0.0)
URL: https://lupin.rapsimng.bangyou.me/, https://github.com/byzheng/rapsimng.lupin
BugReports: https://github.com/byzheng/rapsimng.lupin/issues
NeedsCompilation: no
Packaged: 2026-09-14 08:06:25 UTC; zhe00a
Author: Bangyou Zheng [aut, cre]
Maintainer: Bangyou Zheng <zheng.bangyou@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-24 05:30:02 UTC

More information about rapsimng.lupin at CRAN
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New package depguard with initial version 0.1.0
Package: depguard
Title: Manifest-Based Dependency Conflict Detection for Sandboxed R Sessions
Version: 0.1.0
Description: Provides lightweight, manifest-based checking of R package dependencies (including transitive dependencies) against the currently installed environment, without requiring a full project lockfile. Designed for sandboxed or ephemeral notebook environments (e.g. Kaggle, Colab, Binder) where 'renv'-style lockfile ownership is impractical. Includes session snapshot/diff tools (building on 'sessioninfo') to detect when an install silently changes the version of a package that is already loaded, and optional single-package version rollback.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 3.5)
Imports: tools, utils, sessioninfo, cli
Suggests: remotes, pak, testthat (>= 3.0.0), knitr, rmarkdown, spelling
VignetteBuilder: knitr
URL: https://github.com/sunraycodes/depguard
BugReports: https://github.com/sunraycodes/depguard/issues
NeedsCompilation: no
Packaged: 2026-09-14 06:59:13 UTC; Kartik
Author: Samruddhi Amol Shah [aut, cre], Kartik Patel [aut], Amrit Pal [ctb]
Maintainer: Samruddhi Amol Shah <samruddhi.bitnbyte@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-24 05:20:02 UTC

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New package RserveTS with initial version 0.8.3
Package: RserveTS
Title: Typed Application Contracts for 'Rserve'
Version: 0.8.3
Description: Defines a typed application contract between R backends and 'TypeScript' clients over 'Rserve'. Users specify the API architecture with typed object capability (Ocap) functions and compile matching 'TypeScript' schemas and deployment scripts for the server. The companion library 'rserve-ts', available on npm <https://www.npmjs.com/package/rserve-ts>, provides the client-side runtime that consumes those schemas.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0), objectProperties, objectSignals
Imports: methods, rlang, Rserve, stats
Suggests: testthat (>= 3.0.0), withr
URL: https://tomelliott.co.nz/RserveTS/, https://github.com/tmelliott/RserveTS
BugReports: https://github.com/tmelliott/RserveTS/issues
NeedsCompilation: no
Packaged: 2026-09-14 03:40:29 UTC; tom
Author: Tom Elliott [aut, cre]
Maintainer: Tom Elliott <tom@inzight.co.nz>
Repository: CRAN
Date/Publication: 2026-09-24 04:40:02 UTC

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New package rapsimng.wheat with initial version 0.1.0
Package: rapsimng.wheat
Title: Crop-Specific Functions and Parameters for APSIM Next Generation Wheat Model
Version: 0.1.0
Description: Provides wheat-specific functions, processes and parameter sets used by wheat model in the Agricultural Production Systems sIMulator ('APSIM') Next Generation. Includes tools for crop process calculations, parameter management and customisation, enabling users to explore, modify and apply wheat model components.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: optree, tidyweather
Suggests: testthat (>= 3.0.0)
URL: https://wheat.rapsimng.bangyou.me/, https://github.com/byzheng/rapsimng.wheat
BugReports: https://github.com/byzheng/rapsimng.wheat/issues
NeedsCompilation: no
Packaged: 2026-09-14 05:16:34 UTC; zhe00a
Author: Bangyou Zheng [aut, cre]
Maintainer: Bangyou Zheng <zheng.bangyou@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-24 05:00:02 UTC

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New package rapsimng.lentil with initial version 0.1.0
Package: rapsimng.lentil
Title: Crop-Specific Functions and Parameters for APSIM Next Generation Lentil Model
Version: 0.1.0
Description: Provides lentil-specific functions, processes and parameter sets used by lentil model in the Agricultural Production Systems sIMulator ('APSIM') Next Generation. Includes tools for crop process calculations, parameter management and customisation, enabling users to explore, modify and apply lentil model components.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: optree (>= 0.1.1), tidyweather (>= 0.3.0)
Suggests: testthat (>= 3.0.0)
URL: https://lentil.rapsimng.bangyou.me/, https://github.com/byzheng/rapsimng.lentil
BugReports: https://github.com/byzheng/rapsimng.lentil/issues
NeedsCompilation: no
Packaged: 2026-09-14 05:20:20 UTC; zhe00a
Author: Bangyou Zheng [aut, cre]
Maintainer: Bangyou Zheng <zheng.bangyou@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-24 05:00:08 UTC

More information about rapsimng.lentil at CRAN
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New package rapsimng.fababean with initial version 0.1.0
Package: rapsimng.fababean
Title: Crop-Specific Functions and Parameters for APSIM Next Generation Fababean Model
Version: 0.1.0
Description: Provides fababean-specific functions, processes and parameter sets used by fababean model in the Agricultural Production Systems sIMulator ('APSIM') Next Generation. Includes tools for crop process calculations, parameter management and customisation, enabling users to explore, modify and apply fababean model components.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: optree, tidyweather (>= 0.3.0)
Suggests: testthat (>= 3.0.0)
URL: https://fababean.rapsimng.bangyou.me/, https://github.com/byzheng/rapsimng.fababean
BugReports: https://github.com/byzheng/rapsimng.fababean/issues
NeedsCompilation: no
Packaged: 2026-09-14 05:22:07 UTC; zhe00a
Author: Bangyou Zheng [aut, cre]
Maintainer: Bangyou Zheng <zheng.bangyou@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-24 05:00:14 UTC

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New package rapsimng.chickpea with initial version 0.1.0
Package: rapsimng.chickpea
Title: Crop-Specific Functions and Parameters for APSIM Next Generation Chickpea Model
Version: 0.1.0
Description: Provides chickpea-specific functions, processes and parameter sets used by chickpea model in the Agricultural Production Systems sIMulator ('APSIM') Next Generation. Includes tools for crop process calculations, parameter management and customisation, enabling users to explore, modify and apply chickpea model components.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: optree, tidyweather (>= 0.3.0)
Suggests: testthat (>= 3.0.0)
URL: https://chickpea.rapsimng.bangyou.me/, https://github.com/byzheng/rapsimng.chickpea
BugReports: https://github.com/byzheng/rapsimng.chickpea/issues
NeedsCompilation: no
Packaged: 2026-09-14 05:24:15 UTC; zhe00a
Author: Bangyou Zheng [aut, cre]
Maintainer: Bangyou Zheng <zheng.bangyou@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-24 05:00:19 UTC

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New package rapsimng.canola with initial version 0.1.0
Package: rapsimng.canola
Title: Crop-Specific Functions and Parameters for APSIM Next Generation Canola Model
Version: 0.1.0
Description: Provides canola-specific functions, processes and parameter sets used by canola model in the Agricultural Production Systems sIMulator ('APSIM') Next Generation. Includes tools for crop process calculations, parameter management and customisation, enabling users to explore, modify and apply canola model components.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: optree, tidyweather
Suggests: testthat (>= 3.0.0)
URL: https://canola.rapsimng.bangyou.me/, https://github.com/byzheng/rapsimng.canola
BugReports: https://github.com/byzheng/rapsimng.canola/issues
NeedsCompilation: no
Packaged: 2026-09-14 05:26:29 UTC; zhe00a
Author: Bangyou Zheng [aut, cre]
Maintainer: Bangyou Zheng <zheng.bangyou@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-24 05:00:25 UTC

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New package genoaligner with initial version 1.0.0
Package: genoaligner
Title: GPU-Portable Pairwise Sequence Alignment (WFA + Smith-Waterman)
Version: 1.0.0
Description: Pairwise sequence alignment from one portable C++17 core: edit-distance (Levenshtein / WFA-equivalent) and Smith-Waterman local alignment, both with score and CIGAR reconstruction. The core builds and runs anywhere (it is the CPU backend, so it needs no GPU toolchain); the wavefront/GPU backend (ROCm/CUDA) computes the same results with acceleration and is tracked in the sibling C++ repository. A batch API aligns many pairs in one call and reports how many were resolved, so silent under-serving is impossible. Designed to slot into data.frame/tibble pipelines.
URL: https://github.com/alrobles/genoaligner-r, https://alrobles.github.io/genoaligner-r/
BugReports: https://github.com/alrobles/genoaligner-r/issues
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-US
Depends: R (>= 4.1.0)
Imports: Rcpp
LinkingTo: Rcpp
Suggests: testthat (>= 3.0.0), knitr, rmarkdown, spelling
SystemRequirements: C++17
NeedsCompilation: yes
Packaged: 2026-09-13 20:33:24 UTC; alrobles
Author: Angel Robles-Fernandez [aut, cre]
Maintainer: Angel Robles-Fernandez <a.l.robles.fernandez@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-24 04:20:02 UTC

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New package gcemod with initial version 0.3.0
Package: gcemod
Title: Generalized Competing Event Models with Lunn-McNeil Testing
Version: 0.3.0
Date: 2026-09-02
Description: Fits generalized competing event (GCE) models and estimates covariate effects on omega-plus, the ratio of the hazard for an event of interest to the hazard for a competing event, on both the cause-specific (Cox) and subdistribution (Fine-Gray) hazard scales. Confidence intervals and p-values are obtained from the Lunn-McNeil (1995) stacked (augmented) data approach. The package builds GCE risk scores from the model linear predictor, identifies risk-score cutpoints that maximize the separation in omega-plus between groups, and produces cumulative incidence ("alligator") plots by risk group and calibration plots of predicted versus observed omega-plus. It also compares covariate effects across the primary, competing, and total (composite) events, and estimates covariate effects on the ratio of cumulative incidence functions (a cumulative-incidence-scale GCE model). Methods follow Carmona et al. (2014) <doi:10.1016/j.ijrobp.2014.03.047>, Mell et al. (2024) <doi:10.1016/j.eururo.2 [...truncated...]
License: GPL (>= 2)
Encoding: UTF-8
Language: en-US
LazyData: true
Depends: R (>= 3.5.0)
Imports: survival, cmprsk, ggplot2 (>= 3.5.2), patchwork, stats
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-09-03 00:37:58 UTC; lorenmell
Author: Loren Mell [aut, cre]
Maintainer: Loren Mell <lmell@ucsd.edu>
Repository: CRAN
Date/Publication: 2026-09-24 04:20:07 UTC

More information about gcemod at CRAN
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