Tue, 04 Feb 2025

Package AhoCorasickTrie updated to version 0.1.3 with previous version 0.1.2 dated 2020-09-29

Title: Fast Searching for Multiple Keywords in Multiple Texts
Description: Aho-Corasick is an optimal algorithm for finding many keywords in a text. It can locate all matches in a text in O(N+M) time; i.e., the time needed scales linearly with the number of keywords (N) and the size of the text (M). Compare this to the naive approach which takes O(N*M) time to loop through each pattern and scan for it in the text. This implementation builds the trie (the generic name of the data structure) and runs the search in a single function call. If you want to search multiple texts with the same trie, the function will take a list or vector of texts and return a list of matches to each text. By default, all 128 ASCII characters are allowed in both the keywords and the text. A more efficient trie is possible if the alphabet size can be reduced. For example, DNA sequences use at most 19 distinct characters and usually only 4; protein sequences use at most 26 distinct characters and usually only 20. UTF-8 (Unicode) matching is not currently supported.
Author: Matt Chambers [aut, cre], Tomas Petricek [aut, cph], Vanderbilt University [cph]
Maintainer: Matt Chambers <matt.chambers42@gmail.com>

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Package Umpire updated to version 2.0.11 with previous version 2.0.10 dated 2020-11-10

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

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Package multilevLCA updated to version 2.0.0 with previous version 1.5.2 dated 2024-10-12

Title: Estimates and Plots Single-Level and Multilevel Latent Class Models
Description: Efficiently estimates single- and multilevel latent class models with covariates, allowing for output visualization in all specifications. For more technical details, see Lyrvall et al (2023) <doi:10.48550/arXiv.2305.07276>.
Author: Roberto Di Mari [aut, cre], Johan Lyrvall [aut], Zsuzsa Bakk [ctb], Jennifer Oser [ctb], Jouni Kuha [ctb]
Maintainer: Roberto Di Mari <roberto.dimari@unict.it>

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Package metadat updated to version 1.4-0 with previous version 1.2-0 dated 2022-04-06

Title: Meta-Analysis Datasets
Description: A collection of meta-analysis datasets for teaching purposes, illustrating/testing meta-analytic methods, and validating published analyses.
Author: Wolfgang Viechtbauer [aut, cre] , Thomas White [aut] , Daniel Noble [aut] , Alistair Senior [aut] , W. Kyle Hamilton [aut] , Guido Schwarzer [dtc]
Maintainer: Wolfgang Viechtbauer <wvb@metafor-project.org>

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Package posologyr updated to version 1.2.8 with previous version 1.2.7 dated 2024-09-13

Title: Individual Dose Optimization using Population Pharmacokinetics
Description: Personalize drug regimens using individual pharmacokinetic (PK) and pharmacokinetic-pharmacodynamic (PK-PD) profiles. By combining therapeutic drug monitoring (TDM) data with a population model, 'posologyr' offers accurate posterior estimates and helps compute optimal individualized dosing regimens. The empirical Bayes estimates are computed following the method described by Kang et al. (2012) <doi:10.4196/kjpp.2012.16.2.97>.
Author: Cyril Leven [aut, cre, cph] , Matthew Fidler [ctb] , Emmanuelle Comets [ctb], Audrey Lavenu [ctb], Marc Lavielle [ctb]
Maintainer: Cyril Leven <cyril.leven@chu-brest.fr>

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Package plotthis updated to version 0.5.1 with previous version 0.5.0 dated 2025-01-09

Title: High-Level Plotting Built Upon 'ggplot2' and Other Plotting Packages
Description: Provides high-level API and a wide range of options to create stunning, publication-quality plots effortlessly. It is built upon 'ggplot2' and other plotting packages, and is designed to be easy to use and to work seamlessly with 'ggplot2' objects. It is particularly useful for creating complex plots with multiple layers, facets, and annotations. It also provides a set of functions to create plots for specific types of data, such as Venn diagrams, alluvial diagrams, and phylogenetic trees. The package is designed to be flexible and customizable, and to work well with the 'ggplot2' ecosystem. The API can be found at <https://pwwang.github.io/plotthis/reference/index.html>.
Author: Panwen Wang [aut, cre]
Maintainer: Panwen Wang <pwwang@pwwang.com>

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Package MixtureMissing updated to version 3.0.4 with previous version 3.0.3 dated 2024-10-15

Title: Robust and Flexible Model-Based Clustering for Data Sets with Missing Values at Random
Description: Implementations of various robust and flexible model-based clustering methods for data sets with missing values at random. Two main models are: Multivariate Contaminated Normal Mixture (MCNM, Tong and Tortora, 2022, <doi:10.1007/s11634-021-00476-1>) and Multivariate Generalized Hyperbolic Mixture (MGHM, Wei et al., 2019, <doi:10.1016/j.csda.2018.08.016>). Mixtures via some special or limiting cases of the multivariate generalized hyperbolic distribution are also included: Normal-Inverse Gaussian, Symmetric Normal-Inverse Gaussian, Skew-Cauchy, Cauchy, Skew-t, Student's t, Normal, Symmetric Generalized Hyperbolic, Hyperbolic Univariate Marginals, Hyperbolic, and Symmetric Hyperbolic.
Author: Hung Tong [aut, cre], Cristina Tortora [aut, ths, dgs]
Maintainer: Hung Tong <hungtongmx@gmail.com>

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Package gmoTree updated to version 1.4.1 with previous version 1.4.0 dated 2025-02-04

Title: Get and Modify 'oTree' Data
Description: Efficiently manage and process data from 'oTree' experiments. Import 'oTree' data and clean them by using functions that handle messy data, dropouts, and other problematic cases. Create IDs, calculate the time, transfer variables between app data frames, and delete sensitive information. Review your experimental data prior to running the experiment and automatically generate a detailed summary of the variables used in your 'oTree' code. Information on 'oTree' is found in Chen, D. L., Schonger, M., & Wickens, C. (2016) <doi:10.1016/j.jbef.2015.12.001>.
Author: Patricia F. Zauchner [aut, trl, cre, cph]
Maintainer: Patricia F. Zauchner <patricia.zauchner@gmx.at>

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Package constrainedKriging updated to version 0.2-11 with previous version 0.2-10 dated 2025-02-01

Title: Constrained, Covariance-Matching Constrained and Universal Point or Block Kriging
Description: Provides functions for efficient computation of non-linear spatial predictions with local change of support (Hofer, C. and Papritz, A. (2011) "constrainedKriging: An R-package for customary, constrained and covariance-matching constrained point or block kriging" <doi:10.1016/j.cageo.2011.02.009>). This package supplies functions for two-dimensional spatial interpolation by constrained (Cressie, N. (1993) "Aggregation in geostatistical problems" <doi:10.1007/978-94-011-1739-5_3>), covariance-matching constrained (Aldworth, J. and Cressie, N. (2003) "Prediction of nonlinear spatial functionals" <doi:10.1016/S0378-3758(02)00321-X>) and universal (external drift) Kriging for points or blocks of any shape from data with a non-stationary mean function and an isotropic weakly stationary covariance function. The linear spatial interpolation methods, constrained and covariance-matching constrained Kriging, provide approximately unbiased prediction for non-linear target value [...truncated...]
Author: Christoph Hofer [aut], Andreas Papritz [ctb, cre]
Maintainer: Andreas Papritz <papritz@retired.ethz.ch>

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Package QuadratiK updated to version 1.1.3 with previous version 1.1.2 dated 2024-10-29

Title: Collection of Methods Constructed using Kernel-Based Quadratic Distances
Description: It includes test for multivariate normality, test for uniformity on the d-dimensional Sphere, non-parametric two- and k-sample tests, random generation of points from the Poisson kernel-based density and clustering algorithm for spherical data. For more information see Saraceno G., Markatou M., Mukhopadhyay R. and Golzy M. (2024) <doi:10.48550/arXiv.2402.02290> Markatou, M. and Saraceno, G. (2024) <doi:10.48550/arXiv.2407.16374>, Ding, Y., Markatou, M. and Saraceno, G. (2023) <doi:10.5705/ss.202022.0347>, and Golzy, M. and Markatou, M. (2020) <doi:10.1080/10618600.2020.1740713>.
Author: Giovanni Saraceno [aut, cre] , Marianthi Markatou [aut], Raktim Mukhopadhyay [aut], Mojgan Golzy [aut], Hingee Kassel [rev], Emi Tanaka [rev]
Maintainer: Giovanni Saraceno <giovanni.saraceno@unipd.it>

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Package metasnf updated to version 2.0.0 with previous version 1.1.1 dated 2024-11-08

Title: Meta Clustering with Similarity Network Fusion
Description: Framework to facilitate patient subtyping with similarity network fusion and meta clustering. The similarity network fusion (SNF) algorithm was introduced by Wang et al. (2014) in <doi:10.1038/nmeth.2810>. SNF is a data integration approach that can transform high-dimensional and diverse data types into a single similarity network suitable for clustering with minimal loss of information from each initial data source. The meta clustering approach was introduced by Caruana et al. (2006) in <doi:10.1109/ICDM.2006.103>. Meta clustering involves generating a wide range of cluster solutions by adjusting clustering hyperparameters, then clustering the solutions themselves into a manageable number of qualitatively similar solutions, and finally characterizing representative solutions to find ones that are best for the user's specific context. This package provides a framework to easily transform multi-modal data into a wide range of similarity network fusion-derived cluster solutio [...truncated...]
Author: Prashanth S Velayudhan [aut, cre], Xiaoqiao Xu [aut], Prajkta Kallurkar [aut], Ana Patricia Balbon [aut], Maria T Secara [aut], Adam Taback [aut], Denise Sabac [aut], Nicholas Chan [aut], Shihao Ma [aut], Bo Wang [aut], Daniel Felsky [aut], Stephanie [...truncated...]
Maintainer: Prashanth S Velayudhan <psvelayu@gmail.com>

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More information about metasnf at CRAN
Permanent link

Package FIESTA updated to version 3.7.0 with previous version 3.6.4 dated 2024-06-07

Title: Forest Inventory Estimation and Analysis
Description: A research estimation tool for analysts that work with sample-based inventory data from the U.S. Department of Agriculture, Forest Service, Forest Inventory and Analysis (FIA) Program.
Author: Tracey Frescino [aut], Gretchen Moisen [aut], Paul Patterson [aut], Chris Toney [aut], Grayson White [aut, cre] , Joshua Yamamoto [aut]
Maintainer: Grayson White <graysonwhite13@gmail.com>

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Package irboost updated to version 0.2-1.0 with previous version 0.1-1.5 dated 2024-04-18

Title: Iteratively Reweighted Boosting for Robust Analysis
Description: Fit a predictive model using iteratively reweighted boosting (IRBoost) to minimize robust loss functions within the CC-family (concave-convex). This constitutes an application of iteratively reweighted convex optimization (IRCO), where convex optimization is performed using the functional descent boosting algorithm. IRBoost assigns weights to facilitate outlier identification. Applications include robust generalized linear models and robust accelerated failure time models. Wang (2025) <doi:10.6339/24-JDS1138>.
Author: Zhu Wang [aut, cre]
Maintainer: Zhu Wang <zhuwang@gmail.com>

Diff between irboost versions 0.1-1.5 dated 2024-04-18 and 0.2-1.0 dated 2025-02-04

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Package SSBtools updated to version 1.7.0 with previous version 1.6.0 dated 2024-12-04

Title: Statistics Norway's Miscellaneous Tools
Description: Functions used by other packages from Statistics Norway are gathered. General data manipulation functions, algorithms for statistical disclosure control (Langsrud, 2024) <doi:10.1007/978-3-031-69651-0_6> and functions for hierarchical computations by sparse model matrices are included (Langsrud, 2023) <doi:10.32614/RJ-2023-088>.
Author: Oeyvind Langsrud [aut, cre] , Daniel Lupp [aut] , Bjoern-Helge Mevik [ctb], Vidar Norstein Klungre [rev] , Statistics Norway [cph]
Maintainer: Oeyvind Langsrud <oyl@ssb.no>

Diff between SSBtools versions 1.6.0 dated 2024-12-04 and 1.7.0 dated 2025-02-04

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New package SQLFormatteR with initial version 0.0.1
Package: SQLFormatteR
Title: Format SQL Queries
Version: 0.0.1
Description: A convenient interface for formatting 'SQL' queries directly within 'R'. It acts as a wrapper around the 'sql_format' Rust crate. The package allows you to format 'SQL' code with customizable options, including indentation, case formatting, and more, ensuring your 'SQL' queries are clean, readable, and consistent.
License: MIT + file LICENSE
URL: https://dataupsurge.github.io/SQLFormatteR/, https://github.com/dataupsurge/SQLFormatteR
BugReports: https://github.com/dataupsurge/SQLFormatteR/issues
Imports: assertthat
Suggests: covr (>= 3.6.4), docopt (>= 0.7.1), git2r (>= 0.35.0), jsonlite (>= 1.8.9), lintr (>= 3.1.2), optparse (>= 1.7.5), precommit (>= 0.4.3), rextendr (>= 0.3.1), roxygen2 (>= 7.3.2), styler (>= 1.10.3), testthat (>= 3.0.0)
Encoding: UTF-8
SystemRequirements: Cargo (Rust's package manager), rustc >= 1.65.0
NeedsCompilation: yes
Packaged: 2025-02-04 11:11:05 UTC; morgan
Author: Morgan Durand [aut, cre, cph], Authors of the dependent Rust crates [aut]
Maintainer: Morgan Durand <morgan@dataupsurge.com>
Repository: CRAN
Date/Publication: 2025-02-04 17:40:15 UTC

More information about SQLFormatteR at CRAN
Permanent link

New package shiny2docker with initial version 0.0.1
Package: shiny2docker
Title: Generate Dockerfiles for 'Shiny' Applications
Version: 0.0.1
Description: Automates the creation of Dockerfiles for deploying 'Shiny' applications. By integrating with 'renv' for dependency management and leveraging Docker-based solutions, it simplifies the process of containerizing 'Shiny' apps, ensuring reproducibility and consistency across different environments.
License: MIT + file LICENSE
Imports: attachment (>= 0.4.3), dockerfiler, here, yesno
Encoding: UTF-8
URL: https://github.com/VincentGuyader/shiny2docker
BugReports: https://github.com/VincentGuyader/shiny2docker/issues
Suggests: shiny, renv, testthat (>= 3.0.0), knitr, rmarkdown, rstudioapi
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2025-02-04 10:29:45 UTC; PC
Author: Vincent Guyader [aut, cre]
Maintainer: Vincent Guyader <vincent@thinkr.fr>
Repository: CRAN
Date/Publication: 2025-02-04 17:40:02 UTC

More information about shiny2docker at CRAN
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New package rmcmc with initial version 0.1.1
Package: rmcmc
Title: Robust Markov Chain Monte Carlo Methods
Version: 0.1.1
Description: Functions for simulating Markov chains using the Barker proposal to compute Markov chain Monte Carlo (MCMC) estimates of expectations with respect to a target distribution on a real-valued vector space. The Barker proposal, described in Livingstone and Zanella (2022) <doi:10.1111/rssb.12482>, is a gradient-based MCMC algorithm inspired by the Barker accept-reject rule. It combines the robustness of simpler MCMC schemes, such as random-walk Metropolis, with the efficiency of gradient-based methods, such as the Metropolis adjusted Langevin algorithm. The key function provided by the package is sample_chain(), which allows sampling a Markov chain with a specified target distribution as its stationary distribution. The chain is sampled by generating proposals and accepting or rejecting them using a Metropolis-Hasting acceptance rule. During an initial warm-up stage, the parameters of the proposal distribution can be adapted, with adapters available to both: tune the scale of the prop [...truncated...]
License: MIT + file LICENSE
Encoding: UTF-8
Suggests: bridgestan (>= 2.5.0), knitr, posterior, progress, ramcmc, rmarkdown, testthat (>= 3.0.0)
URL: https://github.com/UCL/rmcmc, http://github-pages.ucl.ac.uk/rmcmc/
BugReports: https://github.com/UCL/rmcmc/issues
Imports: Matrix, rlang, withr
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2025-02-04 16:29:30 UTC; matt
Author: Matthew M. Graham [aut, cre] , Samuel Livingstone [aut] , University College London [cph], Engineering and Physical Sciences Research Council [fnd]
Maintainer: Matthew M. Graham <m.graham@ucl.ac.uk>
Repository: CRAN
Date/Publication: 2025-02-04 17:50:02 UTC

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New package MOsemiind with initial version 0.1.0
Package: MOsemiind
Title: Marshall-Olkin Shock Models with Semi-Independent Time
Version: 0.1.0
Description: Provides tools for analyzing Marshall-Olkin shock models semi-independent time. It includes interactive 'shiny' applications for exploring copula-based dependence structures, along with functions for modeling and visualization. The methods are based on Mijanovic and Popovic (2024, submitted) "An R package for Marshall-Olkin shock models with semi-independent times."
License: MIT + file LICENSE
Encoding: UTF-8
Imports: copula, graphics, pracma, shiny, stats
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2025-02-04 09:36:17 UTC; Andjela
Author: Andjela Mijanovic [aut, cre], Bozidar Popovic [aut]
Maintainer: Andjela Mijanovic <andjela.m@ucg.ac.me>
Repository: CRAN
Date/Publication: 2025-02-04 17:30:02 UTC

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New package kpiwidget with initial version 0.1.0
Package: kpiwidget
Title: KPI Widgets for Quarto Dashboards with Crosstalk
Version: 0.1.0
Description: Provides an easy way to create interactive KPI (key performance indicator) widgets for 'Quarto' dashboards using 'Crosstalk'. The package enables visualization of key metrics in a structured format, supporting interactive filtering and linking with other 'Crosstalk'-enabled components. Designed for use in 'Quarto' Dashboards.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: crosstalk, htmlwidgets
Suggests: dplyr, flexdashboard, htmltools, knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
URL: https://arnold-kakas.github.io/kpiwidget/, https://github.com/Arnold-Kakas/kpiwidget
BugReports: https://github.com/Arnold-Kakas/kpiwidget/issues
NeedsCompilation: no
Packaged: 2025-02-04 16:40:27 UTC; Arnold
Author: Arnold Kakas [aut, cre, cph]
Maintainer: Arnold Kakas <kakasarnold@gmail.com>
Repository: CRAN
Date/Publication: 2025-02-04 17:50:07 UTC

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Package gmoTree updated to version 1.4.0 with previous version 1.3.0 dated 2024-12-06

Title: Get and Modify 'oTree' Data
Description: Efficiently manage and process data from 'oTree' experiments. Import 'oTree' data and clean them by using functions that handle messy data, dropouts, and other problematic cases. Create IDs, calculate the time, transfer variables between app data frames, and delete sensitive information. Review your experimental data prior to running the experiment and automatically generate a detailed summary of the variables used in your 'oTree' code. Information on 'oTree' is found in Chen, D. L., Schonger, M., & Wickens, C. (2016) <doi:10.1016/j.jbef.2015.12.001>.
Author: Patricia F. Zauchner [aut, trl, cre, cph]
Maintainer: Patricia F. Zauchner <patricia.zauchner@gmx.at>

Diff between gmoTree versions 1.3.0 dated 2024-12-06 and 1.4.0 dated 2025-02-04

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 gmoTree-1.4.0/gmoTree/R/pagesec.R                                                                  |    7 
 gmoTree-1.4.0/gmoTree/R/show_constant.R                                                            |   19 
 gmoTree-1.4.0/gmoTree/R/show_dropouts.R                                                            |   12 
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 gmoTree-1.4.0/gmoTree/inst/CITATION                                                                |    4 
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 gmoTree-1.4.0/gmoTree/man/make_ids.Rd                                                              |   15 
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 gmoTree-1.4.0/gmoTree/man/messy_time.Rd                                                            |    4 
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Package ggbreak updated to version 0.1.4 with previous version 0.1.3 dated 2025-01-08

Title: Set Axis Break for 'ggplot2'
Description: An implementation of scale functions for setting axis breaks of a 'gg' plot (S Xu (2021) <doi:10.3389/fgene.2021.774846>).
Author: Guangchuang Yu [aut, cre, cph] , Shuangbin Xu [aut]
Maintainer: Guangchuang Yu <guangchuangyu@gmail.com>

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Package rollupTree updated to version 0.2.0 with previous version 0.1.0 dated 2025-01-20

Title: Perform Recursive Computations
Description: Mass rollup for a Bill of Materials is an example of a class of computations in which elements are arranged in a tree structure and some property of each element is a computed function of the corresponding values of its child elements. Leaf elements, i.e., those with no children, have values assigned. In many cases, the combining function is simple arithmetic sum; in other cases (e.g., mass properties), the combiner may involve other information such as the geometric relationship between parent and child, or statistical relations such as root-sum-of-squares (RSS). This package implements a general function for such problems. It is adapted to specific recursive computations by functional programming techniques; the caller passes a function as the update parameter to rollup() (or, at a lower level, passes functions as the get, set, combine, and override parameters to update_prop()) at runtime to specify the desired operations. The implementation relies on graph-theoretic algorithms from [...truncated...]
Author: James Steven Jenkins [aut, cre, cph]
Maintainer: James Steven Jenkins <sjenkins@studioj.us>

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Package joineRML updated to version 0.4.7 with previous version 0.4.6 dated 2023-01-19

Title: Joint Modelling of Multivariate Longitudinal Data and Time-to-Event Outcomes
Description: Fits the joint model proposed by Henderson and colleagues (2000) <doi:10.1093/biostatistics/1.4.465>, but extended to the case of multiple continuous longitudinal measures. The time-to-event data is modelled using a Cox proportional hazards regression model with time-varying covariates. The multiple longitudinal outcomes are modelled using a multivariate version of the Laird and Ware linear mixed model. The association is captured by a multivariate latent Gaussian process. The model is estimated using a Monte Carlo Expectation Maximization algorithm. This project was funded by the Medical Research Council (Grant number MR/M013227/1).
Author: Graeme L. Hickey [cre, aut] , Pete Philipson [aut] , Andrea Jorgensen [ctb] , Ruwanthi Kolamunnage-Dona [aut] , Paula Williamson [ctb] , Dimitris Rizopoulos [ctb, dtc] , Alessandro Gasparini [aut] , Medical Research Council [fnd]
Maintainer: Graeme L. Hickey <graemeleehickey@gmail.com>

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Package gstat updated to version 2.1-3 with previous version 2.1-2 dated 2024-09-05

Title: Spatial and Spatio-Temporal Geostatistical Modelling, Prediction and Simulation
Description: Variogram modelling; simple, ordinary and universal point or block (co)kriging; spatio-temporal kriging; sequential Gaussian or indicator (co)simulation; variogram and variogram map plotting utility functions; supports sf and stars.
Author: Edzer Pebesma [aut, cre] , Benedikt Graeler [aut]
Maintainer: Edzer Pebesma <edzer.pebesma@uni-muenster.de>

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Package fbnet updated to version 1.0.4 with previous version 1.0.3 dated 2023-07-01

Title: Forensic Bayesian Networks
Description: Open-source package for computing likelihood ratios in kinship testing and human identification cases. It has the core function of the software GENis, developed by Fundación Sadosky. It relies on a Bayesian Networks framework and is particularly well suited to efficiently perform large-size queries against databases of missing individuals.
Author: Franco Marsico [aut, cre], Ariel Chernomoretz [aut]
Maintainer: Franco Marsico <franco.lmarsico@gmail.com>

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Package RSAGA updated to version 1.4.2 with previous version 1.4.0 dated 2022-12-09

Title: SAGA Geoprocessing and Terrain Analysis
Description: Provides access to geocomputing and terrain analysis functions of the geographical information system (GIS) 'SAGA' (System for Automated Geoscientific Analyses) from within R by running the command line version of SAGA. This package furthermore provides several R functions for handling ASCII grids, including a flexible framework for applying local functions (including predict methods of fitted models) and focal functions to multiple grids. SAGA GIS is available under GPL-2 / LGPL-2 licences from <https://sourceforge.net/projects/saga-gis/>.
Author: Alexander Brenning [aut, cre] , Donovan Bangs [aut], Marc Becker [aut], Patrick Schratz [ctb] , Fabian Polakowski [ctb]
Maintainer: Alexander Brenning <alexander.brenning@uni-jena.de>

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Package forensIT updated to version 1.1.1 with previous version 1.0.0 dated 2023-06-22

Title: Information Theory Tools for Forensic Analysis
Description: The 'forensIT' package is a comprehensive statistical toolkit tailored for handling missing person cases. By leveraging information theory metrics, it enables accurate assessment of kinship, particularly when limited genetic evidence is available. With a focus on optimizing statistical power, 'forensIT' empowers investigators to effectively prioritize family members, enhancing the reliability and efficiency of missing person investigations.
Author: Franco Marsico [aut, cre], Ariel Chernomoretz [aut]
Maintainer: Franco Marsico <franco.lmarsico@gmail.com>

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Package BMisc updated to version 1.4.8 with previous version 1.4.7 dated 2025-01-10

Title: Miscellaneous Functions for Panel Data, Quantiles, and Printing Results
Description: These are miscellaneous functions for working with panel data, quantiles, and printing results. For panel data, the package includes functions for making a panel data balanced (that is, dropping missing individuals that have missing observations in any time period), converting id numbers to row numbers, and to treat repeated cross sections as panel data under the assumption of rank invariance. For quantiles, there are functions to make distribution functions from a set of data points (this is particularly useful when a distribution function is created in several steps), to combine distribution functions based on some external weights, and to invert distribution functions. Finally, there are several other miscellaneous functions for obtaining weighted means, weighted distribution functions, and weighted quantiles; to generate summary statistics and their differences for two groups; and to add or drop covariates from formulas.
Author: Brantly Callaway [aut, cre]
Maintainer: Brantly Callaway <brantly.callaway@uga.edu>

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Package ssifs updated to version 1.0.4 with previous version 1.0.2 dated 2023-05-12

Title: Stochastic Search Inconsistency Factor Selection
Description: Evaluating the consistency assumption of Network Meta-Analysis both globally and locally in the Bayesian framework. Inconsistencies are located by applying Bayesian variable selection to the inconsistency factors. The implementation of the method is described by Seitidis et al. (2023) <doi:10.1002/sim.9891>.
Author: Georgios Seitidis [aut, cre] , Stavros Nikolakopoulos [aut] , Ioannis Ntzoufras [aut] , Dimitris Mavridis [aut]
Maintainer: Georgios Seitidis <g.seitidis@uoi.gr>

Diff between ssifs versions 1.0.2 dated 2023-05-12 and 1.0.4 dated 2025-02-04

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Package netmeta updated to version 3.1-0 with previous version 3.0-2 dated 2025-01-22

Title: Network Meta-Analysis using Frequentist Methods
Description: A comprehensive set of functions providing frequentist methods for network meta-analysis (Balduzzi et al., 2023) <doi:10.18637/jss.v106.i02> and supporting Schwarzer et al. (2015) <doi:10.1007/978-3-319-21416-0>, Chapter 8 "Network Meta-Analysis": - frequentist network meta-analysis following Rücker (2012) <doi:10.1002/jrsm.1058>; - additive network meta-analysis for combinations of treatments (Rücker et al., 2020) <doi:10.1002/bimj.201800167>; - network meta-analysis of binary data using the Mantel-Haenszel or non-central hypergeometric distribution method (Efthimiou et al., 2019) <doi:10.1002/sim.8158>, or penalised logistic regression (Evrenoglou et al., 2022) <doi:10.1002/sim.9562>; - rankograms and ranking of treatments by the Surface under the cumulative ranking curve (SUCRA) (Salanti et al., 2013) <doi:10.1016/j.jclinepi.2010.03.016>; - ranking of treatments using P-scores (frequentist analogue of SUCRAs without resampling) according to [...truncated...]
Author: Gerta Ruecker [aut] , Ulrike Krahn [aut], Jochem Koenig [aut] , Orestis Efthimiou [aut] , Annabel Davies [aut] , Theodoros Papakonstantinou [aut] , Theodoros Evrenoglou [ctb] , Krzysztof Ciomek [ctb] , Guido Schwarzer [aut, cre]
Maintainer: Guido Schwarzer <guido.schwarzer@uniklinik-freiburg.de>

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Package HVT updated to version 25.2.1 with previous version 24.9.1 dated 2024-09-11

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

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Package RoBMA updated to version 3.4.0 with previous version 3.3.0 dated 2025-01-15

Title: Robust Bayesian Meta-Analyses
Description: A framework for estimating ensembles of meta-analytic and meta-regression models (assuming either presence or absence of the effect, heterogeneity, publication bias, and moderators). The RoBMA framework uses Bayesian model-averaging to combine the competing meta-analytic models into a model ensemble, weights the posterior parameter distributions based on posterior model probabilities and uses Bayes factors to test for the presence or absence of the individual components (e.g., effect vs. no effect; Bartoš et al., 2022, <doi:10.1002/jrsm.1594>; Maier, Bartoš & Wagenmakers, 2022, <doi:10.1037/met0000405>). Users can define a wide range of prior distributions for + the effect size, heterogeneity, publication bias (including selection models and PET-PEESE), and moderator components. The package provides convenient functions for summary, visualizations, and fit diagnostics.
Author: Frantisek Bartos [aut, cre] , Maximilian Maier [aut] , Eric-Jan Wagenmakers [ths] , Joris Goosen [ctb], Matthew Denwood [cph] , Martyn Plummer [cph]
Maintainer: Frantisek Bartos <f.bartos96@gmail.com>

Diff between RoBMA versions 3.3.0 dated 2025-01-15 and 3.4.0 dated 2025-02-04

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New package RFplus with initial version 1.2-2
Package: RFplus
Title: Progressive Bias Correction of Satellite Environmental Data
Version: 1.2-2
Encoding: UTF-8
Maintainer: Jonnathan Augusto Landi Bermeo <jonnathan.landi@outlook.com>
Description: Implements a bias correction method that combines Random Forest models with Quantile Mapping to improve the accuracy of satellite-derived environmental datasets. The model corrects biases in meteorological variables, such as precipitation and temperature, by integrating in situ measurements and a Digital Elevation Model (DEM).
License: GPL (>= 3)
Depends: R (>= 4.4.0)
Imports: terra, randomForest, data.table, dplyr, pbapply, qmap
URL: https://github.com/Jonnathan-Landi/RFplus
BugReports: https://github.com/Jonnathan-Landi/RFplus/issues
NeedsCompilation: no
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
Packaged: 2025-02-03 23:36:34 UTC; Jonna
Author: Jonnathan Augusto Landi Bermeo [aut, cre, cph]
Repository: CRAN
Date/Publication: 2025-02-04 09:10:02 UTC

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Package maptiles updated to version 0.9.0 with previous version 0.8.0 dated 2024-10-22

Title: Download and Display Map Tiles
Description: To create maps from tiles, 'maptiles' downloads, composes and displays tiles from a large number of providers (e.g. 'OpenStreetMap', 'Stadia', 'Esri', 'CARTO', or 'Thunderforest').
Author: Timothee Giraud [cre, aut] , Diego Hernangomez [ctb] , Robert J. Hijmans [ctb] , Hugh A. Graham [ctb]
Maintainer: Timothee Giraud <timothee.giraud@cnrs.fr>

Diff between maptiles versions 0.8.0 dated 2024-10-22 and 0.9.0 dated 2025-02-04

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Package primes updated to version 1.6.1 with previous version 1.6.0 dated 2024-01-08

Title: Fast Functions for Prime Numbers
Description: Fast functions for dealing with prime numbers, such as testing whether a number is prime and generating a sequence prime numbers. Additional functions include finding prime factors and Ruth-Aaron pairs, finding next and previous prime numbers in the series, finding or estimating the nth prime, estimating the number of primes less than or equal to an arbitrary number, computing primorials, prime k-tuples (e.g., twin primes), finding the greatest common divisor and smallest (least) common multiple, testing whether two numbers are coprime, and computing Euler's totient function. Most functions are vectorized for speed and convenience.
Author: Os Keyes [aut], Paul Egeler [aut, cre]
Maintainer: Paul Egeler <paulegeler@gmail.com>

Diff between primes versions 1.6.0 dated 2024-01-08 and 1.6.1 dated 2025-02-04

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New package nlpembeds with initial version 1.0.0
Package: nlpembeds
Title: Natural Language Processing Embeddings
Version: 1.0.0
Description: Provides efficient methods to compute co-occurrence matrices, pointwise mutual information (PMI) and singular value decomposition (SVD). In the biomedical and clinical settings, one challenge is the huge size of databases, e.g. when analyzing data of millions of patients over tens of years. To address this, this package provides functions to efficiently compute monthly co-occurrence matrices, which is the computational bottleneck of the analysis, by using the 'RcppAlgos' package and sparse matrices. Furthermore, the functions can be called on 'SQL' databases, enabling the computation of co-occurrence matrices of tens of gigabytes of data, representing millions of patients over tens of years. Partly based on Hong C. (2021) <doi:10.1038/s41746-021-00519-z>.
Imports: data.table, magrittr, Matrix, methods, parallel, RcppAlgos, reshape2, RSQLite, rsvd
Depends: R (>= 3.5.0)
Suggests: knitr, testthat
VignetteBuilder: knitr
License: GPL-3
Encoding: UTF-8
URL: https://gitlab.com/thomaschln/nlpembeds
BugReports: https://gitlab.com/thomaschln/nlpembeds/-/issues
NeedsCompilation: no
Packaged: 2025-02-03 20:02:33 UTC; root
Author: Thomas Charlon [aut, cre] , Doudou Zhou [ctb] , CELEHS [aut]
Maintainer: Thomas Charlon <charlon@protonmail.com>
Repository: CRAN
Date/Publication: 2025-02-04 08:30:01 UTC

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New package fastQR with initial version 1.0.0
Package: fastQR
Title: Fast QR Decomposition and Update
Version: 1.0.0
Date: 2025-01-25
Author: Mauro Bernardi [aut, cre], Claudio Busatto [aut], Manuela Cattelan [aut]
Maintainer: Mauro Bernardi <mauro.bernardi@unipd.it>
Description: Efficient algorithms for performing, updating, and downdating the QR decomposition, R decomposition, or the inverse of the R decomposition of a matrix as rows or columns are added or removed. It also includes functions for solving linear systems of equations, normal equations for linear regression models, and normal equations for linear regression with a RIDGE penalty. For a detailed introduction to these methods, see the book by Golub and Van Loan (2013, <doi:10.1007/978-3-319-05089-8>) for complete introduction to the methods.
License: GPL (>= 2)
Imports: Rcpp (>= 1.0.10), RcppEigen, Rdpack
LinkingTo: Rcpp, RcppArmadillo, RcppEigen
Encoding: UTF-8
SystemRequirements: GNU make
NeedsCompilation: yes
Packaged: 2025-02-03 22:19:19 UTC; maurobernardi
Repository: CRAN
Date/Publication: 2025-02-04 08:40:01 UTC

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Package singleRcapture updated to version 0.2.2 with previous version 0.2.1.4 dated 2025-01-07

Title: Single-Source Capture-Recapture Models
Description: Implementation of single-source capture-recapture methods for population size estimation using zero-truncated, zero-one truncated and zero-truncated one-inflated Poisson, Geometric and Negative Binomial regression as well as Zelterman's and Chao's regression. Package includes point and interval estimators for the population size with variances estimated using analytical or bootstrap method. Details can be found in: van der Heijden et all. (2003) <doi:10.1191/1471082X03st057oa>, Böhning and van der Heijden (2019) <doi:10.1214/18-AOAS1232>, Böhning et al. (2020) Capture-Recapture Methods for the Social and Medical Sciences or Böhning and Friedl (2021) <doi:10.1007/s10260-021-00556-8>.
Author: Piotr Chlebicki [aut, ctb] , Maciej Beresewicz [aut, cre]
Maintainer: Maciej Beresewicz <maciej.beresewicz@ue.poznan.pl>

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 singleRcapture-0.2.2/singleRcapture/R/oiztnegbin.R                           |   18 -
 singleRcapture-0.2.2/singleRcapture/R/oiztpoisson.R                          |   17 -
 singleRcapture-0.2.2/singleRcapture/R/parametricBootstrap.R                  |    8 
 singleRcapture-0.2.2/singleRcapture/R/plots.R                                |   63 +---
 singleRcapture-0.2.2/singleRcapture/R/predict.R                              |    2 
 singleRcapture-0.2.2/singleRcapture/R/sandwichMethods.R                      |   23 +
 singleRcapture-0.2.2/singleRcapture/R/semiparametricBootstrap.R              |    3 
 singleRcapture-0.2.2/singleRcapture/R/simulate.R                             |    1 
 singleRcapture-0.2.2/singleRcapture/R/smallMethods.R                         |    9 
 singleRcapture-0.2.2/singleRcapture/R/strataEstimation.R                     |   19 -
 singleRcapture-0.2.2/singleRcapture/R/summary.R                              |    4 
 singleRcapture-0.2.2/singleRcapture/R/updates.R                              |    3 
 singleRcapture-0.2.2/singleRcapture/R/zelterman.R                            |   10 
 singleRcapture-0.2.2/singleRcapture/R/zotgeom.R                              |    7 
 singleRcapture-0.2.2/singleRcapture/R/zotnegbin.R                            |   39 +-
 singleRcapture-0.2.2/singleRcapture/R/zotpoisson.R                           |   16 -
 singleRcapture-0.2.2/singleRcapture/R/ztHurdlegeom.R                         |   24 +
 singleRcapture-0.2.2/singleRcapture/R/ztHurdlenegbin.R                       |   29 --
 singleRcapture-0.2.2/singleRcapture/R/ztHurdlepoisson.R                      |   32 +-
 singleRcapture-0.2.2/singleRcapture/R/ztgeom.R                               |   15 -
 singleRcapture-0.2.2/singleRcapture/R/ztnegbin.R                             |   84 +-----
 singleRcapture-0.2.2/singleRcapture/R/ztoigeom.R                             |   26 -
 singleRcapture-0.2.2/singleRcapture/R/ztoinegbin.R                           |   18 -
 singleRcapture-0.2.2/singleRcapture/R/ztoipoisson.R                          |   33 +-
 singleRcapture-0.2.2/singleRcapture/R/ztpoisson.R                            |    8 
 singleRcapture-0.2.2/singleRcapture/README.md                                |   67 ++---
 singleRcapture-0.2.2/singleRcapture/build/singleRcapture.pdf                 |binary
 singleRcapture-0.2.2/singleRcapture/build/stage23.rdb                        |binary
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 singleRcapture-0.2.2/singleRcapture/inst/doc                                 |only
 singleRcapture-0.2.2/singleRcapture/inst/tinytest/test_developer_only.R      |    1 
 singleRcapture-0.2.2/singleRcapture/inst/tinytest/test_inflated_hurdle.R     |    2 
 singleRcapture-0.2.2/singleRcapture/inst/tinytest/test_singleRcapture.R      |    1 
 singleRcapture-0.2.2/singleRcapture/inst/tinytest/test_zerotruncated.R       |    1 
 singleRcapture-0.2.2/singleRcapture/man/estimatePopsize.Rd                   |    2 
 singleRcapture-0.2.2/singleRcapture/man/estimatePopsizeFit.Rd                |    2 
 singleRcapture-0.2.2/singleRcapture/man/figures/README-plot-example-1.png    |only
 singleRcapture-0.2.2/singleRcapture/man/figures/README-plot-inflated-1.png   |only
 singleRcapture-0.2.2/singleRcapture/man/figures/README-unnamed-chunk-5-1.png |binary
 singleRcapture-0.2.2/singleRcapture/man/marginalFreq.Rd                      |    2 
 singleRcapture-0.2.2/singleRcapture/man/netherlandsimmigrant.Rd              |    2 
 singleRcapture-0.2.2/singleRcapture/man/plot.singleRStaticCountData.Rd       |    4 
 singleRcapture-0.2.2/singleRcapture/man/popSizeEst.Rd                        |    2 
 singleRcapture-0.2.2/singleRcapture/man/predict.singleRStaticCountData.Rd    |    5 
 singleRcapture-0.2.2/singleRcapture/man/redoPopEstimation.Rd                 |    2 
 singleRcapture-0.2.2/singleRcapture/man/summary.singleRmargin.Rd             |    2 
 singleRcapture-0.2.2/singleRcapture/man/vcov.singleRStaticCountData.Rd       |    2 
 singleRcapture-0.2.2/singleRcapture/man/vcovHC.singleRStaticCountData.Rd     |    2 
 singleRcapture-0.2.2/singleRcapture/vignettes                                |only
 69 files changed, 563 insertions(+), 834 deletions(-)

More information about singleRcapture at CRAN
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