Wed, 15 Oct 2025

Package rsynthbio updated to version 3.0.0 with previous version 2.2.1 dated 2025-09-12

Title: Synthesize Bio API Wrapper
Description: Access Synthesize Bio models from their API <https://app.synthesize.bio/> using this wrapper that provides a convenient interface to the Synthesize Bio API, allowing users to generate realistic gene expression data based on specified biological conditions. This package enables researchers to easily access AI-generated transcriptomic data for various modalities including bulk RNA-seq, single-cell RNA-seq, microarray data, and more.
Author: Candace Savonen [aut, cre]
Maintainer: Candace Savonen <cansav09@gmail.com>

Diff between rsynthbio versions 2.2.1 dated 2025-09-12 and 3.0.0 dated 2025-10-15

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Package simDAG updated to version 0.4.1 with previous version 0.4.0 dated 2025-08-27

Title: Simulate Data from a DAG and Associated Node Information
Description: Simulate complex data from a given directed acyclic graph and information about each individual node. Root nodes are simply sampled from the specified distribution. Child Nodes are simulated according to one of many implemented regressions, such as logistic regression, linear regression, poisson regression or any other function. Also includes a comprehensive framework for discrete-time simulation, and networks-based simulation which can generate even more complex longitudinal and dependent data. For more details, see Robin Denz, Nina Timmesfeld (2025) <doi:10.48550/arXiv.2506.01498>.
Author: Robin Denz [aut, cre], Katharina Meiszl [aut]
Maintainer: Robin Denz <robin.denz@rub.de>

Diff between simDAG versions 0.4.0 dated 2025-08-27 and 0.4.1 dated 2025-10-15

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Package whep updated to version 0.2.0 with previous version 0.1.0 dated 2025-07-25

Title: Processing Agro-Environmental Data
Description: A set of tools for processing and analyzing data developed in the context of the "Who Has Eaten the Planet" (WHEP) project, funded by the European Research Council (ERC). For more details on multi-regional input–output model "Food and Agriculture Biomass Input–Output" (FABIO) see Bruckner et al. (2019) <doi:10.1021/acs.est.9b03554>.
Author: Catalin Covaci [aut, cre] , Eduardo Aguilera [aut, cph] , Joao Serra [ctb] , European Research Council [fnd]
Maintainer: Catalin Covaci <catalin.covaci@csic.es>

Diff between whep versions 0.1.0 dated 2025-07-25 and 0.2.0 dated 2025-10-15

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Package ClassificationEnsembles updated to version 0.7.1 with previous version 0.7.0 dated 2025-10-12

Title: Automatically Builds 12 Classification Models
Description: Automatically builds 12 classification models from data. The package returns 26 plots, 5 tables and a summary report. The package automatically builds six individual classification models, including error (RMSE) and predictions. That data is used to create an ensemble, which is then modeled using six methods. The process is repeated as many times as the user requests. The mean of the results are presented in a summary table. The package returns the confusion matrices for all 12 models, tables of the correlation of the numeric data, the results of the variance inflation process, the head of the ensemble and the head of the data frame.
Author: Russ Conte [aut, cre, cph]
Maintainer: Russ Conte <russconte@mac.com>

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Package impectR updated to version 2.5.1 with previous version 2.4.3 dated 2025-09-08

Title: Access Data from the 'Impect' API
Description: Pull data from the 'Impect' Customer API <https://glossary.impect.com/api-design>. The package can retrieve data such as events or match sums.
Author: Impect GmbH [cph], Florian Schmitt [aut, cre], Thomas Walentin [ctb]
Maintainer: Florian Schmitt <florian.schmitt@impect.com>

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Package fastbeta updated to version 0.5.0 with previous version 0.4.0 dated 2025-04-28

Title: Fast Approximation of Time-Varying Infectious Disease Transmission Rates
Description: A fast method for approximating time-varying infectious disease transmission rates from disease incidence time series and other data, based on a discrete time approximation of an SEIR model, as analyzed in Jagan et al. (2020) <doi:10.1371/journal.pcbi.1008124>.
Author: Mikael Jagan [aut, cre]
Maintainer: Mikael Jagan <jaganmn@mcmaster.ca>

Diff between fastbeta versions 0.4.0 dated 2025-04-28 and 0.5.0 dated 2025-10-15

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Package curephEM updated to version 0.3.2 with previous version 0.3.0 dated 2024-02-02

Title: NPMLE for Logistic-Cox Cure-Rate Model
Description: Expectation-Maximization (EM) algorithm for point estimation and variance estimation to the nonparametric maximum likelihood estimator (NPMLE) for logistic-Cox cure-rate model with left truncation and right- censoring. See Hou, Chambers and Xu (2017) <doi:10.1007/s10985-017-9415-2>.
Author: Evan Ren [aut], Jue Hou [cre]
Maintainer: Jue Hou <hou00123@umn.edu>

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Package catSurv updated to version 1.6.0 with previous version 1.5.0 dated 2022-12-03

Title: Computerized Adaptive Testing for Survey Research
Description: Provides methods of computerized adaptive testing for survey researchers. See Montgomery and Rossiter (2020) <doi:10.1093/jssam/smz027>. Includes functionality for data fit with the classic item response methods including the latent trait model, the Birnbaum three parameter model, the graded response, and the generalized partial credit model. Additionally, includes several ability parameter estimation and item selection routines. During item selection, all calculations are done in compiled C++ code.
Author: Jacob Montgomery [aut], Erin Rossiter [aut, cre]
Maintainer: Erin Rossiter <erossite@nd.edu>

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Package rrda updated to version 0.2.3 with previous version 0.1.1 dated 2025-04-29

Title: Ridge Redundancy Analysis for High-Dimensional Omics Data
Description: Efficient framework for ridge redundancy analysis (rrda), tailored for high-dimensional omics datasets where the number of predictors exceeds the number of samples. The method leverages Singular Value Decomposition (SVD) to avoid direct inversion of the covariance matrix, enhancing scalability and performance. It also introduces a memory-efficient storage strategy for coefficient matrices, enabling practical use in large-scale applications. The package supports cross-validation for selecting regularization parameters and reduced-rank dimensions, making it a robust and flexible tool for multivariate analysis in omics research. Please refer to our article (Yoshioka et al., 2025) for more details.
Author: Hayato Yoshioka [aut] , Julie Aubert [aut, cre] , Tristan Mary-Huard [aut]
Maintainer: Julie Aubert <julie.aubert@inrae.fr>

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Package rgee updated to version 1.1.8 with previous version 1.1.7 dated 2023-09-27

Title: R Bindings for Calling the 'Earth Engine' API
Description: Earth Engine <https://earthengine.google.com/> client library for R. All of the 'Earth Engine' API classes, modules, and functions are made available. Additional functions implemented include importing (exporting) of Earth Engine spatial objects, extraction of time series, interactive map display, assets management interface, and metadata display. See <https://r-spatial.github.io/rgee/> for further details.
Author: Cesar Aybar [aut] , Wu Qiusheng [ctb] , Lesly Bautista [ctb] , Roy Yali [ctb] , Antony Barja [ctb] , Kevin Ushey [ctb], Jeroen Ooms [ctb] , Tim Appelhans [ctb], JJ Allaire [ctb], Yuan Tang [ctb], Samapriya Roy [ctb], MariaElena Adauto [ctb] , Gabriel [...truncated...]
Maintainer: Matthieu Stigler <Matthieu.Stigler@gmail.com>

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Package PatientLevelPrediction updated to version 6.5.1 with previous version 6.5.0 dated 2025-07-25

Title: Develop Clinical Prediction Models Using the Common Data Model
Description: A user friendly way to create patient level prediction models using the Observational Medical Outcomes Partnership Common Data Model. Given a cohort of interest and an outcome of interest, the package can use data in the Common Data Model to build a large set of features. These features can then be used to fit a predictive model with a number of machine learning algorithms. This is further described in Reps (2017) <doi:10.1093/jamia/ocy032>.
Author: Egill Fridgeirsson [aut, cre], Jenna Reps [aut], Martijn Schuemie [aut], Marc Suchard [aut], Patrick Ryan [aut], Peter Rijnbeek [aut], Observational Health Data Science and Informatics [cph]
Maintainer: Egill Fridgeirsson <e.fridgeirsson@erasmusmc.nl>

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Package mlexperiments updated to version 0.0.8 with previous version 0.0.7 dated 2025-09-09

Title: Machine Learning Experiments
Description: Provides 'R6' objects to perform parallelized hyperparameter optimization and cross-validation. Hyperparameter optimization can be performed with Bayesian optimization (via 'ParBayesianOptimization' <https://cran.r-project.org/package=ParBayesianOptimization>) and grid search. The optimized hyperparameters can be validated using k-fold cross-validation. Alternatively, hyperparameter optimization and validation can be performed with nested cross-validation. While 'mlexperiments' focuses on core wrappers for machine learning experiments, additional learner algorithms can be supplemented by inheriting from the provided learner base class.
Author: Lorenz A. Kapsner [cre, aut, cph]
Maintainer: Lorenz A. Kapsner <lorenz.kapsner@gmail.com>

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Package planr updated to version 0.6.2 with previous version 0.6.1 dated 2025-09-25

Title: Tools for Supply Chain Management, Demand and Supply Planning
Description: Perform flexible and quick calculations for Demand and Supply Planning, such as projected inventories and coverages, as well as replenishment plan. For any time bucket, daily, weekly or monthly, and any granularity level, product or group of products.
Author: Nicolas Nguyen [aut, cre]
Maintainer: Nicolas Nguyen <nikonguyen@yahoo.fr>

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Package gdverse updated to version 1.5.1 with previous version 1.5 dated 2025-10-10

Title: Analysis of Spatial Stratified Heterogeneity
Description: Detecting spatial associations via spatial stratified heterogeneity, accounting for spatial dependencies, interpretability, complex interactions, and robust stratification. In addition, it supports the spatial stratified heterogeneity family described in Lv et al. (2025)<doi:10.1111/tgis.70032>.
Author: Wenbo Lv [aut, cre, cph] , Yangyang Lei [aut] , Fangmei Liu [aut] , Jianwu Yan [aut] , Yongze Song [aut] , Wufan Zhao [aut]
Maintainer: Wenbo Lv <lyu.geosocial@gmail.com>

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Package gadget3 updated to version 0.14-0 with previous version 0.13-0 dated 2025-04-19

Title: Globally-Applicable Area Disaggregated General Ecosystem Toolbox V3
Description: A framework to assist creation of marine ecosystem models, generating either 'R' or 'C++' code which can then be optimised using the 'TMB' package and standard 'R' tools. Principally designed to reproduce gadget2 models in 'TMB', but can be extended beyond gadget2's capabilities. Kasper Kristensen, Anders Nielsen, Casper W. Berg, Hans Skaug, Bradley M. Bell (2016) <doi:10.18637/jss.v070.i05> "TMB: Automatic Differentiation and Laplace Approximation.". Begley, J., & Howell, D. (2004) <https://core.ac.uk/download/pdf/225936648.pdf> "An overview of Gadget, the globally applicable area-disaggregated general ecosystem toolbox. ICES.".
Author: Jamie Lentin [aut, cre] , Bjarki Thor Elvarsson [aut] , William Butler [aut] , Marine and Freshwater Research Institute [cph]
Maintainer: Jamie Lentin <lentinj@shuttlethread.com>

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Package CITMIC updated to version 0.1.3 with previous version 0.1.2 dated 2024-11-08

Title: Estimation of Cell Infiltration Based on Cell Crosstalk
Description: A systematic biology tool was developed to identify cell infiltration via Individualized Cell-Cell interaction network. 'CITMIC' first constructed a weighted cell interaction network through integrating Cell-target interaction information, molecular function data from Gene Ontology (GO) database and gene transcriptomic data in specific sample, and then, it used a network propagation algorithm on the network to identify cell infiltration for the sample. Ultimately, cell infiltration in the patient dataset was obtained by normalizing the centrality scores of the cells.
Author: Junwei Han [aut, cre, cph], Xilong Zhao [aut]
Maintainer: Junwei Han <hanjunwei1981@163.com>

Diff between CITMIC versions 0.1.2 dated 2024-11-08 and 0.1.3 dated 2025-10-15

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Package pacotest updated to version 0.4.3 with previous version 0.4.2 dated 2022-11-04

Title: Testing for Partial Copulas and the Simplifying Assumption in Vine Copulas
Description: Routines for two different test types, the Constant Conditional Correlation (CCC) test and the Vectorial Independence (VI) test are provided (Kurz and Spanhel (2022) <doi:10.1214/22-EJS2051>). The tests can be applied to check whether a conditional copula coincides with its partial copula. Functions to test whether a regular vine copula satisfies the so-called simplifying assumption or to test a single copula within a regular vine copula to be a (j-1)-th order partial copula are available. The CCC test comes with a decision tree approach to allow testing in high-dimensional settings.
Author: Malte S. Kurz [aut, cre]
Maintainer: Malte S. Kurz <mkurz-software@gmx.de>

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Package frailtypack updated to version 3.7.1 with previous version 3.7.0 dated 2025-03-06

Title: Shared, Joint (Generalized) Frailty Models; Surrogate Endpoints
Description: The following several classes of frailty models using a penalized likelihood estimation on the hazard function but also a parametric estimation can be fit using this R package: 1) A shared frailty model (with gamma or log-normal frailty distribution) and Cox proportional hazard model. Clustered and recurrent survival times can be studied. 2) Additive frailty models for proportional hazard models with two correlated random effects (intercept random effect with random slope). 3) Nested frailty models for hierarchically clustered data (with 2 levels of clustering) by including two iid gamma random effects. 4) Joint frailty models in the context of the joint modelling for recurrent events with terminal event for clustered data or not. A joint frailty model for two semi-competing risks and clustered data is also proposed. 5) Joint general frailty models in the context of the joint modelling for recurrent events with terminal event data with two independent frailty terms. 6) Joint Neste [...truncated...]
Author: Virginie Rondeau [aut, cre] , Juan R. Gonzalez [aut], Yassin Mazroui [aut], Audrey Mauguen [aut], Amadou Diakite [aut], Alexandre Laurent [aut], Myriam Lopez [aut], Agnieszka Krol [aut], Casimir L. Sofeu [aut], Julien Dumerc [aut], Denis Rustand [aut [...truncated...]
Maintainer: Virginie Rondeau <virginie.rondeau@u-bordeaux.fr>

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Package expss updated to version 0.11.7 with previous version 0.11.6 dated 2023-07-15

Title: Tables, Labels and Some Useful Functions from Spreadsheets and 'SPSS' Statistics
Description: Package computes and displays tables with support for 'SPSS'-style labels, multiple and nested banners, weights, multiple-response variables and significance testing. There are facilities for nice output of tables in 'knitr', 'Shiny', '*.xlsx' files, R and 'Jupyter' notebooks. Methods for labelled variables add value labels support to base R functions and to some functions from other packages. Additionally, the package brings popular data transformation functions from 'SPSS' Statistics and 'Excel': 'RECODE', 'COUNT', 'COUNTIF', 'VLOOKUP' and etc. These functions are very useful for data processing in marketing research surveys. Package intended to help people to move data processing from 'Excel' and 'SPSS' to R.
Author: Gregory Demin [aut, cre], Sebastian Jeworutzki [ctb] , Dan Chaltiel [ctb], John Williams [ctb], Tom Elliott [ctb]
Maintainer: Gregory Demin <gdemin@gmail.com>

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Package Silhouette updated to version 0.9.6 with previous version 0.9.4 dated 2025-07-30

Title: Proximity Measure Based Diagnostics for Standard, Soft, and Multi-Way Clustering
Description: Quantifies clustering quality by measuring both cohesion within clusters and separation between clusters. Implements advanced silhouette width computations for diverse clustering structures, including: simplified silhouette (Van der Laan et al., 2003) <doi:10.1080/0094965031000136012>, Probability of Alternative Cluster normalization methods (Raymaekers & Rousseeuw, 2022) <doi:10.1080/10618600.2022.2050249>, fuzzy clustering and silhouette diagnostics using membership probabilities (Campello & Hruschka, 2006; Menardi, 2011; Bhat & Kiruthika, 2024) <doi:10.1016/j.fss.2006.07.006>, <doi:10.1007/s11222-010-9169-0>, <doi:10.1080/23737484.2024.2408534>, and multi-way clustering extensions such as block and tensor clustering (Schepers et al., 2008; Bhat & Kiruthika, 2025) <doi:10.1007/s00357-008-9005-9>, <doi:10.21203/rs.3.rs-6973596/v1>. Provides tools for computation and visualization (Rousseeuw, 1987) <doi:10.1016/0377-0427(87)9 [...truncated...]
Author: Shrikrishna Bhat K [aut, cre, cph] , Kiruthika C [aut]
Maintainer: Shrikrishna Bhat K <skbhat.in@gmail.com>

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Package sentopics readmission to version 0.7.6 with previous version 0.7.5 dated 2025-09-29

Title: Tools for Joint Sentiment and Topic Analysis of Textual Data
Description: A framework that joins topic modeling and sentiment analysis of textual data. The package implements a fast Gibbs sampling estimation of Latent Dirichlet Allocation (Griffiths and Steyvers (2004) <doi:10.1073/pnas.0307752101>) and Joint Sentiment/Topic Model (Lin, He, Everson and Ruger (2012) <doi:10.1109/TKDE.2011.48>). It offers a variety of helpers and visualizations to analyze the result of topic modeling. The framework also allows enriching topic models with dates and externally computed sentiment measures. A flexible aggregation scheme enables the creation of time series of sentiment or topical proportions from the enriched topic models. Moreover, a novel method jointly aggregates topic proportions and sentiment measures to derive time series of topical sentiment.
Author: Olivier Delmarcelle [aut, cre] , Samuel Borms [ctb] , Chengua Lin [cph] , Yulan He [cph] , Jose Bernardo [cph] , David Robinson [cph] ), Julia Silge [cph] , ORCID: <https://orcid.org/0000-0002-3671-836X>)
Maintainer: Olivier Delmarcelle <delmarcelle.olivier@gmail.com>

This is a re-admission after prior archival of version 0.7.5 dated 2025-09-29

Diff between sentopics versions 0.7.5 dated 2025-09-29 and 0.7.6 dated 2025-10-15

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Package rhoR updated to version 1.3.1 with previous version 1.3.0.3 dated 2020-09-13

Title: Rho for Inter Rater Reliability
Description: Rho is used to test the generalization of inter rater reliability (IRR) statistics. Calculating rho starts by generating a large number of simulated, fully-coded data sets: a sizable collection of hypothetical populations, all of which have a kappa value below a given threshold -- which indicates unacceptable agreement. Then kappa is calculated on a sample from each of those sets in the collection to see if it is equal to or higher than the kappa in then real sample. If less than five percent of the distribution of samples from the simulated data sets is greater than actual observed kappa, the null hypothesis is rejected and one can conclude that if the two raters had coded the rest of the data, we would have acceptable agreement (kappa above the threshold).
Author: Brendan Eagan [aut], Brad Rogers [aut], Rebecca Pozen [aut], Cody L Marquart [cre, aut] , David Williamson Shaffer [aut]
Maintainer: Cody L Marquart <cody.marquart@wisc.edu>

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Package mlr3fda updated to version 0.3.0 with previous version 0.2.0 dated 2024-07-22

Title: Extending 'mlr3' to Functional Data Analysis
Description: Extends the 'mlr3' ecosystem to functional analysis by adding support for irregular and regular functional data as defined in the 'tf' package. The package provides 'PipeOps' for preprocessing functional columns and for extracting scalar features, thereby allowing standard machine learning algorithms to be applied afterwards. Available operations include simple functional features such as the mean or maximum, smoothing, interpolation, flattening, and functional 'PCA'.
Author: Sebastian Fischer [aut, cre] , Maximilian Muecke [aut] , Fabian Scheipl [ctb] , Bernd Bischl [ctb]
Maintainer: Sebastian Fischer <sebf.fischer@gmail.com>

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Package EvidenceSynthesis updated to version 1.1.0 with previous version 1.0.0 dated 2025-08-26

Title: Synthesizing Causal Evidence in a Distributed Research Network
Description: Routines for combining causal effect estimates and study diagnostics across multiple data sites in a distributed study, without sharing patient-level data. Allows for normal and non-normal approximations of the data-site likelihood of the effect parameter.
Author: Martijn Schuemie [aut, cre], Marc A. Suchard [aut], Fan Bu [aut], Observational Health Data Science and Informatics [cph]
Maintainer: Martijn Schuemie <schuemie@ohdsi.org>

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Package DeclareDesign updated to version 1.1.0 with previous version 1.0.10 dated 2024-04-21

Title: Declare and Diagnose Research Designs
Description: Researchers can characterize and learn about the properties of research designs before implementation using `DeclareDesign`. Ex ante declaration and diagnosis of designs can help researchers clarify the strengths and limitations of their designs and to improve their properties, and can help readers evaluate a research strategy prior to implementation and without access to results. It can also make it easier for designs to be shared, replicated, and critiqued.
Author: Graeme Blair [aut] , Jasper Cooper [aut] , Alexander Coppock [aut, cre] , Macartan Humphreys [aut] , Neal Fultz [aut]
Maintainer: Alexander Coppock <acoppock@gmail.com>

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Package BioTIMEr updated to version 0.2.6 with previous version 0.2.5 dated 2025-09-19

Title: Tools to Use and Explore the 'BioTIME' Database
Description: The 'BioTIME' database was first published in 2018 and inspired ideas, questions, project and research article. To make it even more accessible, an R package was created. The 'BioTIMEr' package provides tools designed to interact with the 'BioTIME' database. The functions provided include the 'BioTIME' recommended methods for preparing (gridding and rarefaction) time series data, a selection of standard biodiversity metrics (including species richness, numerical abundance and exponential Shannon) alongside examples on how to display change over time. It also includes a sample subset of both the query and meta data, the full versions of which are freely available on the 'BioTIME' website <https://biotime.st-andrews.ac.uk/home.php>.
Author: Alban Sagouis [aut, cre] , Faye Moyes [aut] , Ines S. Martins [aut, rev] , Shane A. Blowes [ctb] , Viviana Brambilla [ctb] , Cher F. Y. Chow [ctb] , Ada Fontrodona-Eslava [ctb] , Laura Antao [ctb, rev] , Jonathan M. Chase [fnd] , Maria Dornelas [fnd, [...truncated...]
Maintainer: Alban Sagouis <alban.sagouis@idiv.de>

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Package bakerrr updated to version 0.2.0 with previous version 0.1.0 dated 2025-10-01

Title: Background-Parallel Jobs
Description: Easily launch, track, and control functions as background-parallel jobs. Includes robust utilities for job status, error handling, resource monitoring, and result collection. Designed for scalable workflows in interactive and automated settings (local or remote). Integrates with multiple backends; supports flexible automation pipelines and live job tracking. For more information, see <https://anirbanshaw24.github.io/bakerrr/>.
Author: Anirban Shaw [aut, cre]
Maintainer: Anirban Shaw <anirbanshaw24@gmail.com>

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Package quicR (with last version 2.1.0) was removed from CRAN

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2025-02-26 2.1.0
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Package regMMD updated to version 0.0.2 with previous version 0.0.1 dated 2024-10-25

Title: Robust Regression and Estimation Through Maximum Mean Discrepancy Minimization
Description: The functions in this package compute robust estimators by minimizing a kernel-based distance known as MMD (Maximum Mean Discrepancy) between the sample and a statistical model. Recent works proved that these estimators enjoy a universal consistency property, and are extremely robust to outliers. Various optimization algorithms are implemented: stochastic gradient is available for most models, but the package also allows gradient descent in a few models for which an exact formula is available for the gradient. In terms of distribution fit, a large number of continuous and discrete distributions are available: Gaussian, exponential, uniform, gamma, Poisson, geometric, etc. In terms of regression, the models available are: linear, logistic, gamma, beta and Poisson. Alquier, P. and Gerber, M. (2024) <doi:10.1093/biomet/asad031> Cherief-Abdellatif, B.-E. and Alquier, P. (2022) <doi:10.3150/21-BEJ1338>.
Author: Pierre Alquier [aut, cre] , Mathieu Gerber [aut]
Maintainer: Pierre Alquier <pierre.alquier.stat@gmail.com>

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Package progressr updated to version 0.17.0 with previous version 0.16.0 dated 2025-09-19

Title: An Inclusive, Unifying API for Progress Updates
Description: A minimal, unifying API for scripts and packages to report progress updates from anywhere including when using parallel processing. The package is designed such that the developer can to focus on what progress should be reported on without having to worry about how to present it. The end user has full control of how, where, and when to render these progress updates, e.g. in the terminal using utils::txtProgressBar(), cli::cli_progress_bar(), in a graphical user interface using utils::winProgressBar(), tcltk::tkProgressBar() or shiny::withProgress(), via the speakers using beepr::beep(), or on a file system via the size of a file. Anyone can add additional, customized, progression handlers. The 'progressr' package uses R's condition framework for signaling progress updated. Because of this, progress can be reported from almost anywhere in R, e.g. from classical for and while loops, from map-reduce API:s like the lapply() family of functions, 'purrr', 'plyr', and 'foreach'. It will als [...truncated...]
Author: Henrik Bengtsson [aut, cre, cph]
Maintainer: Henrik Bengtsson <henrikb@braju.com>

Diff between progressr versions 0.16.0 dated 2025-09-19 and 0.17.0 dated 2025-10-15

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More information about progressr at CRAN
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Package fastmatrix updated to version 0.6-2 with previous version 0.6 dated 2025-07-07

Title: Fast Computation of some Matrices Useful in Statistics
Description: Small set of functions to fast computation of some matrices and operations useful in statistics and econometrics. Currently, there are functions for efficient computation of duplication, commutation and symmetrizer matrices with minimal storage requirements. Some commonly used matrix decompositions (LU and LDL), basic matrix operations (for instance, Hadamard, Kronecker products and the Sherman-Morrison formula) and iterative solvers for linear systems are also available. In addition, the package includes a number of common statistical procedures such as the sweep operator, weighted mean and covariance matrix using an online algorithm, linear regression (using Cholesky, QR, SVD, sweep operator and conjugate gradients methods), ridge regression (with optimal selection of the ridge parameter considering several procedures), omnibus tests for univariate normality, functions to compute the multivariate skewness, kurtosis, the Mahalanobis distance (checking the positive defineteness), and t [...truncated...]
Author: Felipe Osorio [aut, cre] , Alonso Ogueda [aut]
Maintainer: Felipe Osorio <faosorios.stat@gmail.com>

Diff between fastmatrix versions 0.6 dated 2025-07-07 and 0.6-2 dated 2025-10-15

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Package DiNAMIC.Duo updated to version 1.0.4 with previous version 1.0.3 dated 2025-04-03

Title: Finding Recurrent DNA Copy Number Alterations and Differences
Description: In tumor tissue, underlying genomic instability can lead to DNA copy number alterations, e.g., copy number gains or losses. Sporadic copy number alterations occur randomly throughout the genome, whereas recurrent alterations are observed in the same genomic region across multiple independent samples, perhaps because they provide a selective growth advantage. Here we use cyclic shift permutations to identify recurrent copy number alterations in a single cohort or recurrent copy number differences in two cohorts based on a common set of genomic markers. Additional functionality is provided to perform downstream analyses, including the creation of summary files and graphics. DiNAMIC.Duo builds upon the original DiNAMIC package of Walter et al. (2011) <doi:10.1093/bioinformatics/btq717> and leverages the theory developed in Walter et al. (2015) <doi:10.1093/biomet/asv046>. An article describing DiNAMIC.Duo by Walter et al. (2022) can be found at <doi: 10.1093/bioinformatics/ [...truncated...]
Author: Vonn Walter [aut, cre] , Hyo Young Choi [aut] , Xiaobei Zhao [aut] , Yan Gao [aut] , David Neil Hayes [aut]
Maintainer: Vonn Walter <vwalter1@pennstatehealth.psu.edu>

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Package cropgrowdays updated to version 0.2.2 with previous version 0.2.1 dated 2024-03-12

Title: Crop Growing Degree Days and Agrometeorological Calculations
Description: Calculate agrometeorological variables for crops including growing degree days (McMaster, GS & Wilhelm, WW (1997) <doi:10.1016/S0168-1923(97)00027-0>), cumulative rainfall, number of stress days and cumulative or mean radiation and evaporation. Convert dates to day of year and vice versa. Also, download curated and interpolated Australian weather data from the Queensland Government DES longpaddock website <https://www.longpaddock.qld.gov.au/>. This data is freely available under the Creative Commons 4.0 licence.
Author: Peter Baker [aut, cre] , Miranda Mortlock [aut]
Maintainer: Peter Baker <drpetebaker@gmail.com>

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