Mon, 09 Sep 2024

Package unmconf updated to version 1.0.0 with previous version 0.1.0 dated 2023-12-12

Title: Modeling with Unmeasured Confounding
Description: Tools for fitting and assessing Bayesian multilevel regression models that account for unmeasured confounders.
Author: Ryan Hebdon [aut], James Stamey [aut] , David Kahle [aut, cre] , Xiang Zhang [aut]
Maintainer: David Kahle <david@kahle.io>

Diff between unmconf versions 0.1.0 dated 2023-12-12 and 1.0.0 dated 2024-09-09

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Package bigstatsr updated to version 1.6.1 with previous version 1.5.12 dated 2022-10-14

Title: Statistical Tools for Filebacked Big Matrices
Description: Easy-to-use, efficient, flexible and scalable statistical tools. Package bigstatsr provides and uses Filebacked Big Matrices via memory-mapping. It provides for instance matrix operations, Principal Component Analysis, sparse linear supervised models, utility functions and more <doi:10.1093/bioinformatics/bty185>.
Author: Florian Prive [aut, cre], Michael Blum [ths], Hugues Aschard [ths]
Maintainer: Florian Prive <florian.prive.21@gmail.com>

Diff between bigstatsr versions 1.5.12 dated 2022-10-14 and 1.6.1 dated 2024-09-09

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Package ageutils updated to version 0.0.5 with previous version 0.0.4 dated 2024-06-26

Title: Collection of Functions for Working with Age Intervals
Description: Provides a collection of efficient functions for working with individual ages and corresponding intervals. These include functions for conversion from an age to an interval, aggregation of ages with associated counts in to intervals and the splitting of interval counts based on specified age distributions.
Author: Tim Taylor [aut, cre, cph] , Edwin van Leeuwen [aut]
Maintainer: Tim Taylor <tim.taylor@hiddenelephants.co.uk>

Diff between ageutils versions 0.0.4 dated 2024-06-26 and 0.0.5 dated 2024-09-09

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Package CoImp updated to version 2.0.1 with previous version 2.0.0 dated 2024-05-09

Title: Parametric and Non-Parametric Copula-Based Imputation Methods
Description: Copula-based imputation methods: parametric and non-parametric algorithms for missing multivariate data through conditional copulas.
Author: Francesca Marta Lilja Di Lascio [aut, cre], Aurora Gatto [aut], Simone Giannerini [aut]
Maintainer: Francesca Marta Lilja Di Lascio <marta.dilascio@unibz.it>

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Package snplinkage updated to version 1.2.0 with previous version 1.0.0 dated 2023-05-04

Title: Single Nucleotide Polymorphisms Linkage Disequilibrium Visualizations
Description: Linkage disequilibrium visualizations of up to several hundreds of single nucleotide polymorphisms (SNPs), annotated with chromosomic positions and gene names. Two types of plots are available for small numbers of SNPs (<40) and for large numbers (tested up to 500). Both can be extended by combining other ggplots, e.g. association studies results, and functions enable to directly visualize the effect of SNP selection methods, as minor allele frequency filtering and TagSNP selection, with a second correlation heatmap. The SNPs correlations are computed on Genotype Data objects from the 'GWASTools' package using the 'SNPRelate' package, and the plots are customizable 'ggplot2' and 'gtable' objects and are annotated using the 'biomaRt' package. Usage is detailed in the vignette with example data and results from up to 500 SNPs of 1,200 scans are in Charlon T. (2019) <doi:10.13097/archive-ouverte/unige:161795>.
Author: Thomas Charlon [aut, cre] , Karl Forner [aut], Alessandro Di Cara [aut], Jerome Wojcik [aut]
Maintainer: Thomas Charlon <charlon@protonmail.com>

Diff between snplinkage versions 1.0.0 dated 2023-05-04 and 1.2.0 dated 2024-09-09

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Package LMest updated to version 3.2.1 with previous version 3.2.0 dated 2024-08-30

Title: Generalized Latent Markov Models
Description: Latent Markov models for longitudinal continuous and categorical data. See Bartolucci, Pandolfi, Pennoni (2017)<doi:10.18637/jss.v081.i04>.
Author: Francesco Bartolucci [aut, cre], Silvia Pandolfi [aut], Fulvia Pennoni [aut], Alessio Farcomeni [ctb], Alessio Serafini [ctb]
Maintainer: Francesco Bartolucci <francesco.bartolucci@unipg.it>

Diff between LMest versions 3.2.0 dated 2024-08-30 and 3.2.1 dated 2024-09-09

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Package TMB updated to version 1.9.15 with previous version 1.9.14 dated 2024-07-03

Title: Template Model Builder: A General Random Effect Tool Inspired by 'ADMB'
Description: With this tool, a user should be able to quickly implement complex random effect models through simple C++ templates. The package combines 'CppAD' (C++ automatic differentiation), 'Eigen' (templated matrix-vector library) and 'CHOLMOD' (sparse matrix routines available from R) to obtain an efficient implementation of the applied Laplace approximation with exact derivatives. Key features are: Automatic sparseness detection, parallelism through 'BLAS' and parallel user templates.
Author: Kasper Kristensen [aut, cre, cph], Brad Bell [cph], Hans Skaug [ctb], Arni Magnusson [ctb], Casper Berg [ctb], Anders Nielsen [ctb], Martin Maechler [ctb], Theo Michelot [ctb], Mollie Brooks [ctb], Alex Forrence [ctb], Christoffer Moesgaard Albertsen [...truncated...]
Maintainer: Kasper Kristensen <kaskr@dtu.dk>

Diff between TMB versions 1.9.14 dated 2024-07-03 and 1.9.15 dated 2024-09-09

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Package survAUC updated to version 1.3-0 with previous version 1.2-0 dated 2023-03-21

Title: Estimators of Prediction Accuracy for Time-to-Event Data
Description: Provides a variety of functions to estimate time-dependent true/false positive rates and AUC curves from a set of censored survival data.
Author: Sergej Potapov [aut], Werner Adler [aut], Matthias Schmid [aut], Frederic Bertrand [cre, aut]
Maintainer: Frederic Bertrand <frederic.bertrand@utt.fr>

Diff between survAUC versions 1.2-0 dated 2023-03-21 and 1.3-0 dated 2024-09-09

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Package spTDyn updated to version 2.0.3 with previous version 2.0.2 dated 2022-11-22

Title: Spatially Varying and Spatio-Temporal Dynamic Linear Models
Description: Fits, spatially predicts, and temporally forecasts space-time data using Gaussian Process (GP): (1) spatially varying coefficient process models and (2) spatio-temporal dynamic linear models. Bakar et al., (2016). Bakar et al., (2015).
Author: K. Shuvo Bakar [aut, cre] , Philip Kokic [ctb], Huidong Jin [ctb]
Maintainer: K. Shuvo Bakar <shuvo.bakar@gmail.com>

Diff between spTDyn versions 2.0.2 dated 2022-11-22 and 2.0.3 dated 2024-09-09

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Package secretbase updated to version 1.0.2 with previous version 1.0.1 dated 2024-07-22

Title: Cryptographic Hash, Extendable-Output and Base64 Functions
Description: Fast and memory-efficient streaming hash functions and base64 encoding / decoding. Hashes strings and raw vectors directly. Stream hashes files potentially larger than memory, as well as in-memory objects through R's serialization mechanism. Implementations include the SHA-256, SHA-3 and 'Keccak' cryptographic hash functions, SHAKE256 extendable-output function (XOF), and 'SipHash' pseudo-random function.
Author: Charlie Gao [aut, cre] , Hibiki AI Limited [cph]
Maintainer: Charlie Gao <charlie.gao@shikokuchuo.net>

Diff between secretbase versions 1.0.1 dated 2024-07-22 and 1.0.2 dated 2024-09-09

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Package rshift updated to version 3.1.1 with previous version 3.1.0 dated 2024-09-03

Title: Paleoecology Functions for Regime Shift Analysis
Description: Contains a variety of functions, based around regime shift analysis of paleoecological data. Citations: Rodionov() from Rodionov (2004) <doi:10.1029/2004GL019448> Lanzante() from Lanzante (1996) <doi:10.1002/(SICI)1097-0088(199611)16:11%3C1197::AID-JOC89%3E3.0.CO;2-L> Hellinger_trans from Numerical Ecology, Legendre & Legendre (ISBN 9780444538680) rolling_autoc from Liu, Gao & Wang (2018) <doi:10.1016/j.scitotenv.2018.06.276> Sample data sets lake_data & lake_RSI processed from Bush, Silman & Urrego (2004) <doi:10.1126/science.1090795> Sample data set January_PDO from NOAA: <https://www.ncei.noaa.gov/access/monitoring/pdo/>.
Author: Alex H. Room [aut, cre, cph] , Felipe Franco-Gaviria [ctb, fnd] , Dunia H. Urrego [ctb, fnd] , The authors of the dependency Rust crates [ctb]
Maintainer: Alex H. Room <alexhroom+cran@protonmail.com>

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Package mlr3fselect updated to version 1.1.0 with previous version 1.0.0 dated 2024-06-29

Title: Feature Selection for 'mlr3'
Description: Feature selection package of the 'mlr3' ecosystem. It selects the optimal feature set for any 'mlr3' learner. The package works with several optimization algorithms e.g. Random Search, Recursive Feature Elimination, and Genetic Search. Moreover, it can automatically optimize learners and estimate the performance of optimized feature sets with nested resampling.
Author: Marc Becker [aut, cre] , Patrick Schratz [aut] , Michel Lang [aut] , Bernd Bischl [aut] , John Zobolas [aut]
Maintainer: Marc Becker <marcbecker@posteo.de>

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Package dvir updated to version 3.3.0 with previous version 3.2.1 dated 2023-10-15

Title: Disaster Victim Identification
Description: Joint DNA-based disaster victim identification (DVI), as described in Vigeland and Egeland (2021) <doi:10.21203/rs.3.rs-296414/v1>. Identification is performed by optimising the joint likelihood of all victim samples and reference individuals. Individual identification probabilities, conditional on all available information, are derived from the joint solution in the form of posterior pairing probabilities. 'dvir' is part of the 'pedsuite' collection of packages for pedigree analysis.
Author: Magnus Dehli Vigeland [aut, cre] , Thore Egeland [aut]
Maintainer: Magnus Dehli Vigeland <m.d.vigeland@medisin.uio.no>

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Package Directional updated to version 6.8 with previous version 6.7 dated 2024-07-05

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) Phillip J. Paine, Simon P. Preston Michail Tsagris and Andrew T. A. Wood (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) P. J. Paine, S. P. Preston, M. Tsagris and Andrew T. A. Wood (2020). "Spherical regression models with general covariates and anisotropic errors". Statistics and Computing 30(1): 153--165. <d [...truncated...]
Author: Michail Tsagris [aut, cre], Giorgos Athineou [aut], Christos Adam [aut], Anamul Sajib [ctb], Eli Amson [ctb], Micah J. Waldstein [ctb], Zehao Yu [aut]
Maintainer: Michail Tsagris <mtsagris@uoc.gr>

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Package billboarder updated to version 0.5.0 with previous version 0.4.1 dated 2023-09-29

Title: Create Interactive Chart with the JavaScript 'Billboard' Library
Description: Provides an 'htmlwidgets' interface to 'billboard.js', a re-usable easy interface JavaScript chart library, based on D3 v4+. Chart types include line charts, scatterplots, bar/lollipop charts, histogram/density plots, pie/donut charts and gauge charts. All charts are interactive, and a proxy method is implemented to smoothly update a chart without rendering it again in 'shiny' apps.
Author: Victor Perrier [aut, cre], Fanny Meyer [aut], NAVER Corp [cph] , Mike Bostock [cph]
Maintainer: Victor Perrier <victor.perrier@dreamrs.fr>

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Package bbotk updated to version 1.1.0 with previous version 1.0.1 dated 2024-07-24

Title: Black-Box Optimization Toolkit
Description: Features highly configurable search spaces via the 'paradox' package and optimizes every user-defined objective function. The package includes several optimization algorithms e.g. Random Search, Iterated Racing, Bayesian Optimization (in 'mlr3mbo') and Hyperband (in 'mlr3hyperband'). bbotk is the base package of 'mlr3tuning', 'mlr3fselect' and 'miesmuschel'.
Author: Marc Becker [cre, aut] , Jakob Richter [aut] , Michel Lang [aut] , Bernd Bischl [aut] , Martin Binder [aut], Olaf Mersmann [ctb]
Maintainer: Marc Becker <marcbecker@posteo.de>

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Package florabr updated to version 1.3.0 with previous version 1.2.0 dated 2024-05-16

Title: Explore Flora e Funga do Brasil Database
Description: A collection of functions designed to retrieve, filter and spatialize data from the Flora e Funga do Brasil dataset. For more information about the dataset, please visit <https://floradobrasil.jbrj.gov.br/consulta/>.
Author: Weverton Trindade [aut, cre]
Maintainer: Weverton Trindade <wevertonf1993@gmail.com>

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Package negligible updated to version 0.1.9 with previous version 0.1.7 dated 2024-04-30

Title: A Collection of Functions for Negligible Effect/Equivalence Testing
Description: Researchers often want to evaluate whether there is a negligible relationship among variables. The 'negligible' package provides functions that are useful for conducting negligible effect testing (also called equivalence testing). For example, there are functions for evaluating the equivalence of means or the presence of a negligible association (correlation or regression). Beribisky, N., Mara, C., & Cribbie, R. A. (2020) <doi:10.20982/tqmp.16.4.p424>. Beribisky, N., Davidson, H., Cribbie, R. A. (2019) <doi:10.7717/peerj.6853>. Shiskina, T., Farmus, L., & Cribbie, R. A. (2018) <doi:10.20982/tqmp.14.3.p167>. Mara, C. & Cribbie, R. A. (2017) <doi:10.1080/00220973.2017.1301356>. Counsell, A. & Cribbie, R. A. (2015) <doi:10.1111/bmsp.12045>. van Wieringen, K. & Cribbie, R. A. (2014) <doi:10.1111/bmsp.12015>. Goertzen, J. R. & Cribbie, R. A. (2010) <doi:10.1348/000711009x475853>. Cribbie, R. A., Gruman, J. & Arpin-Cribbi [...truncated...]
Author: Robert Cribbie [aut, cre], Udi Alter [aut], Nataly Beribisky [aut], Phil Chalmers [aut], Alyssa Counsell [aut], Linda Farmus [aut], Naomi Martinez Gutierrez [aut], Victoria Ng [ctb]
Maintainer: Robert Cribbie <cribbie@yorku.ca>

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Package MethEvolSIM updated to version 0.1.6 with previous version 0.1.5 dated 2024-08-16

Title: Simulate DNA Methylation Dynamics on Different Genomic Structures along Genealogies
Description: DNA methylation is an epigenetic modification involved in genomic stability, gene regulation, development and disease. DNA methylation occurs mainly through the addition of a methyl group to cytosines, for example to cytosines in a CpG dinucleotide context (CpG stands for a cytosine followed by a guanine). Tissue-specific methylation patterns lead to genomic regions with different characteristic methylation levels. E.g. in vertebrates CpG islands (regions with high CpG content) that are associated to promoter regions of expressed genes tend to be unmethylated. 'MethEvolSIM' is a model-based simulation software for the generation and modification of cytosine methylation patterns along a given tree, which can be a genealogy of cells within an organism, a coalescent tree of DNA sequences sampled from a population, or a species tree. The simulations are based on an extension of the model of Grosser & Metzler (2020) <doi:10.1186/s12859-020-3438-5> and allows for changes of the met [...truncated...]
Author: Sara Castillo Vicente [aut, cre], Dirk Metzler [aut, ths]
Maintainer: Sara Castillo Vicente <castillo@bio.lmu.de>

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Package ElliptCopulas updated to version 0.1.4.1 with previous version 0.1.3 dated 2022-04-25

Title: Inference of Elliptical Distributions and Copulas
Description: Provides functions for the simulation and the nonparametric estimation of elliptical distributions, meta-elliptical copulas and trans-elliptical distributions, following the article Derumigny and Fermanian (2022) <doi:10.1016/j.jmva.2022.104962>.
Author: Alexis Derumigny [aut, cre] , Jean-David Fermanian [aut] , Victor Ryan [aut], Rutger van der Spek [ctb]
Maintainer: Alexis Derumigny <a.f.f.derumigny@tudelft.nl>

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Package TrialEmulation updated to version 0.0.3.9 with previous version 0.0.3.8 dated 2024-01-24

Title: Causal Analysis of Observational Time-to-Event Data
Description: Implements target trial emulation methods to apply randomized clinical trial design and analysis in an observational setting. Using marginal structural models, it can estimate intention-to-treat and per-protocol effects in emulated trials using electronic health records. A description and application of the method can be found in Danaei et al (2013) <doi:10.1177/0962280211403603>.
Author: Roonak Rezvani [aut] , Isaac Gravestock [aut, cre] , Li Su [aut], Medical Research Council [fnd], F. Hoffmann-La Roche AG [cph, fnd]
Maintainer: Isaac Gravestock <isaac.gravestock@roche.com>

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New package tidytuesdayR with initial version 1.1.2
Package: tidytuesdayR
Title: Access the Weekly 'TidyTuesday' Project Dataset
Version: 1.1.2
Description: 'TidyTuesday' is a project by the 'Data Science Learning Community' in which they post a weekly dataset in a public data repository (<https://github.com/rfordatascience/tidytuesday>) for people to analyze and visualize. This package provides the tools to easily download this data and the description of the source.
License: MIT + file LICENSE
URL: https://dslc-io.github.io/tidytuesdayR/, https://github.com/dslc-io/tidytuesdayR
BugReports: https://github.com/dslc-io/tidytuesdayR/issues
Depends: R (>= 3.5.0)
Imports: cli, gh, glue, jsonlite, lubridate (>= 1.7.0), magrittr, purrr (>= 1.0.0), readr (>= 1.0.0), rlang, rvest (>= 0.3.2), tidyr, tools (>= 3.1.0), usethis, xml2 (>= 1.2.0)
Suggests: covr, pkgdown, readxl (>= 1.0.0), rstudioapi (>= 0.2), stringr, testthat (>= 3.0.0), tibble, withr
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2024-09-09 12:00:57 UTC; jonth
Author: Jon Harmon [aut, cre] , Ellis Hughes [aut], Thomas Mock [ctb], Data Science Learning Community [dtc]
Maintainer: Jon Harmon <jonthegeek@gmail.com>
Repository: CRAN
Date/Publication: 2024-09-09 12:40:03 UTC

More information about tidytuesdayR at CRAN
Permanent link

Package psvmSDR updated to version 1.0.2 with previous version 1.0.1 dated 2024-08-30

Title: Unified Principal Sufficient Dimension Reduction Package
Description: A unified and user-friendly framework for applying the principal sufficient dimension reduction methods for both linear and nonlinear cases. The package has an extendable power by varying loss functions for the support vector machine, even for an user-defined arbitrary function, unless those are convex and differentiable everywhere over the support (Li et al. (2011) <doi:10.1214/11-AOS932>). Also, it provides a real-time sufficient dimension reduction update procedure using the principal least squares support vector machine (Artemiou et al. (2021) <doi:10.1016/j.patcog.2020.107768>).
Author: Jungmin Shin [aut, cre], Seung Jun Shin [aut], Andreas Artemiou [aut]
Maintainer: Jungmin Shin <jungminshin@korea.ac.kr>

Diff between psvmSDR versions 1.0.1 dated 2024-08-30 and 1.0.2 dated 2024-09-09

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 psvmSDR-1.0.2/psvmSDR/R/psvmSDR-package.R |    2 +-
 psvmSDR-1.0.2/psvmSDR/man/npsdr.Rd        |    2 +-
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 9 files changed, 18 insertions(+), 19 deletions(-)

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Permanent link

Package wINEQ updated to version 1.2.1 with previous version 1.2.0 dated 2023-04-21

Title: Inequality Measures for Weighted Data
Description: Computes inequality measures of a given variable taking into account weights. Suitable for ratio, interval and ordered scale. Includes Gini, Theil, Leti index, Palma ratio, 20:20 ratio, Allison and Foster index, Jenkins index, Cowell and Flechaire index, Abul Naga and Yalcin index, Apouey index, Blair and Lacy index. Bootstrap provides distribution of inequality measures enabling significance tests.
Author: Sebastian Wojcik [aut, cre] , Agnieszka Giemza [aut], Katarzyna Machowska [aut], Jaroslaw Napora [aut]
Maintainer: Sebastian Wojcik <S.Wojcik@stat.gov.pl>

Diff between wINEQ versions 1.2.0 dated 2023-04-21 and 1.2.1 dated 2024-09-09

 DESCRIPTION               |   10 -
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 NAMESPACE                 |    2 
 NEWS.md                   |   28 ++++
 R/inequalityMeasure.R     |  276 ++++++++++++++++++++++++++++++----------------
 R/inequalityMeasureBoot.R |   26 ++--
 data/Tourism.rda          |binary
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More information about wINEQ at CRAN
Permanent link

New package mwcsr with initial version 0.1.9
Package: mwcsr
Title: Solvers for Maximum Weight Connected Subgraph Problem and Its Variants
Version: 0.1.9
Description: Algorithms for solving various Maximum Weight Connected Subgraph Problems, including variants with budget constraints, cardinality constraints, weighted edges and signals. The package represents an R interface to high-efficient solvers based on relax-and-cut approach (Álvarez-Miranda E., Sinnl M. (2017) <doi:10.1016/j.cor.2017.05.015>) mixed-integer programming (Loboda A., Artyomov M., and Sergushichev A. (2016) <doi:10.1007/978-3-319-43681-4_17>) and simulated annealing.
Depends: R (>= 3.5)
Imports: methods, igraph, Rcpp
Suggests: knitr, rmarkdown, mathjaxr, testthat, BioNet, roxygen2, DLBCL
SystemRequirements: Java (>=8)
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
VignetteBuilder: knitr
URL: https://github.com/ctlab/mwcsr
BugReports: https://github.com/ctlab/mwcsr/issues
LinkingTo: Rcpp
NeedsCompilation: yes
Packaged: 2024-09-08 19:27:21 UTC; aloboda
Author: Alexander Loboda [aut, cre], Nikolay Poperechnyi [aut], Eduardo Alvarez-Miranda [aut], Markus Sinnl [aut], Alexey Sergushichev [aut], Paul Hosler Jr. [cph] , www.hamcrest.org [cph] , Barak Naveh and Contributors [cph] , The Apache Software Foundation [...truncated...]
Maintainer: Alexander Loboda <aleks.loboda@gmail.com>
Repository: CRAN
Date/Publication: 2024-09-09 11:30:10 UTC

More information about mwcsr at CRAN
Permanent link

Package LorenzRegression updated to version 2.0.0 with previous version 1.0.0 dated 2023-02-28

Title: Lorenz and Penalized Lorenz Regressions
Description: Inference for the Lorenz and penalized Lorenz regressions. More broadly, the package proposes functions to assess inequality and graphically represent it. The Lorenz Regression procedure is introduced in Heuchenne and Jacquemain (2022) <doi:10.1016/j.csda.2021.107347> and in Jacquemain, A., C. Heuchenne, and E. Pircalabelu (2024) <doi:10.1214/23-EJS2200>.
Author: Alexandre Jacquemain [aut, cre] , Xingjie Shi [ctb]
Maintainer: Alexandre Jacquemain <aljacquemain@gmail.com>

Diff between LorenzRegression versions 1.0.0 dated 2023-02-28 and 2.0.0 dated 2024-09-09

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 96 files changed, 3445 insertions(+), 3028 deletions(-)

More information about LorenzRegression at CRAN
Permanent link

Package aggTrees updated to version 2.1.0 with previous version 2.0.2 dated 2023-09-20

Title: Aggregation Trees
Description: Nonparametric data-driven approach to discovering heterogeneous subgroups in a selection-on-observables framework. 'aggTrees' allows researchers to assess whether there exists relevant heterogeneity in treatment effects by generating a sequence of optimal groupings, one for each level of granularity. For each grouping, we obtain point estimation and inference about the group average treatment effects. Please reference the use as Di Francesco (2022) <doi:10.2139/ssrn.4304256>.
Author: Riccardo Di Francesco [aut, cre, cph]
Maintainer: Riccardo Di Francesco <difrancesco.riccardo96@gmail.com>

Diff between aggTrees versions 2.0.2 dated 2023-09-20 and 2.1.0 dated 2024-09-09

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Package geepack updated to version 1.3.11.1 with previous version 1.3.11 dated 2024-06-06

Title: Generalized Estimating Equation Package
Description: Generalized estimating equations solver for parameters in mean, scale, and correlation structures, through mean link, scale link, and correlation link. Can also handle clustered categorical responses. See e.g. Halekoh and Højsgaard, (2005, <doi:10.18637/jss.v015.i02>), for details.
Author: Soeren Hoejsgaard [aut, cre, cph], Ulrich Halekoh [aut, cph], Jun Yan [aut, cph], Claus Thorn Ekstroem [ctb], CRAN Team [ctb]
Maintainer: Soeren Hoejsgaard <sorenh@math.aau.dk>

Diff between geepack versions 1.3.11 dated 2024-06-06 and 1.3.11.1 dated 2024-09-09

 DESCRIPTION                 |   14 ++++++++------
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 12 files changed, 34 insertions(+), 32 deletions(-)

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Package BREADR updated to version 1.0.2 with previous version 1.0.1 dated 2023-04-12

Title: Estimates Degrees of Relatedness (Up to the Second Degree) for Extreme Low-Coverage Data
Description: The goal of the package is to provide an easy-to-use method for estimating degrees of relatedness (up to the second degree) for extreme low-coverage data. The package also allows users to quantify and visualise the level of confidence in the estimated degrees of relatedness.
Author: Jono Tuke [aut, cre] , Adam B. Rohrlach [aut] , Wolfgang Haak [aut] , Divyaratan Popli [aut]
Maintainer: Jono Tuke <simon.tuke@adelaide.edu.au>

Diff between BREADR versions 1.0.1 dated 2023-04-12 and 1.0.2 dated 2024-09-09

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New package RefBasedMI with initial version 0.2.0
Package: RefBasedMI
Title: Reference-Based Imputation for Longitudinal Clinical Trials with Protocol Deviation
Version: 0.2.0
Description: Imputation of missing numerical outcomes for a longitudinal trial with protocol deviations. The package uses distinct treatment arm-based assumptions for the unobserved data, following the general algorithm of Carpenter, Roger, and Kenward (2013) <doi:10.1080/10543406.2013.834911>, and the causal model of White, Royes and Best (2020) <doi:10.1080/10543406.2019.1684308>. Sensitivity analyses to departures from these assumptions can be done by the Delta method of Roger. The program uses the same algorithm as the 'mimix' 'Stata' package written by Suzie Cro, with additional coding for the causal model and delta method. The reference-based methods are jump to reference (J2R), copy increments in reference (CIR), copy reference (CR), and the causal model, all of which must specify the reference treatment arm. Other methods are missing at random (MAR) and the last mean carried forward (LMCF). Individual-specific imputation methods (and their reference groups) can be specified.
URL: https://github.com/UCL/RefBasedMI
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: data.table, Hmisc, mice, pastecs, assertthat
Depends: R (>= 3.5.0)
NeedsCompilation: yes
Packaged: 2024-09-04 10:17:04 UTC; rmjlmqu
Author: Kevin McGrath [aut], Matteo Quartagno [cre]
Maintainer: Matteo Quartagno <m.quartagno@ucl.ac.uk>
Repository: CRAN
Date/Publication: 2024-09-09 09:10:01 UTC

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New package PoweREST with initial version 0.1.0
Package: PoweREST
Title: A Bootstrap-Based Power Estimation Tool for Spatial Transcriptomics
Version: 0.1.0
Imports: scam, Seurat, dplyr, plotly, resample, xgboost, magrittr, rayshader, ggplot2
Suggests: patchwork, boot, knitr, rmarkdown, fields, rayrender, tidyr
Description: Power estimation and sample size calculation for 10X Visium Spatial Transcriptomics data to detect differential expressed genes between two conditions based on bootstrap resampling. See Shui et al. (2024) <doi:10.1101/2024.08.30.610564> for method details.
Encoding: UTF-8
VignetteBuilder: knitr
License: MIT + file LICENSE
Depends: R (>= 2.10)
LazyData: true
NeedsCompilation: no
Packaged: 2024-09-04 13:17:57 UTC; shuilan
Author: Lan Shui [aut, cre]
Maintainer: Lan Shui <Lan.Shui@uth.tmc.edu>
Repository: CRAN
Date/Publication: 2024-09-09 09:30:02 UTC

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Package MiscMetabar updated to version 0.9.3 with previous version 0.9.1 dated 2024-04-28

Title: Miscellaneous Functions for Metabarcoding Analysis
Description: Facilitate the description, transformation, exploration, and reproducibility of metabarcoding analyses. 'MiscMetabar' is mainly built on top of the 'phyloseq', 'dada2' and 'targets' R packages. It helps to build reproducible and robust bioinformatics pipelines in R. 'MiscMetabar' makes ecological analysis of alpha and beta-diversity easier, more reproducible and more powerful by integrating a large number of tools. Important features are described in Taudière A. (2023) <doi:10.21105/joss.06038>.
Author: Adrien Taudiere [aut, cre, cph]
Maintainer: Adrien Taudiere <adrien.taudiere@zaclys.net>

Diff between MiscMetabar versions 0.9.1 dated 2024-04-28 and 0.9.3 dated 2024-09-09

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 MiscMetabar-0.9.3/MiscMetabar/tests/testthat/test_phyloseq_class.R     |    2 
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 161 files changed, 2283 insertions(+), 1083 deletions(-)

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Package jtdm updated to version 0.1-3 with previous version 0.1-2 dated 2023-11-12

Title: Joint Modelling of Functional Traits
Description: Fitting and analyzing a Joint Trait Distribution Model. The Joint Trait Distribution Model is implemented in the Bayesian framework using conjugate priors and posteriors, thus guaranteeing fast inference. In particular the package computes joint probabilities and multivariate confidence intervals, and enables the investigation of how they depend on the environment through partial response curves. The method implemented by the package is described in Poggiato et al. (2023) <doi:10.1111/geb.13706>.
Author: Giovanni Poggiato [aut, cre, cph]
Maintainer: Giovanni Poggiato <giov.poggiato@gmail.com>

Diff between jtdm versions 0.1-2 dated 2023-11-12 and 0.1-3 dated 2024-09-09

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New package handwriterApp with initial version 1.0.1
Package: handwriterApp
Title: A 'shiny' Application for Handwriting Analysis
Version: 1.0.1
Description: Perform statistical writership analysis of scanned handwritten documents with a 'shiny' app for 'handwriter'.
License: GPL (>= 3)
Encoding: UTF-8
Depends: R (>= 2.10)
LazyData: true
Imports: bslib, dplyr, handwriter, magick, magrittr, rmarkdown, shiny, shinycssloaders, shinyFiles, shinyjs, stringr, tidyr
Suggests: testthat (>= 3.0.0)
URL: https://github.com/CSAFE-ISU/handwriterApp
BugReports: https://github.com/CSAFE-ISU/handwriterApp/issues
NeedsCompilation: no
Packaged: 2024-09-04 14:36:48 UTC; stephanie
Author: Iowa State University of Science and Technology on behalf of its Center for Statistics and Applications in Forensic Evidence [aut, cph, fnd], Stephanie Reinders [aut, cre]
Maintainer: Stephanie Reinders <srein@iastate.edu>
Repository: CRAN
Date/Publication: 2024-09-09 09:50:02 UTC

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New package gdverse with initial version 1.0.0
Package: gdverse
Title: Geographical Detector Models
Version: 1.0.0
Description: Analyzing spatial factors and exploring spatial associations based on the concept of spatial stratified heterogeneity, and also takes into account local spatial dependencies, spatial interpretability, potential spatial interactions, and robust spatial stratification. Additionally, it supports geographical detector models established in academic literature.
License: GPL-3
Encoding: UTF-8
Language: en-US
URL: https://ausgis.github.io/gdverse/, https://github.com/ausgis/gdverse
BugReports: https://github.com/ausgis/gdverse/issues
Depends: R (>= 4.1.0)
Imports: classInt, dplyr, forcats, geosphere, ggplot2, magrittr, parallel, patchwork, purrr, reticulate, rpart, scatterpie, sf, spdep, stats, tibble, tidyr, utils
Suggests: cowplot, knitr, PieGlyph, Rcpp, Rdimtools, rmarkdown, terra, testthat (>= 3.0.0), tidyverse
LinkingTo: Rcpp
VignetteBuilder: knitr
LazyData: true
NeedsCompilation: yes
Packaged: 2024-09-04 16:29:35 UTC; dell
Author: Wenbo Lv [aut, cre, cph] , Yangyang Lei [aut] , Yongze Song [aut] , Wufan Zhao [aut] , Jianwu Yan [aut]
Maintainer: Wenbo Lv <lyu.geosocial@gmail.com>
Repository: CRAN
Date/Publication: 2024-09-09 10:00:03 UTC

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New package anoint with initial version 1.5
Package: anoint
Title: Analysis of Interactions
Version: 1.5
Date: 2024-09-04
Maintainer: Ravi Varadhan <ravi.varadhan@jhu.edu>
Description: The tools in this package are intended to help researchers assess multiple treatment-covariate interactions with data from a parallel-group randomized controlled clinical trial. The methods implemented in the package were proposed in Kovalchik, Varadhan and Weiss (2013) <doi: 10.1002/sim.5881>.
License: GPL (>= 2)
LazyLoad: yes
Depends: R (>= 2.13.0), stats, survival, MASS, graphics, grid
Imports: methods, glmnet
NeedsCompilation: no
Packaged: 2024-09-04 15:07:59 UTC; raviv
Repository: CRAN
Author: Ravi Varadhan [aut, cre], Stephanie Kovalchik [aut], Leon Wang [ctb]
Date/Publication: 2024-09-09 10:00:09 UTC

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New package vachette with initial version 0.40.0
Package: vachette
Title: A Method for Visualization of Pharmacometric Models
Version: 0.40.0
Description: A method to visualize pharmacometric analyses which are impacted by covariate effects. Variability-aligned covariate harmonized-effects and time-transformation equivalent ('vachette') facilitates intuitive overlays of data and model predictions, allowing for comprehensive comparison without dilution effects. 'vachette' improves upon previous methods Lommerse et al. (2021) <doi:10.1002/psp4.12679>, enabling its application to all pharmacometric models and enhancing Visual Predictive Checks (VPC) by integrating data into cohesive plots that can highlight model misspecification.
URL: https://github.com/certara/vachette
BugReports: https://github.com/certara/vachette/issues
Depends: R (>= 4.0)
License: LGPL-3
Encoding: UTF-8
Suggests: knitr, rmarkdown, mrgsolve, tidyvpc, testthat (>= 3.0.0), learnr
Imports: ggplot2, tidyr, dplyr, magrittr, prospectr, Hmisc, purrr, minpack.lm, progress, rlang, utils, photobiology
NeedsCompilation: no
Packaged: 2024-09-04 03:31:27 UTC; jcraig
Author: Jos Lommerse [aut], Anna Largajolli [aut], James Craig [aut, cre], Nele Mueller-Plock [ctb], Jeff Sachs [ctb], Amy Cheung [ctb], Certara USA, Inc. [cph, fnd]
Maintainer: James Craig <james.craig@certara.com>
Repository: CRAN
Date/Publication: 2024-09-09 08:50:02 UTC

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New package pedtricks with initial version 0.4.2
Package: pedtricks
Title: Visualize, Summarize and Simulate Data from Pedigrees
Version: 0.4.2
Description: Sensitivity and power analysis, for calculating statistics describing pedigrees from wild populations, and for visualizing pedigrees.
URL: https://juliengamartin.github.io/pedtricks/
BugReports: https://github.com/JulienGAMartin/pedtricks/issues
Language: en-US
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
LazyLoad: yes
Depends: R (>= 4.0)
Imports: ggplot2, dplyr, kinship2, tidyr, Matrix, mvtnorm, MCMCglmm, nadiv, genetics, methods, igraph
NeedsCompilation: no
Packaged: 2024-09-04 00:28:02 UTC; julien
Author: Julien Martin [aut, cre] , Matthew Wolak [aut] , Susan Johnston [aut] , Michael Morrissey [aut]
Maintainer: Julien Martin <julien.martin@uottawa.ca>
Repository: CRAN
Date/Publication: 2024-09-09 08:50:06 UTC

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Package OBIC updated to version 3.0.3 with previous version 3.0.2 dated 2024-03-05

Title: Calculate the Open Bodem Index (OBI) Score
Description: The Open Bodem Index (OBI) is a method to evaluate the quality of soils of agricultural fields in The Netherlands and the sustainability of the current agricultural practices. The OBI score is based on four main criteria: chemical, physical, biological and management, which consist of more than 21 indicators. By providing results of a soil analysis and management info the 'OBIC' package can be use to calculate he scores, indicators and derivatives that are used by the OBI. More information about the Open Bodem Index can be found at <https://openbodemindex.nl/>.
Author: Sven Verweij [aut, cre] , Gerard Ros [aut] , Yuki Fujita [aut] , Wilbrand Hendrik Riechelman [aut] , Kees van den Dool [aut] , Job de Pater [ctb], Nutrienten Managment Instituut [cph]
Maintainer: Sven Verweij <sven.verweij@nmi-agro.nl>

Diff between OBIC versions 3.0.2 dated 2024-03-05 and 3.0.3 dated 2024-09-09

 DESCRIPTION                              |    8 ++++----
 MD5                                      |   24 ++++++++++++------------
 NEWS.md                                  |    7 +++++++
 R/obic.R                                 |    2 +-
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New package lab2clean with initial version 1.0.0
Package: lab2clean
Title: Automation and Standardization of Cleaning Clinical Lab Data
Version: 1.0.0
Description: Navigating the shift of clinical laboratory data from primary everyday clinical use to secondary research purposes presents a significant challenge. Given the substantial time and expertise required for lab data pre-processing and cleaning and the lack of all-in-one tools tailored for this need, we developed our algorithm 'lab2clean' as an open-source R-package. 'lab2clean' package is set to automate and standardize the intricate process of cleaning clinical laboratory results. With a keen focus on improving the data quality of laboratory result values, our goal is to equip researchers with a straightforward, plug-and-play tool, making it smoother for them to unlock the true potential of clinical laboratory data in clinical research and clinical machine learning (ML) model development. Version 1.0 of the algorithm is described in detail in 'Zayed et al. (2024)' <doi:10.1186/s12911-024-02652-7>.
License: GPL (>= 3)
Encoding: UTF-8
Imports: data.table, stats, utils
Suggests: knitr, rmarkdown, printr
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2024-09-04 05:57:23 UTC; u0148644
Author: Ahmed Zayed [aut, cre] , Arne Janssens [aut, ctb], Pavlos Mamouris [ctb]
Maintainer: Ahmed Zayed <ahmed.zayed@kuleuven.be>
Depends: R (>= 3.5.0)
Repository: CRAN
Date/Publication: 2024-09-09 09:00:02 UTC

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New package FuzzyImputationTest with initial version 0.2.0
Package: FuzzyImputationTest
Title: Imputation Procedures and Quality Tests for Fuzzy Data
Version: 0.2.0
Description: Special procedures for the imputation of missing fuzzy numbers are still underdeveloped. The goal of the package is to provide the new d-imputation method (DIMP for short, Romaniuk, M. and Grzegorzewski, P. "Fuzzy Data Imputation with DIMP and FGAIN" RB/23/2023 (2023)) and covert some classical ones applied in R packages ('missForest','miceRanger','knn') for use with fuzzy datasets. Additionally, specially tailored benchmarking tests are provided to check and compare these imputation procedures with fuzzy datasets.
License: GPL-3
NeedsCompilation: yes
Imports: stats, methods, FuzzySimRes, FuzzyNumbers, missForest, miceRanger, VIM
Encoding: UTF-8
Depends: R (>= 3.5.0)
Suggests: testthat (>= 3.0.0)
Packaged: 2024-09-04 06:53:46 UTC; mroman
Author: Maciej Romaniuk [cre, aut]
Maintainer: Maciej Romaniuk <mroman@ibspan.waw.pl>
Repository: CRAN
Date/Publication: 2024-09-09 09:00:05 UTC

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Package MantaID updated to version 1.0.4 with previous version 1.0.3 dated 2024-08-27

Title: A Machine-Learning Based Tool to Automate the Identification of Biological Database IDs
Description: The number of biological databases is growing rapidly, but different databases use different IDs to refer to the same biological entity. The inconsistency in IDs impedes the integration of various types of biological data. To resolve the problem, we developed 'MantaID', a data-driven, machine-learning based approach that automates identifying IDs on a large scale. The 'MantaID' model's prediction accuracy was proven to be 99%, and it correctly and effectively predicted 100,000 ID entries within two minutes. 'MantaID' supports the discovery and exploitation of ID patterns from large quantities of databases. (e.g., up to 542 biological databases). An easy-to-use freely available open-source software R package, a user-friendly web application, and API were also developed for 'MantaID' to improve applicability. To our knowledge, 'MantaID' is the first tool that enables an automatic, quick, accurate, and comprehensive identification of large quantities of IDs, and can therefore be used as a [...truncated...]
Author: Zhengpeng Zeng [aut, cre, ctb] , Longfei Mao [aut, cph] , Feng Yu [aut] , Jiamin Hu [ctb] , Xiting Wang [ctb]
Maintainer: Zhengpeng Zeng <molaison@foxmail.com>

Diff between MantaID versions 1.0.3 dated 2024-08-27 and 1.0.4 dated 2024-09-09

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Package fdicdata (with last version 0.1.0) was removed from CRAN

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

2023-04-12 0.1.0

Permanent link
Package qtlmt (with last version 0.1-6) was removed from CRAN

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

2017-07-25 0.1-6
2017-07-20 0.1-5
2015-11-12 0.1-4
2013-03-12 0.1-3
2011-07-04 0.1-2
2011-06-27 0.1-1
2011-06-24 0.1

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Package norMmix updated to version 0.2-0 with previous version 0.1-1 dated 2024-04-16

Title: Direct MLE for Multivariate Normal Mixture Distributions
Description: Multivariate Normal (i.e. Gaussian) Mixture Models (S3) Classes. Fitting models to data using 'MLE' (maximum likelihood estimation) for multivariate normal mixtures via smart parametrization using the 'LDL' (Cholesky) decomposition, see McLachlan and Peel (2000, ISBN:9780471006268), Celeux and Govaert (1995) <doi:10.1016/0031-3203(94)00125-6>.
Author: Nicolas Trutmann [aut, cre], Martin Maechler [aut, ths]
Maintainer: Nicolas Trutmann <nicolas.trutmann@gmx.ch>

Diff between norMmix versions 0.1-1 dated 2024-04-16 and 0.2-0 dated 2024-09-09

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Package REDCapR updated to version 1.2.0 with previous version 1.1.0 dated 2022-08-10

Title: Interaction Between R and REDCap
Description: Encapsulates functions to streamline calls from R to the REDCap API. REDCap (Research Electronic Data CAPture) is a web application for building and managing online surveys and databases developed at Vanderbilt University. The Application Programming Interface (API) offers an avenue to access and modify data programmatically, improving the capacity for literate and reproducible programming.
Author: Will Beasley [aut, cre] , David Bard [ctb] , Thomas Wilson [ctb], John J Aponte [ctb], Rollie Parrish [ctb] , Benjamin Nutter [ctb], Andrew Peters [ctb] , Hao Zhu [ctb] , Janosch Linkersdoerfer [ctb] , Jonathan Mang [ctb] , Felix Torres [ctb], Philip [...truncated...]
Maintainer: Will Beasley <wibeasley@hotmail.com>

Diff between REDCapR versions 1.1.0 dated 2022-08-10 and 1.2.0 dated 2024-09-09

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 REDCapR-1.2.0/REDCapR/DESCRIPTION                                                                           |   53 
 REDCapR-1.2.0/REDCapR/MD5                                                                                   |  429 +-
 REDCapR-1.2.0/REDCapR/NAMESPACE                                                                             |   12 
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 REDCapR-1.2.0/REDCapR/R/REDCapR-package.R                                                                   |   23 
 REDCapR-1.2.0/REDCapR/R/constant.R                                                                          |   29 
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 REDCapR-1.2.0/REDCapR/R/helpers-testing.R                                                                   |   11 
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 REDCapR-1.2.0/REDCapR/R/redcap-version.R                                                                    |   46 
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 REDCapR-1.2.0/REDCapR/R/redcap-write.R                                                                      |  108 
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 REDCapR-1.2.0/REDCapR/README.md                                                                             |   12 
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 REDCapR-1.2.0/REDCapR/inst/WORDLIST                                                                         |   54 
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Package hytest updated to version 0.1.1 with previous version 0.1.0 dated 2024-06-04

Title: Hypothesis Testing Based on Neyman-Pearson Lemma and Likelihood Ratio Test
Description: Error type I and Optimal critical values to test statistical hypothesis based on Neyman-Pearson Lemma and Likelihood ratio test based on random samples from several distributions. The families of distributions are Bernoulli, Exponential, Geometric, Inverse Normal, Normal, Gamma, Gumbel, Lognormal, Poisson, and Weibull. This package is an ideal resource to help with the teaching of Statistics. The main references for this package are Casella G. and Berger R. (2003,ISBN:0-534-24312-6 , "Statistical Inference. Second Edition", Duxbury Press) and Hogg, R., McKean, J., and Craig, A. (2019,ISBN:013468699, "Introduction to Mathematical Statistic. Eighth edition", Pearson).
Author: Carlos Alberto Cardozo Delgado [aut, cre, cph]
Maintainer: Carlos Alberto Cardozo Delgado <cardozorpackages@gmail.com>

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Package abess updated to version 0.4.9 with previous version 0.4.8 dated 2023-09-19

Title: Fast Best Subset Selection
Description: Extremely efficient toolkit for solving the best subset selection problem <https://www.jmlr.org/papers/v23/21-1060.html>. This package is its R interface. The package implements and generalizes algorithms designed in <doi:10.1073/pnas.2014241117> that exploits a novel sequencing-and-splicing technique to guarantee exact support recovery and globally optimal solution in polynomial times for linear model. It also supports best subset selection for logistic regression, Poisson regression, Cox proportional hazard model, Gamma regression, multiple-response regression, multinomial logistic regression, ordinal regression, (sequential) principal component analysis, and robust principal component analysis. The other valuable features such as the best subset of group selection <doi:10.1287/ijoc.2022.1241> and sure independence screening <doi:10.1111/j.1467-9868.2008.00674.x> are also provided.
Author: Jin Zhu [aut, cre] , Zezhi Wang [aut], Liyuan Hu [aut], Junhao Huang [aut], Kangkang Jiang [aut], Yanhang Zhang [aut], Borui Tang [aut], Shiyun Lin [aut], Junxian Zhu [aut], Canhong Wen [aut], Heping Zhang [aut] , Xueqin Wang [aut] , spectra contribu [...truncated...]
Maintainer: Jin Zhu <zhuj37@mail2.sysu.edu.cn>

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