Wed, 22 Oct 2025

Package echarty updated to version 1.7.0 with previous version 1.6.6 dated 2025-01-15

Title: Minimal R/Shiny Interface to JavaScript Library 'ECharts'
Description: Deliver the full functionality of 'ECharts' with minimal overhead. 'echarty' users build R lists for 'ECharts' API. Lean set of powerful commands.
Author: Larry Helgason [aut, cre]
Maintainer: Larry Helgason <larry@helgasoft.com>

Diff between echarty versions 1.6.6 dated 2025-01-15 and 1.7.0 dated 2025-10-22

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Package pumBayes updated to version 1.0.1 with previous version 1.0.0 dated 2025-05-30

Title: Bayesian Estimation of Probit Unfolding Models for Binary Preference Data
Description: Bayesian estimation and analysis methods for Probit Unfolding Models (PUMs), a novel class of scaling models designed for binary preference data. These models allow for both monotonic and non-monotonic response functions. The package supports Bayesian inference for both static and dynamic PUMs using Markov chain Monte Carlo (MCMC) algorithms with minimal or no tuning. Key functionalities include posterior sampling, hyperparameter selection, data preprocessing, model fit evaluation, and visualization. The methods are particularly suited to analyzing voting data, such as from the U.S. Congress or Supreme Court, but can also be applied in other contexts where non-monotonic responses are expected. For methodological details, see Shi et al. (2025) <doi:10.48550/arXiv.2504.00423>.
Author: Skylar Shi [aut, cre] , Abel Rodriguez [aut] , Rayleigh Lei [aut] , Jonathan Olmsted [cph]
Maintainer: Skylar Shi <dshi98@uw.edu>

Diff between pumBayes versions 1.0.0 dated 2025-05-30 and 1.0.1 dated 2025-10-22

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Package immunogenetr updated to version 1.0.1 with previous version 1.0.0 dated 2025-08-19

Title: A Comprehensive Toolkit for Clinical HLA Informatics
Description: A comprehensive toolkit for clinical Human Leukocyte Antigen (HLA) informatics, built on 'tidyverse' <https://tidyverse.tidyverse.org/> principles and making use of genotype list string (GL string, Mack et al. (2023) <doi:10.1111/tan.15126>) for storing and computing HLA genotype data. Specific functionalities include: coercion of HLA data in tabular format to and from GL string; calculation of matching and mismatching in all directions, with multiple output formats; automatic formatting of HLA data for searching within a GL string; truncation of molecular HLA data to a specific number of fields; and reading HLA genotypes in HML files and extracting the GL string. This library is intended for research use. Any application making use of this package in a clinical setting will need to be independently validated according to local regulations.
Author: Nicholas Brown [cre, aut] , Busra Coskun [aut]
Maintainer: Nicholas Brown <nicholas.brown@pennmedicine.upenn.edu>

Diff between immunogenetr versions 1.0.0 dated 2025-08-19 and 1.0.1 dated 2025-10-22

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Package UComp updated to version 5.1.4 with previous version 5.1.2 dated 2025-10-21

Title: Automatic Univariate Time Series Modelling of many Kinds
Description: Comprehensive analysis and forecasting of univariate time series using automatic time series models of many kinds. Harvey AC (1989) <doi:10.1017/CBO9781107049994>. Pedregal DJ and Young PC (2002) <doi:10.1002/9780470996430>. Durbin J and Koopman SJ (2012) <doi:10.1093/acprof:oso/9780199641178.001.0001>. Hyndman RJ, Koehler AB, Ord JK, and Snyder RD (2008) <doi:10.1007/978-3-540-71918-2>. Gómez V, Maravall A (2000) <doi:10.1002/9781118032978>. Pedregal DJ, Trapero JR and Holgado E (2024) <doi:10.1016/j.ijforecast.2023.09.004>.
Author: Diego J. Pedregal [aut, cre]
Maintainer: Diego J. Pedregal <Diego.Pedregal@uclm.es>

Diff between UComp versions 5.1.2 dated 2025-10-21 and 5.1.4 dated 2025-10-22

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Package spicy updated to version 0.3.0 with previous version 0.2.1 dated 2025-10-04

Title: Descriptive Statistics and Data Management Tools
Description: Extracts and summarizes metadata from data frames, including variable names, labels, types, and missing values. Computes compact descriptive statistics, frequency tables, and cross-tabulations to assist with efficient data exploration. Includes an interactive and exportable codebook generator for documenting variable metadata. Facilitates the identification of missing data patterns and structural issues in datasets. Designed to streamline initial data management and exploratory analysis workflows within 'R'.
Author: Amal Tawfik [aut, cre, cph]
Maintainer: Amal Tawfik <amal.tawfik@hesav.ch>

Diff between spicy versions 0.2.1 dated 2025-10-04 and 0.3.0 dated 2025-10-22

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Package PSAboot updated to version 1.3.9 with previous version 1.3.8 dated 2023-10-23

Title: Bootstrapping for Propensity Score Analysis
Description: It is often advantageous to test a hypothesis more than once in the context of propensity score analysis (Rosenbaum, 2012) <doi:10.1093/biomet/ass032>. The functions in this package facilitate bootstrapping for propensity score analysis (PSA). By default, bootstrapping using two classification tree methods (using 'rpart' and 'ctree' functions), two matching methods (using 'Matching' and 'MatchIt' packages), and stratification with logistic regression. A framework is described for users to implement additional propensity score methods. Visualizations are emphasized for diagnosing balance; exploring the correlation relationships between bootstrap samples and methods; and to summarize results.
Author: Jason Bryer [aut, cre]
Maintainer: Jason Bryer <jason@bryer.org>

Diff between PSAboot versions 1.3.8 dated 2023-10-23 and 1.3.9 dated 2025-10-22

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Package ohun readmission to version 1.0.4 with previous version 1.0.3 dated 2025-07-22

Title: Optimizing Acoustic Signal Detection
Description: Facilitates the automatic detection of acoustic signals, providing functions to diagnose and optimize the performance of detection routines. Detections from other software can also be explored and optimized. This package has been peer-reviewed by rOpenSci. Araya-Salas et al. (2022) <doi:10.1101/2022.12.13.520253>.
Author: Marcelo Araya-Salas [aut, cre] , Alec L. Robitaille [rev] , Sam Lapp [rev]
Maintainer: Marcelo Araya-Salas <marcelo.araya@ucr.ac.cr>

This is a re-admission after prior archival of version 1.0.3 dated 2025-07-22

Diff between ohun versions 1.0.3 dated 2025-07-22 and 1.0.4 dated 2025-10-22

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Package hmcdm updated to version 2.1.2 with previous version 2.1.1 dated 2023-03-19

Title: Hidden Markov Cognitive Diagnosis Models for Learning
Description: Fitting hidden Markov models of learning under the cognitive diagnosis framework. The estimation of the hidden Markov diagnostic classification model, the first order hidden Markov model, the reduced-reparameterized unified learning model, and the joint learning model for responses and response times.
Author: Susu Zhang [aut], Shiyu Wang [aut], Yinghan Chen [aut], Sunbeom Kwon [aut, cre]
Maintainer: Sunbeom Kwon <sunbeom2@illinois.edu>

Diff between hmcdm versions 2.1.1 dated 2023-03-19 and 2.1.2 dated 2025-10-22

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Package diffval updated to version 1.2.0 with previous version 1.1.0 dated 2023-03-09

Title: Vegetation Patterns
Description: Find, visualize and explore patterns of differential taxa in vegetation data (namely in a phytosociological table), using the Differential Value (DiffVal). Patterns are searched through mathematical optimization algorithms. Ultimately, Total Differential Value (TDV) optimization aims at obtaining classifications of vegetation data based on differential taxa, as in the traditional geobotanical approach (Monteiro-Henriques 2025, <doi:10.3897/VCS.140466>). The Gurobi optimizer, as well as the R package 'gurobi', can be installed from <https://www.gurobi.com/products/gurobi-optimizer/>. The useful vignette Gurobi Installation Guide, from package 'prioritizr', can be found here: <https://prioritizr.net/articles/gurobi_installation_guide.html>.
Author: Tiago Monteiro-Henriques [aut, cre] , Jorge Orestes Cerdeira [aut] , Fundacao para a Ciencia e a Tecnologia, Portugal [fnd]
Maintainer: Tiago Monteiro-Henriques <tmh.dev@icloud.com>

Diff between diffval versions 1.1.0 dated 2023-03-09 and 1.2.0 dated 2025-10-22

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New package tind with initial version 0.2
Package: tind
Title: A Common Representation of Time Indices of Different Types
Version: 0.2
Date: 2025-10-18
Description: Provides an easy-to-use tind class representing time indices of different types (years, quarters, months, ISO 8601 weeks, dates, time of day, date-time, and arbitrary integer/numeric indices). Includes an extensive collection of functions for calendrical computations (including business applications), index conversions, index parsing, and other operations. Auxiliary classes representing time differences and time intervals (with set operations and index matching functionality) are also provided. All routines have been optimised for speed in order to facilitate computations on large datasets. More details regarding calendars in general and calendrical algorithms can be found in "Calendar FAQ" by Claus Tøndering <https://www.tondering.dk/claus/calendar.html>.
Depends: R (>= 3.6.0)
Suggests: crayon, methods, stats, testthat, knitr, rmarkdown, fansi, htmltools
Enhances: utils, graphics, ggplot2, zoo, timeDate, chron, data.table
License: GPL-3
URL: https://github.com/dever-pl/tind
BugReports: https://github.com/dever-pl/tind/issues
Encoding: UTF-8
NeedsCompilation: yes
VignetteBuilder: knitr
Packaged: 2025-10-18 19:06:55 UTC; dever
Author: Grzegorz Klima [aut, cre, cph]
Maintainer: Grzegorz Klima <dever@post.pl>
Repository: CRAN
Date/Publication: 2025-10-22 19:10:02 UTC

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New package OmopOnSpark with initial version 0.1.0
Package: OmopOnSpark
Title: Using a Common Data Model on 'Spark'
Version: 0.1.0
Description: Use health data in the Observational Medical Outcomes Partnership Common Data Model format in 'Spark'. Functionality includes creating all required tables and fields and creation of a single reference to the data. Native 'Spark' functionality is supported.
License: Apache License (>= 2)
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: cli, datasets, DBI, dbplyr, dplyr, glue, omopgenerics (>= 1.3.1), purrr, rlang, stringr
Suggests: testthat (>= 3.0.0), omock, knitr, rmarkdown, CDMConnector, OmopSketch, odbc, R6, crayon, sparklyr, DatabaseConnector
VignetteBuilder: knitr
URL: https://OHDSI.github.io/OmopOnSpark/
NeedsCompilation: no
Packaged: 2025-10-19 18:42:36 UTC; orms0426
Author: Edward Burn [aut, cre] , Marti Catala [aut]
Maintainer: Edward Burn <edward.burn@ndorms.ox.ac.uk>
Repository: CRAN
Date/Publication: 2025-10-22 19:20:02 UTC

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Package ClimaRep updated to version 1.0 with previous version 0.7 dated 2025-08-24

Title: Estimating Climate Representativeness
Description: Offers tools to estimate the climate representativeness of reference polygons and quantifies its transformation under future climate change scenarios. Approaches described in Mingarro and Lobo (2018) <doi:10.32800/abc.2018.41.0333> and Mingarro and Lobo (2022) <doi:10.1017/S037689292100014X>.
Author: Mario Mingarro [aut, cre] , Gabriel del Barrio [ctb] , Jorge M. Lobo [ctb]
Maintainer: Mario Mingarro <mario_mingarro@mncn.csic.es>

Diff between ClimaRep versions 0.7 dated 2025-08-24 and 1.0 dated 2025-10-22

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New package ci with initial version 0.0.1
Package: ci
Title: Confidence Intervals for Education
Version: 0.0.1
Description: An educational package providing intuitive functions for calculating confidence intervals (CI) for various statistical parameters. Designed primarily for teaching and learning about statistical inference (particularly confidence intervals). Offers user-friendly wrappers around established methods for proportions, means, and bootstrap-based intervals. Integrates seamlessly with Tidyverse workflows, making it ideal for classroom demonstrations and student exercises.
License: GPL (>= 3)
URL: https://github.com/GegznaV/ci
BugReports: https://github.com/GegznaV/ci/issues
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: DescTools, dplyr, tidyr, purrr, forcats, tibble, checkmate
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2025-10-19 20:21:15 UTC; ViG
Author: Vilmantas Gegzna [aut, cre]
Maintainer: Vilmantas Gegzna <GegznaV@gmail.com>
Repository: CRAN
Date/Publication: 2025-10-22 19:30:02 UTC

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New package bayesQRsurvey with initial version 0.1.4
Package: bayesQRsurvey
Title: Bayesian Quantile Regression Models for Complex Survey Data Analysis
Version: 0.1.4
Description: Provides Bayesian quantile regression models for complex survey data under informative sampling using survey-weighted estimators. Both single- and multiple-output models are supported. To accelerate computation, all algorithms are implemented in 'C++' using 'Rcpp', 'RcppArmadillo', and 'RcppEigen', and are called from 'R'. See Nascimento and Gonçalves (2024) <doi:10.1093/jssam/smae015> and Nascimento and Gonçalves (2025, in press) <https://academic.oup.com/jssam>.
License: MIT + file LICENSE
Encoding: UTF-8
LinkingTo: Rcpp, RcppArmadillo, RcppEigen
Imports: Rcpp, stats, graphics, methods, pracma, ggplot2, rlang, posterior
Suggests: MASS, knitr, rmarkdown, grDevices, testthat (>= 3.0.0)
SystemRequirements: BLAS, LAPACK
URL: https://github.com/torodriguezt/bayesQRsurvey
BugReports: https://github.com/torodriguezt/bayesQRsurvey/issues
NeedsCompilation: yes
Packaged: 2025-10-18 21:02:55 UTC; Tomas
Author: Tomas Rodriguez Taborda [aut, cre], Johnatan Cardona Jimenez [aut], Marcus L. Nascimento [aut], Kelly Cristina Mota Goncalves [aut]
Maintainer: Tomas Rodriguez Taborda <torodriguezt@unal.edu.co>
Depends: R (>= 3.5.0)
Repository: CRAN
Date/Publication: 2025-10-22 19:10:10 UTC

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New package scf with initial version 1.0.4
Package: scf
Title: Analyzing the Survey of Consumer Finances
Version: 1.0.4
Description: Analyze public-use micro data from the Survey of Consumer Finances. Provides tools to download prepared data files, construct replicate-weighted multiply imputed survey designs, compute descriptive statistics and model estimates, and produce plots and tables. Methods follow design-based inference for complex surveys and pooling across multiple imputations. See the package website and the code book for background.
License: MIT + file LICENSE
URL: https://github.com/jncohen/scf
BugReports: https://github.com/jncohen/scf/issues
Depends: R (>= 3.6)
Imports: ggplot2, haven, httr, rlang, stats, survey, utils
Suggests: dplyr, hexbin, kableExtra, knitr, mitools, rmarkdown, markdown, testthat (>= 3.0.0)
VignetteBuilder: knitr, markdown, rmarkdown
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2025-10-18 11:04:17 UTC; jcohen
Author: Joseph Cohen [aut, cre]
Maintainer: Joseph Cohen <joseph.cohen@qc.cuny.edu>
Repository: CRAN
Date/Publication: 2025-10-22 19:00:02 UTC

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Package pmartR updated to version 2.5.1 with previous version 2.5.0 dated 2025-04-23

Title: Panomics Marketplace - Quality Control and Statistical Analysis for Panomics Data
Description: Provides functionality for quality control processing and statistical analysis of mass spectrometry (MS) omics data, in particular proteomic (either at the peptide or the protein level), lipidomic, and metabolomic data, as well as RNA-seq based count data and nuclear magnetic resonance (NMR) data. This includes data transformation, specification of groups that are to be compared against each other, filtering of features and/or samples, data normalization, data summarization (correlation, PCA), and statistical comparisons between defined groups. Implements methods described in: Webb-Robertson et al. (2014) <doi:10.1074/mcp.M113.030932>. Webb-Robertson et al. (2011) <doi:10.1002/pmic.201100078>. Matzke et al. (2011) <doi:10.1093/bioinformatics/btr479>. Matzke et al. (2013) <doi:10.1002/pmic.201200269>. Polpitiya et al. (2008) <doi:10.1093/bioinformatics/btn217>. Webb-Robertson et al. (2010) <doi:10.1021/pr1005247>.
Author: Lisa Bramer [aut, cre], Kelly Stratton [aut], Daniel Claborne [aut], Evan Glasscock [ctb], Rachel Richardson [ctb], David Degnan [ctb], Evan Martin [ctb]
Maintainer: Lisa Bramer <lisa.bramer@pnnl.gov>

Diff between pmartR versions 2.5.0 dated 2025-04-23 and 2.5.1 dated 2025-10-22

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New package NeEDS4BigData with initial version 1.0.1
Package: NeEDS4BigData
Title: New Experimental Design Based Subsampling Methods for Big Data
Version: 1.0.1
Maintainer: Amalan Mahendran <amalan0595@gmail.com>
Description: Subsampling methods for big data under different models and assumptions. Starting with linear regression and leading to Generalised Linear Models, softmax regression, and quantile regression. Specifically, the model-robust subsampling method proposed in Mahendran, A., Thompson, H., and McGree, J. M. (2023) <doi:10.1007/s00362-023-01446-9>, where multiple models can describe the big data, and the subsampling framework for potentially misspecified Generalised Linear Models in Mahendran, A., Thompson, H., and McGree, J. M. (2025) <doi:10.48550/arXiv.2510.05902>.
License: MIT + file LICENSE
URL: https://github.com/Amalan-ConStat/NeEDS4BigData,https://amalan-constat.github.io/NeEDS4BigData/index.html
BugReports: https://github.com/Amalan-ConStat/NeEDS4BigData/issues
Depends: R (>= 4.1.0)
Imports: dplyr, foreach, gam, ggh4x, ggplot2, ggridges, matrixStats, mvnfast, psych, Rdpack, Rfast, rlang, stats, tidyr
Suggests: doParallel, ggpubr, kableExtra, knitr, parallel, rmarkdown, spelling, testthat, vctrs, pillar
Encoding: UTF-8
Language: en-GB
LazyData: true
LazyDataCompression: xz
NeedsCompilation: no
Packaged: 2025-10-18 14:12:20 UTC; amala
Author: Amalan Mahendran [aut, cre]
Repository: CRAN
Date/Publication: 2025-10-22 19:00:08 UTC

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New package mcmodule with initial version 1.1.0
Package: mcmodule
Title: Modular Monte Carlo Risk Analysis
Version: 1.1.0
Description: Framework for building modular Monte Carlo risk analysis models. It extends the capabilities of 'mc2d' to facilitate working with multiple risk pathways, variates and scenarios. It provides tools to organize risk analysis in independent flexible modules, perform multivariate Monte Carlo node operations, automate the creation of Monte Carlo nodes and visualize risk analysis models. For more details see Ciria (2025) <https://nataliaciria.github.io/mcmodule/articles/mcmodule>.
License: GPL (>= 3)
Encoding: UTF-8
URL: https://nataliaciria.github.io/mcmodule/, https://github.com/NataliaCiria/mcmodule
BugReports: https://github.com/NataliaCiria/mcmodule/issues
Suggests: knitr, rmarkdown, testthat (>= 3.0.0), visNetwork, igraph, bookdown
Imports: dplyr
Depends: mc2d, R (>= 3.5)
LazyData: true
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2025-10-18 05:57:44 UTC; Natalia
Author: Natalia Ciria [aut, cre, cph] , Alberto Allepuz [ths] , Giovanna Ciaravino [ths]
Maintainer: Natalia Ciria <nataliaciria@hotmail.com>
Repository: CRAN
Date/Publication: 2025-10-22 18:50:02 UTC

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New package CFM with initial version 0.6.0
Package: CFM
Title: Analyzing Censored Factor Models
Version: 0.6.0
Description: Provides generation and estimation of censored factor models for high-dimensional data with censored errors (normal, t, logistic). Includes Sparse Orthogonal Principal Components (SOPC), and evaluation metrics. Based on Guo G. (2023) <doi:10.1007/s00180-022-01270-z>.
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-US
Depends: R (>= 3.5.0)
Imports: stats, MASS, psych, matrixcalc, crch
Suggests: testthat (>= 3.0.0), ggplot2
NeedsCompilation: no
Packaged: 2025-10-18 01:51:44 UTC; 86188
Author: Guangbao Guo [aut, cre], Tong Meng [aut]
Maintainer: Guangbao Guo <ggb11111111@163.com>
Repository: CRAN
Date/Publication: 2025-10-22 18:50:10 UTC

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New package BRPL with initial version 1.0.2
Package: BRPL
Title: Methods for Bivariate Poverty Line Calculations
Version: 1.0.2
Description: Provides tools for identifying subgroups within populations based on individual response patterns to specific interventions or treatments. Designed to support researchers and clinicians in exploring heterogeneous treatment effects and developing personalized therapeutic strategies. Offers functionality for analyzing and visualizing the interplay between two variables, thereby enhancing the interpretation of social sustainability metrics. The package focuses on bivariate discriminant analysis and aims to clarify relationships between indicator variables.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: graphics, methods
Depends: R (>= 3.5.0)
Suggests: testthat (>= 3.0.0)
LazyData: true
NeedsCompilation: no
Packaged: 2025-10-03 20:53:34 UTC; rmk
Author: Franziska Dorn [aut, cre], Rene-Marcel Kruse [aut], Thomas Kneib [aut]
Maintainer: Franziska Dorn <franziska.dorn@uni-due.de>
Repository: CRAN
Date/Publication: 2025-10-22 18:40:08 UTC

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New package alpmixBayes with initial version 0.1.0
Package: alpmixBayes
Title: Bayesian Estimation for Alpha-Mixture Survival Models
Version: 0.1.0
Description: Implements Bayesian estimation and inference for alpha-mixture survival models, including Weibull and Exponential based components, with tools for simulation and posterior summaries. The methods target applications in reliability and biomedical survival analysis. The package implements Bayesian estimation for the alpha-mixture methodology introduced in Asadi et al. (2019) <doi:10.1017/jpr.2019.72>.
Maintainer: Feng Luan <fluan1@niu.edu>
Imports: MCMCpack, stats, utils, gtools
License: GPL-3
Encoding: UTF-8
LazyData: true
LazyDataCompression: xz
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2025-10-17 19:22:24 UTC; feng
Author: Feng Luan [aut, cre], Zhexuan Yang [aut], Duchwan Ryu [aut]
Depends: R (>= 3.5.0)
Repository: CRAN
Date/Publication: 2025-10-22 18:40:02 UTC

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Package magi updated to version 1.2.5 with previous version 1.2.4 dated 2024-06-22

Title: MAnifold-Constrained Gaussian Process Inference
Description: Provides fast and accurate inference for the parameter estimation problem in Ordinary Differential Equations, including the case when there are unobserved system components. Implements the MAGI method (MAnifold-constrained Gaussian process Inference) of Yang, Wong, and Kou (2021) <doi:10.1073/pnas.2020397118>. A user guide is provided by the accompanying software paper Wong, Yang, and Kou (2024) <doi:10.18637/jss.v109.i04>.
Author: Shihao Yang [aut, cre] , Samuel W.K. Wong [aut] , S.C. Kou [ctb, cph]
Maintainer: Shihao Yang <shihao.yang@isye.gatech.edu>

Diff between magi versions 1.2.4 dated 2024-06-22 and 1.2.5 dated 2025-10-22

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Package animint2 updated to version 2025.10.17 with previous version 2025.9.16 dated 2025-09-22

Title: Animated Interactive Grammar of Graphics
Description: Functions are provided for defining animated, interactive data visualizations in R code, and rendering on a web page. The 2018 Journal of Computational and Graphical Statistics paper, <doi:10.1080/10618600.2018.1513367> describes the concepts implemented.
Author: Toby Hocking [aut, cre] , Biplab Sutradhar [ctb] , Hadley Wickham [aut] , Winston Chang [aut] , RStudio [cph] , Nicholas Lewin-Koh [aut] , Martin Maechler [aut] , Randall Prium [aut] , Susan VanderPlas [aut] , Carson Sievert [aut] , Kevin Ferris [aut [...truncated...]
Maintainer: Toby Hocking <toby.hocking@r-project.org>

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Package phoenix updated to version 1.1.3 with previous version 1.1.2 dated 2025-05-02

Title: The Phoenix Pediatric Sepsis and Septic Shock Criteria
Description: Implementation of the Phoenix and Phoenix-8 Sepsis Criteria as described in "Development and Validation of the Phoenix Criteria for Pediatric Sepsis and Septic Shock" by Sanchez-Pinto, Bennett, DeWitt, Russell et al. (2024) <doi:10.1001/jama.2024.0196> (Drs. Sanchez-Pinto and Bennett contributed equally to this manuscript; Dr. DeWitt and Mr. Russell contributed equally to the manuscript), "International Consensus Criteria for Pediatric Sepsis and Septic Shock" by Schlapbach, Watson, Sorce, Argent, et al. (2024) <doi:10.1001/jama.2024.0179> (Drs Schlapbach, Watson, Sorce, and Argent contributed equally) and the application note "phoenix: an R package and Python module for calculating the Phoenix pediatric sepsis score and criteria" by DeWitt, Russell, Rebull, Sanchez-Pinto, and Bennett (2024) <doi:10.1093/jamiaopen/ooae066>.
Author: Peter DeWitt [aut, cre] , Seth Russell [ctb] , Meg Rebull [ctb] , Tell Bennett [ctb] , L. Nelson Sanchez-Pinto [ctb]
Maintainer: Peter DeWitt <peter.dewitt@cuanschutz.edu>

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Package labelled updated to version 2.16.0 with previous version 2.15.0 dated 2025-09-16

Title: Manipulating Labelled Data
Description: Work with labelled data imported from 'SPSS' or 'Stata' with 'haven' or 'foreign'. This package provides useful functions to deal with "haven_labelled" and "haven_labelled_spss" classes introduced by 'haven' package.
Author: Joseph Larmarange [aut, cre] , Daniel Ludecke [ctb], Hadley Wickham [ctb], Michal Bojanowski [ctb], Francois Briatte [ctb]
Maintainer: Joseph Larmarange <joseph@larmarange.net>

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Package arcpbf updated to version 0.2.0 with previous version 0.1.7 dated 2025-04-10

Title: Process ArcGIS Protocol Buffer FeatureCollections
Description: Fast processing of ArcGIS FeatureCollection protocol buffers in R. It is designed to work seamlessly with 'httr2' and integrates with 'sf'.
Author: Josiah Parry [aut, cre]
Maintainer: Josiah Parry <josiah.parry@gmail.com>

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Package SimpleUpset updated to version 0.1.3 with previous version 0.1.2 dated 2025-10-06

Title: Create Upset Plots
Description: Create Upset plots using a combination of 'ggplot2' and 'patchwork'.
Author: Stevie Pederson [aut, cre]
Maintainer: Stevie Pederson <stephen.pederson.au@gmail.com>

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Package pracma updated to version 2.4.6 with previous version 2.4.4 dated 2023-11-09

Title: Practical Numerical Math Functions
Description: Provides a large number of functions from numerical analysis and linear algebra, numerical optimization, differential equations, time series, plus some well-known special mathematical functions. Uses 'MATLAB' function names where appropriate to simplify porting.
Author: Hans W. Borchers [aut, cre]
Maintainer: Hans W. Borchers <hwborchers@googlemail.com>

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Package tikatuwq updated to version 0.7.2 with previous version 0.6.2 dated 2025-10-07

Title: Water Quality Assessment and Environmental Compliance in Brazil
Description: Tools to import, clean, validate, and analyze freshwater quality data in Brazil. Implements water quality indices including the Water Quality Index (WQI/IQA), the Trophic State Index (TSI/IET) after Carlson (1977) <doi:10.4319/lo.1977.22.2.0361> and Lamparelli (2004) <https://www.teses.usp.br/teses/disponiveis/41/41134/tde-20032006-075813/publico/TeseLamparelli2004.pdf>, and the National Sanitation Foundation Water Quality Index (NSF WQI) <doi:10.1007/s11157-023-09650-7>. The package also checks compliance with Brazilian standard CONAMA Resolution 357/2005 <https://conama.mma.gov.br/?id=450&option=com_sisconama&task=arquivo.download> and generates reproducible reports for routine monitoring workflows.
Author: Vinicius Saraiva Santos [aut, cre]
Maintainer: Vinicius Saraiva Santos <vinisaraiva@gmail.com>

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Package resourcecode updated to version 0.4.0 with previous version 0.3.0 dated 2025-08-21

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 nlmixr2lib updated to version 0.3.1 with previous version 0.3.0 dated 2024-10-07

Title: A Model Library for 'nlmixr2'
Description: A model library for 'nlmixr2'. The models include (and plan to include) pharmacokinetic, pharmacodynamic, and disease models used in pharmacometrics. Where applicable, references for each model are included in the meta-data for each individual model. The package also includes model composition and modification functions to make model updates easier.
Author: Richard Hooijmaijers [aut], Matthew Fidler [aut] , Bill Denney [aut, cre]
Maintainer: Bill Denney <wdenney@humanpredictions.com>

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Package medfateland updated to version 2.8.1 with previous version 2.7.0 dated 2025-08-28

Title: Mediterranean Landscape Simulation
Description: Simulate forest hydrology, forest function and dynamics over landscapes [De Caceres et al. (2015) <doi:10.1016/j.agrformet.2015.06.012>]. Parallelization is allowed in several simulation functions and simulations may be conducted including spatial processes such as lateral water transfer and seed dispersal.
Author: Miquel De Caceres [aut, cre], Aitor Ameztegui [aut] , Maria Gonzalez [aut] , Nuria Aquilue [aut], Daniel Caviedes-Voullieme [aut], Mario Morales-Hernandez [aut], Mario Beltran [ctb], Rodrigo Balaguer-Romano [ctb] , Roberto Molowny-Horas [ctb]
Maintainer: Miquel De Caceres <miquelcaceres@gmail.com>

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Package HVT updated to version 25.2.7 with previous version 25.2.6 dated 2025-10-14

Title: Constructing Hierarchical Voronoi Tessellations and Overlay Heatmaps for Data Analysis
Description: Facilitates building topology preserving maps for data analysis.
Author: Zubin Dowlaty [aut, cre], Mu Sigma, Inc. [cph]
Maintainer: Zubin Dowlaty <zubin.dowlaty@mu-sigma.com>

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Package googleLanguageR updated to version 0.3.1.1 with previous version 0.3.1 dated 2025-08-24

Title: Call Google's 'Natural Language', 'Cloud Translation', 'Cloud Speech', and 'Cloud Text-to-Speech' APIs
Description: Access Google Cloud machine learning APIs for text and speech tasks. Use the Cloud Translation API for text detection and translation, the Natural Language API to analyze sentiment, entities, and syntax, the Cloud Speech API to transcribe audio to text, and the Cloud Text-to-Speech API to synthesize text into audio files.
Author: Aleksander Dietrichson [ctb], Mark Edmondson [aut], John Muschelli [ctb], Neal Richardson [rev] , Julia Gustavsen [rev] , Cheryl Isabella Lim [aut, cre]
Maintainer: Cheryl Isabella Lim <cheryl.academic@gmail.com>

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Permanent link

Package BAwiR updated to version 1.4 with previous version 1.3.4 dated 2025-02-14

Title: Analysis of Basketball Data
Description: Collection of tools to work with European basketball data. Functions available are related to friendly web scraping, data management and visualization. Data were obtained from <https://www.euroleaguebasketball.net/euroleague/>, <https://www.euroleaguebasketball.net/eurocup/> and <https://www.acb.com/>, following the instructions of their respectives robots.txt files, when available. Box score data are available for the three leagues. Play-by-play and spatial shooting data are also available for the Spanish league. Methods for analysis include a population pyramid, 2D plots, circular plots of players' percentiles, plots of players' monthly/yearly stats, team heatmaps, team shooting plots, team four factors plots, cross-tables with the results of regular season games, maps of nationalities, combinations of lineups, possessions-related variables, timeouts, performance by periods, personal fouls, offensive rebounds and different types of shooting charts. Please see Vinue [...truncated...]
Author: Guillermo Vinue [aut, cre]
Maintainer: Guillermo Vinue <guillermo.vinue@uv.es>

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Permanent link

Package teal.modules.general updated to version 0.5.1 with previous version 0.5.0 dated 2025-08-20

Title: General Modules for 'teal' Applications
Description: Prebuilt 'shiny' modules containing tools for viewing data, visualizing data, understanding missing and outlier values within your data and performing simple data analysis. This extends 'teal' framework that supports reproducible research and analysis.
Author: Dawid Kaledkowski [aut, cre], Pawel Rucki [aut], Mahmoud Hallal [aut], Ondrej Slama [ctb], Maciej Nasinski [aut], Konrad Pagacz [aut], Nikolas Burkoff [aut], F. Hoffmann-La Roche AG [cph, fnd]
Maintainer: Dawid Kaledkowski <dawid.kaledkowski@roche.com>

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Package mev updated to version 2.0 with previous version 1.17 dated 2024-07-09

Title: Modelling of Extreme Values
Description: Various tools for the analysis of univariate, multivariate and functional extremes. Exact simulation from max-stable processes (Dombry, Engelke and Oesting, 2016, <doi:10.1093/biomet/asw008>, R-Pareto processes for various parametric models, including Brown-Resnick (Wadsworth and Tawn, 2014, <doi:10.1093/biomet/ast042>) and Extremal Student (Thibaud and Opitz, 2015, <doi:10.1093/biomet/asv045>). Threshold selection methods, including Wadsworth (2016) <doi:10.1080/00401706.2014.998345>, and Northrop and Coleman (2014) <doi:10.1007/s10687-014-0183-z>. Multivariate extreme diagnostics. Estimation and likelihoods for univariate extremes, e.g., Coles (2001) <doi:10.1007/978-1-4471-3675-0>.
Author: Leo Belzile [aut, cre] , Jennifer L. Wadsworth [aut], Paul J. Northrop [aut] , Raphael Huser [aut] , Scott D. Grimshaw [aut] , Jin Zhang [ctb], Michael A. Stephens [ctb], Art B. Owen [ctb]
Maintainer: Leo Belzile <belzilel@gmail.com>

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Package biodosetools updated to version 3.7.1 with previous version 3.7 dated 2025-10-14

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 dated 2025-10-14 and 3.7.1 dated 2025-10-22

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Package warbleR readmission to version 1.1.37 with previous version 1.1.36 dated 2025-07-28

Title: Streamline Bioacoustic Analysis
Description: Functions aiming to facilitate the analysis of the structure of animal acoustic signals in 'R'. 'warbleR' makes use of the basic sound analysis tools from the packages 'tuneR' and 'seewave', and offers new tools for exploring and quantifying acoustic signal structure. The package allows to organize and manipulate multiple sound files, create spectrograms of complete recordings or individual signals in different formats, run several measures of acoustic structure, and characterize different structural levels in acoustic signals (Araya-Salas et al 2016 <doi:10.1111/2041-210X.12624>).
Author: Marcelo Araya-Salas [aut, cre] , Grace Smith-Vidaurre [aut]
Maintainer: Marcelo Araya-Salas <marcelo.araya@ucr.ac.cr>

This is a re-admission after prior archival of version 1.1.36 dated 2025-07-28

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Package unitizer updated to version 1.4.23 with previous version 1.4.22 dated 2025-03-18

Title: Interactive R Unit Tests
Description: Simplifies regression tests by comparing objects produced by test code with earlier versions of those same objects. If objects are unchanged the tests pass, otherwise execution stops with error details. If in interactive mode, tests can be reviewed through the provided interactive environment.
Author: Brodie Gaslam [aut, cre], Michael https://github.com/MichaelChirico [ctb], R Core Team [cph]
Maintainer: Brodie Gaslam <brodie.gaslam@yahoo.com>

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Package rfars readmission to version 2.0.2 with previous version 2.0.1 dated 2025-10-02

Title: Download and Analyze Crash Data
Description: Easily Download Analysis-Ready Crash Data from the U.S. National Highway Traffic Safety Administration.
Author: Steve Jackson [aut, cre]
Maintainer: Steve Jackson <steve.jackson@toxcel.com>

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Package promises updated to version 1.4.0 with previous version 1.3.3 dated 2025-05-29

Title: Abstractions for Promise-Based Asynchronous Programming
Description: Provides fundamental abstractions for doing asynchronous programming in R using promises. Asynchronous programming is useful for allowing a single R process to orchestrate multiple tasks in the background while also attending to something else. Semantics are similar to 'JavaScript' promises, but with a syntax that is idiomatic R.
Author: Joe Cheng [aut], Barret Schloerke [aut, cre] , Winston Chang [aut] , Charlie Gao [aut] , Posit Software, PBC [cph, fnd]
Maintainer: Barret Schloerke <barret@posit.co>

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Package depower updated to version 2025.10.21 with previous version 2025.1.20 dated 2025-01-23

Title: Power Analysis for Differential Expression Studies
Description: Provides a convenient framework to simulate, test, power, and visualize data for differential expression studies with lognormal or negative binomial outcomes. Supported designs are two-sample comparisons of independent or dependent outcomes. Power may be summarized in the context of controlling the per-family error rate or family-wise error rate. Negative binomial methods are described in Yu, Fernandez, and Brock (2017) <doi:10.1186/s12859-017-1648-2> and Yu, Fernandez, and Brock (2020) <doi:10.1186/s12859-020-3541-7>.
Author: Brett Klamer [aut, cre] , Lianbo Yu [aut]
Maintainer: Brett Klamer <code@brettklamer.com>

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 88 files changed, 3908 insertions(+), 1554 deletions(-)

More information about depower at CRAN
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Package cmsafops updated to version 1.4.2 with previous version 1.4.1 dated 2025-04-08

Title: Tools for CM SAF NetCDF Data
Description: The Satellite Application Facility on Climate Monitoring (CM SAF) is a ground segment of the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) and one of EUMETSATs Satellite Application Facilities. The CM SAF contributes to the sustainable monitoring of the climate system by providing essential climate variables related to the energy and water cycle of the atmosphere (<https://www.cmsaf.eu>). It is a joint cooperation of eight National Meteorological and Hydrological Services. The 'cmsafops' R-package provides a collection of R-operators for the analysis and manipulation of CM SAF NetCDF formatted data. Other CF conform NetCDF data with time, longitude and latitude dimension should be applicable, but there is no guarantee for an error-free application. CM SAF climate data records are provided for free via (<https://wui.cmsaf.eu/safira>). Detailed information and test data are provided on the CM SAF webpage (<http://www.cmsaf.eu/R_toolbox& [...truncated...]
Author: Steffen Kothe [aut, cre], Danny Parsons [ctb]
Maintainer: Steffen Kothe <Steffen.Kothe@dwd.de>

Diff between cmsafops versions 1.4.1 dated 2025-04-08 and 1.4.2 dated 2025-10-22

 DESCRIPTION                              |    8 
 MD5                                      | 1011 +++++-----
 NAMESPACE                                |  336 +--
 NEWS.md                                  |  730 +++----
 R/acsaf_box_mergetime.R                  |  856 ++++----
 R/add_grid_info.R                        |  210 +-
 R/arith_wrapper.R                        |  446 ++--
 R/arithc_wrapper.R                       |  248 +-
 R/box_mergetime.R                        |  796 ++++----
 R/calc_allDatesNc.R                      |   76 
 R/calc_field.R                           |   74 
 R/calc_overlapping_time.R                |  328 +--
 R/calc_regres_coef_a.R                   |   30 
 R/calc_regres_coef_b.R                   |   30 
 R/calc_timestepNc.R                      |  250 +-
 R/calc_timx_result.R                     |  122 -
 R/calc_trend.R                           |  136 -
 R/calc_trend_advanced.R                  |  254 +-
 R/change_att.R                           |  226 +-
 R/check.coordinate.system.R              |   80 
 R/check_constant.R                       |   10 
 R/check_dims.R                           |   58 
 R/check_format.R                         |   20 
 R/check_infile.R                         |   18 
 R/check_infiles.R                        |   24 
 R/check_nc_version.R                     |   26 
 R/check_outfile.R                        |   18 
 R/check_overwrite.R                      |   14 
 R/check_variable.R                       |   10 
 R/cmsaf.abs.R                            |  302 +--
 R/cmsaf.add.R                            |  168 -
 R/cmsaf.addc.R                           |  134 -
 R/cmsaf.adjust.two.files.R               |  514 ++---
 R/cmsaf.cat.R                            |  482 ++---
 R/cmsaf.detrend.R                        |  378 +--
 R/cmsaf.div.R                            |  168 -
 R/cmsaf.divc.R                           |  134 -
 R/cmsaf.mk.test.R                        |  406 ++--
 R/cmsaf.mul.R                            |  168 -
 R/cmsaf.mulc.R                           |  136 -
 R/cmsaf.regres.R                         |  352 +--
 R/cmsaf.stats.R                          |  244 +-
 R/cmsaf.stats.station.data.R             |  428 ++--
 R/cmsaf.sub.R                            |  166 -
 R/cmsaf.sub.rel.R                        |  294 +--
 R/cmsaf.subc.R                           |  136 -
 R/cmsaf.transform.coordinate.system.R    |  220 +-
 R/cmsafops.R                             |  198 +-
 R/constants.R                            |  280 +-
 R/correct_filename.R                     |   20 
 R/dayavg.R                               |  132 -
 R/daymax.R                               |  124 -
 R/daymean.R                              |  132 -
 R/daymin.R                               |  124 -
 R/daypctl.R                              |  130 -
 R/dayrange.R                             |  364 +--
 R/daysd.R                                |  124 -
 R/daysum.R                               |  122 -
 R/dayvar.R                               |  124 -
 R/dayx_wrapper.R                         |  302 +--
 R/define_dims.R                          |   86 
 R/define_vars.R                          |   46 
 R/define_vars_mk.test.R                  |   62 
 R/define_vars_trend.R                    |   84 
 R/define_vars_trend_advanced.R           |  102 -
 R/divdpm.R                               |  132 -
 R/extract.level.R                        |  402 ++--
 R/extract.period.R                       |  526 ++---
 R/fld_cor_covar_wrapper.R                |  286 +-
 R/fldcor.R                               |  152 -
 R/fldcovar.R                             |  152 -
 R/fldmax.R                               |  126 -
 R/fldmean.R                              |  126 -
 R/fldmin.R                               |  126 -
 R/fldrange.R                             |  128 -
 R/fldsd.R                                |  126 -
 R/fldsum.R                               |  126 -
 R/fldx_wrapper.R                         |  210 +-
 R/getDateID.R                            |   28 
 R/getTimeRange.R                         |   78 
 R/get_basename.R                         |   68 
 R/get_climatology.R                      |   58 
 R/get_cor_data.R                         |   62 
 R/get_cor_data_fld.R                     |   32 
 R/get_date_time.R                        |   68 
 R/get_dimensions.R                       |  110 -
 R/get_nc_version.R                       |   34 
 R/get_processing_time_string.R           |   40 
 R/get_time.R                             |  198 +-
 R/get_time_bnds_1.R                      |   14 
 R/get_time_bnds_from_file.R              |   16 
 R/get_time_bnds_mul.R                    |   28 
 R/get_time_bounds.R                      |   26 
 R/get_time_bounds_doy.R                  |   26 
 R/get_time_bounds_hour.R                 |   26 
 R/get_time_bounds_month.R                |   26 
 R/get_time_bounds_run.R                  |   18 
 R/get_time_bounds_timrange.R             |   54 
 R/get_time_bounds_year.R                 |   26 
 R/get_time_info.R                        |   42 
 R/get_var_atts.R                         |   36 
 R/get_var_from_vars.R                    |   26 
 R/get_var_from_vars_all.R                |   26 
 R/get_var_prec.R                         |   16 
 R/gridboxmax.R                           |  130 -
 R/gridboxmean.R                          |  130 -
 R/gridboxmin.R                           |  130 -
 R/gridboxrange.R                         |  130 -
 R/gridboxsd.R                            |  130 -
 R/gridboxsum.R                           |  130 -
 R/gridboxvar.R                           |  130 -
 R/gridboxx_wrapper.R                     |  558 ++---
 R/hourmean.R                             |  128 -
 R/hoursum.R                              |  128 -
 R/hourx_wrapper.R                        |  236 +-
 R/is_leap_year.R                         |    6 
 R/is_url.R                               |    4 
 R/keep_sig_alongside.R                   |only
 R/levbox_mergetime.R                     |  186 -
 R/map_regular.R                          |  598 +++---
 R/mermean.R                              |  126 -
 R/merx_wrapper.R                         |  218 +-
 R/mon.anomaly.R                          |  420 ++--
 R/mon.anomaly.climatology.R              |  357 +--
 R/mon_num_above.R                        |  130 -
 R/mon_num_below.R                        |  130 -
 R/mon_num_equal.R                        |  130 -
 R/mon_num_wrapper.R                      |  276 +-
 R/monavg.R                               |  136 -
 R/mondaymean.R                           |  400 ++--
 R/monmax.R                               |  124 -
 R/monmean.R                              |  136 -
 R/monmin.R                               |  124 -
 R/monpctl.R                              |  134 -
 R/monsd.R                                |  126 -
 R/monsum.R                               |  124 -
 R/monvar.R                               |  126 -
 R/monx_wrapper.R                         |  342 +--
 R/muldpm.R                               |  130 -
 R/multimonmean.R                         |  342 +--
 R/multimonsum.R                          |  364 +--
 R/multiplelm.R                           |   34 
 R/ncinfo.R                               |  242 +-
 R/num_above.R                            |  134 -
 R/num_below.R                            |  134 -
 R/num_equal.R                            |  134 -
 R/num_wrapper.R                          |  182 -
 R/read_file.R                            |  163 -
 R/read_file_all.R                        |  144 -
 R/read_gridfile.R                        |   54 
 R/read_ncvar.R                           |  174 -
 R/redefine_grid_vars.R                   |   72 
 R/release_questions.R                    |   36 
 R/remap.R                                |  660 +++---
 R/runmax.R                               |  132 -
 R/runmean.R                              |  126 -
 R/runmin.R                               |  130 -
 R/runrange.R                             |  126 -
 R/runsd.R                                |  132 -
 R/runsum.R                               |  132 -
 R/runx_wrapper.R                         |  310 +--
 R/seas.anomaly.R                         |  464 ++--
 R/seasmean.R                             |  128 -
 R/seassd.R                               |  128 -
 R/seassum.R                              |  128 -
 R/seasvar.R                              |  130 -
 R/seasx_wrapper.R                        |  322 +--
 R/sellonlatbox.R                         |  446 ++--
 R/selmon.R                               |  310 +--
 R/selperiod.R                            |  356 +--
 R/selpoint.R                             |  506 ++---
 R/selpoint.multi.R                       |  800 ++++----
 R/seltime.R                              |  310 +--
 R/selyear.R                              |  314 +--
 R/set_seasons.R                          |   54 
 R/simplelm.R                             |   46 
 R/simplelm2.R                            |   50 
 R/tim_cor_covar_wrapper.R                |  356 +--
 R/timavg.R                               |  138 -
 R/timcor.R                               |  152 -
 R/timcovar.R                             |  152 -
 R/timcumsum.R                            |  598 +++---
 R/timmax.R                               |  124 -
 R/timmean.R                              |  126 -
 R/timmin.R                               |  124 -
 R/timpctl.R                              |  134 -
 R/timsd.R                                |  126 -
 R/timselmean.R                           |  124 -
 R/timselsum.R                            |  130 -
 R/timselx_wrapper.R                      |  238 +-
 R/timsum.R                               |  126 -
 R/timx_wrapper.R                         |  164 -
 R/trend.R                                |  296 +--
 R/trend_advanced.R                       |  332 +--
 R/wfldmean.R                             |  130 -
 R/write_output_file.R                    |  222 +-
 R/write_output_file_mk.test.R            |  228 +-
 R/write_output_file_trend.R              |  264 +-
 R/write_output_file_trend_advanced.R     |  284 +-
 R/xdpm_wrapper.R                         |  244 +-
 R/ydaymax.R                              |  124 -
 R/ydaymean.R                             |  322 +--
 R/ydaymin.R                              |  124 -
 R/ydayrange.R                            |  124 -
 R/ydaysd.R                               |  126 -
 R/ydaysum.R                              |  122 -
 R/ydayx_wrapper.R                        |  270 +-
 R/ydrunmean.R                            |  132 -
 R/ydrunsd.R                              |  132 -
 R/ydrunsum.R                             |  132 -
 R/ydrunx_wrapper.R                       |   98 -
 R/year.anomaly.R                         |  318 +--
 R/yearmax.R                              |  126 -
 R/yearmean.R                             |  308 +--
 R/yearmin.R                              |  124 -
 R/yearrange.R                            |  126 -
 R/yearsd.R                               |  126 -
 R/yearsum.R                              |  308 +--
 R/yearvar.R                              |  124 -
 R/yearx_wrapper.R                        |  258 +-
 R/ymonmax.R                              |  126 -
 R/ymonmean.R                             |  126 -
 R/ymonmedian.R                           |  126 -
 R/ymonmin.R                              |  126 -
 R/ymonsd.R                               |  126 -
 R/ymonsum.R                              |  126 -
 R/ymonx_wrapper.R                        |  270 +-
 R/yseasmax.R                             |  126 -
 R/yseasmean.R                            |  132 -
 R/yseasmin.R                             |  126 -
 R/yseassd.R                              |  126 -
 R/yseasx_wrapper.R                       |  256 +-
 R/zonmean.R                              |  126 -
 R/zonsum.R                               |  126 -
 R/zonx_wrapper.R                         |  230 +-
 inst/WORDLIST                            |  363 +--
 man/acsaf_box_mergetime.Rd               |  118 -
 man/add_grid_info.Rd                     |   76 
 man/box_mergetime.Rd                     |  244 +-
 man/calc_allDatesNc.Rd                   |   32 
 man/calc_overlapping_time.Rd             |   76 
 man/calc_timestepNc.Rd                   |   32 
 man/change_att.Rd                        |  178 -
 man/check.coordinate.system.Rd           |   40 
 man/cmsaf.abs.Rd                         |  188 -
 man/cmsaf.add.Rd                         |  240 +-
 man/cmsaf.addc.Rd                        |  198 +-
 man/cmsaf.adjust.two.files.Rd            |  112 -
 man/cmsaf.cat.Rd                         |  168 -
 man/cmsaf.detrend.Rd                     |  198 +-
 man/cmsaf.div.Rd                         |  240 +-
 man/cmsaf.divc.Rd                        |  198 +-
 man/cmsaf.mk.test.Rd                     |  208 +-
 man/cmsaf.mul.Rd                         |  240 +-
 man/cmsaf.mulc.Rd                        |  200 +-
 man/cmsaf.regres.Rd                      |  196 +-
 man/cmsaf.stats.Rd                       |  118 -
 man/cmsaf.stats.station.data.Rd          |   96 -
 man/cmsaf.sub.Rd                         |  238 +-
 man/cmsaf.sub.rel.Rd                     |  110 -
 man/cmsaf.subc.Rd                        |  200 +-
 man/cmsaf.transform.coordinate.system.Rd |   74 
 man/dayavg.Rd                            |  206 +-
 man/daymax.Rd                            |  196 +-
 man/daymean.Rd                           |  206 +-
 man/daymin.Rd                            |  196 +-
 man/daypctl.Rd                           |  204 +-
 man/dayrange.Rd                          |  198 +-
 man/daysd.Rd                             |  196 +-
 man/daysum.Rd                            |  196 +-
 man/dayvar.Rd                            |  196 +-
 man/divdpm.Rd                            |  194 +-
 man/extract.level.Rd                     |  222 +-
 man/extract.period.Rd                    |  200 +-
 man/fldcor.Rd                            |  214 +-
 man/fldcovar.Rd                          |  214 +-
 man/fldmax.Rd                            |  180 -
 man/fldmean.Rd                           |  180 -
 man/fldmin.Rd                            |  180 -
 man/fldrange.Rd                          |  182 -
 man/fldsd.Rd                             |  180 -
 man/fldsum.Rd                            |  180 -
 man/get_basename.Rd                      |   66 
 man/get_date_time.Rd                     |   54 
 man/get_dimensions.Rd                    |   32 
 man/get_nc_version.Rd                    |   28 
 man/get_processing_time_string.Rd        |   42 
 man/get_time.Rd                          |   52 
 man/get_time_info.Rd                     |   36 
 man/gridboxmax.Rd                        |  194 +-
 man/gridboxmean.Rd                       |  194 +-
 man/gridboxmin.Rd                        |  194 +-
 man/gridboxrange.Rd                      |  194 +-
 man/gridboxsd.Rd                         |  194 +-
 man/gridboxsum.Rd                        |  194 +-
 man/gridboxvar.Rd                        |  194 +-
 man/hourmean.Rd                          |  174 -
 man/hoursum.Rd                           |  174 -
 man/levbox_mergetime.Rd                  |  256 +-
 man/map_regular.Rd                       |  166 -
 man/mermean.Rd                           |  162 -
 man/mon.anomaly.Rd                       |  210 +-
 man/mon.anomaly.climatology.Rd           |   81 
 man/mon_num_above.Rd                     |  216 +-
 man/mon_num_below.Rd                     |  216 +-
 man/mon_num_equal.Rd                     |  216 +-
 man/monavg.Rd                            |  220 +-
 man/mondaymean.Rd                        |  208 +-
 man/monmax.Rd                            |  208 +-
 man/monmean.Rd                           |  220 +-
 man/monmin.Rd                            |  208 +-
 man/monpctl.Rd                           |  220 +-
 man/monsd.Rd                             |  210 +-
 man/monsum.Rd                            |  208 +-
 man/monvar.Rd                            |  210 +-
 man/muldpm.Rd                            |  194 +-
 man/multimonmean.Rd                      |  222 +-
 man/multimonsum.Rd                       |  220 +-
 man/ncinfo.Rd                            |  126 -
 man/num_above.Rd                         |  206 +-
 man/num_below.Rd                         |  206 +-
 man/num_equal.Rd                         |  206 +-
 man/read_file.Rd                         |   39 
 man/read_ncvar.Rd                        |  128 -
 man/remap.Rd                             |  264 +-
 man/runmax.Rd                            |  194 +-
 man/runmean.Rd                           |  190 -
 man/runmin.Rd                            |  192 +-
 man/runrange.Rd                          |  190 -
 man/runsd.Rd                             |  194 +-
 man/runsum.Rd                            |  194 +-
 man/seas.anomaly.Rd                      |  184 -
 man/seasmean.Rd                          |  188 -
 man/seassd.Rd                            |  188 -
 man/seassum.Rd                           |  188 -
 man/seasvar.Rd                           |  188 -
 man/sellonlatbox.Rd                      |  212 +-
 man/selmon.Rd                            |  192 +-
 man/selperiod.Rd                         |  198 +-
 man/selpoint.Rd                          |  216 +-
 man/selpoint.multi.Rd                    |  254 +-
 man/seltime.Rd                           |  192 +-
 man/selyear.Rd                           |  194 +-
 man/timavg.Rd                            |  210 +-
 man/timcor.Rd                            |  214 +-
 man/timcovar.Rd                          |  214 +-
 man/timcumsum.Rd                         |   86 
 man/timmax.Rd                            |  196 +-
 man/timmean.Rd                           |  198 +-
 man/timmin.Rd                            |  196 +-
 man/timpctl.Rd                           |  208 +-
 man/timsd.Rd                             |  198 +-
 man/timselmean.Rd                        |  174 -
 man/timselsum.Rd                         |  178 -
 man/timsum.Rd                            |  198 +-
 man/trend.Rd                             |  238 +-
 man/trend_advanced.Rd                    |  258 +-
 man/wfldmean.Rd                          |  184 -
 man/ydaymax.Rd                           |  196 +-
 man/ydaymean.Rd                          |  198 +-
 man/ydaymin.Rd                           |  196 +-
 man/ydayrange.Rd                         |  196 +-
 man/ydaysd.Rd                            |  198 +-
 man/ydaysum.Rd                           |  196 +-
 man/ydrunmean.Rd                         |  194 +-
 man/ydrunsd.Rd                           |  194 +-
 man/ydrunsum.Rd                          |  194 +-
 man/year.anomaly.Rd                      |  182 -
 man/yearmax.Rd                           |  182 -
 man/yearmean.Rd                          |  182 -
 man/yearmin.Rd                           |  182 -
 man/yearrange.Rd                         |  182 -
 man/yearsd.Rd                            |  182 -
 man/yearsum.Rd                           |  182 -
 man/yearvar.Rd                           |  182 -
 man/ymonmax.Rd                           |  210 +-
 man/ymonmean.Rd                          |  210 +-
 man/ymonmedian.Rd                        |  210 +-
 man/ymonmin.Rd                           |  210 +-
 man/ymonsd.Rd                            |  210 +-
 man/ymonsum.Rd                           |  210 +-
 man/yseasmax.Rd                          |  186 -
 man/yseasmean.Rd                         |  192 +-
 man/yseasmin.Rd                          |  186 -
 man/yseassd.Rd                           |  186 -
 man/zonmean.Rd                           |  170 -
 man/zonsum.Rd                            |  170 -
 tests/spelling.R                         |    6 
 tests/testdata/SelpointRef_A.csv         |   74 
 tests/testdata/SelpointRef_B.csv         |   74 
 tests/testthat.R                         |    8 
 tests/testthat/create_testdata.R         | 2964 +++++++++++++++----------------
 tests/testthat/helper.R                  |   16 
 tests/testthat/test_add_grid_info.R      | 1252 ++++++-------
 tests/testthat/test_box_mergetime.R      | 2314 ++++++++++++------------
 tests/testthat/test_change_att.R         | 1384 +++++++-------
 tests/testthat/test_cmsaf.abs.R          |  406 ++--
 tests/testthat/test_cmsaf.add.R          | 1934 ++++++++++----------
 tests/testthat/test_cmsaf.addc.R         | 1954 ++++++++++----------
 tests/testthat/test_cmsaf.cat.R          | 1562 ++++++++--------
 tests/testthat/test_cmsaf.detrend.R      |  394 ++--
 tests/testthat/test_cmsaf.div.R          | 1978 ++++++++++----------
 tests/testthat/test_cmsaf.divc.R         | 1808 +++++++++---------
 tests/testthat/test_cmsaf.mul.R          | 1944 ++++++++++----------
 tests/testthat/test_cmsaf.mulc.R         | 1946 ++++++++++----------
 tests/testthat/test_cmsaf.regres.R       |  378 +--
 tests/testthat/test_cmsaf.sub.R          | 1890 +++++++++----------
 tests/testthat/test_cmsaf.subc.R         | 1934 ++++++++++----------
 tests/testthat/test_dayavg.R             | 1376 +++++++-------
 tests/testthat/test_daymax.R             | 1376 +++++++-------
 tests/testthat/test_daymean.R            | 1376 +++++++-------
 tests/testthat/test_daymin.R             | 1376 +++++++-------
 tests/testthat/test_daypctl.R            | 1376 +++++++-------
 tests/testthat/test_dayrange.R           | 1256 ++++++-------
 tests/testthat/test_daysd.R              | 1376 +++++++-------
 tests/testthat/test_daysum.R             | 1376 +++++++-------
 tests/testthat/test_dayvar.R             | 1376 +++++++-------
 tests/testthat/test_divdpm.R             | 1180 ++++++------
 tests/testthat/test_extract.level.R      | 1546 +++-------------
 tests/testthat/test_extract.period.R     |  744 +++----
 tests/testthat/test_fldcor.R             |  168 -
 tests/testthat/test_fldcovar.R           |  168 -
 tests/testthat/test_fldmax.R             |  392 ++--
 tests/testthat/test_fldmean.R            |  390 ++--
 tests/testthat/test_fldmin.R             |  390 ++--
 tests/testthat/test_fldrange.R           |  392 ++--
 tests/testthat/test_fldsd.R              |  392 ++--
 tests/testthat/test_fldsum.R             |  392 ++--
 tests/testthat/test_gridboxmax.R         |  244 +-
 tests/testthat/test_gridboxmean.R        |  244 +-
 tests/testthat/test_gridboxmin.R         |  244 +-
 tests/testthat/test_gridboxrange.R       |  244 +-
 tests/testthat/test_gridboxsd.R          |  244 +-
 tests/testthat/test_gridboxsum.R         |  244 +-
 tests/testthat/test_gridboxvar.R         |  244 +-
 tests/testthat/test_levbox_mergetime.R   |  192 +-
 tests/testthat/test_mermean.R            |  184 -
 tests/testthat/test_mon.anomaly.R        |  226 +-
 tests/testthat/test_monavg.R             |  422 ++--
 tests/testthat/test_monmax.R             |  412 ++--
 tests/testthat/test_monmean.R            |  410 ++--
 tests/testthat/test_monmin.R             |  410 ++--
 tests/testthat/test_monpctl.R            |  428 ++--
 tests/testthat/test_monsd.R              |  416 ++--
 tests/testthat/test_monsum.R             |  414 ++--
 tests/testthat/test_monvar.R             |  428 ++--
 tests/testthat/test_muldpm.R             |  178 -
 tests/testthat/test_multimonmean.R       |  178 -
 tests/testthat/test_multimonsum.R        |  180 -
 tests/testthat/test_runmax.R             |  188 -
 tests/testthat/test_runmean.R            |  192 +-
 tests/testthat/test_runmin.R             |  190 -
 tests/testthat/test_runrange.R           |  172 -
 tests/testthat/test_runsd.R              |  188 -
 tests/testthat/test_runsum.R             |  190 -
 tests/testthat/test_seasmean.R           |  178 -
 tests/testthat/test_seassd.R             |  260 +-
 tests/testthat/test_seassum.R            |  178 -
 tests/testthat/test_seasvar.R            |  260 +-
 tests/testthat/test_sellonlatbox.R       | 2264 +++++++++++------------
 tests/testthat/test_selmon.R             | 1834 +++++++++----------
 tests/testthat/test_selperiod.R          | 1832 +++++++++----------
 tests/testthat/test_selpoint.R           | 1728 +++++++++---------
 tests/testthat/test_selpoint.multi.R     |  144 -
 tests/testthat/test_seltime.R            | 1518 +++++++--------
 tests/testthat/test_selyear.R            | 1832 +++++++++----------
 tests/testthat/test_timavg.R             | 1462 +++++++--------
 tests/testthat/test_timcor.R             |  234 +-
 tests/testthat/test_timcovar.R           |  232 +-
 tests/testthat/test_timcumsum.R          |  762 +++----
 tests/testthat/test_timmax.R             | 1612 ++++++++--------
 tests/testthat/test_timmean.R            | 1462 +++++++--------
 tests/testthat/test_timmin.R             | 1612 ++++++++--------
 tests/testthat/test_timpctl.R            | 1922 ++++++++++----------
 tests/testthat/test_timsd.R              | 1608 ++++++++--------
 tests/testthat/test_timselmean.R         |  192 +-
 tests/testthat/test_timselsum.R          |  192 +-
 tests/testthat/test_timsum.R             | 1460 +++++++--------
 tests/testthat/test_wfldmean.R           |  382 +--
 tests/testthat/test_ydaymax.R            |  534 ++---
 tests/testthat/test_ydaymean.R           |  508 ++---
 tests/testthat/test_ydaymin.R            |  534 ++---
 tests/testthat/test_ydayrange.R          |  466 ++--
 tests/testthat/test_ydaysd.R             |  466 ++--
 tests/testthat/test_ydaysum.R            |  534 ++---
 tests/testthat/test_ydrunmean.R          |  242 +-
 tests/testthat/test_ydrunsd.R            |  246 +-
 tests/testthat/test_ydrunsum.R           |  238 +-
 tests/testthat/test_year.anomaly.R       |  386 ++--
 tests/testthat/test_yearmax.R            |  406 ++--
 tests/testthat/test_yearmean.R           |  388 ++--
 tests/testthat/test_yearmin.R            |  406 ++--
 tests/testthat/test_yearrange.R          |  406 ++--
 tests/testthat/test_yearsd.R             |  406 ++--
 tests/testthat/test_yearsum.R            |  396 ++--
 tests/testthat/test_yearvar.R            |  406 ++--
 tests/testthat/test_ymonmax.R            |  886 ++++-----
 tests/testthat/test_ymonmean.R           |  408 ++--
 tests/testthat/test_ymonmin.R            |  408 ++--
 tests/testthat/test_ymonsd.R             |  414 ++--
 tests/testthat/test_ymonsum.R            |  408 ++--
 tests/testthat/test_yseasmax.R           |  404 ++--
 tests/testthat/test_yseasmean.R          |  404 ++--
 tests/testthat/test_yseasmin.R           |  404 ++--
 tests/testthat/test_yseassd.R            |  408 ++--
 tests/testthat/test_zonmean.R            |  176 -
 tests/testthat/test_zonsum.R             |  176 -
 507 files changed, 79228 insertions(+), 80102 deletions(-)

More information about cmsafops at CRAN
Permanent link

Package clusterGGM updated to version 0.1.1 with previous version 0.1.0 dated 2025-10-17

Title: Sparse Gaussian Graphical Modeling with Variable Clustering
Description: Perform sparse estimation of a Gaussian graphical model (GGM) with node aggregation through variable clustering. Currently, the package implements the clusterpath estimator of the Gaussian graphical model (CGGM) (Touw, Alfons, Groenen & Wilms, 2025; <doi:10.48550/arXiv.2407.00644>).
Author: Daniel J.W. Touw [aut] , Andreas Alfons [aut, cre] , Ines Wilms [aut] , Patrick J.F. Groenen [ths]
Maintainer: Andreas Alfons <alfons@ese.eur.nl>

Diff between clusterGGM versions 0.1.0 dated 2025-10-17 and 0.1.1 dated 2025-10-22

 clusterGGM-0.1.0/clusterGGM/src/clock.h         |only
 clusterGGM-0.1.1/clusterGGM/DESCRIPTION         |    8 +-
 clusterGGM-0.1.1/clusterGGM/MD5                 |   16 ++---
 clusterGGM-0.1.1/clusterGGM/NEWS                |only
 clusterGGM-0.1.1/clusterGGM/R/cggm.R            |    3 -
 clusterGGM-0.1.1/clusterGGM/R/cggm_wrapper.R    |    2 
 clusterGGM-0.1.1/clusterGGM/build/partial.rdb   |binary
 clusterGGM-0.1.1/clusterGGM/man/cggm.Rd         |    3 -
 clusterGGM-0.1.1/clusterGGM/src/cggm_export.cpp |   66 ------------------------
 clusterGGM-0.1.1/clusterGGM/src/utils.cpp       |   14 +++++
 10 files changed, 26 insertions(+), 86 deletions(-)

More information about clusterGGM at CRAN
Permanent link

Package lsirm12pl updated to version 1.3.9 with previous version 1.3.8 dated 2025-10-14

Title: Latent Space Item Response Model
Description: Analysis of dichotomous and continuous response data using latent factor by both 1PL LSIRM and 2PL LSIRM as described in Jeon et al. (2021) <doi:10.1007/s11336-021-09762-5>. It includes original 1PL LSIRM and 2PL LSIRM provided for binary response data and its extension for continuous response data. Bayesian model selection with spike-and-slab prior and method for dealing data with missing value under missing at random, missing completely at random are also supported. Various diagnostic plots are available to inspect the latent space and summary of estimated parameters.
Author: Dongyoung Go [aut], Gwanghee Kim [aut, cre], Jina Park [aut], Ickhoon Jin [ctb], Minjeong Jeon [ctb]
Maintainer: Gwanghee Kim <musagh08@yonsei.ac.kr>

Diff between lsirm12pl versions 1.3.8 dated 2025-10-14 and 1.3.9 dated 2025-10-22

 DESCRIPTION                             |    8 
 MD5                                     |  162 ++++++-------
 R/RcppExports.R                         |  144 ++++++------
 R/lsirm.R                               |  243 ++++++++++----------
 R/lsirm1pl_fixed_gamma.R                |   11 
 R/lsirm1pl_fixed_gamma_mar.R            |   10 
 R/lsirm1pl_fixed_gamma_mcar.R           |   11 
 R/lsirm1pl_mar.R                        |    9 
 R/lsirm1pl_mar_ss.R                     |   14 -
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 R/lsirm1pl_normal_fixed_gamma.R         |   12 -
 R/lsirm1pl_normal_fixed_gamma_mar.R     |   14 -
 R/lsirm1pl_normal_fixed_gamma_mcar.R    |   14 -
 R/lsirm1pl_normal_mar.R                 |   16 -
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 R/lsirm1pl_o.R                          |    8 
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 R/lsirm2pl_fixed_gamma.R                |   12 -
 R/lsirm2pl_fixed_gamma_mar.R            |   14 -
 R/lsirm2pl_fixed_gamma_mcar.R           |   14 -
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 R/lsirm2pl_mar_ss.R                     |   18 -
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 R/lsirm2pl_normal_fixed_gamma.R         |   14 -
 R/lsirm2pl_normal_fixed_gamma_mar.R     |   16 -
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 R/lsirm2pl_normal_mar.R                 |   18 -
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 R/lsirm2pl_normal_o.R                   |   12 -
 R/lsirm2pl_normal_ss.R                  |   14 -
 R/lsirm2pl_o.R                          |  313 +++++++++++++-------------
 R/lsirm2pl_ss.R                         |   16 -
 man/lsirm1pl.Rd                         |    6 
 man/lsirm1pl_fixed_gamma.Rd             |    8 
 man/lsirm1pl_fixed_gamma_mar.Rd         |    8 
 man/lsirm1pl_fixed_gamma_mcar.Rd        |    8 
 man/lsirm1pl_mar.Rd                     |    8 
 man/lsirm1pl_mar_ss.Rd                  |    8 
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 man/lsirm1pl_mcar_ss.Rd                 |    8 
 man/lsirm1pl_normal_fixed_gamma.Rd      |    8 
 man/lsirm1pl_normal_fixed_gamma_mar.Rd  |    8 
 man/lsirm1pl_normal_fixed_gamma_mcar.Rd |    8 
 man/lsirm1pl_normal_mar.Rd              |    8 
 man/lsirm1pl_normal_mar_ss.Rd           |    8 
 man/lsirm1pl_normal_mcar.Rd             |    8 
 man/lsirm1pl_normal_mcar_ss.Rd          |    8 
 man/lsirm1pl_normal_o.Rd                |    8 
 man/lsirm1pl_normal_ss.Rd               |    8 
 man/lsirm1pl_o.Rd                       |    8 
 man/lsirm1pl_ss.Rd                      |    8 
 man/lsirm2pl.Rd                         |    9 
 man/lsirm2pl_fixed_gamma.Rd             |   11 
 man/lsirm2pl_fixed_gamma_mar.Rd         |   11 
 man/lsirm2pl_fixed_gamma_mcar.Rd        |   11 
 man/lsirm2pl_mar.Rd                     |   11 
 man/lsirm2pl_mar_ss.Rd                  |   11 
 man/lsirm2pl_mcar.Rd                    |   11 
 man/lsirm2pl_mcar_ss.Rd                 |   11 
 man/lsirm2pl_normal_fixed_gamma.Rd      |   11 
 man/lsirm2pl_normal_fixed_gamma_mar.Rd  |   11 
 man/lsirm2pl_normal_fixed_gamma_mcar.Rd |   11 
 man/lsirm2pl_normal_mar.Rd              |   11 
 man/lsirm2pl_normal_mar_ss.Rd           |   11 
 man/lsirm2pl_normal_mcar.Rd             |   11 
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 man/lsirm2pl_normal_o.Rd                |   11 
 man/lsirm2pl_normal_ss.Rd               |   11 
 man/lsirm2pl_o.Rd                       |   11 
 man/lsirm2pl_ss.Rd                      |   11 
 src/RcppExports.cpp                     |  378 +++++++++++++++++++-------------
 src/lsirm1pl.cpp                        |  256 ++++++++++++---------
 src/lsirm2pl.cpp                        |  334 +++++++++++++++-------------
 src/utility_cpp.cpp                     |   93 ++++---
 82 files changed, 1623 insertions(+), 1156 deletions(-)

More information about lsirm12pl at CRAN
Permanent link

Package psychonetrics updated to version 0.13.2 with previous version 0.13.1 dated 2025-06-02

Title: Structural Equation Modeling and Confirmatory Network Analysis
Description: Multi-group (dynamical) structural equation models in combination with confirmatory network models from cross-sectional, time-series and panel data <doi:10.31234/osf.io/8ha93>. Allows for confirmatory testing and fit as well as exploratory model search.
Author: Sacha Epskamp [aut, cre]
Maintainer: Sacha Epskamp <mail@sachaepskamp.com>

Diff between psychonetrics versions 0.13.1 dated 2025-06-02 and 0.13.2 dated 2025-10-22

 DESCRIPTION                                         |    7 
 MD5                                                 |  512 ++--
 NAMESPACE                                           |  400 +--
 NEWS                                                |  382 +--
 R/00_codeOrganization.R                             |   44 
 R/00_steps_to_implement_distribution.R              |   20 
 R/00_steps_to_implement_estimator.R                 |   18 
 R/00_steps_to_implement_model.R                     |   30 
 R/01_classes.R                                      |  444 ++--
 R/02_algebrahelpers_Solve.R                         |  122 -
 R/02_algebrahelpers_blockToeplitz.R                 |   40 
 R/02_algebrahelpers_checkJacobian.R                 |  250 +-
 R/02_algebrahelpers_expected_latent_residual_covs.R |  124 -
 R/02_algebrahelpers_expectedmodel.R                 |   48 
 R/02_algebrahelpers_kronecker.R                     |    2 
 R/02_algebrahelpers_lavUtils.R                      |   48 
 R/02_algebrahelpers_matrixexponent.R                |   20 
 R/02_algebrahelpers_maxcor.R                        |   22 
 R/02_algebrahelpers_modelMatrix.R                   |   26 
 R/02_algebrahelpers_quantiletransform.R             |   20 
 R/02_algebrahelpers_spectralshift.R                 |   50 
 R/02_algebrahelpers_trysolve.R                      |   52 
 R/02_algebrahelpers_vectorize.R                     |   56 
 R/02_algebrahelpers_vectorizeMatrices.R             |  116 -
 R/02_algebrahelpers_weighted_geomean.R              |    2 
 R/02_modelformation_PCCPDC.R                        |   32 
 R/03_modelformation_adjust_p_values.R               |  116 -
 R/03_modelformation_defaultoptimizer.R              |    6 
 R/03_modelformation_factorstart.R                   |   40 
 R/03_modelformation_fixAdj.R                        |  162 -
 R/03_modelformation_fixMatrix.R                     |  160 -
 R/03_modelformation_fixMu.R                         |   82 
 R/03_modelformation_fixTau.R                        |  170 -
 R/03_modelformation_formModelMatrices.R             |  152 -
 R/03_modelformation_generateParameterTable.R        |  540 ++--
 R/03_modelformation_impliedcovstructures.R          |  272 +-
 R/03_modelformation_labtoind.R                      |   56 
 R/03_modelformation_matrixSetup_Isingbeta.R         |   65 
 R/03_modelformation_matrixSetup_Isingtau.R          |   54 
 R/03_modelformation_matrixSetup_SD.R                |  102 
 R/03_modelformation_matrixSetup_beta.R              |   76 
 R/03_modelformation_matrixSetup_cholesky.R          |  126 -
 R/03_modelformation_matrixSetup_delta.R             |  124 -
 R/03_modelformation_matrixSetup_isingomega.R        |   64 
 R/03_modelformation_matrixSetup_kappa.R             |  134 -
 R/03_modelformation_matrixSetup_lambda.R            |  452 ++--
 R/03_modelformation_matrixSetup_mu.R                |   68 
 R/03_modelformation_matrixSetup_omega.R             |  200 -
 R/03_modelformation_matrixSetup_rho.R               |  104 
 R/03_modelformation_matrixSetup_sigma.R             |  130 -
 R/03_modelformation_matrixSetup_tau.R               |   74 
 R/03_modelformation_missingpatterns.R               |  314 +-
 R/03_modelformation_missingpatterns_covs.R          |  174 -
 R/03_modelformation_samplestats.R                   |   16 
 R/03_modelformation_samplestats_norawts.R           | 1304 ++++++------
 R/03_modelformation_samplestats_rawts.R             |  192 -
 R/03_modelformation_sparseordense.R                 |   90 
 R/03_modelformation_startvaluesandbounds.R          |  104 
 R/03_modelformation_tsData.R                        |  344 +--
 R/04_generalFit_fitfunction.R                       |   88 
 R/04_generalFit_gradient.R                          |  258 +-
 R/04_generalFit_logLikelihood.R                     |   36 
 R/04_generalfit_FisherInformation.R                 |  468 ++--
 R/04_generalfit_VCOV.R                              |   28 
 R/04_generalfit_impliedModel.R                      |   80 
 R/04_generalfit_loglikelihood_Ising.R               |  176 -
 R/04_generalfit_loglikelihood_gauss.R               |  232 +-
 R/04_generalfit_prepareModel.R                      |  154 -
 R/04_modelformation_matrixSetup_flexcov.R           |  138 -
 R/05_MLestimator_expected_hessian_Gauss.R           |  126 -
 R/05_MLestimator_expected_hessian_Ising.R           |  178 -
 R/05_MLestimator_fit_Gauss.R                        |   36 
 R/05_MLestimator_fit_Ising.R                        |   76 
 R/05_MLestimator_fitfunction.R                      |   22 
 R/05_MLestimator_gradient_Gauss.R                   |  146 -
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 R/06_ULS_expectedHessian.R                          |   64 
 R/06_ULS_fitfunction.R                              |  154 -
 R/06_ULS_gradient.R                                 |  124 -
 R/06_weightsMatrix.R                                |   76 
 R/07_FIMLestimator_expected_hessian_Gauss.R         |  302 +-
 R/07_FIMLestimator_fit_Gauss.R                      |  194 -
 R/07_FIMLestimator_fitfunction.R                    |   20 
 R/07_FIMLestimator_gradient_Gauss.R                 |  302 +-
 R/08_outputHelpers_NAtoFALSE.R                      |    4 
 R/08_outputHelpers_NAtoTRUE.R                       |    4 
 R/08_outputHelpers_goodNum.R                        |   92 
 R/08_outputHelpers_logo.R                           |   72 
 R/09_modelmodification_clearpars.R                  |   40 
 R/09_modelmodifivation_emergencystart.R             |  166 -
 R/14_varcov_derivatives.R                           |  434 ++--
 R/14_varcov_implied.R                               |   92 
 R/14_varcov_prepare.R                               |  136 -
 R/15_lvm_derivatives.R                              |  428 +--
 R/15_lvm_identify.R                                 |  436 ++--
 R/15_lvm_implied.R                                  |  122 -
 R/15_lvm_prepare.R                                  |  122 -
 R/16_var1_derivatives.R                             |  362 +--
 R/16_var1_implied.R                                 |  150 -
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 R/18_dlvm1_derivatives.R                            |  814 +++----
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 R/19_tsdlvm1_prepare.R                              |  116 -
 R/20_meta_varcov_derivatives.R                      |  584 ++---
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 R/21_Ising_derivatives.R                            |   57 
 R/21_Ising_helperfunctions.R                        |   32 
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 R/22_ml_lvm_derivatives.R                           |  424 +--
 R/22_ml_lvm_identify.R                              |  576 ++---
 R/22_ml_lvm_implied.R                               |  258 +-
 R/22_ml_lvm_prepare.R                               |  116 -
 R/RcppExports.R                                     | 1342 ++++++------
 R/a_models_Ising.R                                  |  478 ++--
 R/a_models_bifactor.R                               |   90 
 R/a_models_cholesky.R                               |   18 
 R/a_models_corr.R                                   |   18 
 R/a_models_dlvm1.R                                  | 2166 ++++++++++----------
 R/a_models_frombootnet.R                            |   78 
 R/a_models_ggm.R                                    |   18 
 R/a_models_gvar.R                                   |    8 
 R/a_models_joingroups.R                             |  244 +-
 R/a_models_latentgrowth.R                           |  198 -
 R/a_models_lnm.R                                    |    6 
 R/a_models_lrnm.R                                   |    6 
 R/a_models_lvm.R                                    |  858 +++----
 R/a_models_meta_ggm.R                               |    4 
 R/a_models_meta_varcov.R                            | 1310 ++++++------
 R/a_models_ml_lnm.R                                 |    4 
 R/a_models_ml_lrnm.R                                |    4 
 R/a_models_ml_lvm.R                                 | 1196 +++++------
 R/a_models_ml_rnm.R                                 |    4 
 R/a_models_ml_tsdlvm1.R                             |  356 +--
 R/a_models_ml_tslvgvar.R                            |   44 
 R/a_models_panelgvar.R                              |  154 -
 R/a_models_precision.R                              |   18 
 R/a_models_ri_clpm.R                                |  450 ++--
 R/a_models_rnm.R                                    |    6 
 R/a_models_sem.R                                    |    6 
 R/a_models_tsdlvm1.R                                |  826 +++----
 R/a_models_tslvgvar.R                               |    6 
 R/a_models_var1.R                                   |  642 ++---
 R/a_models_varcov.R                                 |  812 +++----
 R/b_modelexpansions_addMIs.R                        |  450 ++--
 R/b_modelexpansions_addSEs.R                        |  206 -
 R/b_modelexpansions_addfit.R                        |  560 ++---
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 R/d_stepup.R                                        |  890 ++++----
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 R/f_conveneince_fake_optimr.R                       |   60 
 R/f_conveneince_generate.R                          |   66 
 R/f_conveneince_setEstimator.R                      |    6 
 R/f_conveneince_setoptimizer.R                      |   56 
 R/f_conveneince_setverbose.R                        |    8 
 R/f_conveneince_usecpp.R                            |   22 
 R/f_convenience_CIplot.R                            |  878 ++++----
 R/f_convenience_MIs.R                               |  268 +-
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 R/f_convenience_bootstrap.R                         |  174 -
 R/f_convenience_bootstrap_SEs.R                     |   12 
 R/f_convenience_bootstrap_warning.R                 |    4 
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 R/f_convenience_ergodicity.R                        |  450 ++--
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 R/f_convenience_logbook.R                           |   84 
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Package galaxias updated to version 0.1.1 with previous version 0.1.0 dated 2025-07-07

Title: Describe, Package, and Share Biodiversity Data
Description: The Darwin Core data standard is widely used to share biodiversity information, most notably by the Global Biodiversity Information Facility and its partner nodes; but converting data to this standard can be tricky. 'galaxias' is functionally similar to 'devtools', but with a focus on building Darwin Core Archives rather than R packages, enabling data to be shared and re-used with relative ease. For details see Wieczorek and colleagues (2012) <doi:10.1371/journal.pone.0029715>.
Author: Martin Westgate [aut, cre], Shandiya Balasubramaniam [aut], Dax Kellie [aut]
Maintainer: Martin Westgate <martin.westgate@csiro.au>

Diff between galaxias versions 0.1.0 dated 2025-07-07 and 0.1.1 dated 2025-10-22

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Package Directional updated to version 7.3 with previous version 7.2 dated 2025-07-02

Title: A Collection of Functions for Directional Data Analysis
Description: A collection of functions for directional data (including massive data, with millions of observations) analysis. Hypothesis testing, discriminant and regression analysis, MLE of distributions and more are included. The standard textbook for such data is the "Directional Statistics" by Mardia, K. V. and Jupp, P. E. (2000). Other references include: a) Paine J.P., Preston S.P., Tsagris M. and Wood A.T.A. (2018). "An elliptically symmetric angular Gaussian distribution". Statistics and Computing 28(3): 689-697. <doi:10.1007/s11222-017-9756-4>. b) Tsagris M. and Alenazi A. (2019). "Comparison of discriminant analysis methods on the sphere". Communications in Statistics: Case Studies, Data Analysis and Applications 5(4):467--491. <doi:10.1080/23737484.2019.1684854>. c) Paine J.P., Preston S.P., Tsagris M. and Wood A.T.A. (2020). "Spherical regression models with general covariates and anisotropic errors". Statistics and Computing 30(1): 153--165. <doi:10.1007/s11222-019-09872 [...truncated...]
Author: Michail Tsagris [aut, cre], Giorgos Athineou [aut], Christos Adam [aut], Zehao Yu [aut], Anamul Sajib [ctb], Eli Amson [ctb], Micah J. Waldstein [ctb], Panagiotis Papastamoulis [ctb]
Maintainer: Michail Tsagris <mtsagris@uoc.gr>

Diff between Directional versions 7.2 dated 2025-07-02 and 7.3 dated 2025-10-22

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Package arcgislayers updated to version 0.5.1 with previous version 0.5.0 dated 2025-09-19

Title: Harness ArcGIS Data Services
Description: Enables users of 'ArcGIS Enterprise', 'ArcGIS Online', or 'ArcGIS Platform' to read, write, publish, or manage vector and raster data via ArcGIS location services REST API endpoints <https://developers.arcgis.com/rest/>.
Author: Josiah Parry [aut, cre] , Eli Pousson [ctb] , Kenneth Vernon [ctb] , Martha Bass [ctb] , Antony Barja [ctb]
Maintainer: Josiah Parry <josiah.parry@gmail.com>

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Package ggscidca updated to version 0.2.6 with previous version 0.2.5 dated 2025-09-05

Title: Plotting Decision Curve Analysis with Coloured Bars
Description: Decision curve analysis is a method for evaluating and comparing prediction models that incorporates clinical consequences, requires only the data set on which the models are tested, and can be applied to models that have either continuous or dichotomous results. The 'ggscidca' package adds coloured bars of discriminant relevance to the traditional decision curve. Improved practicality and aesthetics. This method was described by Balachandran VP (2015) <doi:10.1016/S1470-2045(14)71116-7>.
Author: Qiang Liu [aut, cre]
Maintainer: Qiang Liu <dege857@163.com>

Diff between ggscidca versions 0.2.5 dated 2025-09-05 and 0.2.6 dated 2025-10-22

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