Tue, 16 Dec 2025

Package RStanTVA updated to version 0.3.2 with previous version 0.3.0 dated 2025-05-08

Title: TVA Models in 'Stan' using 'R' and 'StanTVA'
Description: 'Stan' implementation of the Theory of Visual Attention (TVA; Bundesen, 1990; <doi:10.1037/0033-295X.97.4.523>) and numerous convenience functions for generating, compiling, fitting, and analyzing TVA models.
Author: Maximilian M. Rabe [aut, cre] , Soeren Kyllingsbaek [aut]
Maintainer: Maximilian M. Rabe <maximilian.rabe@uni-potsdam.de>

Diff between RStanTVA versions 0.3.0 dated 2025-05-08 and 0.3.2 dated 2025-12-16

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More information about RStanTVA at CRAN
Permanent link

Package msce readmission to version 1.0.2 with previous version 1.0.1 dated 2020-10-29

Title: Hazard of Multi-Stage Clonal Expansion Models
Description: Functions to calculate hazard and survival function of Multi-Stage Clonal Expansion Models used in cancer epidemiology. For the Two-Stage Clonal Expansion Model an exact solution is implemented assuming piecewise constant parameters, see Heidenreich, Luebeck, Moolgavkar (1997) <doi:10.1111/j.1539-6924.1997.tb00878.x>. Numerical solutions are provided for its extensions, see also Little, Vineis, Li (2008) <doi:10.1016/j.jtbi.2008.05.027>.
Author: Cristoforo Simonetto [aut, cre] , Jan Christian Kaiser [ctb]
Maintainer: Cristoforo Simonetto <cristoforo.simonetto@ph.tum.de>

This is a re-admission after prior archival of version 1.0.1 dated 2020-10-29

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Package gripp updated to version 0.2.21 with previous version 0.2.20 dated 2019-08-24

Title: General Inverse Problem Platform
Description: Set of functions designed to solve inverse problems. The direct problem is used to calculate a cost function to be minimized. Here are listed some papers using Inverse Problems solvers and sensitivity analysis: (Jader Lugon Jr.; Antonio J. Silva Neto 2011) <doi:10.1590/S1678-58782011000400003>. (Jader Lugon Jr.; Antonio J. Silva Neto; Pedro P.G.W. Rodrigues 2008) <doi:10.1080/17415970802082864>. (Jader Lugon Jr.; Antonio J. Silva Neto; Cesar C. Santana 2008) <doi:10.1080/17415970802082922>.
Author: Jader Lugon Junior [aut, cre] , Antonio Jose Silva Neto [aut]
Maintainer: Jader Lugon Junior <jlugonjr@gmail.com>

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More information about gripp at CRAN
Permanent link

Package corrselect updated to version 3.0.5 with previous version 3.0.2 dated 2025-11-29

Title: Correlation-Based and Model-Based Predictor Pruning
Description: Provides functions for predictor pruning using association-based and model-based approaches. Includes corrPrune() for fast correlation-based pruning, modelPrune() for VIF-based regression pruning, and exact graph-theoretic algorithms (Eppstein–Löffler–Strash, Bron–Kerbosch) for exhaustive subset enumeration. Supports linear models, GLMs, and mixed models ('lme4', 'glmmTMB').
Author: Gilles Colling [aut, cre]
Maintainer: Gilles Colling <gilles.colling051@gmail.com>

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 corrselect-3.0.5/corrselect/DESCRIPTION                                                                            |   14 
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 corrselect-3.0.5/corrselect/R/RcppExports.R                                                                        |    4 
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 corrselect-3.0.5/corrselect/inst/doc/quickstart.Rmd                                                                |    6 
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Package Colossus updated to version 1.4.6 with previous version 1.4.5 dated 2025-12-07

Title: "Risk Model Regression and Analysis with Complex Non-Linear Models"
Description: Performs survival analysis using general non-linear models. Risk models can be the sum or product of terms. Each term is the product of exponential/linear functions of covariates. Additionally sub-terms can be defined as a sum of exponential, linear threshold, and step functions. Cox Proportional hazards <https://en.wikipedia.org/wiki/Proportional_hazards_model>, Poisson <https://en.wikipedia.org/wiki/Poisson_regression>, and Fine-Gray competing risks <https://www.publichealth.columbia.edu/research/population-health-methods/competing-risk-analysis> regression are supported. This work was sponsored by NASA Grants 80NSSC19M0161 and 80NSSC23M0129 through a subcontract from the National Council on Radiation Protection and Measurements (NCRP). The computing for this project was performed on the Beocat Research Cluster at Kansas State University, which is funded in part by NSF grants CNS-1006860, EPS-1006860, EPS-0919443, ACI-1440548, CHE-1726332, and NIH P20GM113109.
Author: Eric Giunta [aut, cre] , Amir Bahadori [ctb] , Dan Andresen [ctb] , Linda Walsh [ctb] , Benjamin French [ctb] , Lawrence Dauer [ctb] , John Boice Jr [ctb] , Kansas State University [cph], NASA [fnd], NCRP [fnd], NRC [fnd]
Maintainer: Eric Giunta <egiunta@ksu.edu>

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Package snazzieR updated to version 0.1.2 with previous version 0.1.1 dated 2025-05-11

Title: Chic and Sleek Functions for Beautiful Statisticians
Description: Because your linear models deserve better than console output. A sleek color palette and kable styling to make your regression results look sharper than they are. Includes support for Partial Least Squares (PLS) regression via both the SVD and NIPALS algorithms, along with a unified interface for model fitting and fabulous LaTeX and console output formatting. See the package website at <https://finitesample.space/snazzier>.
Author: Aidan J. Wagner [aut, cre]
Maintainer: Aidan J. Wagner <JesusButForGayPeople@proton.me>

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Package SampleSizeDiagnostics updated to version 0.1.1 with previous version 0.1.0 dated 2024-07-26

Title: Choosing Sample Size for Evaluating a Diagnostic Test
Description: Calculates the sample size needed for evaluating a diagnostic test based on sensitivity, specificity, prevalence, and desired precision. Based on Buderer (1996) <doi:10.1111/j.1553-2712.1996.tb03538.x>.
Author: Mohamed Kamal [aut, cre]
Maintainer: Mohamed Kamal <mohamedkamalhospital@gmail.com>

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Package ganGenerativeData updated to version 2.1.6 with previous version 2.1.4 dated 2024-12-12

Title: Generate Generative Data for a Data Source
Description: Generative Adversarial Networks are applied to generate generative data for a data source. A generative model consisting of a generator and a discriminator network is trained. During iterative training the distribution of generated data is converging to that of the data source. Direct applications of generative data are the created functions for data evaluation, missing data completion and data classification. A software service for accelerated training of generative models on graphics processing units is available. Reference: Goodfellow et al. (2014) <doi:10.48550/arXiv.1406.2661>.
Author: Werner Mueller [aut, cre]
Maintainer: Werner Mueller <werner.mueller5@chello.at>

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Package dynatop updated to version 0.2.4 with previous version 0.2.3 dated 2022-10-10

Title: An Implementation of Dynamic TOPMODEL Hydrological Model in R
Description: An R implementation and enhancement of the Dynamic TOPMODEL semi-distributed hydrological model originally proposed by Beven and Freer (2001) <doi:10.1002/hyp.252>. The 'dynatop' package implements code for simulating models which can be created using the 'dynatopGIS' package.
Author: Paul Smith [aut, cre] , Peter Metcalfe [aut]
Maintainer: Paul Smith <paul@waternumbers.co.uk>

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Package LowWAFOMNX (with last version 1.1.1) was removed from CRAN

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

2017-08-24 1.1.1
2017-07-11 1.0

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Package LowWAFOMSobol (with last version 1.1.1) was removed from CRAN

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

2017-08-29 1.1.1
2017-07-13 1.0

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Package Ryacas0 (with last version 0.4.5) was removed from CRAN

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

2025-09-04 0.4.5
2023-01-12 0.4.4
2020-09-29 0.4.3
2019-10-09 0.4.2

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Package IBLM updated to version 1.0.2 with previous version 1.0.1 dated 2025-11-19

Title: Interpretable Boosted Linear Models
Description: Implements Interpretable Boosted Linear Models (IBLMs). These combine a conventional generalized linear model (GLM) with a machine learning component, such as XGBoost. The package also provides tools within for explaining and analyzing these models. For more details see Gawlowski and Wang (2025) <https://ifoa-adswp.github.io/IBLM/reference/figures/iblm_paper.pdf>.
Author: Karol Gawlowski [aut, cre, cph], Paul Beard [aut]
Maintainer: Karol Gawlowski <Karol.Gawlowski@citystgeorges.ac.uk>

Diff between IBLM versions 1.0.1 dated 2025-11-19 and 1.0.2 dated 2025-12-16

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Package survivalSL updated to version 1.0 with previous version 0.98 dated 2025-07-02

Title: Super Learner for Survival Prediction from Censored Data
Description: Several functions and S3 methods to construct a super learner in the presence of censored times-to-event and to evaluate its prognostic capacities.
Author: Yohann Foucher [aut, cre] , Camille Sabathe [aut]
Maintainer: Yohann Foucher <yohann.foucher@univ-poitiers.fr>

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Package tidyfst updated to version 1.8.3 with previous version 1.8.2 dated 2025-05-07

Title: Tidy Verbs for Fast Data Manipulation
Description: A toolkit of tidy data manipulation verbs with 'data.table' as the backend. Combining the merits of syntax elegance from 'dplyr' and computing performance from 'data.table', 'tidyfst' intends to provide users with state-of-the-art data manipulation tools with least pain. This package is an extension of 'data.table'. While enjoying a tidy syntax, it also wraps combinations of efficient functions to facilitate frequently-used data operations.
Author: Tian-Yuan Huang [aut, cre]
Maintainer: Tian-Yuan Huang <huang.tian-yuan@qq.com>

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Package statnet.common updated to version 4.13.0 with previous version 4.12.0 dated 2025-05-30

Title: Common R Scripts and Utilities Used by the Statnet Project Software
Description: Non-statistical utilities used by the software developed by the Statnet Project. They may also be of use to others.
Author: Pavel N. Krivitsky [aut, cre] , Skye Bender-deMoll [ctb], Chad Klumb [ctb] , Michal Bojanowski [ctb]
Maintainer: Pavel N. Krivitsky <pavel@statnet.org>

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Package pkgdiff updated to version 1.0.1 with previous version 1.0.0 dated 2025-11-24

Title: Identifies Package Differences
Description: Identifies differences between versions of a package. Specifically, the functions help determine if there are breaking changes from one package version to the next. The package also includes a stability assessment, to help you determine the overall stability of a package, or even an entire repository.
Author: David Bosak [aut, cre], Brian Varney [ctb], Kevin Putschko [ctb]
Maintainer: David Bosak <dbosak01@gmail.com>

Diff between pkgdiff versions 1.0.0 dated 2025-11-24 and 1.0.1 dated 2025-12-16

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Package EMT updated to version 1.3.2 with previous version 1.3.1 dated 2024-03-26

Title: Exact Multinomial Test: Goodness-of-Fit Test for Discrete Multivariate Data
Description: Goodness-of-fit tests for discrete multivariate data. It is tested if a given observation is likely to have occurred under the assumption of an ab-initio model. Monte Carlo methods are provided to make the package capable of solving high-dimensional problems.
Author: Uwe Menzel [aut, cre]
Maintainer: Uwe Menzel <uwemenzel@gmail.com>

Diff between EMT versions 1.3.1 dated 2024-03-26 and 1.3.2 dated 2025-12-16

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Package pxmake updated to version 0.19.0 with previous version 0.18.0 dated 2025-05-30

Title: Make PX-Files in R
Description: Create PX-files from scratch or read and modify existing ones. Includes a function for every PX keyword, making metadata manipulation simple and human-readable.
Author: Johan Ejstrud [cre, aut], Lars Pedersen [aut], Statistics Greenland [cph]
Maintainer: Johan Ejstrud <johan@ejstrud.com>

Diff between pxmake versions 0.18.0 dated 2025-05-30 and 0.19.0 dated 2025-12-16

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Package OralOpioids updated to version 2.0.5 with previous version 2.0.4 dated 2025-01-09

Title: Retrieving Oral Opioid Information
Description: Provides details such as Morphine Equivalent Dose (MED), brand name and opioid content which are calculated of all oral opioids authorized for sale by Health Canada and the FDA based on their Drug Identification Number (DIN) or National Drug Code (NDC). MEDs are calculated based on recommendations by Canadian Institute for Health Information (CIHI) and Von Korff et al (2008) and information obtained from Health Canada's Drug Product Database's monthly data dump or FDA Daily database for Canadian and US databases respectively. Please note in no way should output from this package be a substitute for medical advise. All medications should only be consumed on prescription from a licensed healthcare provider.
Author: Ankona Banerjee [aut, cre] , Erik Stricker [aut]
Maintainer: Ankona Banerjee <ankonanagpur@gmail.com>

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Package gaselect updated to version 1.0.24 with previous version 1.0.23 dated 2025-04-14

Title: Genetic Algorithm (GA) for Variable Selection from High-Dimensional Data
Description: Provides a genetic algorithm for finding variable subsets in high dimensional data with high prediction performance. The genetic algorithm can use ordinary least squares (OLS) regression models or partial least squares (PLS) regression models to evaluate the prediction power of variable subsets. By supporting different cross-validation schemes, the user can fine-tune the tradeoff between speed and quality of the solution.
Author: David Kepplinger [aut, cre]
Maintainer: David Kepplinger <david.kepplinger@gmail.com>

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Package toxpiR updated to version 1.3.1 with previous version 1.3.0 dated 2024-09-12

Title: Create ToxPi Prioritization Models
Description: Enables users to build 'ToxPi' prioritization models and provides functionality within the grid framework for plotting ToxPi graphs. 'toxpiR' allows for more customization than the 'ToxPi GUI' (<https://toxpi.github.io/>) and integration into existing workflows for greater ease-of-use, reproducibility, and transparency. toxpiR package behaves nearly identically to the GUI; the package documentation includes notes about all differences. The vignettes download example files from <https://github.com/ToxPi/ToxPi-example-files>.
Author: Jonathon F Fleming [aut, cre] , Dayne L Filer [aut, fnd] , Dillon T Lloyd [aut], Preethi Thunga [aut] , Skylar W Marvel [aut], Alison A Motsinger-Reif [fnd] , David M Reif [aut, fnd]
Maintainer: Jonathon F Fleming <jffleming0129@gmail.com>

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Package Rcan updated to version 1.3.92 with previous version 1.3.91 dated 2024-09-24

Title: Cancer Registry Data Analysis and Visualisation
Description: Tools for basic and advance cancer statistics and graphics. Groups individual data, merges registry data and population data, calculates age-specific rate, age-standardized rate, cumulative risk, estimated annual percentage rate with standards error. Creates graphics across variable and time, such as age-specific trends, bar chart and period-cohort trends.
Author: Mathieu Laversanne [aut, cre], Jerome Vignat [aut], Cancer Surveillance Unit [cph]
Maintainer: Mathieu Laversanne <laversannem@iarc.who.int>

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Package omicsTools updated to version 1.1.7 with previous version 1.0.5 dated 2023-07-03

Title: Omics Data Process Toolbox
Description: Processing and analyzing omics data from genomics, transcriptomics, proteomics, and metabolomics platforms. It provides functions for preprocessing, normalization, visualization, and statistical analysis, as well as machine learning algorithms for predictive modeling. 'omicsTools' is an essential tool for researchers working with high-throughput omics data in fields such as biology, bioinformatics, and medicine.The QC-RLSC (quality control–based robust LOESS signal correction) algorithm is used for normalization. Dunn et al. (2011) <doi:10.1038/nprot.2011.335>.
Author: Yaoxiang Li [cre, aut]
Maintainer: Yaoxiang Li <liyaoxiang@outlook.com>

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Package datetoiso updated to version 1.2.1 with previous version 1.2.0 dated 2025-12-07

Title: Convert and Impute Dates to ISO 8601 Format and Reconcile Data Sets
Description: Provides tools for converting and imputing date values to the ISO 8601 standard format and for reconciling differences between two versions of a data set. The package automatically detects date patterns within data frame columns and converts them to consistent ISO-formatted dates, with optional imputation of missing day or month components based on user-defined rules. It also includes functionality to identify inserted, deleted, and updated records, as well as column- and value-level changes, when comparing old and new versions of a data frame. Only one date format may be applied within a single column.
Author: Lukasz Andrzejewski [aut, cre]
Maintainer: Lukasz Andrzejewski <lukasz.coding@gmail.com>

Diff between datetoiso versions 1.2.0 dated 2025-12-07 and 1.2.1 dated 2025-12-16

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Package biodosetools updated to version 3.7.2 with previous version 3.7.1.2 dated 2025-12-04

Title: 'shiny' Application for Biological Dosimetry
Description: A tool to perform all different statistical tests and calculations needed by Biological dosimetry Laboratories. Detailed documentation is available in <https://biodosetools-team.github.io/documentation/>.
Author: Alfredo Hernandez [aut] , Anna Frances-Abellan [aut, cre] , David Endesfelder [aut], Pere Puig [aut]
Maintainer: Anna Frances-Abellan <anna.frances@uab.cat>

Diff between biodosetools versions 3.7.1.2 dated 2025-12-04 and 3.7.2 dated 2025-12-16

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Package akc updated to version 0.9.9.2 with previous version 0.9.9.1 dated 2025-02-25

Title: Automatic Knowledge Classification
Description: A tidy framework for automatic knowledge classification and visualization. Currently, the core functionality of the framework is mainly supported by modularity-based clustering (community detection) in keyword co-occurrence network, and focuses on co-word analysis of bibliometric research. However, the designed functions in 'akc' are general, and could be extended to solve other tasks in text mining as well.
Author: Tian-Yuan Huang [aut, cre]
Maintainer: Tian-Yuan Huang <huang.tian-yuan@qq.com>

Diff between akc versions 0.9.9.1 dated 2025-02-25 and 0.9.9.2 dated 2025-12-16

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New package seasonalytics with initial version 0.1.0
Package: seasonalytics
Title: Compute Seasonality Index, Seasonalized and Deseaonalised the Time Series Data
Version: 0.1.0
Author: Dr. Pramit Pandit [aut], Mr. Ankit Kumar Singh [aut, cre], Ms. Anita Sarkar [aut], Ms. Moumita Paul [aut], Dr. Bikramjeet Ghose [aut]
Maintainer: Mr. Ankit Kumar Singh <ankitsinghvns32@gmail.com>
Description: The computation of a seasonal index is a fundamental step in time-series forecasting when the data exhibits seasonality. Specifically, a seasonal index quantifies — for each season (e.g. month, quarter, week) — the relative magnitude of the seasonal effect compared to the overall average level of the series. This package has been developed to compute seasonal index for time series data and it also seasonalise and desesaonalise the time series data.
License: GPL-3
Encoding: UTF-8
Imports: seastests
Suggests: testthat (>= 3.0.0)
Packaged: 2025-12-10 14:04:06 UTC; HP
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2025-12-16 14:30:02 UTC

More information about seasonalytics at CRAN
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Package resourcecode updated to version 0.5.1 with previous version 0.5.0 dated 2025-11-10

Title: Access to the 'RESOURCECODE' Hindcast Database
Description: Utility functions to download data from the 'RESOURCECODE' hindcast database of sea-states, time series of sea-state parameters and time series of 1D and 2D wave spectra. See <https://resourcecode.ifremer.fr> for more details about the available data. Also provides facilities to plot and analyse downloaded data, such as computing the sea-state parameters from both the 1D and 2D surface elevation variance spectral density.
Author: Nicolas Raillard [aut, cre]
Maintainer: Nicolas Raillard <nicolas.raillard@ifremer.fr>

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Package nlgeocoder readmission to version 0.2.2 with previous version 0.1.3 dated 2018-10-08

Title: Geocoding for the Netherlands
Description: Interface to the open location server API of 'Publieke Diensten Op de Kaart' (<http://www.pdok.nl>). It offers geocoding, address suggestions and lookup of geographical objects. Included is an utility function for displaying leaflet tiles restricted to the Netherlands.
Author: Willy Tadema [aut], Egge-Jan Polle [aut], Edwin de Jonge [aut, cre] , Juris Breidaks [ctb]
Maintainer: Edwin de Jonge <edwindjonge@gmail.com>

This is a re-admission after prior archival of version 0.1.3 dated 2018-10-08

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New package iccCompare with initial version 1.1.0
Package: iccCompare
Title: Comparison of Dependent Intraclass Correlation Coefficients
Version: 1.1.0
Maintainer: Josep Lluis Carrasco <jlcarrasco@ub.edu>
Depends: R (>= 4.5)
Imports: nlme, dplyr, Deriv, MASS, furrr, future, progressr,parallelly, bbmle, mvtnorm
Suggests: cccrm
Description: Provides methods for testing the equality of dependent intraclass correlation coefficients (ICCs) estimated using linear mixed-effects models. Several of the implemented approaches are based on the work of Donner and Zou (2002) <doi:10.1111/1467-9884.00324>.
License: GPL (>= 2)
LazyData: true
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2025-12-10 12:15:12 UTC; jlcarrasco
Author: Josep Lluis Carrasco [aut, cre], Gonzalo Peon Pena [aut]
Repository: CRAN
Date/Publication: 2025-12-16 14:30:06 UTC

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New package fgdiR with initial version 0.1.0
Package: fgdiR
Title: Functional Gait Deviation Index
Version: 0.1.0
Description: A typical gait analysis requires the examination of the motion of nine joint angles on the left-hand side and six joint angles on the right-hand side across multiple subjects. Due to the quantity and complexity of the data, it is useful to calculate the amount by which a subject’s gait deviates from an average normal profile and to represent this deviation as a single number. Such a measure can quantify the overall severity of a condition affecting walking, monitor progress, or evaluate the outcome of an intervention prescribed to improve the gait pattern. This R package provides tools for computing the Functional Gait Deviation Index, a novel index for quantifying gait pathology using multivariate functional principal component analysis. The package supports analysis at the level of both legs combined, individual legs, and individual joints/planes. It includes functions for functional data preprocessing, multivariate functional principal component decomposition, FGDI computation, and [...truncated...]
Depends: R (>= 3.5.0)
Imports: ggplot2, dplyr, tidyr, Matrix, magrittr, refund,
Suggests: knitr, rmarkdown, ggpubr, gridExtra, forcats, knitr, rmarkdown,
License: GPL-3
Encoding: UTF-8
LazyData: true
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2025-12-10 12:11:44 UTC; michellecarey
Author: Michelle Carey [aut, cre], Sajal Kaur Minhas [aut]
Maintainer: Michelle Carey <michelle.carey@ucd.ie>
Repository: CRAN
Date/Publication: 2025-12-16 14:20:02 UTC

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Package mixAR updated to version 0.22.9 with previous version 0.22.8 dated 2023-12-18

Title: Mixture Autoregressive Models
Description: Model time series using mixture autoregressive (MAR) models. Implemented are frequentist (EM) and Bayesian methods for estimation, prediction and model evaluation. See Wong and Li (2002) <doi:10.1111/1467-9868.00222>, Boshnakov (2009) <doi:10.1016/j.spl.2009.04.009>), and the extensive references in the documentation.
Author: Georgi N. Boshnakov [aut, cre] , Davide Ravagli [aut]
Maintainer: Georgi N. Boshnakov <georgi.boshnakov@manchester.ac.uk>

Diff between mixAR versions 0.22.8 dated 2023-12-18 and 0.22.9 dated 2025-12-16

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Package glmnetr updated to version 0.6-3 with previous version 0.6-2 dated 2025-08-19

Title: Nested Cross Validation for the Relaxed Lasso and Other Machine Learning Models
Description: Cross validation informed Relaxed LASSO (or more generally elastic net), gradient boosting machine ('xgboost'), Random Forest ('RandomForestSRC'), Oblique Random Forest ('aorsf'), Artificial Neural Network (ANN), Recursive Partitioning ('RPART') or step wise regression models are fit. Cross validation leave out samples (leading to nested cross validation) or bootstrap out-of-bag samples are used to evaluate and compare performances between these models with results presented in tabular or graphical means. Calibration plots can also be generated, again based upon (outer nested) cross validation or bootstrap leave out (out of bag) samples. Note, at the time of this writing, in order to fit gradient boosting machine models one must install the packages 'DiceKriging' and 'rgenoud' using the install.packages() function. For some datasets, for example when the design matrix is not of full rank, 'glmnet' may have very long run times when fitting the relaxed lasso model, from our experience [...truncated...]
Author: Walter K Kremers [aut, cre] , Nicholas B Larson [ctb]
Maintainer: Walter K Kremers <kremers.walter@mayo.edu>

Diff between glmnetr versions 0.6-2 dated 2025-08-19 and 0.6-3 dated 2025-12-16

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Package ggeffects updated to version 2.3.2 with previous version 2.3.1 dated 2025-08-20

Title: Create Tidy Data Frames of Marginal Effects for 'ggplot' from Model Outputs
Description: Compute marginal effects and adjusted predictions from statistical models and returns the result as tidy data frames. These data frames are ready to use with the 'ggplot2'-package. Effects and predictions can be calculated for many different models. Interaction terms, splines and polynomial terms are also supported. The main functions are ggpredict(), ggemmeans() and ggeffect(). There is a generic plot()-method to plot the results using 'ggplot2'.
Author: Daniel Luedecke [aut, cre] , Frederik Aust [ctb] , Sam Crawley [ctb] , Mattan S. Ben-Shachar [ctb] , Sean C. Anderson [ctb]
Maintainer: Daniel Luedecke <d.luedecke@uke.de>

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Package fastglm updated to version 0.0.4 with previous version 0.0.3 dated 2022-05-23

Title: Fast and Stable Fitting of Generalized Linear Models using 'RcppEigen'
Description: Fits generalized linear models efficiently using 'RcppEigen'. The iteratively reweighted least squares implementation utilizes the step-halving approach of Marschner (2011) <doi:10.32614/RJ-2011-012> to help safeguard against convergence issues.
Author: Jared Huling [aut, cre], Douglas Bates [cph], Dirk Eddelbuettel [cph], Romain Francois [cph], Yixuan Qiu [cph]
Maintainer: Jared Huling <jaredhuling@gmail.com>

Diff between fastglm versions 0.0.3 dated 2022-05-23 and 0.0.4 dated 2025-12-16

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New package waysign with initial version 0.1.0
Package: waysign
Title: Multi-Purpose and High-Performance Routing
Version: 0.1.0
Description: Provides routing based on the 'path-tree' 'Rust' crate. The routing is general purpose in the sense that any type of R object can be associated with a path, not just a handler function.
License: MIT + file LICENSE
Encoding: UTF-8
SystemRequirements: Cargo (Rust's package manager), rustc >= 1.65.0, xz
Depends: R (>= 4.2)
Suggests: testthat (>= 3.0.0)
Imports: rlang (>= 1.1.0)
URL: https://github.com/thomasp85/waysign
BugReports: https://github.com/thomasp85/waysign/issues
NeedsCompilation: yes
Packaged: 2025-12-08 07:25:17 UTC; thomas
Author: Thomas Lin Pedersen [aut, cre] , Posit, PBC [cph, fnd]
Maintainer: Thomas Lin Pedersen <thomas.pedersen@posit.co>
Repository: CRAN
Date/Publication: 2025-12-16 12:40:02 UTC

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Package SuperCell updated to version 1.1 with previous version 1.0.1 dated 2024-10-25

Title: Simplification of scRNA-Seq Data by Merging Together Similar Cells
Description: Aggregates large single-cell data into metacell dataset by merging together gene expression of very similar cells. 'SuperCell' uses 'velocyto.R' <doi:10.1038/s41586-018-0414-6> <https://github.com/velocyto-team/velocyto.R> for RNA velocity and 'WeightedCluster' <doi:10.12682/lives.2296-1658.2013.24> <https://mephisto.unige.ch/weightedcluster/> for weighted clustering on metacells. We also recommend installing 'scater' Bioconductor package <doi:10.18129/B9.bioc.scater> <https://bioconductor.org/packages/release/bioc/html/scater.html>.
Author: Mariia Bilous [aut], Matei Teleman [cre]
Maintainer: Matei Teleman <matei.teleman@unil.ch>

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Package NlinTS updated to version 1.4.6 with previous version 1.4.5 dated 2021-02-01

Title: Models for Non Linear Causality Detection in Time Series
Description: Models for non-linear time series analysis and causality detection. The main functionalities of this package consist of an implementation of the classical causality test (C.W.J.Granger 1980) <doi:10.1016/0165-1889(80)90069-X>, and a non-linear version of it based on feed-forward neural networks. This package contains also an implementation of the Transfer Entropy <doi:10.1103/PhysRevLett.85.461>, and the continuous Transfer Entropy using an approximation based on the k-nearest neighbors <doi:10.1103/PhysRevE.69.066138>. There are also some other useful tools, like the VARNN (Vector Auto-Regressive Neural Network) prediction model, the Augmented test of stationarity, and the discrete and continuous entropy and mutual information.
Author: Youssef Hmamouche [aut, cre]
Maintainer: Youssef Hmamouche <hmamoucheyussef@gmail.com>

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Package dawaR updated to version 0.3.2 with previous version 0.3.1 dated 2025-11-18

Title: An API Wrapper for 'DAWA' - 'The Danish Address Web API'
Description: Functions for interacting with all sections of the official 'Danish Address Web API' (also known as 'DAWA') <https://api.dataforsyningen.dk>. The development of this package is completely independent from the government agency, Klimadatastyrelsen, who maintains the API.
Author: Aleksander Bang-Larsen [aut, cre, cph] , Agency of Climate Data [ctb]
Maintainer: Aleksander Bang-Larsen <contact@aleksanderbl.dk>

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Package biostats updated to version 1.1.1 with previous version 1.1.0 dated 2025-12-06

Title: Biostatistics and Clinical Data Analysis
Description: Biostatistical and clinical data analysis, including descriptive statistics, exploratory data analysis, sample size and power calculations, statistical inference, and data visualization. Normality tests are implemented following Mishra et al. (2019) <doi:10.4103/aca.ACA_157_18>, omnibus test procedures are based on Blanca et al. (2017) <doi:10.3758/s13428-017-0918-2> and Field et al. (2012, ISBN:9781446200469), while sample size and power calculation methods follow Chow et al. (2017) <doi:10.1201/9781315183084>.
Author: Sebastian Quirarte-Justo [aut, cre] , Angela Carolina Montano-Ruiz [aut] , Jose Maria Torres-Arellano [aut] , Laboratorios Sophia S.A. de C.V. [cph, fnd]
Maintainer: Sebastian Quirarte-Justo <sebastian.quirarte@sophia.com.mx>

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Package rpact updated to version 4.3.0 with previous version 4.2.1 dated 2025-07-24

Title: Confirmatory Adaptive Clinical Trial Design and Analysis
Description: Design and analysis of confirmatory adaptive clinical trials with continuous, binary, and survival endpoints according to the methods described in the monograph by Wassmer and Brannath (2025) <doi:10.1007/978-3-031-89669-9>. This includes classical group sequential as well as multi-stage adaptive hypotheses tests that are based on the combination testing principle.
Author: Gernot Wassmer [aut] , Friedrich Pahlke [aut, cre] , Till Jensen [ctb], Daniel Sabanes Bove [ctb] , Stephen Schueuerhuis [ctb] , Tobias Muetze [ctb]
Maintainer: Friedrich Pahlke <friedrich.pahlke@rpact.com>

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Package spant updated to version 3.8.0 with previous version 3.7.0 dated 2025-11-20

Title: MR Spectroscopy Analysis Tools
Description: Tools for reading, visualising and processing Magnetic Resonance Spectroscopy data. The package includes methods for spectral fitting: Wilson (2021) <DOI:10.1002/mrm.28385>, Wilson (2025) <DOI:10.1002/mrm.30462> and spectral alignment: Wilson (2018) <DOI:10.1002/mrm.27605>.
Author: Martin Wilson [cre, aut] , Yong Wang [ctb], John Muschelli [ctb]
Maintainer: Martin Wilson <martin@pipegrep.co.uk>

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Package wsrf updated to version 1.7.31 with previous version 1.7.30 dated 2023-01-06

Title: Weighted Subspace Random Forest for Classification
Description: A parallel implementation of Weighted Subspace Random Forest. The Weighted Subspace Random Forest algorithm was proposed in the International Journal of Data Warehousing and Mining by Baoxun Xu, Joshua Zhexue Huang, Graham Williams, Qiang Wang, and Yunming Ye (2012) <DOI:10.4018/jdwm.2012040103>. The algorithm can classify very high-dimensional data with random forests built using small subspaces. A novel variable weighting method is used for variable subspace selection in place of the traditional random variable sampling.This new approach is particularly useful in building models from high-dimensional data.
Author: Qinghan Meng [aut], He Zhao [aut, cre] , Graham J. Williams [aut] , Junchao Lv [aut], Baoxun Xu [aut], Joshua Zhexue Huang [aut]
Maintainer: He Zhao <Simon.Yansen.Zhao@gmail.com>

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Package TUvalues updated to version 1.1.0 with previous version 1.0.0 dated 2025-05-22

Title: Tools for Calculating Allocations in Game Theory using Exact and Approximated Methods
Description: The main objective of cooperative Transferable-Utility games (TU-games) is to allocate a good among the agents involved. The package implements major solution concepts including the Shapley value, Banzhaf value, and egalitarian rules, alongside their extensions for structured games: the Owen value and Banzhaf-Owen value for games with a priori unions, and the Myerson value for communication games on networks. To address the inherent exponential computational complexity of exact evaluation, the package offers both exact algorithms and linear approximation methods based on sampling, enabling the analysis of large-scale games. Additionally, it supports core set-based solutions, allowing computation of the vertices and the centroid of the core.
Author: Maria D. Guillen [cre, aut] , Juan Carlos Goncalves [aut]
Maintainer: Maria D. Guillen <maria.guilleng@umh.es>

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Package simstudy updated to version 0.9.1 with previous version 0.9.0 dated 2025-10-06

Title: Simulation of Study Data
Description: Simulates data sets in order to explore modeling techniques or better understand data generating processes. The user specifies a set of relationships between covariates, and generates data based on these specifications. The final data sets can represent data from randomized control trials, repeated measure (longitudinal) designs, and cluster randomized trials. Missingness can be generated using various mechanisms (MCAR, MAR, NMAR).
Author: Keith Goldfeld [aut, cre] , Jacob Wujciak-Jens [aut]
Maintainer: Keith Goldfeld <keith.goldfeld@nyulangone.org>

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Package nparACT updated to version 0.9.1 with previous version 0.9.0 dated 2025-09-23

Title: Non-Parametric Measures of Actigraphy Data
Description: Computes interdaily stability (IS), intradaily variability (IV) & the relative amplitude (RA) from actigraphy data as described in Blume et al. (2016) <doi: 10.1016/j.mex.2016.05.006> and van Someren et al. (1999) <doi: 10.3109/07420529908998724>. Additionally, it also computes L5 (i.e. the 5 hours with lowest average actigraphy amplitude) and M10 (the 10 hours with highest average amplitude) as well as the respective start times. The flex versions will also compute the L-value for a user-defined number of minutes. IS describes the strength of coupling of a rhythm to supposedly stable zeitgebers. It varies between 0 (Gaussian Noise) and 1 for perfect IS. IV describes the fragmentation of a rhythm, i.e. the frequency and extent of transitions between rest and activity. It is near 0 for a perfect sine wave, about 2 for Gaussian noise and may be even higher when a definite ultradian period of about 2 hrs is present. RA is the relative amplitude of a rhythm. Note that to ob [...truncated...]
Author: Christine Blume [aut, cre]
Maintainer: Christine Blume <christine.blume@unibas.ch>

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Package mvabund updated to version 4.2.8 with previous version 4.2.1 dated 2022-02-16

Title: Statistical Methods for Analysing Multivariate Abundance Data
Description: A set of tools for displaying, modeling and analysing multivariate abundance data in community ecology. See 'mvabund-package.Rd' for details of overall package organization. The package is implemented with the Gnu Scientific Library (<http://www.gnu.org/software/gsl/>) and 'Rcpp' (<http://dirk.eddelbuettel.com/code/rcpp.html>) 'R' / 'C++' classes.
Author: Yi Wang [aut], Ulrike Naumann [aut], Dirk Eddelbuettel [aut], John Wilshire [aut], David Warton [aut, cre], Julian Byrnes [ctb], Ralph dos Santos Silva [ctb, cph], Jenni Niku [ctb], Ian Renner [ctb], Stephen Wright [ctb]
Maintainer: David Warton <David.Warton@unsw.edu.au>

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Package lfl updated to version 2.3.1 with previous version 2.3.0 dated 2025-06-27

Title: Linguistic Fuzzy Logic
Description: Various algorithms related to linguistic fuzzy logic: mining for linguistic fuzzy association rules, composition of fuzzy relations, performing perception-based logical deduction (PbLD), and forecasting time-series using fuzzy rule-based ensemble (FRBE). The package also contains basic fuzzy-related algebraic functions capable of handling missing values in different styles (Bochvar, Sobocinski, Kleene etc.), computation of Sugeno integrals and fuzzy transform.
Author: Michal Burda [aut, cre]
Maintainer: Michal Burda <michal.burda@osu.cz>

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Package WRI updated to version 0.2.1 with previous version 0.2.0 dated 2022-07-08

Title: Wasserstein Regression and Inference
Description: Implementation of the methodologies described in 1) Alexander Petersen, Xi Liu and Afshin A. Divani (2021) <doi:10.1214/20-aos1971>, including global F tests, partial F tests, intrinsic Wasserstein-infinity bands and Wasserstein density bands, and 2) Chao Zhang, Piotr Kokoszka and Alexander Petersen (2022) <doi:10.1111/jtsa.12590>, including estimation, prediction, and inference of the Wasserstein autoregressive models.
Author: Xi Liu [aut, cre], Chao Zhang [aut], Matthew Coleman [aut], Alexander Petersen [aut]
Maintainer: Xi Liu <xiliu@ucsb.edu>

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Package Pijavski updated to version 1.0.5 with previous version 1.0.3 dated 2020-10-22

Title: Global Univariate Minimization
Description: Global univariate minimization of Lipschitz functions is performed by using Pijavski method, which was published in Pijavski (1972) <DOI:10.1016/0041-5553(72)90115-2>.
Author: Gleb Beliakov [aut, cre], Gita Das [aut], Jonathan Wells [ctb], Hewlett-Packard Company [ctb], Silicon Graphics Computer Systems Inc. [ctb]
Maintainer: Gleb Beliakov <gleb@deakin.edu.au>

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Package nimbleHMC updated to version 0.2.4 with previous version 0.2.3 dated 2024-12-18

Title: Hamiltonian Monte Carlo and Other Gradient-Based MCMC Sampling Algorithms for 'nimble'
Description: Provides gradient-based MCMC sampling algorithms for use with the MCMC engine provided by the 'nimble' package. This includes two versions of Hamiltonian Monte Carlo (HMC) No-U-Turn (NUTS) sampling, and (under development) Langevin samplers. The `NUTS_classic` sampler implements the original HMC-NUTS algorithm as described in Hoffman and Gelman (2014) <doi:10.48550/arXiv.1111.4246>. The `NUTS` sampler is a modern version of HMC-NUTS sampling matching the HMC sampler available in version 2.32.2 of Stan (Stan Development Team, 2023). In addition, convenience functions are provided for generating and modifying MCMC configuration objects which employ HMC sampling. Functionality of the 'nimbleHMC' package is described further in Turek, et al (2024) <doi: 10.21105/joss.06745>.
Author: Daniel Turek [aut, cre], Perry de Valpine [aut], Christopher Paciorek [aut]
Maintainer: Daniel Turek <danielturek@gmail.com>

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Package deepredeff (with last version 0.1.1) was removed from CRAN

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

2021-07-16 0.1.1
2020-10-23 0.1.0

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Package spectre (with last version 1.0.5) was removed from CRAN

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

2025-12-01 1.0.5
2021-07-17 1.0.2

Permanent link
Package emmeans updated to version 2.0.1 with previous version 2.0.0 dated 2025-10-29

Title: Estimated Marginal Means, aka Least-Squares Means
Description: Obtain estimated marginal means (EMMs) for many linear, generalized linear, and mixed models. Compute contrasts or linear functions of EMMs, trends, and comparisons of slopes. Plots and other displays. Least-squares means are discussed, and the term "estimated marginal means" is suggested, in Searle, Speed, and Milliken (1980) Population marginal means in the linear model: An alternative to least squares means, The American Statistician 34(4), 216-221 <doi:10.1080/00031305.1980.10483031>.
Author: Russell V. Lenth [aut, cph], Julia Piaskowski [cre, aut], Balazs Banfai [ctb], Ben Bolker [ctb], Paul Buerkner [ctb], Iago Gine-Vazquez [ctb], Maxime Herve [ctb], Maarten Jung [ctb], Jonathon Love [ctb], Fernando Miguez [ctb], Hannes Riebl [ctb], Hen [...truncated...]
Maintainer: Julia Piaskowski <julia.piask@gmail.com>

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Package xfun updated to version 0.55 with previous version 0.54 dated 2025-10-30

Title: Supporting Functions for Packages Maintained by 'Yihui Xie'
Description: Miscellaneous functions commonly used in other packages maintained by 'Yihui Xie'.
Author: Yihui Xie [aut, cre, cph] , Wush Wu [ctb], Daijiang Li [ctb], Xianying Tan [ctb], Salim Brueggemann [ctb] , Christophe Dervieux [ctb]
Maintainer: Yihui Xie <xie@yihui.name>

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Package virustotal updated to version 0.5.0 with previous version 0.3.0 dated 2025-09-02

Title: R Client for the VirusTotal API
Description: Provides a comprehensive R interface to the VirusTotal API (v2 and v3), a Google service that analyzes files and URLs for viruses, worms, trojans and other malware. Features include file/URL scanning, domain categorization, passive DNS information, IP reputation analysis, and comment/voting systems. Implements rate limiting, error handling, and response validation for robust security analysis workflows.
Author: Gaurav Sood [aut, cre]
Maintainer: Gaurav Sood <gsood07@gmail.com>

Diff between virustotal versions 0.3.0 dated 2025-09-02 and 0.5.0 dated 2025-12-16

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Package sarima updated to version 0.9.5 with previous version 0.9.4 dated 2025-03-18

Title: Simulation and Prediction with Seasonal ARIMA Models
Description: Functions, classes and methods for time series modelling with ARIMA and related models. The aim of the package is to provide consistent interface for the user. For example, a single function autocorrelations() computes various kinds of theoretical and sample autocorrelations. This is work in progress, see the documentation and vignettes for the current functionality. Function sarima() fits extended multiplicative seasonal ARIMA models with trends, exogenous variables and arbitrary roots on the unit circle, which can be fixed or estimated (for the algebraic basis for this see <doi:10.48550/arXiv.2208.05055>, a paper on the methodology is being prepared).
Author: Georgi N. Boshnakov [aut, cre] , Jamie Halliday [aut]
Maintainer: Georgi N. Boshnakov <georgi.boshnakov@manchester.ac.uk>

Diff between sarima versions 0.9.4 dated 2025-03-18 and 0.9.5 dated 2025-12-16

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Package mclogit updated to version 0.9.15 with previous version 0.9.6 dated 2022-10-27

Title: Multinomial Logit Models for Categorical Responses and Discrete Choices
Description: Provides estimators for multinomial logit models in their conditional logit (for discrete choices) and baseline logit variants (for categorical responses), optionally with overdispersion or random effects. Random effects models are estimated using the PQL technique (based on a Laplace approximation) or the MQL technique (based on a Solomon-Cox approximation). Estimates should be treated with caution if the group sizes are small.
Author: Martin Elff [aut, cre]
Maintainer: Martin Elff <martin@elff.eu>

Diff between mclogit versions 0.9.6 dated 2022-10-27 and 0.9.15 dated 2025-12-16

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Package MachineShop updated to version 3.9.1 with previous version 3.9.0 dated 2025-06-09

Title: Machine Learning Models and Tools
Description: Meta-package for statistical and machine learning with a unified interface for model fitting, prediction, performance assessment, and presentation of results. Approaches for model fitting and prediction of numerical, categorical, or censored time-to-event outcomes include traditional regression models, regularization methods, tree-based methods, support vector machines, neural networks, ensembles, data preprocessing, filtering, and model tuning and selection. Performance metrics are provided for model assessment and can be estimated with independent test sets, split sampling, cross-validation, or bootstrap resampling. Resample estimation can be executed in parallel for faster processing and nested in cases of model tuning and selection. Modeling results can be summarized with descriptive statistics; calibration curves; variable importance; partial dependence plots; confusion matrices; and ROC, lift, and other performance curves.
Author: Brian J Smith [aut, cre]
Maintainer: Brian J Smith <brian-j-smith@uiowa.edu>

Diff between MachineShop versions 3.9.0 dated 2025-06-09 and 3.9.1 dated 2025-12-16

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Package gt updated to version 1.2.0 with previous version 1.1.0 dated 2025-09-23

Title: Easily Create Presentation-Ready Display Tables
Description: Build display tables from tabular data with an easy-to-use set of functions. With its progressive approach, we can construct display tables with a cohesive set of table parts. Table values can be formatted using any of the included formatting functions. Footnotes and cell styles can be precisely added through a location targeting system. The way in which 'gt' handles things for you means that you don't often have to worry about the fine details.
Author: Richard Iannone [aut, cre] , Joe Cheng [aut], Barret Schloerke [aut] , Shannon Haughton [aut], Ellis Hughes [aut] , Alexandra Lauer [aut] , Romain Francois [aut], JooYoung Seo [aut] , Ken Brevoort [aut] , Olivier Roy [aut], Posit Software, PBC [cph, [...truncated...]
Maintainer: Richard Iannone <rich@posit.co>

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Package ggsem updated to version 0.9.6 with previous version 0.2.4 dated 2025-02-02

Title: Interactively Visualize Structural Equation Modeling Diagrams
Description: It enables users to perform interactive and reproducible visualizations of path diagrams for structural equation modeling (SEM) and networks using interactive parameter visualization. Meta-data of figure outputs can be either reloaded, replayed or reproduced as objects with figure outputs or images.
Author: Seung Hyun Min [aut, cre]
Maintainer: Seung Hyun Min <seung.min@mail.mcgill.ca>

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Package BAS updated to version 2.0.0 with previous version 1.7.5 dated 2024-11-28

Title: Bayesian Variable Selection and Model Averaging using Bayesian Adaptive Sampling
Description: Package for Bayesian Variable Selection and Model Averaging in linear models and generalized linear models using stochastic or deterministic sampling without replacement from posterior distributions. Prior distributions on coefficients are from Zellner's g-prior or mixtures of g-priors corresponding to the Zellner-Siow Cauchy Priors or the mixture of g-priors from Liang et al (2008) <DOI:10.1198/016214507000001337> for linear models or mixtures of g-priors from Li and Clyde (2019) <DOI:10.1080/01621459.2018.1469992> in generalized linear models. Other model selection criteria include AIC, BIC and Empirical Bayes estimates of g. Sampling probabilities may be updated based on the sampled models using sampling w/out replacement or an efficient MCMC algorithm which samples models using a tree structure of the model space as an efficient hash table. See Clyde, Ghosh and Littman (2010) <DOI:10.1198/jcgs.2010.09049> for details on the sampling algorithms. Uniform prior [...truncated...]
Author: Merlise Clyde [aut, cre, cph] , Michael Littman [ctb], Joyee Ghosh [ctb], Yingbo Li [ctb], Betsy Bersson [ctb], Don van de Bergh [ctb], Quanli Wang [ctb]
Maintainer: Merlise Clyde <clyde@duke.edu>

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Package alakazam updated to version 1.4.2 with previous version 1.4.1 dated 2025-10-02

Title: Immunoglobulin Clonal Lineage and Diversity Analysis
Description: Provides methods for high-throughput adaptive immune receptor repertoire sequencing (AIRR-Seq; Rep-Seq) analysis. In particular, immunoglobulin (Ig) sequence lineage reconstruction, lineage topology analysis, diversity profiling, amino acid property analysis and gene usage. Citations: Gupta and Vander Heiden, et al (2017) <doi:10.1093/bioinformatics/btv359>, Stern, Yaari and Vander Heiden, et al (2014) <doi:10.1126/scitranslmed.3008879>.
Author: Susanna Marquez [cre, aut], Namita Gupta [aut], Nima Nouri [aut], Ruoyi Jiang [aut], Julian Zhou [aut], Kenneth Hoehn [aut], Daniel Gadala-Maria [ctb], Edel Aron [ctb], Cole Jensen [aut], Gisela Gabernet [ctb], Caroline Sullivan [ctb], Hailong Meng [ [...truncated...]
Maintainer: Susanna Marquez <susanna.marquez@yale.edu>

Diff between alakazam versions 1.4.1 dated 2025-10-02 and 1.4.2 dated 2025-12-16

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