Mon, 14 Sep 2026

Package vigicaen updated to version 2.1.0 with previous version 2.0.0 dated 2026-06-24

Title: 'VigiBase' Pharmacovigilance Database Toolbox
Description: Perform the analysis of the World Health Organization (WHO) Pharmacovigilance database 'VigiBase' (Extract Case Level version), <https://who-umc.org/> e.g., load data, perform data management, disproportionality analysis, and descriptive statistics. Intended for pharmacovigilance routine use or studies. This package is NOT supported nor reflect the opinion of the WHO, or the Uppsala Monitoring Centre. Disproportionality methods are described by Norén et al (2013) <doi:10.1177/0962280211403604>.
Author: Charles Dolladille [aut, cre] , Basile Chretien [aut] , Universite de Caen Normandie [cph] , Unite de pharmaco-epidemiologie [cph]
Maintainer: Charles Dolladille <cdolladille@hotmail.com>

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Package SuperLearner updated to version 2.0-42 with previous version 2.0-41 dated 2026-08-21

Title: Super Learner Prediction
Description: Implements the super learner prediction method and contains a library of prediction algorithms to be used in the super learner.
Author: Eric Polley [aut, cre], Erin LeDell [aut], Chris Kennedy [aut], Sam Lendle [ctb], Mark van der Laan [aut, ths]
Maintainer: Eric Polley <epolley@uchicago.edu>

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Package skymodelr updated to version 0.6.4 with previous version 0.3.2 dated 2026-06-27

Title: Generates and Samples Realistic Terrestrial Atmospheres
Description: Generates physically based sky environment maps and radiance samples using the spectral Hosek-Wilkie and Prague atmosphere models. Functions write high-dynamic-range 'OpenEXR' domes in latitude-longitude projections, compute per-direction RGB or 55-channel values, and optionally composite time-accurate star fields and moon phases. Features include automatic sun and moon positioning from date, time and location, support for sea-level and high-altitude observers, wide-spectrum coefficients, and multithreaded C++ acceleration for fast, high-resolution output. For model details, see Hosek and Wilkie (2012) <doi:10.1145/2185520.2185591>, Hosek and Wilkie (2013) <doi:10.1109/MCG.2013.18>, Wilkie et al. (2021) <doi:10.1145/3450626.3459758>, and Vevoda et al. (2022) <doi:10.1111/cgf.14677>.
Author: Tyler Morgan-Wall [aut, cre, cph], Petr Vevoda [ctb], Charles University [cph], Eric Bruneton [ctb, cph], Lukas Hosek [ctb, cph], Alexander Wilkie [ctb, cph]
Maintainer: Tyler Morgan-Wall <tylermw@gmail.com>

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Package pdynmc updated to version 0.9.13 with previous version 0.9.12 dated 2025-02-20

Title: Moment Condition Based Estimation of Linear Dynamic Panel Data Models
Description: Linear dynamic panel data modeling based on linear and nonlinear moment conditions as proposed by Holtz-Eakin, Newey, and Rosen (1988) <doi:10.2307/1913103>, Ahn and Schmidt (1995) <doi:10.1016/0304-4076(94)01641-C>, and Arellano and Bover (1995) <doi:10.1016/0304-4076(94)01642-D>. Estimation of the model parameters relies on the Generalized Method of Moments (GMM) and instrumental variables (IV) estimation, numerical optimization (when nonlinear moment conditions are employed) and the computation of closed form solutions (when estimation is based on linear moment conditions). One-step, two-step and iterated estimation is available. For inference and specification testing, Windmeijer (2005) <doi:10.1016/j.jeconom.2004.02.005> and doubly corrected standard errors (Hwang, Kang, Lee, 2021 <doi:10.1016/j.jeconom.2020.09.010>) are available. Additionally, serial correlation tests, tests for overidentification, and Wald tests are provided. Functions for visualiz [...truncated...]
Author: Markus Fritsch [aut, cre], Joachim Schnurbus [aut], Andrew Adrian Yu Pua [aut]
Maintainer: Markus Fritsch <Markus.Fritsch@uni-Passau.de>

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Package opencv updated to version 0.6.0 with previous version 0.5.2 dated 2026-02-21

Title: Bindings to 'OpenCV' Computer Vision Library
Description: Exposes some of the available 'OpenCV' <https://opencv.org/> algorithms, such as a QR code scanner, and edge, body or face detection. These can either be applied to analyze static images, or to filter live video footage from a camera device.
Author: Jeroen Ooms [aut, cre] , Jan Wijffels [aut]
Maintainer: Jeroen Ooms <jeroenooms@gmail.com>

Diff between opencv versions 0.5.2 dated 2026-02-21 and 0.6.0 dated 2026-09-14

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Package LSJM updated to version 0.1.1 with previous version 0.1.0 dated 2026-08-04

Title: Estimate Location-Scale Joint Models
Description: Estimation of mixed models including a subject-specific variance that can be time- and covariate-dependent or defined for within- and between-visit variability. In the joint modeling framework, the package handles left truncation, interval censoring, and multistate models, and allows a flexible dependence structure between competing events and the longitudinal marker. Estimation is performed in a frequentist framework using the Marquardt-Levenberg algorithm. Methods are described in Courcoul et al. (2025) <doi:10.1002/sim.70244> and in Courcoul et al. (2026) <doi:10.1002/bimj.70123>.
Author: Leonie Courcoul [aut, cre], Antoine Barbieri [aut], Helene Jacqmin-Gadda [aut]
Maintainer: Leonie Courcoul <courcoul.leonie498@gmail.com>

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Package Guerry updated to version 1.8.5 with previous version 1.8.3 dated 2023-10-24

Title: Maps, Data and Methods Related to Guerry (1833) "Moral Statistics of France"
Description: Contains maps of France in 1830 and multivariate datasets from A.-M. Guerry and others. Statistical and graphic methods related to Guerry's "Moral Statistics of France" are used to understand Guerry's data and illustrate methods. The goal is to facilitate the exploration and development of statistical and graphic methods for multivariate data in a geospatial context of historical interest.
Author: Michael Friendly [aut, cre] , Stephane Dray [aut] , Roger Bivand [ctb], Kathryn DuBois [ctb]
Maintainer: Michael Friendly <friendly@yorku.ca>

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Package toolmaRk updated to version 0.0.2 with previous version 0.0.1 dated 2018-01-16

Title: Tests for Same-Source of Toolmarks
Description: Implements two tests for same-source of toolmarks. The chumbley_non_random() test follows the paper "An Improved Version of a Tool Mark Comparison Algorithm" by Hadler and Morris (2017) <doi:10.1111/1556-4029.13640>. This is an extension of the Chumbley score as previously described in "Validation of Tool Mark Comparisons Obtained Using a Quantitative, Comparative, Statistical Algorithm" by Chumbley et al (2010) <doi:10.1111/j.1556-4029.2010.01424.x>. fixed_width_no_modeling() is based on correlation measures in a diamond shaped area of the toolmark as described in Hadler (2017).
Author: Jeremy Hadler [aut, cre], Max Morris [ths], Heike Hofmann [ctb]
Maintainer: Jeremy Hadler <hadler13@yahoo.com>

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Package thamesmix updated to version 0.1.4 with previous version 0.1.3 dated 2025-07-14

Title: Truncated Harmonic Mean Estimator of the Marginal Likelihood for Mixtures
Description: Implements the truncated harmonic mean estimator (THAMES) of the reciprocal marginal likelihood for uni- and multivariate mixture models using posterior samples and unnormalized log posterior values via reciprocal importance sampling. Metodiev, Irons, Perrot-Dockès, Latouche & Raftery (2025) <doi:10.48550/arXiv.2504.21812>.
Author: Martin Metodiev [aut, cre, cph] , Nicholas J. Irons [aut] , Marie Perrot-Dockes [aut]
Maintainer: Martin Metodiev <m.metodiev@tutanota.com>

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Package summarySCI updated to version 0.1.2 with previous version 0.1.1 dated 2025-10-15

Title: Produces Publication-Ready Summary Tables
Description: Produces tables with descriptive statistics for continuous, categorical and dichotomous variables. It is largely based on the package 'gtsummary'; Sjoberg DD et al. (2021) <doi:10.32614/RJ-2021-053>.
Author: Saemi Schaer [aut], Charlotte Micheloud [cre, aut]
Maintainer: Charlotte Micheloud <Charlotte.Micheloud@swisscancerinstitute.ch>

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Package miic updated to version 2.0.4 with previous version 2.0.3 dated 2024-09-17

Title: Learning Causal or Non-Causal Graphical Models Using Information Theory
Description: Multivariate Information-based Inductive Causation, better known by its acronym MIIC, is a causal discovery method, based on information theory principles, which learns a large class of causal or non-causal graphical models from purely observational data, while including the effects of unobserved latent variables. Starting from a complete graph, the method iteratively removes dispensable edges, by uncovering significant information contributions from indirect paths, and assesses edge-specific confidences from randomization of available data. The remaining edges are then oriented based on the signature of causality in observational data. The recent more interpretable MIIC extension (iMIIC) further distinguishes genuine causes from putative and latent causal effects, while scaling to very large datasets (hundreds of thousands of samples). Since the version 2.0, MIIC also includes a temporal mode (tMIIC) to learn temporal causal graphs from stationary time series data. MIIC has been appli [...truncated...]
Author: Franck Simon [aut, cre], Ali Chemkhi [aut], Tiziana Tocci [aut], Nikita Lagrange [aut], Orianne Debeaupuis [aut], Louise Dupuis [aut], Vincent Cabeli [aut], Honghao Li [aut], Marcel Ribeiro Dantas [aut], Nadir Sella [aut], Louis Verny [aut], Severine [...truncated...]
Maintainer: Franck Simon <franck.simon@curie.fr>

Diff between miic versions 2.0.3 dated 2024-09-17 and 2.0.4 dated 2026-09-14

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 man/hematoData.Rd              |    2 -
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 src/computation_cache.h        |   72 +++++++++++++++++++++++++++++++++++++----
 10 files changed, 95 insertions(+), 27 deletions(-)

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Package DiscreteTests updated to version 0.5.2 with previous version 0.5.1 dated 2026-09-02

Title: Vectorised Computation of P-Values and Their Supports for Several Discrete Statistical Tests
Description: Provides vectorised functions for computing p-values of various common discrete statistical tests, as described e.g. in Agresti (2002) <doi:10.1002/0471249688>, including their distributions. Exact and approximate computation methods are provided. For exact ones, several procedures of determining two-sided p-values are included, which are outlined in more detail in Hirji (2006) <doi:10.1201/9781420036190>.
Author: Florian Junge [cre, aut] , Christina Kihn [aut], Sebastian Doehler [ctb] , Guillermo Durand [ctb]
Maintainer: Florian Junge <diso.fbmn@h-da.de>

Diff between DiscreteTests versions 0.5.1 dated 2026-09-02 and 0.5.2 dated 2026-09-14

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Package BigDataStatMeth updated to version 2.0.5 with previous version 2.0.4 dated 2026-07-19

Title: Scalable Statistical Computing with HDF5-Backed Matrices
Description: A framework for 'scalable' statistical computing on large on-disk matrices stored in 'HDF5' files. It provides efficient block-wise implementations of core linear-algebra operations (matrix multiplication, SVD, PCA, and QR decomposition) written in C++ and R, along with building blocks from which higher-level multivariate methods such as canonical correlation analysis can be constructed. These building blocks are designed not only for direct use, but also as foundational components for developing new statistical methods that must operate on datasets too large to fit in memory. The package supports data provided either as 'HDF5' files or standard R objects, and is intended for high-dimensional applications such as 'omics' and precision-medicine research.
Author: Dolors Pelegri-Siso [aut, cre] , Juan R. Gonzalez [aut]
Maintainer: Dolors Pelegri-Siso <dolors.pelegri@isglobal.org>

Diff between BigDataStatMeth versions 2.0.4 dated 2026-07-19 and 2.0.5 dated 2026-09-14

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 68 files changed, 2435 insertions(+), 475 deletions(-)

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New package rSSP with initial version 0.1.0
Package: rSSP
Title: Single Acceptance Sampling Plans for Time-Truncated Life Test
Version: 0.1.0
Description: Designing single acceptance sampling inspection plans under time-truncated life tests and calculates the minimum required sample size subject to a consumer's risk constraint on the probability of acceptance. Failure probabilities can be supplied from any lifetime distribution, allowing the methodology to be applied without restricting the analysis to a particular probability model. The package also provides plot of the required sample size against the termination ratio. Tripathi et al. (2023) <doi:10.1007/s41872-023-00221-x>; Hu and Gui (2018) <doi:10.1080/09720510.2017.1413044>.
License: GPL-3
Encoding: UTF-8
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-09-03 06:47:19 UTC; Admin
Author: Harsh Tripathi [aut, cre]
Maintainer: Harsh Tripathi <rsearchstat21@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-14 20:00:02 UTC

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New package p2oncology with initial version 0.1.1
Package: p2oncology
Version: 0.1.1
Title: Single Arm Phase 2 Oncology Trial
Author: Ping Gao [aut, cre]
Maintainer: Ping Gao <support@innovatiostat.com>
Description: Single arm phase 2 oncology trial. For more details see P. Gao (2024) <doi:10.1080/10543406.2024.2341673>.
Depends: clinfun, mvtnorm, doParallel
License: MIT + file LICENSE
Encoding: UTF-8
Imports: foreach, dplyr, jsonlite
URL: https://github.com/innovatiostat/rcode
BugReports: https://github.com/innovatiostat/rcode/issues
NeedsCompilation: no
Packaged: 2026-09-04 01:08:02 UTC; chengboqin
Repository: CRAN
Date/Publication: 2026-09-14 19:50:02 UTC

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New package ZINB.GP with initial version 1.0.0
Package: ZINB.GP
Title: Bayesian Zero-Inflated Negative Binomial Gaussian Process Models
Version: 1.0.0
Description: Fits Bayesian zero-inflated negative binomial regression models with Gaussian process random effects for spatial, temporal, or spatiotemporal count data. Provides Markov chain Monte Carlo sampling, configurable random effects in the zero-inflation and count components, and posterior predictive draws. Implements a full GP version of the methods described by He and Huang (2024) <doi:10.1016/j.jspi.2023.106098>.
License: MIT + file LICENSE
Encoding: UTF-8
URL: https://github.com/KingJMS1/GP_ZINB_R, https://kingjms1.github.io/GP_ZINB_R/
BugReports: https://github.com/KingJMS1/GP_ZINB_R/issues
Imports: BayesLogit, LaplacesDemon, MASS, Matrix, msm, mvtnorm, stats
Suggests: coda, knitr, posterior, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-09-04 15:46:22 UTC; 1king
Author: Mahlon Scott [aut], Qing He [aut], Hsin-Hsiung Huang [aut, cre, cph]
Maintainer: Hsin-Hsiung Huang <hsin.huang@ucf.edu>
Repository: CRAN
Date/Publication: 2026-09-14 15:40:10 UTC

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Package TmCalculator updated to version 1.1.0 with previous version 1.0.9 dated 2026-08-28

Title: Genome-Wide Nucleic Acid Melting Temperature Profiling and Multi-Omics Integration
Description: Accurate calculation of nucleic acid melting temperature (Tm) is fundamental to many molecular biology applications, and this software scales Tm analysis from individual sequences to genome‑wide thermodynamic profiling. This package extends Tm analysis from simple sequence level computation to comprehensive genome-wide thermodynamic profiling. It takes multiple input formats including sequence strings, FASTA files, genomic coordinates. The implementation provides three Tm calculation methods: the Wallace rule (Thein & Wallace, 1986), empirical GC‑content formulas (Marmur, 1962; Schildkraut, 2010; Wetmur, 1991; Untergasser, 2012; von Ahsen, 2001), and nearest‑neighbor thermodynamics (Breslauer, 1986; Sugimoto, 1996; Allawi, 1998; SantaLucia, 2004; Freier, 1986; Xia, 1998; Chen, 2012; Bommarito, 2000; Turner, 2010; Sugimoto, 1995; Allawi, 1997; SantaLucia, 2005; Zuber, 2022; Ghosh, 2020, 2023). Nearest-neighbor parameter sets are provided for DNA, RNA and RNA/DNA hybrid duplexes. The [...truncated...]
Author: Junhui Li [cre, aut] , Lihua Julie Zhu [aut]
Maintainer: Junhui Li <ljh.biostat@gmail.com>

Diff between TmCalculator versions 1.0.9 dated 2026-08-28 and 1.1.0 dated 2026-09-14

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 TmCalculator-1.1.0/TmCalculator/NEWS.md                                            |  244 ++-
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New package SensoryDataSets with initial version 0.1.0
Package: SensoryDataSets
Title: A Collection of Sensory Evaluation and Consumer Science Datasets
Version: 0.1.0
Description: Provides a curated collection of datasets for sensory evaluation, consumer research, and related statistical applications. The collection includes consumer acceptance and liking scores, sensory profiles, descriptive evaluations, physical and chemical measurements, wine quality and bitterness assessments, and data from products such as bread, olive oil, orange juice, grape blends, wine, cocktails, and perfume. The package is intended for teaching, exploratory data analysis, statistical modeling, multivariate analysis, consumer studies, and methodological research in sensory and consumer science. The original sources and applicable licensing terms are documented in the 'LICENSES_DETAILS.md' file.
License: GPL (>= 2) | GPL-3
URL: https://github.com/dianarebaza/sensorydatasets, https://dianarebaza.github.io/sensorydatasets/
BugReports: https://github.com/dianarebaza/sensorydatasets/issues
Depends: R (>= 4.1.0)
Imports: utils
Suggests: dplyr, ggplot2, knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
Encoding: UTF-8
Language: en
LazyData: true
NeedsCompilation: no
Packaged: 2026-09-04 19:03:47 UTC; ADMIN
Author: Diana Rebaza Fernandez [aut, cre, cph]
Maintainer: Diana Rebaza Fernandez <drebazaf@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-14 15:40:17 UTC

More information about SensoryDataSets at CRAN
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New package mardist with initial version 1.0.1
Package: mardist
Title: Calculation of Maritime Distances
Version: 1.0.1
Encoding: UTF-8
Date: 2026-09-03
Description: Tools and utilities for calculating distances and visualising maritime routes.
License: EUPL
Depends: R (>= 3.5)
Imports: data.table, dplyr, leaflet, igraph
LazyData: true
NeedsCompilation: no
Packaged: 2026-09-04 13:47:20 UTC; chrisps@delta.europa.eu
Author: Panayotis Christidis [cre, aut]
Maintainer: Panayotis Christidis <Panayotis.Christidis@ec.europa.eu>
Repository: CRAN
Date/Publication: 2026-09-14 15:30:02 UTC

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New package koopman.dmd with initial version 0.2.2
Package: koopman.dmd
Title: Koopman Operator and Dynamic Mode Decomposition for Dynamical Systems
Version: 0.2.2
Description: Dynamic Mode Decomposition (DMD) with Koopman operator theory extensions, powered by a Rust backend via 'extendr'. Provides standard DMD as described in Schmid (2010) <doi:10.1017/S0022112010001217>, DMD with control for forced linear systems following Proctor, Brunton, and Kutz (2016) <doi:10.1137/15M1013857>, Extended DMD with lifting functions, Hankel-DMD via time-delay embedding, Generalized Laplace Analysis for direct eigenfunction computation, and harmonic time averages and mesochronic harmonic plots for phase space analysis as developed in Mezic (2020) <doi:10.48550/arXiv.2009.05883>. Includes built-in area-preserving and chaotic maps for experimentation.
License: MIT + file LICENSE
Encoding: UTF-8
SystemRequirements: Cargo (Rust's package manager), rustc (>= 1.85)
Depends: R (>= 4.0)
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
URL: https://github.com/jimeharrisjr/rust-dmd, https://jimeharrisjr.github.io/rust-dmd/
BugReports: https://github.com/jimeharrisjr/rust-dmd/issues
NeedsCompilation: yes
Biarch: false
Packaged: 2026-09-03 23:59:34 UTC; jimharris
Author: James Harris [aut, cre, cph], The authors of the dependency Rust crates [ctb]
Maintainer: James Harris <jimeharrisjr@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-14 15:20:02 UTC

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New package featR with initial version 0.1.0
Package: featR
Title: A Unified Toolkit for Feature Selection
Version: 0.1.0
Description: Filter, wrapper, and embedded feature-selection methods behind a consistent set of functions that share one calling convention and one return type: correlation and chi-squared filters, information gain, LASSO and elastic net, Bayesian model comparison, Boruta, recursive feature elimination, random forest importance, multivariate adaptive regression splines, support vector machine recursive feature elimination, stepwise selection, and principal component / singular value decomposition helpers. The implemented methods follow Tibshirani (1996) <doi:10.1111/j.2517-6161.1996.tb02080.x>, Zou and Hastie (2005) <doi:10.1111/j.1467-9868.2005.00503.x>, Friedman (1991) <doi:10.1214/aos/1176347963>, Breiman (2001) <doi:10.1023/A:1010933404324>, Guyon, Weston, Barnhill and Vapnik (2002) <doi:10.1023/A:1012487302797>, Kursa and Rudnicki (2010) <doi:10.18637/jss.v036.i11>, and Vehtari, Gelman and Gabry (2017) <doi:10.1007/s11222-016-9696-4>. Heavy modeling en [...truncated...]
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-US
Depends: R (>= 4.1.0)
Imports: data.table, parallel, stats, utils, withr
Suggests: bigstatsr, Boruta, brms, caret, doParallel, e1071, earth, foreach, furrr, future, ggplot2, glmnet, kernlab, knitr, loo, MASS, Matrix, MLmetrics, pbapply, polycor, pROC, PRROC, randomForest, rmarkdown, RSpectra, testthat (>= 3.0.0)
VignetteBuilder: knitr
URL: https://github.com/elkronos/featR
BugReports: https://github.com/elkronos/featR/issues
NeedsCompilation: no
Packaged: 2026-09-04 21:00:35 UTC; appleair
Author: Justin Chase [aut, cre, cph]
Maintainer: Justin Chase <jchase.msu@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-14 15:40:02 UTC

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New package cureAssess with initial version 0.1.0
Package: cureAssess
Title: Assessing Cure Model Appropriateness for Survival Data
Version: 0.1.0
Description: Assesses whether cure models are appropriate for right-censored survival data, where a fraction of subjects may never experience the event of interest. Implements a two-stage workflow combining Kaplan-Meier visualization and comparison of parametric cure and non-cure models by the Akaike information criterion with formal diagnostics for sufficient follow-up and for the presence of a cured fraction. The diagnostics include the statistics of Maller and Zhou (1992) <doi:10.1093/biomet/79.4.731> and Maller and Zhou (1994) <doi:10.1080/01621459.1994.10476889>, the test of Shen (2000) <doi:10.1016/S0167-7152(00)00063-8>, and the ratio estimation of censored uncured subjects ('RECeUS') method of Selukar and Othus (2023) <doi:10.1002/sim.9610>.
License: MIT + file LICENSE
URL: https://github.com/GeethanjaleeM/cureAssess
BugReports: https://github.com/GeethanjaleeM/cureAssess/issues
Encoding: UTF-8
Language: en-US
Depends: R (>= 4.1.0)
Imports: survival, flexsurv, flexsurvcure, survminer, ggplot2, dplyr, stats
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-09-02 19:48:52 UTC; durbadal
Author: Geethanjalee Mudunkotuwa [aut, cre, cph], Durbadal Ghosh [aut]
Maintainer: Geethanjalee Mudunkotuwa <geethanjaleem@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-14 15:50:02 UTC

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New package xplaineff with initial version 0.1.0
Package: xplaineff
Title: Decomposing Global Feature Effects Based on Feature Interactions
Version: 0.1.0
Description: Implements the GADGET (Generalized Additive Decomposition of Global EffecTs) algorithm for interpretable machine learning. The package recursively partitions the feature space to minimize heterogeneity of feature effects (e.g., Accumulated Local Effects or Partial Dependence), producing a tree of regions where effects are more stable. It supports both ALE and PD strategies, works with 'mlr3' learners and provides visualization of the interaction tree and regional effect plots. The method is described in Herbinger, J., Wright, M. N., Nagler, T., Bischl, B., and Casalicchio, G. (2024), "Decomposing Global Feature Effects Based on Feature Interactions" <https://jmlr.org/papers/volume25/23-0699/23-0699.pdf>.
License: MIT + file LICENSE
Depends: R (>= 4.3.0)
URL: https://github.com/mlr-org/xplaineff
BugReports: https://github.com/mlr-org/xplaineff/issues
Encoding: UTF-8
Imports: checkmate (>= 2.3.2), cli (>= 3.0.0), data.table (>= 1.14.0), ggplot2 (>= 3.5.2), ggraph (>= 2.2.1), igraph (>= 2.1.4), mlr3misc (>= 0.14.0), patchwork (>= 1.3.0), R6 (>= 2.6.1), Rcpp (>= 1.0.0)
LinkingTo: Rcpp, RcppArmadillo
Suggests: testthat (>= 3.0.0), iml (>= 0.11.4), mlr3, mlr3learners, ranger, ISLR2, rpart, withr, xgboost
NeedsCompilation: yes
Packaged: 2026-09-04 08:21:15 UTC; zzz
Author: Zizheng Zhang [aut, cre]
Maintainer: Zizheng Zhang <Zizheng.Zhang@stat.uni-muenchen.de>
Repository: CRAN
Date/Publication: 2026-09-14 15:00:02 UTC

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New package AutoViz with initial version 1.0.0
Package: AutoViz
Title: Automated Data Visualization and Exploratory Dashboarding
Version: 1.0.0
Description: Provides automated exploratory data analysis, visualization recommendation, summary statistics, missing-value assessment, outlier screening, and HTML dashboard generation for rectangular data. The package automatically identifies variable types and common analytical relationships and recommends appropriate visualization methods based on data structure, cardinality, and analytical objectives. It provides a transparent, reproducible workflow for data profiling and visualization that can be used independently or as a component within interactive applications.
License: MIT + file LICENSE
Language: en-US
Encoding: UTF-8
Imports: ggplot2, htmltools, rlang
Suggests: testthat (>= 3.0.0), knitr, rmarkdown, shiny
VignetteBuilder: knitr
URL: https://github.com/vinodhpmd/AutoViz
BugReports: https://github.com/vinodhpmd/AutoViz/issues
NeedsCompilation: no
Packaged: 2026-09-04 05:14:50 UTC; m
Author: Vinodhkumar Obli Rajendran [aut, cre], Keerthi Aaradhana [aut]
Maintainer: Vinodhkumar Obli Rajendran <vinodhkumar.rajendran@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-14 14:50:02 UTC

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Package ast2ast readmission to version 1.0 with previous version 0.3.2 dated 2023-12-09

Title: Translates an R Function to a C++ Function
Description: Enable translation of a tiny subset of R to C++. The user has to define a R function which gets translated. For a full list of possible functions check the documentation. After translation an R function is returned which is a shallow wrapper around the C++ code. Alternatively an external pointer to the C++ function is returned to the user. The intention of the package is to generate fast functions which can be used as ode-system or during optimization.
Author: Kraemer Konrad [aut, cre]
Maintainer: Kraemer Konrad <konrad_kraemer@yahoo.de>

This is a re-admission after prior archival of version 0.3.2 dated 2023-12-09

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Package sportsfeatures updated to version 0.2.0 with previous version 0.1.0 dated 2026-06-30

Title: Longitudinal Sports Analytics Asset and Workload Feature Processing
Description: A synthetic, longitudinal athletic dataset generated through a transparent, rule-based simulation engine. Captures individual activity sessions across multiple athletes, environmental conditions, and physiological responses. Specifically designed as an alternative to legacy teaching datasets by introducing realistic hierarchical repeated measures, complex two-way covariate interactions, and a deliberate Missing Not At Random (MNAR) tracking mechanism suitable for advanced imputation workflows. Methodologies implemented are based on van Buuren (2018) <doi:10.1201/9780429492259> and Bates et al. (2015) <doi:10.18637/jss.v067.i01>.
Author: Mohammad Abbas [aut, cre]
Maintainer: Mohammad Abbas <ma.abbas3107@gmail.com>

Diff between sportsfeatures versions 0.1.0 dated 2026-06-30 and 0.2.0 dated 2026-09-14

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Package ggChinaFlag updated to version 0.4.0 with previous version 0.3.0 dated 2026-07-14

Title: Drawing Chinese National and Historical Flags with 'ggplot2'
Description: Provides programmatic implementations for drawing Chinese national and historical flags using analytic geometry and 'ggplot2'-based vector graphics. Flag designs are constructed entirely from geometric primitives such as polygons and rectangles, without relying on external image files. The package is intended for educational demonstration, reproducible visualization, and procedural graphics in R.
Author: Zhaoshuo Liu [aut, cre]
Maintainer: Zhaoshuo Liu <liuzhaoshuo1997@outlook.com>

Diff between ggChinaFlag versions 0.3.0 dated 2026-07-14 and 0.4.0 dated 2026-09-14

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Package fpod updated to version 1.0.2 with previous version 1.0.1 dated 2026-05-12

Title: Read and Process 'FPOD' and 'CPOD' Data
Description: Read 'FPOD' and 'CPOD' data into 'R' directly from the 'FPOD' data files (i.e. .CP1, .CP3, .FP1 and .FP3 files). The 'FPOD' data files contain binary data, so they can't trivially be read into 'R' using the usual approach, e.g. fread() or read.csv(). This package decodes the binary data and imports all the data in one go (i.e. header/metadata, clicks, 'KERNO' classifications, environmental data and pseudo-WAV data). It is then trivial to aggregate data as you please, e.g. detection-positive-minutes per time block. The advantage of handling data processing in 'R' is a long topic, but suffice it to say that it 1) simplifies things (many fewer steps, as different vars have to be exported in multiple goes in the official 'FPOD' app), and more importantly, 2) makes data processing transparent and reproducible. References: Pirotta et al. 2014 <doi:10.1111/1365-2435.12146>.
Author: Andre Moan [aut, cre, cph]
Maintainer: Andre Moan <andre.moan@hi.no>

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Package extRC updated to version 1.3 with previous version 1.2 dated 2020-10-10

Title: Extended RC Models for Contingency Tables
Description: Maximum likelihood estimation of an extended class of row-column (RC) association models for two-dimensional contingency tables, which are formulated by a condition of reduced rank on a matrix of extended association parameters; see Forcina (2019) <doi:10.48550/arXiv.1910.13848>. These parameters are defined by choosing the logit type for the row and column variables among four different options and a transformation derived from suitable divergence measures.
Author: Francesco Bartolucci [aut, cre], Antonio Forcina [aut]
Maintainer: Francesco Bartolucci <francesco.bartolucci@unipg.it>

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Package fpop (with last version 2019.08.26) was removed from CRAN

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

2019-08-27 2019.08.26

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Package reviser updated to version 0.3.1 with previous version 0.3.0 dated 2026-09-02

Title: Analyzing Revisions in Real-Time Time Series Vintages
Description: Analyzes revisions in real-time time series vintages. The package converts between wide revision triangles and tidy long vintages, extracts selected releases, computes revision series, visualizes vintage paths, and summarizes revision properties such as bias, dispersion, autocorrelation, and news-noise diagnostics. It also identifies efficient releases and estimates state-space models for revision nowcasting. Methods are based on Howrey (1978) <doi:10.2307/1924972>, Jacobs and Van Norden (2011) <doi:10.1016/j.jeconom.2010.04.010>, and Kishor and Koenig (2012) <doi:10.1198/jbes.2010.08169>.
Author: Marc Burri [aut, cre, cph] , Philipp Wegmueller [aut, cph]
Maintainer: Marc Burri <marc.burri91@gmail.com>

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Package arcstat updated to version 0.3.0 with previous version 0.2.0 dated 2026-09-11

Title: Arc-Length Statistics: Goodness of Fit, Distributions and a Bayesian Test
Description: Inference from the arc length of statistical functions. Three tools share one pure-C back-end: a goodness-of-fit test based on the arc length of the probability plot, with an analytic saddlepoint null and sensitivity to local density structure that the empirical-distribution tests miss; two constructions that build a distribution from the arc length of its defining curve, the arc-length generator and the quantile arc-length family estimated by L-moments; and a Bayesian nonparametric arc-length goodness-of-fit test on the Dirichlet-process posterior. The same C sources back the 'Python' package 'arcstat'.
Author: M. Theodor Loots [aut, cre]
Maintainer: M. Theodor Loots <theo.loots@gmail.com>

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Package rxode2 updated to version 5.1.7 with previous version 5.1.6 dated 2026-08-04

Title: Facilities for Simulating from ODE-Based Models
Description: Facilities for running simulations from ordinary differential equation ('ODE') models, such as pharmacometrics and other compartmental models. A compilation manager translates the ODE model into C, compiles it, and dynamically loads the object code into R for improved computational efficiency. An event table object facilitates the specification of complex dosing regimens (optional) and sampling schedules. NB: The use of this package requires both C and Fortran compilers, for details on their use with R please see Section 6.3, Appendix A, and Appendix D in the "R Administration and Installation" manual. Also the code is mostly released under GPL. The 'VODE' and 'LSODA' are in the public domain. The vendored 'SUNDIALS' 'CVODE' sources and headers are released under the BSD-3-Clause license. The information is available in the inst/COPYRIGHTS.
Author: Matthew L. Fidler [aut, cre] , Wenping Wang [aut], Aaron Collier [ctb] , Alan Hindmarsh [ctb], Arun Srinivasan [ctb], Ashley Crawford [ctb] , Awad H. Al-Mohy [ctb], Bill Denney [ctb] , Cleve Moler [ctb], Cody J. Balos [ctb] , Dan Shumaker [ctb] , Dan [...truncated...]
Maintainer: Matthew L. Fidler <matthew.fidler@gmail.com>

Diff between rxode2 versions 5.1.6 dated 2026-08-04 and 5.1.7 dated 2026-09-14

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More information about rxode2 at CRAN
Permanent link

Package pslr updated to version 1.2.1 with previous version 1.1.1 dated 2026-07-19

Title: Public Suffix List Engine
Description: A focused implementation of the Public Suffix List (PSL). Bundles a reproducible, pinned PSL snapshot and implements the official prevailing-rule algorithm to answer public-suffix (eTLD) and registrable-domain (eTLD+1) queries. Distinguishes ICANN and PRIVATE rule sections, accepts Unicode and ASCII hostnames via 'punycoder' canonicalization, and supports an explicit, validated offline refresh path. The matcher is compiled with 'cpp11' and requires no external system library. Used as the PSL engine by the 'rurl' package.
Author: Bart Turczynski [aut, cre]
Maintainer: Bart Turczynski <bartek@turczynski.pl>

Diff between pslr versions 1.1.1 dated 2026-07-19 and 1.2.1 dated 2026-09-14

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Package oeli updated to version 0.7.8 with previous version 0.7.7 dated 2026-09-04

Title: Some Utilities for Developing Data Science Software
Description: A collection of general-purpose helper functions that I (and maybe others) find useful when developing data science software. Includes tools for simulation, data transformation, input validation, and more.
Author: Lennart Oelschlaeger [aut, cre]
Maintainer: Lennart Oelschlaeger <oelschlaeger.lennart@gmail.com>

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Package multiflexscan updated to version 0.2.0 with previous version 0.1.0 dated 2026-07-24

Title: Information Criterion and Scan Statistic Approach for Detecting Multiple Disease Clusters
Description: Detecting multiple disease clusters using the information criterion and scan statistic approach developed by Takahashi and Shimadzu (2020) <doi:10.1186/s12942-020-00228-y>.
Author: Takahiro Otani [aut, cre] , Kunihiko Takahashi [aut]
Maintainer: Takahiro Otani <t.otani@aichi-cc.jp>

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Package mand updated to version 3.0 with previous version 2.0 dated 2023-09-12

Title: Multivariate Analysis for Neuroimaging Data
Description: Provides functions for multivariate analysis and visualization of neuroimaging data. The package contains the functions and example data used in the book 'Multivariate Analysis for Neuroimaging Data' by Kawaguchi (2021, ISBN: 978-0367255329). It includes utilities for image visualization, image data matrix construction, basis reconstruction, multicomponent visualization, predictive modeling, simulation, and multiblock analysis. Version 3.0 preserves the public interfaces used in the accompanying package vignettes.
Author: Atsushi Kawaguchi [aut, cre]
Maintainer: Atsushi Kawaguchi <kawa_a24@yahoo.co.jp>

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Package HDElliptical updated to version 0.1.3 with previous version 0.1.2 dated 2026-09-09

Title: High-Dimensional Methods for Elliptically Symmetric Distributions
Description: Fast, documented implementations of robust estimation, testing, dimension reduction, classification, and clustering methods for high-dimensional elliptically symmetric data. Computational kernels use 'Rcpp' and 'RcppArmadillo'. The package follows methods reviewed in Feng (2026), "High-Dimensional Data Analysis for Elliptically Symmetric Distributions" <https://github.com/flnankai/HDElliptical/releases>.
Author: Long Feng [aut, cre, cph] , Dan Zhuang [ctb]
Maintainer: Long Feng <flnankai@nankai.edu.cn>

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Package fsbrain updated to version 0.8.0 with previous version 0.7.0 dated 2026-08-23

Title: Managing and Visualizing Brain Surface Data
Description: Provides high-level access to neuroimaging data from standard software packages like 'FreeSurfer' <https://freesurfer.net/> on the level of subjects and groups. Load morphometry data, surfaces and brain parcellations based on atlases. Mask data using labels, load data for specific atlas regions only, and visualize data and statistical results directly in 'R'.
Author: Tim Schaefer [aut, cre] , The General Hospital Corporation [cph] , Van Essen Lab [cph] , Alexander Schaefer [cph] , Ru Kong [cph] , Lingzhong Fan [cph] , Edmund T. Rolls [cph] , Matthew F. Glasser [cph] , Kathryn Mills [cph]
Maintainer: Tim Schaefer <ts+code@rcmd.org>

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Package EFA.dimensions readmission to version 0.1.9.1 with previous version 0.1.8.8 dated 2026-07-21

Title: Exploratory Factor Analysis Functions for Assessing Dimensionality
Description: Functions for an assortment of factor analysis-related procedures, including eleven procedures for determining the number of factors; for factor analysis with multiple options for methods of extraction and rotation; for bi-factor analysis; for extension factor analysis; options for running the analyses using either raw data or correlation matrices as input and with options for conducting the analyses using Pearson correlations, Kendall correlations, Spearman correlations, gamma correlations, or polychoric correlations; wrapper 'lavaan'-based functions for factorial invariance and exploratory structural equation modeling; functions for the factor-ability of a correlation matrix, for the congruence between factors from different datasets, for the assessment of local independence, for the assessment of factor solution complexity, for internal consistency, and for correcting Pearson correlation coefficients for attenuation due to unreliability. Auerswald & Moshagen (2019, <doi:10.10 [...truncated...]
Author: Brian P. O'Connor [aut, cre]
Maintainer: Brian P. O'Connor <brian.oconnor@ubc.ca>

This is a re-admission after prior archival of version 0.1.8.8 dated 2026-07-21

Diff between EFA.dimensions versions 0.1.8.8 dated 2026-07-21 and 0.1.9.1 dated 2026-09-14

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Package distionary updated to version 0.2.0 with previous version 0.1.1 dated 2026-04-27

Title: Create and Evaluate Probability Distributions
Description: Create and evaluate probability distribution objects from a variety of families or define custom distributions. Automatically compute distributional properties, even when they have not been specified. This package supports statistical modeling and simulations, and forms the core of the probaverse suite of R packages.
Author: Vincenzo Coia [aut, cre, cph], Amogh Joshi [ctb], Shuyi Tan [ctb], Zhipeng Zhu [ctb], olivroy [ctb]
Maintainer: Vincenzo Coia <vincenzo.coia@gmail.com>

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Package combinat updated to version 0.0-9 with previous version 0.0-8 dated 2010-08-05

Title: Combinatorics Utilities
Description: Provides routines for combinatorial enumeration including generation of all combinations, permutations, and lattice points on hypercuboids and simplex lattices. Includes utilities for multinomial distributions: the multinomial probability mass function, random sampling with varying parameters, and encoding conversions between simplex representations. Also supplies exact and log-scale factorial computation and the generalized binomial coefficient for real-valued n. Package functions include procedures described in Reingold, Nievergelt and Deo (1977) Combinatorial Algorithms: Theory and Practice (dl.acm.org/citation.cfm?id=1096489), Feller volume 1, and Nijenhuis and Wilf (1978) Combinatorial Algorithms for Computers and Calculators (ISBN 0125192606 / 9780125192606).
Author: Scott Chasalow [aut], Vince Carey [cre]
Maintainer: Vince Carey <stvjc@channing.harvard.edu>

Diff between combinat versions 0.0-8 dated 2010-08-05 and 0.0-9 dated 2026-09-14

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Package adbcdrivermanager readmission to version 0.24.0-3 with previous version 0.24.0-2 dated 2026-08-23

Title: 'Arrow' Database Connectivity ('ADBC') Driver Manager
Description: Provides a developer-facing interface to 'Arrow' Database Connectivity ('ADBC') for the purposes of driver development, driver testing, and building high-level database interfaces for users. 'ADBC' <https://arrow.apache.org/adbc/> is an API standard for database access libraries that uses 'Arrow' for result sets and query parameters.
Author: Dewey Dunnington [aut, cre] , Apache Arrow [aut, cph], Apache Software Foundation [cph]
Maintainer: Dewey Dunnington <dewey@dunnington.ca>

This is a re-admission after prior archival of version 0.24.0-2 dated 2026-08-23

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Package PNDSIBGE (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:

2024-02-01 0.1.1
2023-11-21 0.1.0

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Package windfarmGA readmission to version 5.0.0 with previous version 4.0.0 dated 2025-01-18

Title: Genetic Algorithm for Wind Farm Layout Optimization
Description: The genetic algorithm is designed to optimize wind farms of any shape. Each layout is encoded as n unique grid-cell identifiers. It requires a predefined amount of turbines, a unified rotor radius and an average wind speed value for each incoming wind direction. A terrain effect model can be included that downloads an 'SRTM' elevation model and loads a Corine Land Cover raster to approximate surface roughness.
Author: Sebastian Gatscha [aut, cre, cph]
Maintainer: Sebastian Gatscha <sebastian_gatscha@gmx.at>

This is a re-admission after prior archival of version 4.0.0 dated 2025-01-18

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Package Sequential updated to version 4.6.3 with previous version 4.6.2 dated 2026-09-08

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

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Package rt.test updated to version 1.26.9 with previous version 1.18.7.9 dated 2018-07-10

Title: Robustified t-Test
Description: Performs one-sample t-test based on robustified statistics using median/MAD (TA) and Hodges-Lehmann/Shamos (TB). For more details, see Park, Wang and Hwang (2022) <doi:10.7232/iems.2022.21.3.432>. This work was partially supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (No. 2022R1A2C1091319).
Author: Chanseok Park [aut, cre] , Min Wang [ctb]
Maintainer: Chanseok Park <statpnu@gmail.com>

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Package rapsimng.decide.core updated to version 0.1.1 with previous version 0.1.0 dated 2026-08-09

Title: Decision-Oriented Analysis Core for APSIM Next Generation Outputs
Description: Provides a low-level interface for analysing Agricultural Production Systems sIMulator ('APSIM') Next Generation simulation outputs to support structured decision-making workflows.
Author: Bangyou Zheng [aut, cre]
Maintainer: Bangyou Zheng <zheng.bangyou@gmail.com>

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Package modeltuning readmission to version 0.1.4 with previous version 0.1.3 dated 2025-12-06

Title: Model Selection and Tuning Utilities
Description: Provides a lightweight framework for model selection and hyperparameter tuning in R. The package offers intuitive tools for grid search, cross-validation, and combined grid search with cross-validation that work seamlessly with virtually any modeling package. Designed for flexibility and ease of use, it standardizes tuning workflows while remaining fully compatible with a wide range of model interfaces and estimation functions.
Author: Daniel Molitor [aut, cre]
Maintainer: Daniel Molitor <molitdj97@gmail.com>

This is a re-admission after prior archival of version 0.1.3 dated 2025-12-06

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Package matSPACE updated to version 0.2.1 with previous version 0.1.0 dated 2026-09-12

Title: Sparse Partial Correlation Estimation for Matrix-Variate Data
Description: Fits sparse partial correlation networks for matrix-variate data by extending the SPACE joint partial correlation estimation framework to a Kronecker-product covariance structure. All partial correlations are estimated simultaneously via an L1-penalized (lasso) shooting algorithm within a single optimization framework, which preserves symmetry of the estimated network and avoids the tuning-parameter selection difficulties of separate node-wise regressions. Optional features include column reweighting, residual variance re-estimation across outer iterations, and automatic generation of a lasso penalty sequence for tuning.
Author: Hyewon Kim [aut, cre], Seongoh Park [aut]
Maintainer: Hyewon Kim <kimhw4126@gmail.com>

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Package ggforestplotR updated to version 0.5.0 with previous version 0.3.1 dated 2026-08-04

Title: Publication-Ready Forest Plots with 'ggplot2'
Description: Transform model coefficients into flexible forest plots using 'ggplot2'. Provides helpers to standardize coefficient data from a range of modelling workflows and render publication-ready forest plots with a consistent interface.
Author: Carson Richardson [aut, cre, cph]
Maintainer: Carson Richardson <carson.richardson@outlook.com>

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Package topolow updated to version 2.1.0 with previous version 2.0.1 dated 2025-08-30

Title: Force-Directed Euclidean Embedding of Dissimilarity Data
Description: A robust implementation of Topolow algorithm. It embeds objects into a low-dimensional Euclidean space from a matrix of pairwise dissimilarities, even when the data do not satisfy metric or Euclidean axioms. The package is particularly well-suited for sparse, incomplete, and censored (thresholded) datasets such as antigenic relationships. The core is a physics-inspired, gradient-free optimization framework that models objects as particles in a physical system, where observed dissimilarities define spring rest lengths and unobserved pairs exert repulsive forces. The package also provides functions specific to antigenic mapping to transform cross-reactivity and binding affinity measurements into accurate spatial representations in a phenotype space. Key features include: * Robust Embedding from Sparse Data: Effectively creates complete and consistent maps (in optimal dimensions) even with high proportions of missing data (e.g., >95%). * Physics-Inspired Optimization: Models objects (e [...truncated...]
Author: Omid Arhami [aut, cre, cph]
Maintainer: Omid Arhami <omid.arhami@uga.edu>

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Package lcpm updated to version 0.1.2 with previous version 0.1.1 dated 2020-01-09

Title: Ordinal Outcomes: Generalized Linear Models with the Log Link
Description: An implementation of the Log Cumulative Probability Model (LCPM) and Proportional Probability Model (PPM) for which the Maximum Likelihood Estimates are determined using constrained optimization. This implementation accounts for the implicit constraints on the parameter space. Other features such as standard errors, z tests and p-values use standard methods adapted from the results based on constrained optimization.
Author: Gurbakhshash Singh [aut, cre], Gordon Hilton Fick [aut]
Maintainer: Gurbakhshash Singh <gsingh@ccsu.edu>

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Package ggincerta updated to version 0.2.1 with previous version 0.2.0 dated 2026-05-25

Title: Extend 'ggplot2' with Layers and Scales for Spatial Uncertainty Visualization
Description: Provide specialized 'ggplot2' layers and scales for spatial uncertainty visualization, including bivariate choropleth maps, pixel maps, glyph maps, and exceedance probability maps.
Author: Xueqi Ma [aut, cre, cph], Emi Tanaka [aut, ths] , Weihao Li [ths] , Quan Vu [ths], Francis Hui [ths]
Maintainer: Xueqi Ma <maggiexma07@gmail.com>

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 R/geom-sf-pixel.R                                                       |    2 
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 R/guide-vsup.R                                                          |  144 -
 R/scale-bivariate-manual.R                                              |   28 
 R/scale-bivariate.R                                                     |  408 ++-
 R/scale-vsup.R                                                          |   39 
 R/vsup-quantize.R                                                       |   50 
 README.md                                                               |  282 +-
 build/partial.rdb                                                       |binary
 data/nc_sim.rda                                                         |only
 man/bivar_fade_palette.Rd                                               |    9 
 man/bivar_palette.Rd                                                    |    9 
 man/bivariate_scale.Rd                                                  |   91 
 man/figures/README-unnamed-chunk-10-1.png                               |binary
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 man/figures/README-unnamed-chunk-6-1.png                                |binary
 man/figures/README-unnamed-chunk-7-1.png                                |binary
 man/figures/README-unnamed-chunk-8-1.png                                |binary
 man/figures/README-unnamed-chunk-9-1.png                                |binary
 man/geom_sf_dualmap.Rd                                                  |    4 
 man/geom_sf_glyph.Rd                                                    |    2 
 man/geom_sf_pixel.Rd                                                    |    7 
 man/ggincerta-package.Rd                                                |    1 
 man/guide_bivariate.Rd                                                  |    5 
 man/guide_glyph.Rd                                                      |    5 
 man/guide_vsup.Rd                                                       |    5 
 man/manual_bivariate_scale.Rd                                           |   55 
 man/nc_sim.Rd                                                           |only
 man/vsup_palette.Rd                                                     |   11 
 man/vsup_quantize.Rd                                                    |   79 
 man/vsup_scale.Rd                                                       |   68 
 tests/testthat/_snaps/geom-sf-glyph/glyph-map-chernoff.svg              | 1218 ++++------
 tests/testthat/_snaps/geom-sf-glyph/glyph-map-regular.svg               |  374 +--
 tests/testthat/_snaps/scale-bivariate/bivariate-map-with-left-guide.svg |  410 +--
 tests/testthat/_snaps/scale-bivariate/bivariate-map.svg                 |  390 +--
 tests/testthat/_snaps/scale-vsup/vsup-map.svg                           |  248 +-
 tests/testthat/test-scale-bivariate.R                                   |  459 +++
 49 files changed, 3131 insertions(+), 2047 deletions(-)

More information about ggincerta at CRAN
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