Tue, 04 Jun 2024

Package echarty updated to version 1.6.4 with previous version 1.6.3 dated 2024-01-12

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, with initial code from John Coene's library echarts4r
Maintainer: Larry Helgason <larry@helgasoft.com>

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Package reformulas updated to version 0.3.0 with previous version 0.2.0 dated 2024-03-13

Title: Machinery for Processing Random Effect Formulas
Description: Takes formulas including random-effects components (formatted as in 'lme4', 'glmmTMB', etc.) and processes them. Includes various helper functions.
Author: Ben Bolker [aut, cre]
Maintainer: Ben Bolker <bolker@mcmaster.ca>

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Package MultiGroupO updated to version 0.3.0 with previous version 0.1.0 dated 2022-01-12

Title: MultiGroup Method and Simulation Data Analysis
Description: Two method new of multigroup and simulation of data. The first technique called multigroup PCA (mgPCA) this multivariate exploration approach that has the idea of considering the structure of groups and / or different types of variables. On the other hand, the second multivariate technique called Multigroup Dimensionality Reduction (MDR) it is another multivariate exploration method that is based on projections. In addition, a method called Single Dimension Exploration (SDE) was incorporated for to analyze the exploration of the data. It could help us in a better way to observe the behavior of the multigroup data with certain variables of interest.
Author: Carolina Millap/'an [aut, cre], Esteban Vegas [aut] , Ferran Reverter [aut]
Maintainer: Carolina Millap/'an <cayoya19@gmail.com>

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Package org updated to version 2024.6.5 with previous version 2022.11.23 dated 2022-11-22

Title: Organising Projects
Description: A system to help you organize projects. Most analyses have three (or more) main sections: code, results, and data, each with different requirements (version control/sharing/encryption). You provide folder locations and 'org' helps you take care of the details.
Author: Richard Aubrey White [aut, cre] , CSIDS [cph]
Maintainer: Richard Aubrey White <hello@rwhite.no>

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New package XML2R with initial version 0.0.8
Package: XML2R
Title: Easier XML Data Collection
Version: 0.0.8
Author: Carson Sievert <cpsievert1@gmail.com>
Maintainer: Carson Sievert <cpsievert1@gmail.com>
Description: Helpers for transforming XML content into number of tables while preserving parent to child relationships.
License: GPL (>= 2)
Depends: R (>= 2.15.1)
Imports: XML, httr, plyr
URL: https://github.com/cpsievert/XML2R
BugReports: https://github.com/cpsievert/XML2R/issues
NeedsCompilation: no
Packaged: 2024-06-04 20:28:15 UTC; cpsievert
Repository: CRAN
Date/Publication: 2024-06-04 21:20:02 UTC

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Package RRPP updated to version 2.0.1 with previous version 2.0.0 dated 2024-02-06

Title: Linear Model Evaluation with Randomized Residuals in a Permutation Procedure
Description: Linear model calculations are made for many random versions of data. Using residual randomization in a permutation procedure, sums of squares are calculated over many permutations to generate empirical probability distributions for evaluating model effects. This packaged is described by Collyer & Adams (2018). Additionally, coefficients, statistics, fitted values, and residuals generated over many permutations can be used for various procedures including pairwise tests, prediction, classification, and model comparison. This package should provide most tools one could need for the analysis of high-dimensional data, especially in ecology and evolutionary biology, but certainly other fields, as well.
Author: Michael Collyer [aut, cre] , Dean Adams [aut]
Maintainer: Michael Collyer <mlcollyer@gmail.com>

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Package markdown updated to version 1.13 with previous version 1.12 dated 2023-12-05

Title: Render Markdown with 'commonmark'
Description: Render Markdown to full and lightweight HTML/LaTeX documents with the 'commonmark' package. This package has been superseded by 'litedown'.
Author: Yihui Xie [aut, cre] , JJ Allaire [aut], Jeffrey Horner [aut], Henrik Bengtsson [ctb], Jim Hester [ctb], Yixuan Qiu [ctb], Kohske Takahashi [ctb], Adam November [ctb], Nacho Caballero [ctb], Jeroen Ooms [ctb], Thomas Leeper [ctb], Joe Cheng [ctb], An [...truncated...]
Maintainer: Yihui Xie <xie@yihui.name>

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Package crm12Comb updated to version 0.1.5 with previous version 0.1.4 dated 2024-05-26

Title: Phase I/II CRM Based Drug Combination Design
Description: Implements the adaptive designs for integrated phase I/II trials of drug combinations via continual reassessment method (CRM) to evaluate toxicity and efficacy simultaneously for each enrolled patient cohort based on Bayesian inference. It supports patients assignment guidance in a single trial using current enrolled data, as well as conducting extensive simulation studies to evaluate operating characteristics before the trial starts. It includes various link functions such as empiric, one-parameter logistic, two-parameter logistic, and hyperbolic tangent, as well as considering multiple prior distributions of the parameters like normal distribution, gamma distribution and exponential distribution to accommodate diverse clinical scenarios. Method using Bayesian framework with empiric link function is described in: Wages and Conaway (2014) <doi:10.1002/sim.6097>.
Author: Junying Wang [cre, aut], Song Wu [aut], Jie Yang [aut]
Maintainer: Junying Wang <junying.wang@stonybrook.edu>

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Package brms.mmrm updated to version 1.0.0 with previous version 0.1.0 dated 2024-02-15

Title: Bayesian MMRMs using 'brms'
Description: The mixed model for repeated measures (MMRM) is a popular model for longitudinal clinical trial data with continuous endpoints, and 'brms' is a powerful and versatile package for fitting Bayesian regression models. The 'brms.mmrm' R package leverages 'brms' to run MMRMs, and it supports a simplified interfaced to reduce difficulty and align with the best practices of the life sciences. References: Bürkner (2017) <doi:10.18637/jss.v080.i01>, Mallinckrodt (2008) <doi:10.1177/009286150804200402>.
Author: William Michael Landau [aut, cre] , Kevin Kunzmann [aut] , Yoni Sidi [aut], Christian Stock [aut] , Eli Lilly and Company [cph, fnd], Boehringer Ingelheim Pharma GmbH & Co. KG [cph, fnd]
Maintainer: William Michael Landau <will.landau.oss@gmail.com>

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Package santoku updated to version 1.0.0 with previous version 0.10.0 dated 2023-10-12

Title: A Versatile Cutting Tool
Description: A tool for cutting data into intervals. Allows singleton intervals. Always includes the whole range of data by default. Flexible labelling. Convenience functions for cutting by quantiles etc. Handles dates, times, units and other vectors.
Author: David Hugh-Jones [aut, cre], Daniel Possenriede [ctb]
Maintainer: David Hugh-Jones <davidhughjones@gmail.com>

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Package smcfcs updated to version 1.8.0 with previous version 1.7.1 dated 2022-11-07

Title: Multiple Imputation of Covariates by Substantive Model Compatible Fully Conditional Specification
Description: Implements multiple imputation of missing covariates by Substantive Model Compatible Fully Conditional Specification. This is a modification of the popular FCS/chained equations multiple imputation approach, and allows imputation of missing covariate values from models which are compatible with the user specified substantive model.
Author: Jonathan Bartlett [aut, cre], Ruth Keogh [aut], Edouard F. Bonneville [aut], Claus Thorn Ekstroem [ctb]
Maintainer: Jonathan Bartlett <jonathan.bartlett1@lshtm.ac.uk>

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Package mlr3oml updated to version 0.10.0 with previous version 0.9.0 dated 2023-09-13

Title: Connector Between 'mlr3' and 'OpenML'
Description: Provides an interface to 'OpenML.org' to list and download machine learning data, tasks and experiments. The 'OpenML' objects can be automatically converted to 'mlr3' objects. For a more sophisticated interface with more upload options, see the 'OpenML' package.
Author: Michel Lang [aut] , Sebastian Fischer [cre, aut]
Maintainer: Sebastian Fischer <sebf.fischer@gmail.com>

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Package howler updated to version 0.3.0 with previous version 0.2.1 dated 2022-10-06

Title: 'Shiny' Extension of 'howler.js'
Description: Audio interactivity within 'shiny' applications using 'howler.js'. Enables the status of the audio player to be sent from the UI to the server, and events such as playing and pausing the audio can be triggered from the server.
Author: Ashley Baldry [aut, cre], James Simpson [aut]
Maintainer: Ashley Baldry <arbaldry91@gmail.com>

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Package rmweather updated to version 0.2.6 with previous version 0.2.5 dated 2023-11-21

Title: Tools to Conduct Meteorological Normalisation and Counterfactual Modelling for Air Quality Data
Description: An integrated set of tools to allow data users to conduct meteorological normalisation and counterfactual modelling for air quality data. The meteorological normalisation technique uses predictive random forest models to remove variation of pollutant concentrations so trends and interventions can be explored in a robust way. For examples, see Grange et al. (2018) <doi:10.5194/acp-18-6223-2018> and Grange and Carslaw (2019) <doi:10.1016/j.scitotenv.2018.10.344>. The random forest models can also be used for counterfactual or business as usual (BAU) modelling by using the models to predict, from the model's perspective, the future. For an example, see Grange et al. (2021) <doi:10.5194/acp-2020-1171>.
Author: Stuart K. Grange [cre, aut]
Maintainer: Stuart K. Grange <stuart.grange@york.ac.uk>

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New package netcom with initial version 2.1.7
Package: netcom
Title: NETwork COMparison Inference
Version: 2.1.7
Date: 2024-5-28
Description: Infer system functioning with empirical NETwork COMparisons. These methods are part of a growing paradigm in network science that uses relative comparisons of networks to infer mechanistic classifications and predict systemic interventions. They have been developed and applied in Langendorf and Burgess (2021) <doi:10.1038/s41598-021-99251-7>, Langendorf (2020) <doi:10.1201/9781351190831-6>, and Langendorf and Goldberg (2019) <doi:10.48550/arXiv.1912.12551>.
URL: https://github.com/langendorfr/netcom
Repository: CRAN
License: GPL-3
Encoding: UTF-8
Depends: R (>= 3.1.0)
Imports: stats, dplyr, tibble, clue, expm, igraph, Matrix, pdist, pracma, vegan, magrittr, foreach, parallel, doParallel, optimx, GenSA, rlang, ggfortify, ggplot2, ggraph, reshape2
Suggests: rmarkdown, knitr, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2024-06-04 16:27:43 UTC; ryan
Author: Ryan Langendorf [aut, cre], Debra Goldberg [ctb], Matthew Burgess [ctb]
Maintainer: Ryan Langendorf <ryan.langendorf@colorado.edu>
Date/Publication: 2024-06-04 17:50:05 UTC

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Package mtarm updated to version 0.1.1 with previous version 0.1.0 dated 2024-05-01

Title: Bayesian Estimation of Multivariate Threshold Autoregressive Models
Description: Estimation, inference and forecasting using the Bayesian approach for multivariate threshold autoregressive (TAR) models in which the distribution used to describe the noise process belongs to the class of Gaussian variance mixtures.
Author: Luis Hernando Vanegas [aut, cre], Sergio Alejandro Calderon [aut], Luz Marina Rondon [aut]
Maintainer: Luis Hernando Vanegas <lhvanegasp@unal.edu.co>

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Package ggpattern updated to version 1.1.1 with previous version 1.0.1 dated 2022-11-09

Title: 'ggplot2' Pattern Geoms
Description: Provides 'ggplot2' geoms filled with various patterns. Includes a patterned version of every 'ggplot2' geom that has a region that can be filled with a pattern. Provides a suite of 'ggplot2' aesthetics and scales for controlling pattern appearances. Supports over a dozen builtin patterns (every pattern implemented by 'gridpattern') as well as allowing custom user-defined patterns.
Author: Mike FC [aut], Trevor L. Davis [aut, cre] , ggplot2 authors [aut]
Maintainer: Trevor L. Davis <trevor.l.davis@gmail.com>

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Package GDILM.SIR updated to version 1.2.1 with previous version 0.1.0 dated 2024-05-14

Title: Inference for Infectious Disease Transmission in SIR Framework
Description: Model and estimate the model parameters for the spatial model of individual-level infectious disease transmission in Susceptible-Infected-Recovered (SIR) framework.
Author: Ruwani Herath [aut, cre], Leila Amiri [ctb], Mahmoud Torabi [ctb]
Maintainer: Ruwani Herath <ruwanirasanjalih@gmail.com>

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Package beastier updated to version 2.5.1 with previous version 2.5 dated 2023-11-07

Title: Call 'BEAST2'
Description: 'BEAST2' (<https://www.beast2.org>) is a widely used Bayesian phylogenetic tool, that uses DNA/RNA/protein data and many model priors to create a posterior of jointly estimated phylogenies and parameters. 'BEAST2' is a command-line tool. This package provides a way to call 'BEAST2' from an 'R' function call.
Author: Richel J.C. Bilderbeek [aut, cre] , Joelle Barido-Sottani [rev] , David Winter [rev] , Jason Griffiths [ctb] , Olivier Roy [ctb], Thijs Janzen [ctb]
Maintainer: Richel J.C. Bilderbeek <rjcbilderbeek@gmail.com>

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Package agua updated to version 0.1.4 with previous version 0.1.3 dated 2023-06-03

Title: 'tidymodels' Integration with 'h2o'
Description: Create and evaluate models using 'tidymodels' and 'h2o' <https://h2o.ai/>. The package enables users to specify 'h2o' as an engine for several modeling methods.
Author: Max Kuhn [aut] , Qiushi Yan [aut, cre], Steven Pawley [aut], Posit Software, PBC [cph, fnd]
Maintainer: Qiushi Yan <qiushi.yann@gmail.com>

Diff between agua versions 0.1.3 dated 2023-06-03 and 0.1.4 dated 2024-06-04

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New package vital with initial version 1.0.0
Package: vital
Version: 1.0.0
Title: Tidy Analysis Tools for Mortality, Fertility, Migration and Population Data
Description: Analysing vital statistics based on tools consistent with the tidyverse. Tools are provided for data visualization, lifetable calculations, computing net migration numbers, Lee-Carter modelling; functional data modelling and forecasting.
Depends: R (>= 4.1.0)
Imports: cobs, distributional, dplyr, fable, fabletools (>= 0.3.3), future.apply, generics, ggplot2, HMDHFDplus (>= 2.0.3), mgcv, patchwork, progressr, purrr, rlang, tibble, tidyr, tidyselect, tsibble, vctrs
Suggests: demography, feasts, testthat (>= 3.0.0)
License: GPL-3
URL: https://pkg.robjhyndman.com/vital/, https://github.com/robjhyndman/vital
Encoding: UTF-8
LazyData: true
BugReports: https://github.com/robjhyndman/vital/issues
NeedsCompilation: no
Packaged: 2024-06-04 07:41:14 UTC; hyndman
Author: Rob Hyndman [aut, cre, cph] , Mitchell O'Hara-Wild [ctb]
Maintainer: Rob Hyndman <Rob.Hyndman@monash.edu>
Repository: CRAN
Date/Publication: 2024-06-04 16:10:02 UTC

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Package RNiftyReg updated to version 2.8.2 with previous version 2.8.1 dated 2023-07-18

Title: Image Registration Using the 'NiftyReg' Library
Description: Provides an 'R' interface to the 'NiftyReg' image registration tools <https://github.com/KCL-BMEIS/niftyreg>. Linear and nonlinear registration are supported, in two and three dimensions.
Author: Jon Clayden [cre, aut] , Marc Modat [aut], Benoit Presles [aut], Thanasis Anthopoulos [aut], Pankaj Daga [aut]
Maintainer: Jon Clayden <code@clayden.org>

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Package ichimoku updated to version 1.5.2 with previous version 1.5.1 dated 2024-04-10

Title: Visualization and Tools for Ichimoku Kinko Hyo Strategies
Description: An implementation of 'Ichimoku Kinko Hyo', also commonly known as 'cloud charts'. Static and interactive visualizations with tools for creating, backtesting and development of quantitative 'ichimoku' strategies. As described in Sasaki (1996, ISBN:4925152009), the technique is a refinement on candlestick charting, originating from Japan and now in widespread use in technical analysis worldwide. Translating as 'one-glance equilibrium chart', it allows the price action and market structure of financial securities to be determined 'at-a-glance'. Incorporates an interface with the OANDA fxTrade API <https://developer.oanda.com/> for retrieving historical and live streaming price data for major currencies, metals, commodities, government bonds and stock indices.
Author: Charlie Gao [aut, cre] , Hibiki AI Limited [cph]
Maintainer: Charlie Gao <charlie.gao@shikokuchuo.net>

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Package EBASE updated to version 1.0.2 with previous version 1.0.1 dated 2024-03-22

Title: Estuarine Bayesian Single-Station Estimation Method for Ecosystem Metabolism
Description: Estimate ecosystem metabolism in a Bayesian framework for individual water quality monitoring stations with continuous dissolved oxygen time series. A mass balance equation is used that provides estimates of parameters for gross primary production, respiration, and gas exchange. Methods adapted from Grace et al. (2015) <doi:10.1002/lom3.10011> and Wanninkhof (2014) <doi:10.4319/lom.2014.12.351>. Details in Beck et al. (2024) <doi:10.1002/lom3.10620>.
Author: Marcus Beck [aut, cre] , Maria Herrmann [aut], Jill Arriola [aut] , Raymond Najjar [aut]
Maintainer: Marcus Beck <mbeck@tbep.org>

Diff between EBASE versions 1.0.1 dated 2024-03-22 and 1.0.2 dated 2024-06-04

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Package BayesMortalityPlus updated to version 0.2.4 with previous version 0.2.3 dated 2024-03-04

Title: Bayesian Mortality Modelling
Description: Fit Bayesian graduation mortality using the Heligman-Pollard model, as seen in Heligman, L., & Pollard, J. H. (1980) <doi:10.1017/S0020268100040257> and Dellaportas, Petros, et al. (2001) <doi:10.1111/1467-985X.00202>, and dynamic linear model (Campagnoli, P., Petris, G., and Petrone, S. (2009) <doi:10.1007/b135794_2>). While Heligman-Pollard has parameters with a straightforward interpretation yielding some rich analysis, the dynamic linear model provides a very flexible adjustment of the mortality curves by controlling the discount factor value. Closing methods for both Heligman-Pollard and dynamic linear model were also implemented according to Dodd, Erengul, et al. (2018) <https://www.jstor.org/stable/48547511>. The Bayesian Lee-Carter model is also implemented to fit historical mortality tables time series to predict the mortality in the following years and to do improvement analysis, as seen in Lee, R. D., & Carter, L. R. (1992) <doi:10.1080/016 [...truncated...]
Author: Laboratorio de Matematica Aplicada
Maintainer: Luiz Fernando Figueiredo <labmapackage@gmail.com>

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Package surveygraph updated to version 0.1.2 with previous version 0.1.1 dated 2024-04-02

Title: Network Representations of Attitudes
Description: A tool for computing network representations of attitudes, extracted from tabular data such as sociological surveys. Development of surveygraph software and training materials was initially funded by the European Union under the ERC Proof-of-concept programme (ERC, Attitude-Maps-4-All, project number: 101069264). Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the European Research Council Executive Agency. Neither the European Union nor the granting authority can be held responsible for them.
Author: Samuel Unicomb [aut, cre], Alejandro Dinkelberg [aut], Padraig MacCarron [aut], David O'Sullivan [aut], Paul Maher [aut], Mike Quayle [aut]
Maintainer: Samuel Unicomb <samuelunicomb@gmail.com>

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Package stokes updated to version 1.2-1 with previous version 1.2-0 dated 2023-08-18

Title: The Exterior Calculus
Description: Provides functionality for working with tensors, alternating forms, wedge products, Stokes's theorem, and related concepts from the exterior calculus. Uses 'disordR' discipline (Hankin, 2022, <doi:10.48550/ARXIV.2210.03856>). The canonical reference would be M. Spivak (1965, ISBN:0-8053-9021-9) "Calculus on Manifolds". To cite the package in publications please use Hankin (2022) <doi:10.48550/ARXIV.2210.17008>.
Author: Robin K. S. Hankin [aut, cre]
Maintainer: Robin K. S. Hankin <hankin.robin@gmail.com>

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Package spatialTIME updated to version 1.3.4-5 with previous version 1.3.4-4 dated 2024-05-29

Title: Spatial Analysis of Vectra Immunoflourescent Data
Description: Visualization and analysis of Vectra Immunoflourescent data. Options for calculating both the univariate and bivariate Ripley's K are included. Calculations are performed using a permutation-based approach presented by Wilson et al. <doi:10.1101/2021.04.27.21256104>.
Author: Jordan Creed [aut], Ram Thapa [aut], Christopher Wilson [aut], Alex Soupir [aut], Oscar Ospina [aut], Julia Wrobel [aut], Brooke Fridley [cph], Fridley Lab [cre]
Maintainer: Fridley Lab <fridley.lab@moffitt.org>

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New package saePseudo with initial version 0.1.0
Package: saePseudo
Title: Small Area Estimation using Averaging Pseudo Area Level Model
Version: 0.1.0
Maintainer: Darin Huwaida <darinhuwaida21@gmail.com>
Description: Provides function for small area estimation at area level using averaging pseudo area level model for variables of interest. A dataset produced by data generation is also provided. This package estimates small areas at the village level and then aggregates them to the sub-district, region, and provincial levels.
License: GPL-3
URL: https://github.com/darinhuwaidaa/saePseudo
BugReports: https://github.com/darinhuwaidaa/saePseudo/issues
Depends: R (>= 3.5.0)
Imports: dplyr, sae
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2024-06-03 18:45:34 UTC; DARIN HUWAIDA
Author: Darin Huwaida [aut, cre], Azka Ubaidillah [aut]
Repository: CRAN
Date/Publication: 2024-06-04 15:50:02 UTC

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New package lacunr with initial version 1.0.1
Package: lacunr
Title: Fast 3D Lacunarity for Voxel Data
Version: 1.0.1
Date: 2024-06-03
URL: https://github.com/ElliottSmeds/lacunr
BugReports: https://github.com/ElliottSmeds/lacunr/issues
Description: Calculates 3D lacunarity from voxel data. It is designed for use with point clouds generated from Light Detection And Ranging (LiDAR) scans in order to measure the spatial heterogeneity of 3-dimensional structures such as forest stands. It provides fast 'C++' functions to efficiently bin point cloud data into voxels and calculate lacunarity using different variants of the gliding-box algorithm originated by Allain & Cloitre (1991) <doi:10.1103/PhysRevA.44.3552>.
License: GPL (>= 3)
Encoding: UTF-8
Imports: Rcpp (>= 1.0.10), data.table, abind, ggplot2, rlang
Suggests: knitr, lidR, rmarkdown, testthat (>= 3.0.0)
LinkingTo: Rcpp, RcppArmadillo, RcppThread
Depends: R (>= 2.10)
LazyData: true
LazyDataCompression: bzip2
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2024-06-03 20:55:07 UTC; easmeds
Author: Elliott Smeds [aut, cre, cph] , J. Antonio Guzman Q. [cph] function)
Maintainer: Elliott Smeds <elliott.alfred93@gmail.com>
Repository: CRAN
Date/Publication: 2024-06-04 16:00:02 UTC

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Package kanjistat updated to version 0.14.1 with previous version 0.14.0 dated 2024-05-29

Title: A Statistical Framework for the Analysis of Japanese Kanji Characters
Description: Various tools and data sets that support the study of kanji, including their morphology, decomposition and concepts of distance and similarity between them.
Author: Dominic Schuhmacher [aut, cre] , Lennart Finke [aut]
Maintainer: Dominic Schuhmacher <dominic.schuhmacher@mathematik.uni-goettingen.de>

Diff between kanjistat versions 0.14.0 dated 2024-05-29 and 0.14.1 dated 2024-06-04

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Package HDTSA updated to version 1.0.3 with previous version 1.0.2 dated 2023-01-07

Title: High Dimensional Time Series Analysis Tools
Description: Procedures for high-dimensional time series analysis including factor analysis proposed by Lam and Yao (2012) <doi:10.1214/12-AOS970> and Chang, Guo and Yao (2015) <doi:10.1016/j.jeconom.2015.03.024>,martingale difference test proposed by Chang, Jiang and Shao (2022) <doi:10.1016/j.jeconom.2022.09.001> in press,principal component analysis proposed by Chang, Guo and Yao (2018) <doi:10.1214/17-AOS1613>, identifying cointegration proposed by Zhang, Robinson and Yao (2019) <doi:10.1080/01621459.2018.1458620>, unit root test proposed by Chang, Cheng and Yao (2021) <doi:10.1093/biomet/asab034>, white noise test proposed by Chang, Yao and Zhou (2017) <doi:10.1093/biomet/asw066>, CP-decomposition for high-dimensional matrix time series proposed by Chang, He, Yang and Yao(2023) <doi:10.1093/jrsssb/qkac011> and Chang, Du, Huang and Yao (2024+), and Statistical inference for high-dimensional spectral density matrix porposed by Chang, Jiang, McElroy [...truncated...]
Author: Chen Lin [aut, cre], Jinyuan Chang [aut], Qiwei Yao [aut]
Maintainer: Chen Lin <linchen@smail.swufe.edu.cn>

Diff between HDTSA versions 1.0.2 dated 2023-01-07 and 1.0.3 dated 2024-06-04

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Package hbamr updated to version 2.3.1 with previous version 2.3.0 dated 2024-03-31

Title: Hierarchical Bayesian Aldrich-McKelvey Scaling via 'Stan'
Description: Perform hierarchical Bayesian Aldrich-McKelvey scaling using Hamiltonian Monte Carlo via 'Stan'. Aldrich-McKelvey ('AM') scaling is a method for estimating the ideological positions of survey respondents and political actors on a common scale using positional survey data. The hierarchical versions of the Bayesian 'AM' model included in this package outperform other versions both in terms of yielding meaningful posterior distributions for respondent positions and in terms of recovering true respondent positions in simulations. The package contains functions for preparing data, fitting models, extracting estimates, plotting key results, and comparing models using cross-validation. The original version of the default model is described in Bølstad (2024) <doi:10.1017/pan.2023.18>.
Author: Joergen Boelstad [aut, cre]
Maintainer: Joergen Boelstad <jorgen.bolstad@stv.uio.no>

Diff between hbamr versions 2.3.0 dated 2024-03-31 and 2.3.1 dated 2024-06-04

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New package goodpractice with initial version 1.0.5
Package: goodpractice
Title: Advice on R Package Building
Version: 1.0.5
Description: Give advice about good practices when building R packages. Advice includes functions and syntax to avoid, package structure, code complexity, code formatting, etc.
License: MIT + file LICENSE
URL: https://docs.ropensci.org/goodpractice/, https://github.com/ropensci-review-tools/goodpractice
BugReports: https://github.com/ropensci-review-tools/goodpractice/issues
Imports: clisymbols, covr, crayon, cyclocomp (>= 1.1.0), desc, jsonlite, lintr (>= 3.0.0), praise, rcmdcheck, rstudioapi, tools, utils, whoami, withr, xml2, xmlparsedata (>= 1.0.1)
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2024-06-03 09:04:17 UTC; smexus
Author: Mark Padgham [aut, cre] , Ascent Digital Services UK Limited [cph] , Karina Marks [aut] , Daniel de Bortoli [aut] , Gabor Csardi [aut], Hannah Frick [aut], Owen Jones [aut] , Hannah Alexander [aut], Ana Simmons [ctb] , Fabian Scheipl [ctb]
Maintainer: Mark Padgham <mark@ropensci.org>
Repository: CRAN
Date/Publication: 2024-06-04 15:40:06 UTC

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Package GGIR updated to version 3.1-1 with previous version 3.1-0 dated 2024-05-06

Title: Raw Accelerometer Data Analysis
Description: A tool to process and analyse data collected with wearable raw acceleration sensors as described in Migueles and colleagues (JMPB 2019), and van Hees and colleagues (JApplPhysiol 2014; PLoSONE 2015). The package has been developed and tested for binary data from 'GENEActiv' <https://activinsights.com/>, binary (.gt3x) and .csv-export data from 'Actigraph' <https://theactigraph.com> devices, and binary (.cwa) and .csv-export data from 'Axivity' <https://axivity.com>. These devices are currently widely used in research on human daily physical activity. Further, the package can handle accelerometer data file from any other sensor brand providing that the data is stored in csv format. Also the package allows for external function embedding.
Author: Vincent T van Hees [aut, cre], Jairo H Migueles [aut] , Severine Sabia [ctb], Matthew R Patterson [ctb], Zhou Fang [ctb], Joe Heywood [ctb], Joan Capdevila Pujol [ctb], Lena Kushleyeva [ctb], Mathilde Chen [ctb], Manasa Yerramalla [ctb], Patrick Bos [...truncated...]
Maintainer: Vincent T van Hees <v.vanhees@accelting.com>

Diff between GGIR versions 3.1-0 dated 2024-05-06 and 3.1-1 dated 2024-06-04

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Package GALLO updated to version 1.5 with previous version 1.4 dated 2024-03-13

Title: Genomic Annotation in Livestock for Positional Candidate LOci
Description: The accurate annotation of genes and Quantitative Trait Loci (QTLs) located within candidate markers and/or regions (haplotypes, windows, CNVs, etc) is a crucial step the most common genomic analyses performed in livestock, such as Genome-Wide Association Studies or transcriptomics. The Genomic Annotation in Livestock for positional candidate LOci (GALLO) is an R package designed to provide an intuitive and straightforward environment to annotate positional candidate genes and QTLs from high-throughput genetic studies in livestock. Moreover, GALLO allows the graphical visualization of gene and QTL annotation results, data comparison among different grouping factors (e.g., methods, breeds, tissues, statistical models, studies, etc.), and QTL enrichment in different livestock species including cattle, pigs, sheep, and chicken, among others.
Author: Pablo Fonseca [aut, cre], Aroa Suarez-Vega [aut], Gabriele Marras [aut], Angela Canovas [aut]
Maintainer: Pablo Fonseca <pfonseca@uoguelph.ca>

Diff between GALLO versions 1.4 dated 2024-03-13 and 1.5 dated 2024-06-04

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New package DrugUtilisation with initial version 0.6.1
Package: DrugUtilisation
Title: Summarise Patient-Level Drug Utilisation in Data Mapped to the OMOP Common Data Model
Version: 0.6.1
Description: Summarise patient-level drug utilisation cohorts using data mapped to the Observational Medical Outcomes Partnership (OMOP) common data model. New users and prevalent users cohorts can be generated and their characteristics, indication and drug use summarised.
License: Apache License (>= 2)
Encoding: UTF-8
Suggests: covr, testthat (>= 3.1.5), odbc, here, RPostgres, duckdb, CodelistGenerator, knitr, PaRe, rmarkdown, DT, magick, DiagrammeRsvg, ggplot2, cowplot, plotly, tibble
Imports: CDMConnector (>= 1.4.0), checkmate, DBI, dbplyr, dplyr, glue, lubridate, tidyr, rlang, RJSONIO, cli, PatientProfiles (>= 0.8.0), magrittr, purrr, tictoc, omopgenerics (>= 0.2.0), visOmopResults, lifecycle
Depends: R (>= 2.10)
LazyData: true
URL: https://darwin-eu-dev.github.io/DrugUtilisation/
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2024-06-03 19:20:37 UTC; martics
Author: Marti Catala [aut, cre] , Mike Du [aut] , Yuchen Guo [aut] , Kim Lopez-Guell [aut] , Edward Burn [ctb] , Xintong Li [ctb] , Marta Alcalde-Herraiz [ctb]
Maintainer: Marti Catala <marti.catalasabate@ndorms.ox.ac.uk>
Repository: CRAN
Date/Publication: 2024-06-04 15:40:11 UTC

More information about DrugUtilisation at CRAN
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New package baf with initial version 0.0.1
Package: baf
Title: Block Assignment Files
Version: 0.0.1
Description: Download and read US Census Bureau data relationship files. Provides support for cleaning and using block assignment files since 2010, as described in <https://www.census.gov/geographies/reference-files/time-series/geo/block-assignment-files.html>. Also includes support for working with block equivalency files, used for years outside of decennial census years.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: cli, curl, dplyr, fs, glue, readr
URL: http://christophertkenny.com/baf/, https://github.com/christopherkenny/baf
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2024-06-03 20:19:17 UTC; chris
Author: Christopher T. Kenny [aut, cre] , Cory McCartan [ctb]
Maintainer: Christopher T. Kenny <christopherkenny@fas.harvard.edu>
Repository: CRAN
Date/Publication: 2024-06-04 16:00:06 UTC

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Package tinytiger updated to version 0.0.9 with previous version 0.0.8 dated 2023-10-17

Title: Lightweight Interface to TIGER/Line Shapefiles
Description: Download geographic shapes from the United States Census Bureau TIGER/Line Shapefiles <https://www.census.gov/geographies/mapping-files/time-series/geo/tiger-line-file.html>. Functions support downloading and reading in geographic boundary data. All downloads can be set up with a cache to avoid multiple downloads. Data is available back to 2000 for most geographies.
Author: Christopher T. Kenny [aut, cre] , Cory McCartan [aut]
Maintainer: Christopher T. Kenny <christopherkenny@fas.harvard.edu>

Diff between tinytiger versions 0.0.8 dated 2023-10-17 and 0.0.9 dated 2024-06-04

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Package pgenlibr updated to version 0.3.7 with previous version 0.3.6 dated 2024-05-27

Title: PLINK 2 Binary (.pgen) Reader
Description: A thin wrapper over PLINK 2's core libraries which provides an R interface for reading .pgen files. A minimal .pvar loader is also included. Chang et al. (2015) \doi{10.1186/s13742-015-0047-8}.
Author: Christopher Chang [aut, cre], Eric Biggers [ctb, cph] , Yann Collet [ctb] , Meta Platforms, Inc. [cph] , Evan Nemerson [ctb, cph] , Przemyslaw Skibinski [ctb] , Nick Terrell [ctb]
Maintainer: Christopher Chang <chrchang@alumni.caltech.edu>

Diff between pgenlibr versions 0.3.6 dated 2024-05-27 and 0.3.7 dated 2024-06-04

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Permanent link

Package waveslim updated to version 1.8.5 with previous version 1.8.4 dated 2022-08-14

Title: Basic Wavelet Routines for One-, Two-, and Three-Dimensional Signal Processing
Description: Basic wavelet routines for time series (1D), image (2D) and array (3D) analysis. The code provided here is based on wavelet methodology developed in Percival and Walden (2000); Gencay, Selcuk and Whitcher (2001); the dual-tree complex wavelet transform (DTCWT) from Kingsbury (1999, 2001) as implemented by Selesnick; and Hilbert wavelet pairs (Selesnick 2001, 2002). All figures in chapters 4-7 of GSW (2001) are reproducible using this package and R code available at the book website(s) below.
Author: Brandon Whitcher
Maintainer: Brandon Whitcher <bwhitcher@gmail.com>

Diff between waveslim versions 1.8.4 dated 2022-08-14 and 1.8.5 dated 2024-06-04

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Package rqPen updated to version 4.1.1 with previous version 4.1 dated 2024-05-07

Title: Penalized Quantile Regression
Description: Performs penalized quantile regression with LASSO, elastic net, SCAD and MCP penalty functions including group penalties. In addition, offers a group penalty that provides consistent variable selection across quantiles. Provides a function that automatically generates lambdas and evaluates different models with cross validation or BIC, including a large p version of BIC. Below URL provides a link to a work in progress vignette.
Author: Ben Sherwood [aut, cre], Adam Maidman [aut], Shaobo Li [aut]
Maintainer: Ben Sherwood <ben.sherwood@ku.edu>

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Package prismjs updated to version 2.0.0 with previous version 1.1.0 dated 2022-12-02

Title: Server-Side Syntax Highlighting
Description: Prism <https://prismjs.com/> is a lightweight, extensible syntax highlighter, built with modern web standards in mind. This package provides server-side rendering in R using 'V8' such that no JavaScript library is required in the resulting HTML documents. Over 400 languages are supported.
Author: Jeroen Ooms [aut, cre] , Lea Verou [cph]
Maintainer: Jeroen Ooms <jeroen@berkeley.edu>

Diff between prismjs versions 1.1.0 dated 2022-12-02 and 2.0.0 dated 2024-06-04

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Package consort updated to version 1.2.2 with previous version 1.2.1 dated 2023-09-22

Title: Create Consort Diagram
Description: To make it easy to create CONSORT diagrams for the transparent reporting of participant allocation in randomized, controlled clinical trials. This is done by creating a standardized disposition data, and using this data as the source for the creation a standard CONSORT diagram. Human effort by supplying text labels on the node can also be achieved.
Author: Alim Dayim [aut, cre]
Maintainer: Alim Dayim <ad938@cam.ac.uk>

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Package CausalMetaR updated to version 0.1.2 with previous version 0.1.1 dated 2024-01-15

Title: Causally Interpretable Meta-Analysis
Description: Provides robust and efficient methods for estimating causal effects in a target population using a multi-source dataset, including those of Dahabreh et al. (2019) <doi:10.1111/biom.13716>, Robertson et al. (2021) <doi:10.48550/arXiv.2104.05905>, and Wang et al. (2024) <doi:10.48550/arXiv.2402.02684>. The multi-source data can be a collection of trials, observational studies, or a combination of both, which have the same data structure (outcome, treatment, and covariates). The target population can be based on an internal dataset or an external dataset where only covariate information is available. The causal estimands available are average treatment effects and subgroup treatment effects. See Wang et al. (2024) <doi:10.48550/arXiv.2402.04341> for a detailed guide on using the package.
Author: Yi Lian [aut], Guanbo Wang [aut], Sean McGrath [aut, cre] , Issa Dahabreh [aut]
Maintainer: Sean McGrath <sean_mcgrath@g.harvard.edu>

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Package BayesSurvive updated to version 0.0.2 with previous version 0.0.1 dated 2024-04-23

Title: Bayesian Survival Models for High-Dimensional Data
Description: An implementation of Bayesian survival models with graph-structured selection priors for sparse identification of omics features predictive of survival (Madjar et al., 2021 <doi:10.1186/s12859-021-04483-z>) and its extension to use a fixed graph via a Markov Random Field (MRF) prior for capturing known structure of omics features, e.g. disease-specific pathways from the Kyoto Encyclopedia of Genes and Genomes database.
Author: Zhi Zhao [aut, cre], Katrin Madjar [aut], Tobias Oestmo Hermansen [aut], Manuela Zucknick [ctb], Joerg Rahnenfuehrer [ctb]
Maintainer: Zhi Zhao <zhi.zhao@medisin.uio.no>

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Package VBel updated to version 1.0.1 with previous version 1.0 dated 2024-05-28

Title: Variational Bayes for Fast and Accurate Empirical Likelihood Inference
Description: Computes the Gaussian variational approximation of the Bayesian empirical likelihood posterior. This is an implementation of the function found in Yu, W., & Bondell, H. D. (2023) <doi:10.1080/01621459.2023.2169701>.
Author: Wei-Chang Yu [aut] , Jeremy Lim [cre, aut]
Maintainer: Jeremy Lim <jeremy.lim@unimelb.edu.au>

Diff between VBel versions 1.0 dated 2024-05-28 and 1.0.1 dated 2024-06-04

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Package VARDetect updated to version 0.1.7 with previous version 0.1.6 dated 2022-05-10

Title: Multiple Change Point Detection in Structural VAR Models
Description: Implementations of Thresholded Block Segmentation Scheme (TBSS) and Low-rank plus Sparse Two Step Procedure (LSTSP) algorithms for detecting multiple changes in structural VAR models. The package aims to address the problem of change point detection in piece-wise stationary VAR models, under different settings regarding the structure of their transition matrices (autoregressive dynamics); specifically, the following cases are included: (i) (weakly) sparse, (ii) structured sparse, and (iii) low rank plus sparse. It includes multiple algorithms and related extensions from Safikhani and Shojaie (2020) <doi:10.1080/01621459.2020.1770097> and Bai, Safikhani and Michailidis (2020) <doi:10.1109/TSP.2020.2993145>.
Author: Yue Bai [aut, cre], Peiliang Bai [aut], Abolfazl Safikhani [aut], George Michailidis [aut]
Maintainer: Yue Bai <baiyue69@gmail.com>

Diff between VARDetect versions 0.1.6 dated 2022-05-10 and 0.1.7 dated 2024-06-04

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New package valueSetCompare with initial version 1.0.0
Package: valueSetCompare
Title: Comparing HRQoL Instrument Value Sets
Version: 1.0.0
Maintainer: Kim Rand <krand@mathsinhealth.com>
Description: The number of countries with multiple Health Related Quality of Life (HRQL) value sets is growing, and this trend is expected to continue. Each instrument and value set characterizes and values health differently. Identical health states can yield different utility values when valued using different value sets. The 'valueSetCompare' package facilitates comparisons of HRQoL value sets, enabling both theoretical and empirical comparisons. For empirical comparisons, it employs a novel simulation-based method by Jiang et al. (2022) <doi:10.1186/s12955-022-02031-8>, allowing users to investigate the responsiveness of HRQoL instruments across the entire health spectrum using cross-sectional data with external health anchors.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.5)
Imports: dplyr, ggplot2, rlang, eq5dsuite
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2024-06-03 09:04:57 UTC; aeste
Author: Kim Rand [aut, cre] , Anabel Estevez-Carrillo [aut]
Repository: CRAN
Date/Publication: 2024-06-04 09:50:12 UTC

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Package ulid updated to version 0.4.0 with previous version 0.3.1 dated 2024-04-02

Title: Generate Universally Unique 'Lexicographically' 'Sortable' Identifiers
Description: Universally unique identifiers ('UUIDs') can be sub-optimal for many uses-cases because they are not the most character efficient way of encoding 128 bits of randomness; v1/v2 versions are impractical in many environments, as they require access to a unique, stable MAC address; v3/v5 versions require a unique seed and produce randomly distributed IDs, which can cause fragmentation in many data structures; v4 provides no other information than randomness which can cause fragmentation in many data structures. Providing an alternative, 'ULIDs' (<https://github.com/ulid/spec>) have 128-bit compatibility with 'UUID', 1.21e+24 unique 'ULIDs' per millisecond, support standard (text) sorting, canonically encoded as a 26 character string, as opposed to the 36 character 'UUID', use 'base32' encoding for better efficiency and readability (5 bits per character), are case insensitive, have no special characters (i.e. are 'URL' safe) and have a monotonic sort order (correctly detects and handl [...truncated...]
Author: Bob Rudis [aut] , Suyash Verma [aut] , Dirk Eddelbuettel [cre]
Maintainer: Dirk Eddelbuettel <edd@debian.org>

Diff between ulid versions 0.3.1 dated 2024-04-02 and 0.4.0 dated 2024-06-04

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New package tinyarray with initial version 2.4.1
Package: tinyarray
Title: Expression Data Analysis and Visualization
Version: 2.4.1
Maintainer: Xiaojie Sun <18763899370@163.com>
Description: The Gene Expression Omnibus (<https://www.ncbi.nlm.nih.gov/geo/>) and The Cancer Genome Atlas (<https://portal.gdc.cancer.gov/>) are widely used medical public databases. Our platform integrates routine analysis and visualization tools for expression data to provide concise and intuitive data analysis and presentation.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: BiocManager, clusterProfiler, dplyr, limma, stringr, tibble, pheatmap, ggplot2, survival, Hmisc, survminer, patchwork
Suggests: testthat, AnnoProbe, GEOquery, Biobase, VennDiagram, FactoMineR, factoextra, knitr, rmarkdown, cowplot, ggpubr, ggplotify, tidyr, labeling, Rtsne, scatterplot3d, ComplexHeatmap, circlize,org.Rn.eg.db,org.Mm.eg.db,org.Hs.eg.db
URL: https://github.com/xjsun1221/tinyarray
BugReports: https://github.com/xjsun1221/tinyarray/issues
Depends: R (>= 4.1.0)
NeedsCompilation: no
Packaged: 2024-06-03 07:46:02 UTC; xiaojie
Author: Xiaojie Sun [aut, cre]
Repository: CRAN
Date/Publication: 2024-06-04 09:45:15 UTC

More information about tinyarray at CRAN
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Package tidySEM updated to version 0.2.7 with previous version 0.2.6 dated 2023-10-24

Title: Tidy Structural Equation Modeling
Description: A tidy workflow for generating, estimating, reporting, and plotting structural equation models using 'lavaan', 'OpenMx', or 'Mplus'. Throughout this workflow, elements of syntax, results, and graphs are represented as 'tidy' data, making them easy to customize. Includes functionality to estimate latent class analyses.
Author: Caspar J. van Lissa [aut, cre] , Mauricio Garnier-Villarreal [ctb] , Frank C Gootjes [ctb]
Maintainer: Caspar J. van Lissa <c.j.vanlissa@tilburguniversity.edu>

Diff between tidySEM versions 0.2.6 dated 2023-10-24 and 0.2.7 dated 2024-06-04

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New package tbea with initial version 1.4.2
Package: tbea
Title: Pre- And Post-Processing in Bayesian Evolutionary Analyses
Version: 1.4.2
Description: Functions are provided for prior specification in divergence time estimation using fossils as well as other kinds of data. It provides tools for interacting with the input and output of Bayesian platforms in evolutionary biology such as 'BEAST2', 'MrBayes', 'RevBayes', or 'MCMCTree'. It Implements a simple measure similarity between probability density functions for comparing prior and posterior Bayesian densities, as well as code for calculating the combination of distributions using conflation of Hill (2008). Functions for estimating the origination time in collections of distributions using the x-intercept (e.g., Draper and Smith, 1998) and stratigraphic intervals (Marshall 2010) are also available. Hill, T. 2008. "Conflations of probability distributions". Transactions of the American Mathematical Society, 363:3351-3372. <doi:10.48550/arXiv.0808.1808>, Draper, N. R. and Smith, H. 1998. "Applied Regression Analysis". 1--706. Wiley Interscience, New York. <DOI:10.1002/978111 [...truncated...]
Depends: R (>= 3.5.0)
Imports: ape, Rfit, boot, graphics, stats, utils, coda
License: GPL-3
Encoding: UTF-8
LazyData: true
URL: https://github.com/gaballench/tbea
BugReports: https://github.com/gaballench/tbea/issues
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2024-06-03 17:33:06 UTC; balleng
Author: Gustavo A. Ballen [aut, cre], Sandra Reinales [aut]
Maintainer: Gustavo A. Ballen <gustavo.a.ballen@gmail.com>
Repository: CRAN
Date/Publication: 2024-06-04 10:20:03 UTC

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Package stopp updated to version 0.2.4 with previous version 0.2.3 dated 2024-04-18

Title: Spatio-Temporal Point Pattern Methods, Model Fitting, Diagnostics, Simulation, Local Tests
Description: Toolbox for different kinds of spatio-temporal analyses to be performed on observed point patterns, following the growing stream of literature on point process theory. This R package implements functions to perform different kinds of analyses on point processes, proposed in the papers (Siino, Adelfio, and Mateu 2018<doi:10.1007/s00477-018-1579-0>; Siino et al. 2018<doi:10.1002/env.2463>; Adelfio et al. 2020<doi:10.1007/s00477-019-01748-1>; D’Angelo, Adelfio, and Mateu 2021<doi:10.1016/j.spasta.2021.100534>; D’Angelo, Adelfio, and Mateu 2022<doi:10.1007/s00362-022-01338-4>; D’Angelo, Adelfio, and Mateu 2023<doi:10.1016/j.csda.2022.107679>). The main topics include modeling, statistical inference, and simulation issues on spatio-temporal point processes on Euclidean space and linear networks.
Author: Nicoletta D'Angelo [aut, cre] , Giada Adelfio [aut]
Maintainer: Nicoletta D'Angelo <nicoletta.dangelo@unipa.it>

Diff between stopp versions 0.2.3 dated 2024-04-18 and 0.2.4 dated 2024-06-04

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New package scDECO with initial version 0.1.0
Package: scDECO
Title: Estimating Dynamic Correlation
Version: 0.1.0
Description: Implementations for two different Bayesian models of differential co-expression. scdeco.cop() fits the bivariate Gaussian copula model from Zichen Ma, Shannon W. Davis, Yen-Yi Ho (2023) <doi:10.1111/biom.13701>, while scdeco.pg() fits the bivariate Poisson-Gamma model from Zhen Yang, Yen-Yi Ho (2022) <doi:10.1111/biom.13457>.
Imports: MASS, rjags, msm
License: GPL (>= 3)
Encoding: UTF-8
URL: https://github.com/YenYiHo-Lab/scDECO
BugReports: https://github.com/YenYiHo-Lab/scDECO/issues
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2024-06-03 17:10:48 UTC; andyb
Author: Anderson Bussing [aut, cre], Yen-Yi Ho [aut, ths], Zichen Ma [aut], Zhen Yang [aut]
Maintainer: Anderson Bussing <abussing@email.sc.edu>
Repository: CRAN
Date/Publication: 2024-06-04 10:16:32 UTC

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New package sbd with initial version 0.1.0
Package: sbd
Title: Size Biased Distributions
Version: 0.1.0
Description: Fitting and plotting parametric or non-parametric size-biased non-negative distributions, with optional covariates if parametric. Rowcliffe, M. et al. (2016) <doi:10.1002/rse2.17>.
URL: https://github.com/MarcusRowcliffe/sbd
BugReports: https://github.com/MarcusRowcliffe/sbd/issues
License: GPL-3
Encoding: UTF-8
Imports: bbmle, MASS, dplyr
LazyData: true
NeedsCompilation: no
Packaged: 2024-06-01 00:01:57 UTC; Rowcliffe.M
Author: Marcus Rowcliffe [aut, cre]
Maintainer: Marcus Rowcliffe <marcus.rowcliffe@ioz.ac.uk>
Depends: R (>= 3.5.0)
Repository: CRAN
Date/Publication: 2024-06-04 09:47:59 UTC

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Package rsconnect updated to version 1.3.1 with previous version 1.3.0 dated 2024-05-24

Title: Deploy Docs, Apps, and APIs to 'Posit Connect', 'shinyapps.io', and 'RPubs'
Description: Programmatic deployment interface for 'RPubs', 'shinyapps.io', and 'Posit Connect'. Supported content types include R Markdown documents, Shiny applications, Plumber APIs, plots, and static web content.
Author: Aron Atkins [aut, cre], Toph Allen [aut], Hadley Wickham [aut], Jonathan McPherson [aut], JJ Allaire [aut], Posit Software, PBC [cph, fnd]
Maintainer: Aron Atkins <aron@posit.co>

Diff between rsconnect versions 1.3.0 dated 2024-05-24 and 1.3.1 dated 2024-06-04

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Package rlang updated to version 1.1.4 with previous version 1.1.3 dated 2024-01-10

Title: Functions for Base Types and Core R and 'Tidyverse' Features
Description: A toolbox for working with base types, core R features like the condition system, and core 'Tidyverse' features like tidy evaluation.
Author: Lionel Henry [aut, cre], Hadley Wickham [aut], mikefc [cph] , Yann Collet [cph] , Posit, PBC [cph, fnd]
Maintainer: Lionel Henry <lionel@posit.co>

Diff between rlang versions 1.1.3 dated 2024-01-10 and 1.1.4 dated 2024-06-04

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Package RJSDMX updated to version 3.3-0 with previous version 3.2-0 dated 2024-04-30

Title: R Interface to SDMX Web Services
Description: Provides functions to retrieve data and metadata from providers that disseminate data by means of SDMX web services. SDMX (Statistical Data and Metadata eXchange) is a standard that has been developed with the aim of simplifying the exchange of statistical information. More about the SDMX standard and the SDMX Web Services can be found at: <https://sdmx.org>.
Author: Attilio Mattiocco, Gianpaolo Lopez, Banca d'Italia
Maintainer: Attilio Mattiocco <attilio.mattiocco@bancaditalia.it>

Diff between RJSDMX versions 3.2-0 dated 2024-04-30 and 3.3-0 dated 2024-06-04

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New package RARtrials with initial version 0.0.1
Package: RARtrials
Title: Response-Adaptive Randomization in Clinical Trials
Version: 0.0.1
Maintainer: Chuyao Xu <cxu870@aucklanduni.ac.nz>
Description: Some response-adaptive randomization methods commonly found in literature are included in this package. These methods include the randomized play-the-winner rule for binary endpoint (Wei and Durham (1978) <doi:10.2307/2286290>), the doubly adaptive biased coin design with minimal variance strategy for binary endpoint (Atkinson and Biswas (2013) <doi:10.1201/b16101>, Rosenberger and Lachin (2015) <doi:10.1002/9781118742112>) and maximal power strategy targeting Neyman allocation for binary endpoint (Tymofyeyev, Rosenberger, and Hu (2007) <doi:10.1198/016214506000000906>) and RSIHR allocation with each letter representing the first character of the names of the individuals who first proposed this rule (Youngsook and Hu (2010) <doi:10.1198/sbr.2009.0056>, Bello and Sabo (2016) <doi:10.1080/00949655.2015.1114116>), A-optimal Allocation for continuous endpoint (Sverdlov and Rosenberger (2013) <doi:10.1080/15598608.2013.783726>), Aa-optimal Allocatio [...truncated...]
Encoding: UTF-8
Depends: R(>= 4.3), stats, pins
Imports: Rdpack(>= 0.7)
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
License: GPL (>= 3)
URL: https://github.com/yayayaoyaoyao/RARtrials
NeedsCompilation: no
Packaged: 2024-06-02 12:04:27 UTC; Chuyao
Author: Chuyao Xu [aut, cre], Thomas Lumley [aut, ths], Alain Vandal [aut, ths], Sofia S. Villar [cph], Kyle J. Wathen [cph]
Repository: CRAN
Date/Publication: 2024-06-04 09:44:57 UTC

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New package RandomProjectionTest with initial version 0.1.4
Package: RandomProjectionTest
Title: Two-Sample Test in High Dimensions using Random Projection
Version: 0.1.4
Description: Performs the random projection test (Lopes et al., (2011) <doi:10.48550/arXiv.1108.2401>) for the one-sample and two-sample hypothesis testing problem for equality of means in the high dimensional setting. We are interested in detecting the mean vector in the one-sample problem or the difference between mean vectors in the two-sample problem.
License: GPL-3
Encoding: UTF-8
Imports: MASS, stats, glue
NeedsCompilation: no
Packaged: 2024-06-03 09:32:33 UTC; jortialo
Author: Juan Ortiz Author [aut, cre, cph, rev]
Maintainer: Juan Ortiz Author <juan.ortiz1alonso@gmail.com>
Repository: CRAN
Date/Publication: 2024-06-04 09:44:51 UTC

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New package hytest with initial version 0.1.0
Package: hytest
Title: Hypothesis Testing Based on Neyman-Pearson Lemma and Likelihood Ratio Test
Version: 0.1.0
Maintainer: Carlos Alberto Cardozo Delgado <cardozorpackages@gmail.com>
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, Normal, Gamma, Lognormal, and Poisson. 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).
License: GPL-3
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2024-06-03 17:03:19 UTC; CARLOS
Author: Carlos Alberto Cardozo Delgado [aut, cre, cph]
Repository: CRAN
Date/Publication: 2024-06-04 10:28:04 UTC

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New package BinaryEPPM with initial version 3.0
Package: BinaryEPPM
Title: Mean and Scale-Factor Modeling of Under- And Over-Dispersed Binary Data
Version: 3.0
Imports: Formula, expm, numDeriv, stats, lmtest, grDevices, graphics
Date: 2024-06-03
Depends: R (>= 3.5.0)
Description: Under- and over-dispersed binary data are modeled using an extended Poisson process model (EPPM) appropriate for binary data. A feature of the model is that the under-dispersion relative to the binomial distribution only needs to be greater than zero, but the over-dispersion is restricted compared to other distributional models such as the beta and correlated binomials. Because of this, the examples focus on under-dispersed data and how, in combination with the beta or correlated distributions, flexible models can be fitted to data displaying both under- and over-dispersion. Using Generalized Linear Model (GLM) terminology, the functions utilize linear predictors for the probability of success and scale-factor with various link functions for p, and log link for scale-factor, to fit a variety of models relevant to areas such as bioassay. Details of the EPPM are in Faddy and Smith (2012) <doi:10.1002/bimj.201100214> and Smith and Faddy (2019) <doi:10.18637/jss.v090.i08>.
License: GPL-2
Suggests: R.rsp
VignetteBuilder: R.rsp
NeedsCompilation: no
Packaged: 2024-06-03 18:18:25 UTC; dmccs
Author: David M. Smith [aut, cre], Malcolm J. Faddy [aut]
Maintainer: David M. Smith <dmccsmith@verizon.net>
Repository: CRAN
Date/Publication: 2024-06-04 10:32:25 UTC

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Package psidR updated to version 2.2 with previous version 2.1 dated 2021-05-07

Title: Build Panel Data Sets from PSID Raw Data
Description: Makes it easy to build panel data in wide format from Panel Survey of Income Dynamics ('PSID') delivered raw data. Downloads data directly from the PSID server using the 'SAScii' package. 'psidR' takes care of merging data from each wave onto a cross-period index file, so that individuals can be followed over time. The user must specify which years they are interested in, and the 'PSID' variable names (e.g. ER21003) for each year (they differ in each year). The package offers helper functions to retrieve variable names from different waves. There are different panel data designs and sample subsetting criteria implemented ("SRC", "SEO", "immigrant" and "latino" samples).
Author: Florian Oswald
Maintainer: Florian Oswald <florian.oswald@gmail.com>

Diff between psidR versions 2.1 dated 2021-05-07 and 2.2 dated 2024-06-04

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Package plsmmLasso updated to version 1.1.0 with previous version 1.0.0 dated 2024-04-04

Title: Variable Selection and Inference for Partial Semiparametric Linear Mixed-Effects Model
Description: Implements a partial linear semiparametric mixed-effects model (PLSMM) featuring a random intercept and applies a lasso penalty to both the fixed effects and the coefficients associated with the nonlinear function. The model also accommodates interactions between the nonlinear function and a grouping variable, allowing for the capture of group-specific nonlinearities. Nonlinear functions are modeled using a set of bases functions. Estimation is conducted using a penalized Expectation-Maximization algorithm, and the package offers flexibility in choosing between various information criteria for model selection. Post-selection inference is carried out using a debiasing method, while inference on the nonlinear functions employs a bootstrap approach.
Author: Sami Leon [aut, cre, cph] , Tong Tong Wu [ths]
Maintainer: Sami Leon <samileon@hotmail.fr>

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Package pharmr updated to version 1.0.0 with previous version 0.96.0 dated 2023-06-15

Title: Interface to the 'Pharmpy' 'Pharmacometrics' Library
Description: Interface to the 'Pharmpy' 'pharmacometrics' library. The 'Reticulate' package is used to interface Python from R.
Author: Rikard Nordgren [aut, cre, cph], Stella Belin [aut, cph], Mats O. Karlsson [sad], Andrew C. Hooker [sad], Xiaomei Chen [sad], Sebastian Ueckert [sad] , Simon Buatois [rev], Joao A. Abrantes [rev], Emilie Schindler [rev], F. Hoffmann-La Roche Ltd. [fn [...truncated...]
Maintainer: Rikard Nordgren <rikard.nordgren@farmaci.uu.se>

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Package pdR updated to version 1.9.2 with previous version 1.9.1 dated 2023-08-21

Title: Threshold Model and Unit Root Tests in Cross-Section and Time Series Data
Description: Threshold model, panel version of Hylleberg et al. (1990) <DOI:10.1016/0304-4076(90)90080-D> seasonal unit root tests, and panel unit root test of Chang (2002) <DOI:10.1016/S0304-4076(02)00095-7>.
Author: Ho Tsung-wu
Maintainer: Ho Tsung-wu <tsungwu@ntnu.edu.tw>

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Package PanelMatch updated to version 2.2.0 with previous version 2.0.1 dated 2022-06-26

Title: Matching Methods for Causal Inference with Time-Series Cross-Sectional Data
Description: Implements a set of methodological tools that enable researchers to apply matching methods to time-series cross-sectional data. Imai, Kim, and Wang (2023) <http://web.mit.edu/insong/www/pdf/tscs.pdf> proposes a nonparametric generalization of the difference-in-differences estimator, which does not rely on the linearity assumption as often done in practice. Researchers first select a method of matching each treated observation for a given unit in a particular time period with control observations from other units in the same time period that have a similar treatment and covariate history. These methods include standard matching methods based on propensity score and Mahalanobis distance, as well as weighting methods. Once matching and refinement is done, treatment effects can be estimated with standard errors. The package also offers diagnostics for researchers to assess the quality of their results.
Author: In Song Kim [aut, cre], Adam Rauh [aut], Erik Wang [aut], Kosuke Imai [aut]
Maintainer: In Song Kim <insong@mit.edu>

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Package nanonext updated to version 1.1.0 with previous version 1.0.0 dated 2024-05-01

Title: NNG (Nanomsg Next Gen) Lightweight Messaging Library
Description: R binding for NNG (Nanomsg Next Gen), a successor to ZeroMQ. NNG is a socket library implementing 'Scalability Protocols', a reliable, high-performance standard for common communications patterns including publish/subscribe, request/reply and service discovery, over in-process, IPC, TCP, WebSocket and secure TLS transports. As its own threaded concurrency framework, provides a toolkit for asynchronous programming and distributed computing, with intuitive 'aio' objects which resolve automatically upon completion of asynchronous operations, and synchronisation primitives allowing R to wait upon events signalled by concurrent threads.
Author: Charlie Gao [aut, cre] , Hibiki AI Limited [cph], R Consortium [fnd]
Maintainer: Charlie Gao <charlie.gao@shikokuchuo.net>

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Package mvcauchy updated to version 1.1 with previous version 1.0 dated 2024-02-06

Title: Multivariate Cauchy Distribution
Description: The Cauchy distribution is a special case of the t distribution when the degrees of freedom are equal to 1. The functions are related to the multivariate Cauchy distribution and include simulation, computation of the density, maximum likelihood estimation, contour plot of the bivariate Cauchy distribution, and discriminant analysis. References include: Nadarajah S. and Kotz S. (2008). "Estimation methods for the multivariate t distribution". Acta Applicandae Mathematicae, 102(1): 99--118. <doi:10.1007/s10440-008-9212-8>, and Kanti V. Mardia, John T. Kent and John M. Bibby (1979). "Multivariate analysis", ISBN:978-0124712522. Academic Press, London.
Author: Michail Tsagris [aut, cre], Christos Adam [ctb]
Maintainer: Michail Tsagris <mtsagris@uoc.gr>

Diff between mvcauchy versions 1.0 dated 2024-02-06 and 1.1 dated 2024-06-04

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New package mcrPioda with initial version 1.3.3
Package: mcrPioda
Version: 1.3.3
Date: 2024-05-30
Title: Method Comparison Regression - Mcr Fork for M- And MM-Deming Regression
Maintainer: Giorgio Pioda <gfwp@ticino.com>
Copyright: This package includes code from the 'clinfun' library owned by Ventatraman E. Seshan (ktau.r and ktau.f).
Depends: R (>= 3.0.0), parallel, robslopes
Imports: stats, graphics, grDevices, methods, rrcov, mixtools
Description: Regression methods to quantify the relation between two measurement methods are provided by this package. In particular it addresses regression problems with errors in both variables and without repeated measurements. It implements the Clinical Laboratory Standard International (CLSI) recommendations (see J. A. Budd et al. (2018, <https://clsi.org/standards/products/method-evaluation/documents/ep09/>) for analytical method comparison and bias estimation using patient samples. Furthermore, algorithms for Theil-Sen and equivariant Passing-Bablok estimators are implemented, see F. Dufey (2020, <doi:10.1515/ijb-2019-0157>) and J. Raymaekers and F. Dufey (2022, <arXiv:2202:08060>). Further the robust M-Deming and MM-Deming (experimental) are available, see G. Pioda (2021, <arXiv:2105:04628>). A comprehensive overview over the implemented methods and references can be found in the manual pages 'mcrPioda-package' and 'mcreg'.
License: GPL (>= 3)
LazyData: true
NeedsCompilation: yes
Packaged: 2024-06-01 08:17:56 UTC; gfwp
Author: Giorgio Pioda [aut, cre] , Sergej Potapov [aut] , Fabian Model [aut], Andre Schuetzenmeister [aut] , Ekaterina Manuilova [aut], Florian Dufey [aut] , Jakob Raymaekers [aut] , Venkatraman E. Seshan [ctb], Roche [cph, fnd]
Repository: CRAN
Date/Publication: 2024-06-04 09:45:26 UTC

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New package LaMa with initial version 1.0.0
Package: LaMa
Title: Fast Numerical Maximum Likelihood Estimation for Latent Markov Models
Version: 1.0.0
Description: The class of latent Markov models, including hidden Markov models, hidden semi-Markov models, state space models, and point processes, is a very popular and powerful framework for inference of time series driven by latent processes. Furthermore, all these models can be fitted using direct numerical maximum likelihood estimation using the so-called forward algorithm as discussed in Zucchini et al. (2016) <doi:10.1201/b20790>. However, due to their great flexibility, researchers using these models in applied work often need to build highly customized models for which standard software implementation is lacking, or the construction of such models in said software is as complicated as writing fully tailored 'R' code. While providing greater flexibility and control, the latter suffers from slow estimation speeds that make custom solutions inconvenient. We address the above issues in two ways. First, standard blocks of code, common to all these model classes, are implemented as simple- [...truncated...]
URL: https://janoleko.github.io/software/, https://github.com/janoleko/LaMa
License: GPL-3
Encoding: UTF-8
Imports: Rcpp, mgcv
LinkingTo: Rcpp, RcppArmadillo
Depends: R (>= 3.5.0)
Suggests: knitr, rmarkdown, testthat (>= 3.0.0), PHSMM
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2024-06-01 10:35:22 UTC; jan-ole
Author: Jan-Ole Koslik [aut, cre]
Maintainer: Jan-Ole Koslik <jan-ole.koslik@uni-bielefeld.de>
Repository: CRAN
Date/Publication: 2024-06-04 09:47:46 UTC

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Package labelr updated to version 0.1.6 with previous version 0.1.5 dated 2024-05-02

Title: Label Data Frames, Variables, and Values
Description: Create and use data frame labels for data frame objects (frame labels), their columns (name labels), and individual values of a column (value labels). Value labels include one-to-one and many-to-one labels for nominal and ordinal variables, as well as numerical range-based value labels for continuous variables. Convert value-labeled variables so each value is replaced by its corresponding value label. Add values-converted-to-labels columns to a value-labeled data frame while preserving parent columns. Filter and subset a value-labeled data frame using labels, while returning results in terms of values. Overlay labels in place of values in common R commands to increase interpretability. Generate tables of value frequencies, with categories expressed as raw values or as labels. Access data frames that show value-to-label mappings for easy reference.
Author: Robert Hartman [aut, cre], The MITRE Corporation [cph]
Maintainer: Robert Hartman <rohartman@gmail.com>

Diff between labelr versions 0.1.5 dated 2024-05-02 and 0.1.6 dated 2024-06-04

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Package insight updated to version 0.20.0 with previous version 0.19.11 dated 2024-05-12

Title: Easy Access to Model Information for Various Model Objects
Description: A tool to provide an easy, intuitive and consistent access to information contained in various R models, like model formulas, model terms, information about random effects, data that was used to fit the model or data from response variables. 'insight' mainly revolves around two types of functions: Functions that find (the names of) information, starting with 'find_', and functions that get the underlying data, starting with 'get_'. The package has a consistent syntax and works with many different model objects, where otherwise functions to access these information are missing.
Author: Daniel Luedecke [aut, cre] , Dominique Makowski [aut, ctb] , Indrajeet Patil [aut, ctb] , Philip Waggoner [aut, ctb] , Mattan S. Ben-Shachar [aut, ctb] , Brenton M. Wiernik [aut, ctb] , Vincent Arel-Bundock [aut, ctb] , Etienne Bacher [aut, ctb] , Ale [...truncated...]
Maintainer: Daniel Luedecke <d.luedecke@uke.de>

Diff between insight versions 0.19.11 dated 2024-05-12 and 0.20.0 dated 2024-06-04

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New package ilabelled with initial version 0.1.0
Package: ilabelled
Title: Simple Handling of Labelled Data
Version: 0.1.0
Author: Christof Lewerenz [aut, cre]
Maintainer: Christof Lewerenz <christof.lewerenz@gmx.net>
Description: Simple handling of survey data. Smart handling of meta-information like e.g. variable-labels value-labels and scale-levels. Easy access and validation of meta-information. Useage of value labels and values respectively for subsetting and recoding data.
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-US
Suggests: testthat (>= 3.0.0)
Imports: methods, stats
URL: https://github.com/clewerenz/ilabelled
BugReports: https://github.com/clewerenz/ilabelled/issues
Depends: R (>= 2.10)
NeedsCompilation: yes
Packaged: 2024-05-31 23:01:36 UTC; lnx
Repository: CRAN
Date/Publication: 2024-06-04 09:51:52 UTC

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New package geostan with initial version 0.6.2
Package: geostan
Title: Bayesian Spatial Analysis
Version: 0.6.2
Date: 2024-05-31
URL: https://connordonegan.github.io/geostan/
BugReports: https://github.com/ConnorDonegan/geostan/issues
Description: For spatial data analysis; provides exploratory spatial analysis tools, spatial regression models, disease mapping models, model diagnostics, and special methods for inference with small area survey data (e.g., the America Community Survey (ACS)) and censored population health surveillance data. Models are pre-specified using the Stan programming language, a platform for Bayesian inference using Markov chain Monte Carlo (MCMC). References: Carpenter et al. (2017) <doi:10.18637/jss.v076.i01>; Donegan (2021) <doi:10.31219/osf.io/3ey65>; Donegan (2022) <doi:10.21105/joss.04716>; Donegan, Chun and Hughes (2020) <doi:10.1016/j.spasta.2020.100450>; Donegan, Chun and Griffith (2021) <doi:10.3390/ijerph18136856>; Morris et al. (2019) <doi:10.1016/j.sste.2019.100301>.
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
Biarch: true
Depends: R (>= 3.4)
Imports: spdep (>= 1.0), sf (>= 1.0-10), ggplot2 (>= 3.0.0), methods, graphics, stats, MASS, truncnorm, signs, gridExtra, utils, Matrix (>= 1.3), Rcpp (>= 0.12.0), RcppParallel (>= 5.0.1), rstan (>= 2.26.0), rstantools (>= 2.1.1)
LinkingTo: BH (>= 1.66.0), Rcpp (>= 0.12.0), RcppEigen (>= 0.3.3.3.0), RcppParallel (>= 5.0.1), rstan (>= 2.26.0), StanHeaders (>= 2.26.0)
Suggests: testthat, knitr, rmarkdown, bayesplot
SystemRequirements: GNU make
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2024-06-02 20:27:46 UTC; connor
Author: Connor Donegan [aut, cre] , Mitzi Morris [ctb], Amy Tims [ctb]
Maintainer: Connor Donegan <connor.donegan@gmail.com>
Repository: CRAN
Date/Publication: 2024-06-04 09:45:37 UTC

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Package genfrn updated to version 0.1.4 with previous version 0.1.3 dated 2024-05-27

Title: Generating Triangular and Trapezoidal Fuzzy Random Numbers via Uniform Distribution
Description: Triangular and trapezoidal fuzzy numbers are used to study fuzzy logic, fuzzy reasoning and approximating, fuzzy regression models, etc. This package builds the generating function for triangular and trapezoidal fuzzy numbers based on Souliotis et al. (2022)<doi:10.3390/math10183350>. They proposed a method for the construction of fuzzy numbers via a cumulative distribution function based on the possibility theory.
Author: Atchanut Rattanalertnusorn [aut, cre]
Maintainer: Atchanut Rattanalertnusorn <atchanut_r@rmutt.ac.th>

Diff between genfrn versions 0.1.3 dated 2024-05-27 and 0.1.4 dated 2024-06-04

 DESCRIPTION |    6 +++---
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New package DNAmotif with initial version 0.1.0
Package: DNAmotif
Title: DNA Sequence Motifs
Version: 0.1.0
Description: Motifs within biological sequences show a significant role. This package utilizes a user-defined threshold value (window size and similarity) to create consensus segments or motifs through local alignment of dynamic programming with gap and it calculates the frequency of each identified motif, offering a detailed view of their prevalence within the dataset. It allows for thorough exploration and understanding of sequence patterns and their biological importance.
License: GPL-3
Encoding: UTF-8
Imports: stats, Biostrings, Rcpp
LinkingTo: Rcpp
NeedsCompilation: yes
Packaged: 2024-06-03 12:16:18 UTC; searc
Author: Subham Ghosh [aut, cre], UB Angadi [aut], Md Yeasin [aut], Dipro Sinha [aut], Saikath Das [aut]
Maintainer: Subham Ghosh <search4aghosh@gmail.com>
Repository: CRAN
Date/Publication: 2024-06-04 09:44:32 UTC

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New package CohortSymmetry with initial version 0.1.0
Package: CohortSymmetry
Title: Sequence Symmetry Analysis Using the Observational Medical Outcomes Partnership Common Data Model
Version: 0.1.0
Maintainer: Xihang Chen <xihang.chen@ndorms.ox.ac.uk>
Description: Calculating crude sequence ratio, adjusted sequence ratio and confidence intervals using data mapped to the Observational Medical Outcomes Partnership Common Data Model.
License: Apache License (>= 2)
Encoding: UTF-8
Suggests: testthat (>= 3.1.5), DBI (>= 1.0.0), DrugUtilisation (>= 0.5.0), CodelistGenerator, duckdb, cli, checkmate, odbc, RPostgres, tidyselect, flextable, gt, knitr, here, dbplyr (>= 2.5.0), rmarkdown
Imports: CDMConnector (>= 1.3.0), dplyr, ggplot2, magrittr, PatientProfiles, rlang, stringr, tibble, visOmopResults (>= 0.3.0), tidyr, omock (>= 0.2.0), stats, omopgenerics (>= 0.2.1)
URL: https://oxford-pharmacoepi.github.io/CohortSymmetry/
BugReports: https://github.com/oxford-pharmacoepi/CohortSymmetry/issues
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2024-05-31 23:07:48 UTC; xihangc
Author: Xihang Chen [aut, cre] , Tyman Stanford [aut] , Berta Raventos [aut] , Nicole Pratt [aut] , Ed Burn [aut] , Marti Catala [aut] , Danielle Newby [aut] , Nuria Mercade-Besora [aut] , Mike Du [aut] , Yuchen Guo [aut] , Kim Lopez [aut] , Marta Alcalde-He [...truncated...]
Repository: CRAN
Date/Publication: 2024-06-04 09:44:35 UTC

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Package CohortAlgebra updated to version 0.3.0 with previous version 0.2.1 dated 2024-06-02

Title: Use of Interval Algebra to Create New Cohort(s) from Existing Cohorts
Description: This software tool is designed to generate new cohorts utilizing data from previously instantiated cohorts. It employs interval algebra operators such as UNION, INTERSECT, and MINUS to manipulate the data within the instantiated cohorts and create new cohorts.
Author: Gowtham Rao [aut, cre], Observational Health Data Science and Informatics [cph]
Maintainer: Gowtham Rao <rao@ohdsi.org>

Diff between CohortAlgebra versions 0.2.1 dated 2024-06-02 and 0.3.0 dated 2024-06-04

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 5 files changed, 47 insertions(+), 76 deletions(-)

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New package CohortCharacteristics with initial version 0.2.1
Package: CohortCharacteristics
Title: Summarise and Visualise Characteristics of Patients in the OMOP CDM
Version: 0.2.1
Maintainer: Marti Catala <marti.catalasabate@ndorms.ox.ac.uk>
Description: Summarise and visualise the characteristics of patients in data mapped to the Observational Medical Outcomes Partnership (OMOP) common data model (CDM).
License: Apache License (>= 2)
Encoding: UTF-8
Suggests: covr, duckdb (>= 0.9.0), testthat (>= 3.1.5), knitr, CodelistGenerator, rmarkdown, glue, odbc, ggplot2, spelling, RPostgres, dbplyr, PaRe, here, magick, plotly, ggraph, DT, cowplot, DiagrammeRsvg, DBI, gt, flextable, tictoc, withr, scales
Imports: CDMConnector (>= 1.3.2), dplyr, tidyr, checkmate, rlang, cli, stringr, omopgenerics (>= 0.2.0), visOmopResults (>= 0.3.0), PatientProfiles (>= 1.0.0), ggpubr, magrittr, snakecase, DiagrammeR
URL: https://darwin-eu-dev.github.io/CohortCharacteristics/
BugReports: https://github.com/darwin-eu-dev/CohortCharacteristics/issues
Language: en-US
Depends: R (>= 2.10)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2024-06-03 15:50:42 UTC; martics
Author: Marti Catala [aut, cre] , Yuchen Guo [aut] , Mike Du [aut] , Kim Lopez-Guell [aut] , Edward Burn [aut] , Nuria Mercade-Besora [ctb] , Marta Alcalde [aut]
Repository: CRAN
Date/Publication: 2024-06-04 09:46:58 UTC

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New package codewhere with initial version 0.1.1
Package: codewhere
Title: Find the Location of an R Package's Code
Version: 0.1.1
Description: Find the location of the code for an R package based on the package's name or string representation. Checks on 'CRAN' based on information in the 'URL' field or 'BioConductor' and 'GitHub' based on constructing a URL, and verifies all paths via testing for a successful response. This can be useful when automating static code analysis based on a list of package names, and similar tasks.
License: MIT + file LICENSE
URL: https://thisisnic.github.io/codewhere/, https://github.com/thisisnic/codewhere/
BugReports: https://github.com/thisisnic/codewhere/issues
Encoding: UTF-8
Imports: httr
Suggests: httptest, testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2024-06-01 08:59:44 UTC; nic
Author: Nic Crane [aut, cre, cph]
Maintainer: Nic Crane <thisisnic@gmail.com>
Repository: CRAN
Date/Publication: 2024-06-04 09:47:09 UTC

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Package care4cmodel updated to version 1.0.2 with previous version 1.0.1 dated 2024-02-28

Title: Carbon-Related Assessment of Silvicultural Concepts
Description: A simulation model and accompanying functions that support assessing silvicultural concepts on the forest estate level with a focus on the CO2 uptake by wood growth and CO2 emissions by forest operations. For achieving this, a virtual forest estate area is split into the areas covered by typical phases of the silvicultural concept of interest. Given initial area shares of these phases, the dynamics of these areas is simulated. The typical carbon stocks and flows which are known for all phases are attributed post-hoc to the areas and upscaled to the estate level. CO2 emissions by forest operations are estimated based on the amounts and dimensions of the harvested timber. Probabilities of damage events are taken into account.
Author: Peter Biber [aut, cre, cph] , Stefano Grigolato [ctb] , Julia Schmucker [ctb] , Enno Uhl [ctb] , Hans Pretzsch [ctb]
Maintainer: Peter Biber <p.biber@tum.de>

Diff between care4cmodel versions 1.0.1 dated 2024-02-28 and 1.0.2 dated 2024-06-04

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Package box.linters updated to version 0.9.1 with previous version 0.9.0 dated 2024-05-25

Title: Linters for 'box' Modules
Description: Static code analysis of 'box' modules. The package enhances code quality by providing linters that check for common issues, enforce best practices, and ensure consistent coding standards.
Author: Ricardo Rodrigo Basa [aut, cre], Jakub Nowicki [aut], Appsilon Sp. z o.o. [cph]
Maintainer: Ricardo Rodrigo Basa <opensource+rodrigo@appsilon.com>

Diff between box.linters versions 0.9.0 dated 2024-05-25 and 0.9.1 dated 2024-06-04

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 tests/testthat/test-box_unused_attached_pkg_fun_linter.R |   72 +++++
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 28 files changed, 768 insertions(+), 47 deletions(-)

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New package bayesEO with initial version 0.2.1
Package: bayesEO
Version: 0.2.1
Title: Bayesian Smoothing of Remote Sensing Image Classification
Maintainer: Gilberto Camara <gilberto.camara.inpe@gmail.com>
Description: A Bayesian smoothing method for post-processing of remote sensing image classification which refines the labelling in a classified image in order to enhance its classification accuracy. Combines pixel-based classification methods with a spatial post-processing method to remove outliers and misclassified pixels.
Encoding: UTF-8
Language: en-US
Depends: R (>= 4.0.0)
URL: https://github.com/e-sensing/bayesEO/
BugReports: https://github.com/e-sensing/bayesEO/issues
License: GPL-3
ByteCompile: true
Imports: dplyr, ggplot2, grDevices, purrr, Rcpp, stars, stats, terra, tibble, tidyr, tmap, yaml
Suggests: RcppArmadillo, testthat
LinkingTo: Rcpp, RcppArmadillo
NeedsCompilation: yes
Packaged: 2024-06-02 02:25:45 UTC; gilberto
Author: Gilberto Camara [aut, cre], Renato Assuncao [aut], Rolf Simoes [aut], Felipe Souza [aut]
Repository: CRAN
Date/Publication: 2024-06-04 09:44:41 UTC

More information about bayesEO at CRAN
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New package autostats with initial version 0.4.1
Package: autostats
Title: Auto Stats
Version: 0.4.1
Maintainer: Harrison Tietze <harrison4192@gmail.com>
Description: Automatically do statistical exploration. Create formulas using 'tidyselect' syntax, and then determine cross-validated model accuracy and variable contributions using 'glm' and 'xgboost'. Contains additional helper functions to create and modify formulas. Has a flagship function to quickly determine relationships between categorical and continuous variables in the data set.
Encoding: UTF-8
Imports: dplyr, stringr, tidyselect, purrr, janitor, tibble, rlang, stats, rlist, broom, magrittr, ggeasy, ggplot2, jtools, gtools, ggthemes, patchwork, tidyr, xgboost, parsnip, recipes, rsample, tune, workflows, framecleaner, presenter, yardstick, dials, party, data.table, nnet, recosystem, Ckmeans.1d.dp, broom.mixed, igraph
URL: https://harrison4192.github.io/autostats/, https://github.com/Harrison4192/autostats
BugReports: https://github.com/Harrison4192/autostats/issues
Suggests: knitr, rmarkdown, forcats, parallel, doParallel, hardhat, flextable, glmnet, ggstance, Matrix, BBmisc, readr, lubridate, ranger, XICOR
VignetteBuilder: knitr
License: MIT + file LICENSE
NeedsCompilation: no
Packaged: 2024-06-03 05:56:13 UTC; harrisontietze
Author: Harrison Tietze [aut, cre]
Depends: R (>= 3.5.0)
Repository: CRAN
Date/Publication: 2024-06-04 09:44:44 UTC

More information about autostats at CRAN
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Package apollo updated to version 0.3.3 with previous version 0.3.2 dated 2024-04-15

Title: Tools for Choice Model Estimation and Application
Description: Choice models are a widely used technique across numerous scientific disciplines. The Apollo package is a very flexible tool for the estimation and application of choice models in R. Users are able to write their own model functions or use a mix of already available ones. Random heterogeneity, both continuous and discrete and at the level of individuals and choices, can be incorporated for all models. There is support for both standalone models and hybrid model structures. Both classical and Bayesian estimation is available, and multiple discrete continuous models are covered in addition to discrete choice. Multi-threading processing is supported for estimation and a large number of pre and post-estimation routines, including for computing posterior (individual-level) distributions are available. For examples, a manual, and a support forum, visit <http://www.ApolloChoiceModelling.com>. For more information on choice models see Train, K. (2009) <isbn:978-0-521-74738-7> and [...truncated...]
Author: Stephane Hess [aut, cre], David Palma [aut], Thomas Hancock [ctb]
Maintainer: Stephane Hess <S.Hess@leeds.ac.uk>

Diff between apollo versions 0.3.2 dated 2024-04-15 and 0.3.3 dated 2024-06-04

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 apollo-0.3.3/apollo/MD5                              |  110 +-
 apollo-0.3.3/apollo/NAMESPACE                        |    4 
 apollo-0.3.3/apollo/R/apollo_avgInterDraws.R         |   17 
 apollo-0.3.3/apollo/R/apollo_basTest.R               |    2 
 apollo-0.3.3/apollo/R/apollo_bootstrap.R             |    4 
 apollo-0.3.3/apollo/R/apollo_classAlloc.R            |    2 
 apollo-0.3.3/apollo/R/apollo_combineModels.R         |   44 
 apollo-0.3.3/apollo/R/apollo_compareInputs.R         |    2 
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 apollo-0.3.3/apollo/R/apollo_el.R                    |    2 
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 apollo-0.3.3/apollo/R/apollo_estimate.R              |   45 
 apollo-0.3.3/apollo/R/apollo_estimateHB.R            |    8 
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 apollo-0.3.3/apollo/R/apollo_lc.R                    |   18 
 apollo-0.3.3/apollo/R/apollo_lcConditionals.R        |   11 
 apollo-0.3.3/apollo/R/apollo_lcEM.R                  |   11 
 apollo-0.3.3/apollo/R/apollo_lrTest.R                |    2 
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 apollo-0.3.3/apollo/R/apollo_mdcnev.R                |    4 
 apollo-0.3.3/apollo/R/apollo_mixConditionals.R       |    4 
 apollo-0.3.3/apollo/R/apollo_mixEM.R                 |    6 
 apollo-0.3.3/apollo/R/apollo_mixUnconditionals.R     |    4 
 apollo-0.3.3/apollo/R/apollo_mnl.R                   |  128 ++
 apollo-0.3.3/apollo/R/apollo_modifyUserDefFunc.R     |   24 
 apollo-0.3.3/apollo/R/apollo_nl.R                    |    2 
 apollo-0.3.3/apollo/R/apollo_normalDensity.R         |    8 
 apollo-0.3.3/apollo/R/apollo_ol.R                    |  142 ++
 apollo-0.3.3/apollo/R/apollo_op.R                    |    6 
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 apollo-0.3.3/apollo/R/apollo_panelProd.R             |  331 +++---
 apollo-0.3.3/apollo/R/apollo_prepareProb.R           |   19 
 apollo-0.3.3/apollo/R/apollo_preprocess.R            |   23 
 apollo-0.3.3/apollo/R/apollo_rrm.R                   |    2 
 apollo-0.3.3/apollo/R/apollo_sharesTest.R            |    2 
 apollo-0.3.3/apollo/R/apollo_validateControl.R       |   12 
 apollo-0.3.3/apollo/R/apollo_varcov.R                |   26 
 apollo-0.3.3/apollo/R/apollo_weighting.R             |    1 
 apollo-0.3.3/apollo/build/vignette.rds               |binary
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 apollo-0.3.3/apollo/man/apollo_varcov.Rd             |    1 
 60 files changed, 1589 insertions(+), 1143 deletions(-)

More information about apollo at CRAN
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Package ANSM5 updated to version 1.0.1 with previous version 1.0.0 dated 2024-05-28

Title: Functions and Data for the Book "Applied Nonparametric Statistical Methods", 5th Edition
Description: Functions and data to accompany the 5th edition of the book "Applied Nonparametric Statistical Methods" (4th edition: Sprent & Smeeton, 2024, ISBN:158488701X), the revisions from the 4th edition including a move from describing the output from a miscellany of statistical software packages to using R. While the output from many of the functions can also be obtained using a range of other R functions, this package provides functions in a unified setting and give output using both p-values and confidence intervals, exemplifying the book's approach of treating p-values as a guide to statistical importance and not an end product in their own right.
Author: Neil Spencer [aut, cre, cph]
Maintainer: Neil Spencer <neilhspencer@gmail.com>

Diff between ANSM5 versions 1.0.0 dated 2024-05-28 and 1.0.1 dated 2024-06-04

 DESCRIPTION                        |    6 
 MD5                                |   10 
 NEWS.md                            |    2 
 R/pearson.R                        |  410 ++++++++++++++++++-------------------
 tests/testthat/test-pearson.R      |    4 
 tests/testthat/test-pearson.beta.R |    2 
 6 files changed, 219 insertions(+), 215 deletions(-)

More information about ANSM5 at CRAN
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Package RMSDp (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:

2023-11-16 0.1.0

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