Tue, 06 Apr 2021

Package RJcluster updated to version 2.5.0 with previous version 0.1.2 dated 2021-03-10

Title: RJ Clustering Algorithm
Description: Clustering algorithm for high dimensional data. This algorithm is ideal for data where N << P. Assuming that P feature measurements on N objects are arranged in an N×P matrix X, this package provides clustering based on the left Gram matrix XX^T. When the P-dimensional feature vectors of objects are drawn independently from a K distinct mixture distribution, the N-dimensional rows of the modified Gram matrix XX^T/P converges almost surely to K distinct cluster means. This transformation/projection thus allows the clusters to be tighter with order of P. To simulate data, type "help('simulate_HD_data')" and to learn how to use the clustering algorithm, type "help('RJclust')".
Author: Rachael Shudde [aut, cre], Shahina Rahman [aut], Valen Johnson [aut]
Maintainer: Rachael Shudde <rachael.shudde@gmail.com>

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Package rheroicons updated to version 0.3.2 with previous version 0.3.1 dated 2021-02-26

Title: A Zero Dependency 'SVG' Icon Library for 'Shiny'
Description: An implementation of the 'Heroicons' icon library for 'shiny' applications and other 'R' web-based projects. You can search, render, and customize icons without 'CSS' or 'JavaScript' dependencies.
Author: David Ruvolo [aut, cre] (<https://orcid.org/0000-0002-5745-5298>), Adam Wathan [ctb, cph] (Author of heroicons library), Steve Schoger [ctb, cph] (Author of heroicons library)
Maintainer: David Ruvolo <dcruvolo@gmail.com>

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Package liver updated to version 1.6 with previous version 1.5 dated 2021-03-09

Title: "Eating the Liver of Data Science"
Description: Provides a collection of helper functions that make various techniques from data science more user-friendly for non-experts. In this way, our aim is to allow non-experts to become familiar with the techniques with only a minimal level of coding knowledge. Indeed, following an ancient Persian idiom, we refer to this as "eating the liver of data science" which could be interpreted as "getting intimately close with data science". Examples of procedures we include are: data partitioning for out-of-sample testing, computing Mean Squared Error (MSE) for quantifying prediction accuracy, and data transformation (z-score and min-max). Besides such helper functions, the package also includes several interesting datasets that are useful for multivariate analysis.
Author: Reza Mohammadi [aut, cre] (<https://orcid.org/0000-0001-9538-0648>), Kevin Burke [aut]
Maintainer: Reza Mohammadi <a.mohammadi@uva.nl>

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Package stplanr updated to version 0.8.2 with previous version 0.8.1 dated 2021-01-07

Title: Sustainable Transport Planning
Description: Tools for transport planning with an emphasis on spatial transport data and non-motorized modes. Enables common transport planning tasks including: downloading and cleaning transport datasets; creating geographic "desire lines" from origin-destination (OD) data; route assignment, locally and via interfaces to routing services such as <https://cyclestreets.net/> and calculation of route segment attributes such as bearing. The package implements the 'travel flow aggregration' method described in Morgan and Lovelace (2020) <doi:10.1177/2399808320942779>. Further information on the package's aim and scope can be found in the vignettes and in a paper in the R Journal (Lovelace and Ellison 2018) <doi:10.32614/RJ-2018-053>.
Author: Robin Lovelace [aut, cre] (<https://orcid.org/0000-0001-5679-6536>), Richard Ellison [aut], Malcolm Morgan [aut] (<https://orcid.org/0000-0002-9488-9183>), Barry Rowlingson [ctb], Nick Bearman [ctb], Nikolai Berkoff [ctb], Scott Chamberlain [rev] (Scott reviewed the package for rOpenSci, see https://github.com/ropensci/onboarding/issues/10), Mark Padgham [ctb], Andrea Gilardi [ctb] (<https://orcid.org/0000-0002-9424-7439>)
Maintainer: Robin Lovelace <rob00x@gmail.com>

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Package regressoR updated to version 1.2.1 with previous version 1.1.9 dated 2020-07-01

Title: Regression Data Analysis System
Description: Perform a supervised data analysis on a database through a 'shiny' graphical interface. It includes methods such as linear regression, penalized regression, k-nearest neighbors, decision trees, ada boosting, extreme gradient boosting, random forest, neural networks, deep learning and support vector machines.
Author: Oldemar Rodriguez R. [aut, cre], Andres Navarro D. [ctb, prg], Diego Jimenez A. [ctb, prg], Ariel Arroyo S. [ctb, prg]
Maintainer: Oldemar Rodriguez R. <oldemar.rodriguez@ucr.ac.cr>

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Package beakr updated to version 0.4.3 with previous version 0.4.2 dated 2021-03-04

Title: A Minimalist Web Framework for R
Description: A minimalist web framework for developing application programming interfaces in R that provides a flexible framework for handling common HTTP-requests, errors, logging, and an ability to integrate any R code as server middle-ware.
Author: Hans Martin [aut], Jonathan Callahan [aut, cre]
Maintainer: Jonathan Callahan <jonathan.s.callahan@gmail.com>

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Package WDI updated to version 2.7.4 with previous version 2.7.3 dated 2021-03-30

Title: World Development Indicators and Other World Bank Data
Description: Search and download data from over 40 databases hosted by the World Bank, including the World Development Indicators ('WDI'), International Debt Statistics, Doing Business, Human Capital Index, and Sub-national Poverty indicators.
Author: Vincent Arel-Bundock [aut, cre] (<https://orcid.org/0000-0003-2042-7063>), Etienne Bacher [ctb]
Maintainer: Vincent Arel-Bundock <vincent.arel-bundock@umontreal.ca>

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Package walker updated to version 1.0.2 with previous version 1.0.1-1 dated 2021-01-30

Title: Bayesian Generalized Linear Models with Time-Varying Coefficients
Description: Bayesian generalized linear models with time-varying coefficients as in Helske (2020, <arXiv:2009.07063>). Gaussian, Poisson, and binomial observations are supported. The Markov chain Monte Carlo (MCMC) computations are done using Hamiltonian Monte Carlo provided by Stan, using a state space representation of the model in order to marginalise over the coefficients for efficient sampling. For non-Gaussian models, the package uses the importance sampling type estimators based on approximate marginal MCMC as in Vihola, Helske, Franks (2020, <doi:10.1111/sjos.12492>).
Author: Jouni Helske [aut, cre] (<https://orcid.org/0000-0001-7130-793X>)
Maintainer: Jouni Helske <jouni.helske@iki.fi>

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Package UCSCXenaTools updated to version 1.4.4 with previous version 1.4.3 dated 2021-03-22

Title: Download and Explore Datasets from UCSC Xena Data Hubs
Description: Download and explore datasets from UCSC Xena data hubs, which are a collection of UCSC-hosted public databases such as TCGA, ICGC, TARGET, GTEx, CCLE, and others. Databases are normalized so they can be combined, linked, filtered, explored and downloaded.
Author: Shixiang Wang [aut, cre] (<https://orcid.org/0000-0001-9855-7357>), Xue-Song Liu [aut] (<https://orcid.org/0000-0002-7736-0077>), Martin Morgan [ctb], Christine Stawitz [rev] (Christine reviewed the package for ropensci, see <https://github.com/ropensci/software-review/issues/315>), Carl Ganz [rev] (Carl reviewed the package for ropensci, see <https://github.com/ropensci/software-review/issues/315>)
Maintainer: Shixiang Wang <w_shixiang@163.com>

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Package NSM3 updated to version 1.16 with previous version 1.15 dated 2020-08-31

Title: Functions and Datasets to Accompany Hollander, Wolfe, and Chicken - Nonparametric Statistical Methods, Third Edition
Description: Designed to replace the tables which were in the back of the first two editions of Hollander and Wolfe - Nonparametric Statistical Methods. Exact procedures are performed when computationally possible. Monte Carlo and Asymptotic procedures are performed otherwise. For those procedures included in the base packages, our code simply provides a wrapper to standardize the output with the other procedures in the package.
Author: Grant Schneider, Eric Chicken, Rachel Becvarik
Maintainer: Grant Schneider <gschneidz@gmail.com>

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Package nadiv updated to version 2.17.1 with previous version 2.17.0 dated 2021-01-14

Title: (Non)Additive Genetic Relatedness Matrices
Description: Constructs (non)additive genetic relationship matrices, and their inverses, from a pedigree to be used in linear mixed effect models (A.K.A. the 'animal model'). Also includes other functions to facilitate the use of animal models. Some functions have been created to be used in conjunction with the R package 'asreml' for the 'ASReml' software, which can be obtained upon purchase from 'VSN' international (<https://www.vsni.co.uk/software/asreml>).
Author: Matthew Wolak [cre, aut]
Maintainer: Matthew Wolak <matthewwolak@gmail.com>

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Package geneExpressionFromGEO updated to version 0.5 with previous version 0.4 dated 2021-01-25

Title: Retrieves Gene Expression Dataset and Gene Symbols from GEO Code
Description: A function that reads in the GEO code of a gene expression dataset, retrieves its data from GEO, (optional) retrieves the gene symbols of the dataset, and returns a simple dataframe table containing all the data. Platforms available: GPL11532, GPL23126, GPL6244, GPL80, GPL8300, GPL80, GPL96, GPL570, GPL571, GPL20115, GPL1293, GPL6102, GPL6104, GPL6883, GPL6884, GPL13497, GPL14550, GPL17077, GPL6480. GEO: Gene Expression Omnibus. ID: identifier code. The GEO datasets are downloaded from the URL <https://ftp.ncbi.nlm.nih.gov/geo/series/>.
Author: Davide Chicco [aut, cre]
Maintainer: Davide Chicco <davidechicco@davidechicco.it>

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Package dparser updated to version 1.3.1-3 with previous version 1.3.1-2 dated 2021-04-03

Title: Port of 'Dparser' Package
Description: A Scannerless GLR parser/parser generator. Note that GLR standing for "generalized LR", where L stands for "left-to-right" and R stands for "rightmost (derivation)". For more information see <https://en.wikipedia.org/wiki/GLR_parser>. This parser is based on the Tomita (1987) algorithm. (Paper can be found at <https://www.aclweb.org/anthology/P84-1073.pdf>). The original 'dparser' package documentation can be found at <http://dparser.sourceforge.net/>. This allows you to add mini-languages to R (like RxODE's ODE mini-language Wang, Hallow, and James 2015 <DOI:10.1002/psp4.12052>) or to parse other languages like 'NONMEM' to automatically translate them to R code. To use this in your code, add a LinkingTo dparser in your DESCRIPTION file and instead of using #include <dparse.h> use #include <dparser.h>. This also provides a R-based port of the make_dparser <http://dparser.sourceforge.net/d/make_dparser.cat> command called mkdparser(). Additionally you can parse an arbitrary grammar within R using the dparse() function, which works on most OSes and is mainly for grammar testing. The fastest parsing, of course, occurs at the C level, and is suggested.
Author: Matthew Fidler [aut, cre], John Plevyak [aut, cph]
Maintainer: Matthew Fidler <matthew.fidler@gmail.com>

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Package pkgload updated to version 1.2.1 with previous version 1.2.0 dated 2021-02-23

Title: Simulate Package Installation and Attach
Description: Simulates the process of installing a package and then attaching it. This is a key part of the 'devtools' package as it allows you to rapidly iterate while developing a package.
Author: Hadley Wickham [aut], Jim Hester [aut, cre], Winston Chang [aut], RStudio [cph], R Core team [ctb] (Some namespace and vignette code extracted from base R)
Maintainer: Jim Hester <jim.hester@rstudio.com>

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Package equateMultiple updated to version 0.1.0 with previous version 0.0.1 dated 2020-10-26

Title: Equating of Multiple Forms
Description: Equating of multiple forms using Item Response Theory (IRT) methods (Battauz M. (2017) <doi:10.1007/s11336-016-9517-x> and Haberman S. J. (2009) <doi:10.1002/j.2333-8504.2009.tb02197.x>).
Author: Michela Battauz
Maintainer: Michela Battauz <michela.battauz@uniud.it>

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Package clustertend updated to version 1.5 with previous version 1.4 dated 2015-05-19

Title: Check the Clustering Tendency
Description: Calculate some statistics aiming to help analyzing the clustering tendency of given data. In the first version, Hopkins' statistic is implemented.
Author: Kevin Wright [aut, cre] (<https://orcid.org/0000-0002-0617-8673>), Luo YiLan [aut], Zeng RuTong [aut]
Maintainer: Kevin Wright <kw.stat@gmail.com>

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Package cglasso updated to version 2.0.3 with previous version 2.0.2 dated 2021-01-21

Title: Conditional Graphical LASSO for Gaussian Graphical Models with Censored and Missing Values
Description: Conditional graphical lasso estimator is an extension of the graphical lasso proposed to estimate the conditional dependence structure of a set of p response variables given q predictors. This package provides suitable extensions developed to study datasets with censored and/or missing values. Standard conditional graphical lasso is available as a special case. Furthermore, the package provides an integrated set of core routines for visualization, analysis, and simulation of datasets with censored and/or missing values drawn from a Gaussian graphical model. Details about the implemented models can be found in Augugliaro et al. (2020b) <doi: 10.1007/s11222-020-09945-7>, Augugliaro et al. (2020a) <doi: 10.1093/biostatistics/kxy043>, Yin et al. (2001) <doi: 10.1214/11-AOAS494> and Stadler et al. (2012) <doi: 10.1007/s11222-010-9219-7>.
Author: Luigi Augugliaro [aut, cre] (<https://orcid.org/0000-0002-4603-7541>), Gianluca Sottile [aut] (<https://orcid.org/0000-0001-9347-7251>), Ernst C. Wit [aut] (<https://orcid.org/0000-0002-3671-9610>), Veronica Vinciotti [aut] (<https://orcid.org/0000-0002-2625-7977>)
Maintainer: Luigi Augugliaro <luigi.augugliaro@unipa.it>

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Package AzureGraph updated to version 1.2.2 with previous version 1.2.1 dated 2021-02-09

Title: Simple Interface to 'Microsoft Graph'
Description: A simple interface to the 'Microsoft Graph' API <https://docs.microsoft.com/en-us/graph/overview>. 'Graph' is a comprehensive framework for accessing data in various online Microsoft services. Currently, this package aims to provide an R interface only to the 'Azure Active Directory' part, with a view to supporting interoperability of R and 'Azure': users, groups, registered apps and service principals. However it can be easily extended to cover other services. Part of the 'AzureR' family of packages.
Author: Hong Ooi [aut, cre], Microsoft [cph]
Maintainer: Hong Ooi <hongooi73@gmail.com>

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Package Rsymphony updated to version 0.1-31 with previous version 0.1-30 dated 2021-03-20

Title: SYMPHONY in R
Description: An R interface to the SYMPHONY solver for mixed-integer linear programs.
Author: Reinhard Harter [aut], Kurt Hornik [aut, cre] (<https://orcid.org/0000-0003-4198-9911>), Stefan Theussl [aut], Cyrille Szymanski [ctb], Florian Schwendinger [ctb]
Maintainer: Kurt Hornik <Kurt.Hornik@R-project.org>

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Package precrec updated to version 0.12.5 with previous version 0.12.1 dated 2021-02-02

Title: Calculate Accurate Precision-Recall and ROC (Receiver Operator Characteristics) Curves
Description: Accurate calculations and visualization of precision-recall and ROC (Receiver Operator Characteristics) curves.
Author: Takaya Saito [aut, cre], Marc Rehmsmeier [aut]
Maintainer: Takaya Saito <takaya.saito@outlook.com>

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Package MDMAPR updated to version 0.2.2 with previous version 0.2.1 dated 2021-03-30

Title: Molecular Detection Mapping and Analysis Platform
Description: Runs a Shiny web application that merges raw 'qPCR' fluorescence data with related metadata to visualize species presence/absence detection patterns and assess data quality. The application calculates threshold values from raw fluorescence data using a method based on the second derivative method, Luu-The et al (2005) <doi:10.2144/05382RR05>, and utilizes the ‘chipPCR’ package by Rödiger, Burdukiewicz, & Schierack (2015) <doi:10.1093/bioinformatics/btv205> to calculate Cq values. The application has the ability to connect to a custom developed MySQL database to populate the applications interface. The application allows users to interact with visualizations such as a dynamic map, amplification curves and standard curves, that allow for zooming and/or filtering. It also enables the generation of customized exportable reports based on filtered mapping data.
Author: Alka Benawra <alkabenawra@rogers.com>
Maintainer: Alka Benawra <alkabenawra@rogers.com>

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Package LexisNexisTools updated to version 0.3.4 with previous version 0.3.3 dated 2020-12-13

Title: Working with Files from 'LexisNexis'
Description: My PhD supervisor once told me that everyone doing newspaper analysis starts by writing code to read in files from the 'LexisNexis' newspaper archive (retrieved e.g., from <http://www.nexis.com/> or any of the partner sites). However, while this is a nice exercise I do recommend, not everyone has the time. This package takes files downloaded from the newspaper archive of 'LexisNexis', reads them into R and offers functions for further processing.
Author: Johannes Gruber [aut, cre]
Maintainer: Johannes Gruber <j.gruber.1@research.gla.ac.uk>

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Package geostats updated to version 1.3 with previous version 1.2 dated 2021-03-13

Title: An Introduction to Statistics for Geoscientists
Description: A collection of datasets and simplified functions for an introductory (geo)statistics module at University College London. Provides functionality for compositional, directional and spatial data, including ternary diagrams, Wulff and Schmidt stereonets, and ordinary kriging interpolation. Implements logistic and (additive and centred) logratio transformations. Computes vector averages and concentration parameters for the von-Mises distribution. Includes a collection of natural and synthetic fractals, and a simulator for deterministic chaos using a magnetic pendulum example. The main purpose of these functions is pedagogical. Researchers can find more complete alternatives for these tools in other packages such as 'compositions', 'robCompositions', 'sp', 'gstat' and 'RFOC'. All the functions are written in plain R, with no compiled code and a minimal number of dependencies. Theoretical background and worked examples are available at <https://tinyurl.com/UCLgeostats/>.
Author: Pieter Vermeesch [aut, cre]
Maintainer: Pieter Vermeesch <p.vermeesch@ucl.ac.uk>

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Package phangorn updated to version 2.6.3 with previous version 2.6.2 dated 2021-03-22

Title: Phylogenetic Reconstruction and Analysis
Description: Allows for estimation of phylogenetic trees and networks using Maximum Likelihood, Maximum Parsimony, distance methods and Hadamard conjugation. Offers methods for tree comparison, model selection and visualization of phylogenetic networks as described in Schliep et al. (2017) <doi:10.1111/2041-210X.12760>.
Author: Klaus Schliep [aut, cre] (<https://orcid.org/0000-0003-2941-0161>), Emmanuel Paradis [aut] (<https://orcid.org/0000-0003-3092-2199>), Leonardo de Oliveira Martins [aut] (<https://orcid.org/0000-0001-5247-1320>), Alastair Potts [aut], Tim W. White [aut], Cyrill Stachniss [ctb], Michelle Kendall [ctb], Keren Halabi [ctb], Richel Bilderbeek [ctb], Kristin Winchell [ctb], Liam Revell [ctb], Mike Gilchrist [ctb], Jeremy Beaulieu [ctb], Brian O'Meara [ctb], Long Qu [ctb]
Maintainer: Klaus Schliep <klaus.schliep@gmail.com>

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Package dbplyr updated to version 2.1.1 with previous version 2.1.0 dated 2021-02-03

Title: A 'dplyr' Back End for Databases
Description: A 'dplyr' back end for databases that allows you to work with remote database tables as if they are in-memory data frames. Basic features works with any database that has a 'DBI' back end; more advanced features require 'SQL' translation to be provided by the package author.
Author: Hadley Wickham [aut, cre], Maximilian Girlich [aut], Edgar Ruiz [aut], RStudio [cph, fnd]
Maintainer: Hadley Wickham <hadley@rstudio.com>

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Package AdvancedBasketballStats updated to version 1.0.1 with previous version 1.0.0 dated 2021-02-16

Title: Advanced Basketball Statistics
Description: Provides different functionalities and calculations used in the world of basketball to analyze the statistics of the players, the statistics of the teams, the statistics of the quintets and the statistics of the plays. For more details of the calculations included in the package can be found in the book Basketball on Paper written by Dean Oliver.
Author: Francisco Javier Cantero [aut, cre], Juan Jose Cuadrado [aut], Universidad de Alcala de Henares [aut]
Maintainer: Francisco Javier Cantero <fco.cantero@edu.uah.es>

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Package UniprotR updated to version 2.0.6 with previous version 2.0.5 dated 2021-03-09

Title: Retrieving Information of Proteins from Uniprot
Description: Connect to Uniprot <https://www.uniprot.org/> to retrieve information about proteins using their accession number such information could be name or taxonomy information, For detailed information kindly read the publication <https://www.sciencedirect.com/science/article/pii/S1874391919303859>.
Author: Mohamed Soudy [aut, cre], Ali Mostafa [aut]
Maintainer: Mohamed Soudy <MohmedSoudy2009@gmail.com>

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Package RcmdrPlugin.RiskDemo updated to version 3.0 with previous version 2.0 dated 2018-10-03

Title: R Commander Plug-in for Risk Demonstration
Description: R Commander plug-in to demonstrate various actuarial and financial risks. It includes valuation of bonds and stocks, portfolio optimization, classical ruin theory, demography and epidemic.
Author: Arto Luoma
Maintainer: Arto Luoma <arto.luoma@wippies.com>

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New package lehdr with initial version 0.2.4
Package: lehdr
Title: Grab Longitudinal Employer-Household Dynamics (LEHD) Flat Files
Version: 0.2.4
Authors@R: c(person("Jamaal", "Green", role = c("cre","aut"), email="jamaal.green@gmail.com"), person("Liming", "Wang", role =c("aut"), email="lmwang@pdx.edu"), person("Dillon", "Mahmoudi", role =c("aut"), email="dillonm@umbc.edu"))
Maintainer: Jamaal Green <jamaal.green@gmail.com>
Description: Designed to query Longitudinal Employer-Household Dynamics (LEHD) workplace/residential association and origin-destination flat files and optionally aggregate Census block-level data to block group, tract, county, or state. Data comes from the LODES FTP server <https://lehd.ces.census.gov/data/lodes/LODES7/>.
Depends: R (>= 3.3.0)
License: MIT + file LICENSE
Encoding: UTF-8
Imports: readr, rlang, stringr, glue, httr, dplyr, rappdirs
Suggests: testthat, knitr, rmarkdown, devtools, pacman
VignetteBuilder: knitr
URL: https://github.com/jamgreen/lehdr/
BugReports: https://github.com/jamgreen/lehdr/issues/
NeedsCompilation: no
Packaged: 2021-04-04 16:32:54 UTC; jamaalg
Author: Jamaal Green [cre, aut], Liming Wang [aut], Dillon Mahmoudi [aut]
Repository: CRAN
Date/Publication: 2021-04-06 09:20:02 UTC

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New package vannstats with initial version 1.0.3.27
Package: vannstats
Title: Simplified Statistics for Vann PA 606
Version: 1.0.3.27
Description: Simplifies functions assess normality for bivariate and multivariate statistical techniques, including hst(), box(), and qq(). Plots designed to replicate those that would result from similar calls in 'SPSS'.
Depends: R (>= 3.2.3)
Imports: MASS, dplyr, ggplot2, rlang, tidyverse, car, purrr, stats, graphics
License: GPL-3
LazyData: true
NeedsCompilation: no
Author: Burrel Vann Jr [aut, cre]
Maintainer: Burrel Vann Jr <bvannjr@sdsu.edu>
Packaged: 2021-04-04 01:27:26 UTC; burrelvannjr
Repository: CRAN
Date/Publication: 2021-04-06 08:50:02 UTC

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Package valueEQ5D updated to version 0.7.1 with previous version 0.6.1 dated 2020-11-03

Title: Scoring the EQ-5D Descriptive System
Description: EQ-5D is a standard instrument (<https://euroqol.org/eq-5d-instruments/>) that measures the quality of life often used in clinical and economic evaluations of health care technologies. Both adult versions of EQ-5D (EQ-5D-3L and EQ-5D-5L) contain a descriptive system and visual analog scale. The descriptive system measures the patient's health in 5 dimensions: the 5L versions has 5 levels and 3L version has 3 levels. The descriptive system scores are usually converted to index values using country specific values sets (that incorporates the country preferences). This package allows the calculation of both descriptive system scores to the index value scores. The value sets for EQ-5D-3L are from the references mentioned in the website <https://euroqol.org/eq-5d-instruments/eq-5d-3l-about/valuation/> The value sets for EQ-5D-3L for a total of 31 countries are used for the valuation (see the user guide for a complete list of references). The value sets for EQ-5D-5L are obtained from references mentioned in the <https://euroqol.org/eq-5d-instruments/eq-5d-5l-about/valuation-standard-value-sets/> and other sources. The value sets for EQ-5D-5L for a total of 17 countries are used for the valuation (see the user guide for a complete list of references). The package can also be used to map 5L scores to 3L index values for 10 countries: Denmark, France, Germany, Japan, Netherlands, Spain, Thailand, UK, USA, and Zimbabwe. The value set and method for mapping are obtained from Van Hout et al (2012) <doi: 10.1016/j.jval.2012.02.008>.
Author: Sheeja Manchira Krishnan [aut, cre]
Maintainer: Sheeja Manchira Krishnan <sheejamk@gmail.com>

Diff between valueEQ5D versions 0.6.1 dated 2020-11-03 and 0.7.1 dated 2021-04-06

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New package surf with initial version 1.0.0
Package: surf
Title: Survey-Based Gross Flows Estimation
Version: 1.0.0
Author: Guilherme Jacob
Date: 2021-04-02
Maintainer: Guilherme Jacob <guilhermejacob91@gmail.com>
Description: Estimation of gross flows under non-response and complex sampling designs, using Gutiérrez, Nascimento Silva and Trujillo (2014) <https://www150.statcan.gc.ca/n1/pub/12-001-x/2014002/article/14113-eng.pdf> complex sampling extension of the non-response model developed by Stasny (1987) <https://www.scb.se/contentassets/ca21efb41fee47d293bbee5bf7be7fb3/some-markov-chain-models-for-nonresponse-in-estimating-gross-labor-force-flows.pdf>. It estimates the gross flows process under non-response by modelling the observable cross-tabulation counts as a two-stage Markov Chain process, combining (1) the unobservable Markov Chain describing the transition of states; and (2) the non-response process, given by the initial response probabilities and the response/non-response transition probabilities.
BugReports: https://github.com/guilhermejacob/surf
Depends: R (>= 3.5.0), stats, Matrix
Imports: numDeriv, survey, MASS, abind
License: GPL-3
LazyData: true
Suggests: testthat, sampling, rmarkdown, knitr
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2021-04-02 22:41:17 UTC; guilherme
Repository: CRAN
Date/Publication: 2021-04-06 08:10:03 UTC

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New package readsparse with initial version 0.1.1-2
Package: readsparse
Title: Read and Write Sparse Matrices in 'SVMLight' and 'LibSVM' Formats
Version: 0.1.1-2
Date: 2021-04-02
Author: David Cortes
Maintainer: David Cortes <david.cortes.rivera@gmail.com>
URL: https://github.com/david-cortes/readsparse
BugReports: https://github.com/david-cortes/readsparse/issues
Description: Read and write labelled sparse matrices in text format as used by software such as 'SVMLight', 'LibSVM', 'ThunderSVM', 'LibFM', 'xLearn', 'XGBoost', 'LightGBM', and others. Supports labelled data for regression, classification (binary, multi-class, multi-label), and ranking (with 'qid' field), and can handle header metadata and comments in files.
License: BSD_2_clause + file LICENSE
Imports: Rcpp (>= 1.0.5), Matrix, methods
Suggests: testthat
LinkingTo: Rcpp
NeedsCompilation: yes
Packaged: 2021-04-02 23:03:09 UTC; david
Repository: CRAN
Date/Publication: 2021-04-06 08:20:02 UTC

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New package MultBiplotR with initial version 1.3.30
Package: MultBiplotR
Title: Multivariate Analysis Using Biplots in R
Version: 1.3.30
Date: 2021-03-30
Author: Jose Luis Vicente-Villardon
Maintainer: Jose Luis Vicente-Villardon <villardon@usal.es>
Description: Several multivariate techniques from a biplot perspective. It is the translation (with many improvements) into R of the previous package developed in 'Matlab'. The package contains some of the main developments of my team during the last 30 years together with some more standard techniques. Package includes: Classical Biplots, HJ-Biplot, Canonical Biplots, MANOVA Biplots, Correspondence Analysis, Canonical Correspondence Analysis, Canonical STATIS-ACT, Logistic Biplots for binary and ordinal data, Multidimensional Unfolding, External Biplots for Principal Coordinates Analysis or Multidimensional Scaling, among many others. References can be found in the help of each procedure.
License: GPL (>= 2)
Encoding: UTF-8
Repository: CRAN
Depends: R (>= 4.0.0)
Suggests:
Imports: MASS, scales, geometry, deldir, mirt, GPArotation, optimr, Hmisc, car, dunn.test, gplots, lattice, polycor, dae, rgl, xtable, mvtnorm
LazyData: yes
Archs: i386, x64
NeedsCompilation: no
Packaged: 2021-04-03 15:31:13 UTC; villardon
Date/Publication: 2021-04-06 08:50:09 UTC

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Package IsoplotRgui updated to version 3.8 with previous version 3.7 dated 2021-03-15

Title: Web Interface to 'IsoplotR'
Description: Provides a graphical user interface to the 'IsoplotR' package for radiometric geochronology. The GUI runs in an internet browser and can either be used offline, or hosted on a server to provide online access to the 'IsoplotR' toolbox.
Author: Pieter Vermeesch [aut, cre], Tim Band [ctb]
Maintainer: Pieter Vermeesch <p.vermeesch@ucl.ac.uk>

Diff between IsoplotRgui versions 3.7 dated 2021-03-15 and 3.8 dated 2021-04-06

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New package gwpcormapper with initial version 0.1.2
Package: gwpcormapper
Title: Geographically Weighted Partial Correlation Mapper
Version: 0.1.2
Authors@R: c(person(given = "Joseph Emile Honour", family = "Percival", role = c("aut", "cre"), email = "ipercival@gmail.com", comment = c(ORCID = "0000-0001-5941-4601")), person(given = "Narumasa", family = "Tsutsumida", role = "aut", email = "rsnaru.jp@gmail.com", comment = c(ORCID = "0000-0002-6333-0301")))
Description: An interactive mapping tool for geographically weighted correlation and partial correlation. Geographically weighted partial correlation coefficients are calculated following (Percival and Tsutsumida, 2017)<doi:10.1553/giscience2017_01_s36> and are described in greater detail in (Tsutsumida et al., 2019)<doi:10.5194/ica-abs-1-372-2019> and (Percival et al., 2021)<arXiv:2101.03491>.
License: GPL-3
Imports: config, golem, shiny, processx, attempt, DT, glue, htmltools, shinydashboard, sf, dplyr, geodist, plotly, crosstalk, viridis, leaflet, tools, shinyjs, Rcpp, corpcor, pkgload, methods
LinkingTo: Rcpp
Encoding: UTF-8
LazyData: true
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
URL: https://github.com/gwpcor/gwpcormapper
BugReports: https://github.com/gwpcor/gwpcormapper/issues
Depends: R (>= 2.10)
NeedsCompilation: yes
Packaged: 2021-04-01 23:47:51 UTC; iosefa
Author: Joseph Emile Honour Percival [aut, cre] (<https://orcid.org/0000-0001-5941-4601>), Narumasa Tsutsumida [aut] (<https://orcid.org/0000-0002-6333-0301>)
Maintainer: Joseph Emile Honour Percival <ipercival@gmail.com>
Repository: CRAN
Date/Publication: 2021-04-06 08:10:06 UTC

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New package gtfsio with initial version 0.1.0
Package: gtfsio
Title: Read and Write General Transit Feed Specification (GTFS) Files
Version: 0.1.0
Authors@R: c(person(given = "Daniel", family = "Herszenhut", role = c("aut", "cre"), email = "dhersz@gmail.com", comment = c(ORCID = "0000-0001-8066-1105")), person(given = "Flavio", family = "Poletti", role = "ctb", email = "flavio.poletti@hotmail.ch"), person(given = "Mark", family = "Padgham", role = "ctb", email = "mark.padgham@email.com"), person(given = "Rafael H. M.", family = "Pereira", role = "ctb", email = "rafa.pereira.br@gmail.com", comment = c(ORCID = "0000-0003-2125-7465")), person(given = "Tom", family = "Buckley", role = "ctb", email = "tom@tbuckl.com"), person(given = "Ipea - Institute for Applied Economic Research", role = c("cph", "fnd")))
Description: Tools for the development of packages related to General Transit Feed Specification (GTFS) files. Establishes a standard for representing GTFS feeds using R data types. Provides fast and flexible functions to read and write GTFS feeds while sticking to this standard. Defines a basic 'gtfs' class which is meant to be extended by packages that depend on it. And offers utility functions that support checking the structure of GTFS objects.
License: MIT + file LICENSE
URL: https://r-transit.github.io/gtfsio/, https://github.com/r-transit/gtfsio
BugReports: https://github.com/r-transit/gtfsio/issues
Imports: data.table, utils, zip
Suggests: knitr, rmarkdown, tinytest
VignetteBuilder: knitr
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2021-04-04 00:06:08 UTC; dhersz
Author: Daniel Herszenhut [aut, cre] (<https://orcid.org/0000-0001-8066-1105>), Flavio Poletti [ctb], Mark Padgham [ctb], Rafael H. M. Pereira [ctb] (<https://orcid.org/0000-0003-2125-7465>), Tom Buckley [ctb], Ipea - Institute for Applied Economic Research [cph, fnd]
Maintainer: Daniel Herszenhut <dhersz@gmail.com>
Repository: CRAN
Date/Publication: 2021-04-06 08:50:05 UTC

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New package GetFREData with initial version 0.6
Package: GetFREData
Title: Reading FRE Corporate Data of Public Traded Companies from B3
Version: 0.6
Date: 2021-04-03
Authors@R: c(person("Marcelo", "Perlin", email = "marceloperlin@gmail.com", role = c("aut", "cre")), person("Guilherme", "Kirch", email = "guilhermekirch@gmail.com", role = c("aut")))
Description: Reads corporate data such as board composition and compensation for companies traded at B3, the Brazilian exchange <http://www.b3.com.br/>. All data is downloaded and imported from the ftp site <http://dados.cvm.gov.br/dados/CIA_ABERTA/DOC/FRE/>.
Depends: R (>= 3.5.0)
Imports: stringr, xml2, dplyr, readr, curl, lubridate, magrittr, purrr, memoise, rvest, tidyr, XML
ByteCompile: true
License: GPL-2
BugReports: https://github.com/msperlin/GetFREData/issues
URL: https://github.com/msperlin/GetFREData/
LazyData: false
Suggests: knitr, rmarkdown, testthat, ggplot2
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-04-03 20:06:33 UTC; msperlin
Author: Marcelo Perlin [aut, cre], Guilherme Kirch [aut]
Maintainer: Marcelo Perlin <marceloperlin@gmail.com>
Repository: CRAN
Date/Publication: 2021-04-06 08:50:16 UTC

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New package gamlss.lasso with initial version 1.0-0
Package: gamlss.lasso
Description: Interface for extra high-dimensional smooth functions for Generalized Additive Models for Location Scale and Shape (GAMLSS) including lasso, ridge, elastic net and least angle regression.
Title: Extra Lasso-Type Additive Terms for GAMLSS
LazyLoad: yes
Version: 1.0-0
Date: 2021-04-01
Depends: R (>= 2.15.0), gamlss (>= 2.4.0), glmnet, lars, Matrix
Suggests: lattice
Authors@R: c(person("Florian", "Ziel", role = c("aut", "cre"), email = "florian.ziel@uni-due.de"), person("Peru", "Muniain", role = "aut"), person("Mikis", "Stasinopoulos", role = "ctb"))
Maintainer: Florian Ziel <florian.ziel@uni-due.de>
License: GPL-2 | GPL-3
URL: https://www.gamlss.com/
NeedsCompilation: no
Packaged: 2021-04-02 22:44:13 UTC; florian
Repository: CRAN
Date/Publication: 2021-04-06 08:20:05 UTC
Author: Florian Ziel [aut, cre], Peru Muniain [aut], Mikis Stasinopoulos [ctb]

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New package galah with initial version 1.0.0
Package: galah
Title: Atlas of Living Australia (ALA) Data and Resources in R
Version: 1.0.0
Authors@R: c(person("Matilda", "Stevenson", email="matilda.stevenson@csiro.au",role=c("aut","cre")), person("Martin", "Westgate", email="martin.westgate@csiro.au", role="aut"), person("Peggy", "Newman", email="peggy.newman@csiro.au", role="aut"))
Description: The Atlas of Living Australia ('ALA') provides tools to enable users of biodiversity information to find, access, combine and visualise data on Australian plants and animals; these have been made available from <https://ala.org.au/>. 'galah' provides a subset of the tools to be directly used within R. It enables the R community to directly access data and resources hosted by the 'ALA'.
Imports: assertthat, crul, data.table, digest, httr, jsonlite (>= 0.9.8), sf, sp, stringr (>= 1.0.0), utils, wellknown
Suggests: covr, dplyr, ggplot2, knitr, ozmaps, pkgdown, rmarkdown, testthat
License: MPL-2.0
URL: https://github.com/AtlasOfLivingAustralia/galah
BugReports: https://github.com/AtlasOfLivingAustralia/galah/issues
Maintainer: Matilda Stevenson <matilda.stevenson@csiro.au>
LazyLoad: yes
VignetteBuilder: knitr
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2021-04-03 06:10:14 UTC; ste748
Author: Matilda Stevenson [aut, cre], Martin Westgate [aut], Peggy Newman [aut]
Repository: CRAN
Date/Publication: 2021-04-06 08:30:02 UTC

More information about galah at CRAN
Permanent link

New package wpa with initial version 1.4.3
Package: wpa
Title: Tools for Analysing and Visualising Workplace Analytics Data
Version: 1.4.3
Authors@R: c( person(given = "Martin", family = "Chan", role = c("aut", "cre"), email = "martin.chan@microsoft.com"), person(given = "Carlos", family = "Morales", role = "aut", email = "carlos.morales@microsoft.com"), person(given = "Mark", family = "Powers", role = "ctb", email = "mark.powers@microsoft.com"), person(given = "Ainize", family = "Cidoncha", role = "ctb", email = "ainize.cidoncha@microsoft.com"), person(given = "Rosamary", family = "Ochoa Vargas", role = "ctb", email = "rosamary.ochoa@microsoft.com"), person(given = "Tannaz", family = "Sattari", role = "ctb", email = "tannaz.sattari@microsoft.com"), person(given = "Lucas", family = "Hogner", role = "ctb", email = "lucas.hogner@microsoft.com"), person(given = "Jasminder", family = "Thind", role = "ctb", email = "jasminder.thind@microsoft.com"), person(given = "Simone", family = "Liebal", role = "ctb", email = "simone.liebal@microsoft.com"), person(given = "Ellen", family = "Trinklein", role = "ctb"), person(given = "Microsoft Corporation", role = "cph") )
Description: Opinionated functions that enable easier and faster analysis of Workplace Analytics data. There are three main types of functions in 'wpa': (i) Standard functions create a 'ggplot' visual or a summary table based on a specific Workplace Analytics metric; (2) Report Generation functions generate HTML reports on a specific analysis area, e.g. Collaboration; (3) Other miscellaneous functions cover more specific applications (e.g. Subject Line text mining) of Workplace Analytics data. This package adheres to 'tidyverse' principles and works well with the pipe syntax. 'wpa' is built with the beginner-to-intermediate R users in mind, and is optimised for simplicity.
URL: https://github.com/microsoft/wpa/
BugReports: https://github.com/microsoft/wpa/issues/
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.1.2)
Imports: dplyr, stats, utils, tidyr, tidyselect (>= 1.0.0), magrittr, purrr, reshape2, ggplot2, ggrepel, scales, htmltools, markdown, rmarkdown, networkD3, DT, tidytext, ggraph, igraph, proxy, ggwordcloud, methods, data.table
VignetteBuilder: knitr
Suggests: knitr, extrafont, leiden, lifecycle, fst, glue
Language: en-US
NeedsCompilation: no
Packaged: 2021-04-02 12:10:03 UTC; martinchan
Author: Martin Chan [aut, cre], Carlos Morales [aut], Mark Powers [ctb], Ainize Cidoncha [ctb], Rosamary Ochoa Vargas [ctb], Tannaz Sattari [ctb], Lucas Hogner [ctb], Jasminder Thind [ctb], Simone Liebal [ctb], Ellen Trinklein [ctb], Microsoft Corporation [cph]
Maintainer: Martin Chan <martin.chan@microsoft.com>
Repository: CRAN
Date/Publication: 2021-04-06 07:50:03 UTC

More information about wpa at CRAN
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New package survivoR with initial version 0.9.2
Package: survivoR
Title: Data from all Seasons of Survivor (US) TV Series in Tidy Format
Version: 0.9.2
Authors@R: person(given = "Daniel", family = "Oehm", role = c("aut", "cre"), email = "danieloehm@gmail.com")
Description: Several datasets which detail the results and events of each season of Survivor. This includes details on the cast, voting history, immunity and reward challenges, jury votes and viewers. This data is useful for practicing data wrangling, graph analytics and analysing how each season of Survivor played out. Includes 'ggplot2' scales and colour palettes for visualisation.
Depends: R (>= 3.5.0)
Imports: dplyr, tidyr, ggplot2, stringr, magrittr, forcats, glue
License: MIT + file LICENSE
URL: https://github.com/doehm/survivoR
BugReports: https://github.com/doehm/survivoR/issues
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2021-04-02 02:03:26 UTC; Dan
Author: Daniel Oehm [aut, cre]
Maintainer: Daniel Oehm <danieloehm@gmail.com>
Repository: CRAN
Date/Publication: 2021-04-06 07:10:02 UTC

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New package selection.index with initial version 1.0.0
Package: selection.index
Title: Analysis of Selection Index in Plant Breeding
Version: 1.0.0
Authors@R: c(person(given = "Zankrut", family = "Goyani", role = c("aut", "cre", "cph"), email = "zankrut20@gmail.com"), person(given = "Alok", family = "Shrivastva", role = "aut", email = "igkvalok@gmail.com"), person(given = "Yogesh", family = "Garde", role = "aut", email = "y.garde@yahoo.co.in"), person(given = "Arvind", family = "Chaudhary", role = "aut", email = "apchaudhary@nau.in"))
Maintainer: Zankrut Goyani <zankrut20@gmail.com>
Description: The aim of most plant breeding programmes is simultaneous improvement of several characters. An objective method involving simultaneous selection for several attributes then becomes necessary. It has been recognised that most rapid improvements in the economic value is expected from selection applied simultaneously to all the characters which determine the economic value of a plant, and appropriate assigned weights to each character according to their economic importance, heritability and correlations between characters. So the selection for economic value is a complex matter. If the component characters are combined together into an index in such a way that when selection is applied to the index, as if index is the character to be improved, most rapid improvement of economic value is expected. Such an index was first proposed by Smith (1937 <doi:10.1111/j.1469-1809.1936.tb02143.x>) based on the Fisher's (1936 <doi:10.1111/j.1469-1809.1936.tb02137.x>) "discriminant function" Dabholkar (1999 <https://books.google.co.in/books?id=mlFtumAXQ0oC&lpg=PA4&ots=Xgxp1qLuxS&dq=elements%20of%20biometrical%20genetics&lr&pg=PP1#v=onepage&q&f=false>). In this package selection index is calculated based on the Smith (1937) selection index method.
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
Depends: R (>= 2.10)
Imports: stats
URL: https://github.com/zankrut20/selection.index
BugReports: https://github.com/zankrut20/selection.index/issues
Suggests: rmarkdown, knitr, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-04-02 16:29:12 UTC; zankr
Author: Zankrut Goyani [aut, cre, cph], Alok Shrivastva [aut], Yogesh Garde [aut], Arvind Chaudhary [aut]
Repository: CRAN
Date/Publication: 2021-04-06 08:00:03 UTC

More information about selection.index at CRAN
Permanent link

Package rbibutils updated to version 2.1 with previous version 2.0 dated 2020-11-18

Title: Convert Between Bibliography Formats
Description: Converts between a number of bibliography formats, including 'BibTeX', 'BibLaTeX' and 'Bibentry'. Includes a port of the 'bibutils' utilities by Chris Putnam <https://sourceforge.net/projects/bibutils/>. Supports all bibliography formats and character encodings implemented in 'bibutils'.
Author: Georgi N. Boshnakov [aut, cre] (R port, modifications to bibutils' C code), Chris Putman [aut] (src/*, author of the bibutils libraries, https://sourceforge.net/projects/bibutils/), Richard Mathar [ctb] (src/addsout.c), Johannes Wilm [ctb] (src/biblatexin.c, src/bltypes.c)
Maintainer: Georgi N. Boshnakov <georgi.boshnakov@manchester.ac.uk>

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Package quanteda.textstats updated to version 0.94 with previous version 0.93 dated 2021-03-15

Title: Textual Statistics for the Quantitative Analysis of Textual Data
Description: Textual statistics functions formerly in the 'quanteda' package. Textual statistics for characterizing and comparing textual data. Includes functions for measuring term and document frequency, the co-occurrence of words, similarity and distance between features and documents, feature entropy, keyword occurrence, readability, and lexical diversity. These functions extend the 'quanteda' package and are specially designed for sparse textual data.
Author: Kenneth Benoit [cre, aut, cph] (<https://orcid.org/0000-0002-0797-564X>), Kohei Watanabe [aut] (<https://orcid.org/0000-0001-6519-5265>), Haiyan Wang [aut] (<https://orcid.org/0000-0003-4992-4311>), Jiong Wei Lua [aut], Jouni Kuha [aut] (<https://orcid.org/0000-0002-1156-8465>), European Research Council [fnd] (ERC-2011-StG 283794-QUANTESS)
Maintainer: Kenneth Benoit <kbenoit@lse.ac.uk>

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Package quanteda.textplots updated to version 0.94 with previous version 0.92 dated 2021-02-18

Title: Plots for the Quantitative Analysis of Textual Data
Description: Plotting functions for visualising textual data. Extends 'quanteda' and related packages with plot methods designed specifically for text data, textual statistics, and models fit to textual data. Plot types include word clouds, lexical dispersion plots, scaling plots, network visualisations, and word 'keyness' plots.
Author: Kenneth Benoit [cre, aut, cph] (<https://orcid.org/0000-0002-0797-564X>), Kohei Watanabe [aut] (<https://orcid.org/0000-0001-6519-5265>), Haiyan Wang [aut] (<https://orcid.org/0000-0003-4992-4311>), Adam Obeng [aut] (<https://orcid.org/0000-0002-2906-4775>), Stefan Müller [aut] (<https://orcid.org/0000-0002-6315-4125>), Akitaka Matsuo [aut] (<https://orcid.org/0000-0002-3323-6330>), Ian Fellows [cph] (authored wordcloud C source code (modified)), European Research Council [fnd] (ERC-2011-StG 283794-QUANTESS)
Maintainer: Kenneth Benoit <kbenoit@lse.ac.uk>

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Package quanteda.textmodels updated to version 0.9.4 with previous version 0.9.3 dated 2021-03-07

Title: Scaling Models and Classifiers for Textual Data
Description: Scaling models and classifiers for sparse matrix objects representing textual data in the form of a document-feature matrix. Includes original implementations of 'Laver', 'Benoit', and Garry's (2003) <doi:10.1017/S0003055403000698>, 'Wordscores' model, Perry and 'Benoit's' (2017) <arXiv:1710.08963> class affinity scaling model, and 'Slapin' and 'Proksch's' (2008) <doi:10.1111/j.1540-5907.2008.00338.x> 'wordfish' model, as well as methods for correspondence analysis, latent semantic analysis, and fast Naive Bayes and linear 'SVMs' specially designed for sparse textual data.
Author: Kenneth Benoit [cre, aut, cph] (<https://orcid.org/0000-0002-0797-564X>), Kohei Watanabe [aut] (<https://orcid.org/0000-0001-6519-5265>), Haiyan Wang [aut] (<https://orcid.org/0000-0003-4992-4311>), Patrick O. Perry [aut] (<https://orcid.org/0000-0001-7460-127X>), Benjamin Lauderdale [aut] (<https://orcid.org/0000-0003-3090-0969>), Johannes Gruber [aut] (<https://orcid.org/0000-0001-9177-1772>), William Lowe [aut] (<https://orcid.org/0000-0002-1549-6163>), Vikas Sindhwani [cph] (authored svmlin C++ source code), European Research Council [fnd] (ERC-2011-StG 283794-QUANTESS)
Maintainer: Kenneth Benoit <kbenoit@lse.ac.uk>

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Package quanteda updated to version 3.0.0 with previous version 2.1.2 dated 2020-09-23

Title: Quantitative Analysis of Textual Data
Description: A fast, flexible, and comprehensive framework for quantitative text analysis in R. Provides functionality for corpus management, creating and manipulating tokens and ngrams, exploring keywords in context, forming and manipulating sparse matrices of documents by features and feature co-occurrences, analyzing keywords, computing feature similarities and distances, applying content dictionaries, applying supervised and unsupervised machine learning, visually representing text and text analyses, and more.
Author: Kenneth Benoit [cre, aut, cph] (<https://orcid.org/0000-0002-0797-564X>), Kohei Watanabe [aut] (<https://orcid.org/0000-0001-6519-5265>), Haiyan Wang [aut] (<https://orcid.org/0000-0003-4992-4311>), Paul Nulty [aut] (<https://orcid.org/0000-0002-7214-4666>), Adam Obeng [aut] (<https://orcid.org/0000-0002-2906-4775>), Stefan Müller [aut] (<https://orcid.org/0000-0002-6315-4125>), Akitaka Matsuo [aut] (<https://orcid.org/0000-0002-3323-6330>), William Lowe [aut] (<https://orcid.org/0000-0002-1549-6163>), Christian Müller [ctb], European Research Council [fnd] (ERC-2011-StG 283794-QUANTESS)
Maintainer: Kenneth Benoit <kbenoit@lse.ac.uk>

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Package poismf updated to version 0.3.0 with previous version 0.2.7 dated 2021-01-08

Title: Factorization of Sparse Counts Matrices Through Poisson Likelihood
Description: Creates a low-rank factorization of a sparse counts matrix by maximizing Poisson likelihood with l1/l2 regularization with all non-negative latent factors (e.g. for recommender systems or topic modeling) (Cortes, (2018) <arXiv:1811.01908>). Similar to hierarchical Poisson factorization, but follows an optimization-based approach with regularization instead of a hierarchical structure, and is fit through gradient-based methods instead of variational inference.
Author: David Cortes [aut, cre, cph], Jean-Sebastien Roy [cph], Stephen Nash [cph]
Maintainer: David Cortes <david.cortes.rivera@gmail.com>

Diff between poismf versions 0.2.7 dated 2021-01-08 and 0.3.0 dated 2021-04-06

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Package packageRank updated to version 0.4.1 with previous version 0.4.0 dated 2021-03-01

Title: Computation and Visualization of Package Download Counts and Percentiles
Description: Compute and visualize the cross-sectional and longitudinal number and rank percentile of package downloads from RStudio's CRAN mirror.
Author: Peter Li [aut, cre]
Maintainer: Peter Li <lindbrook@gmail.com>

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New package multiridge with initial version 1.5
Package: multiridge
Title: Fast Cross-Validation for Multi-Penalty Ridge Regression
Version: 1.5
Date: 2021-04-02
Author: Mark A. van de Wiel
Maintainer: Mark A. van de Wiel <mark.vdwiel@amsterdamumc.nl>
Depends: R (>= 3.5.0), survival, pROC, risksetROC, mgcv, snowfall
Description: Multi-penalty linear, logistic and cox ridge regression, including estimation of the penalty parameters by efficient (repeated) cross-validation and marginal likelihood maximization. Multiple high-dimensional data types that require penalization are allowed, as well as unpenalized variables. Paired and preferential data types can be specified. See Van de Wiel et al. (2021), <arXiv:2005.09301>.
License: GPL (>= 3)
NeedsCompilation: no
Packaged: 2021-04-02 07:17:48 UTC; VNOB-0735
Repository: CRAN
Date/Publication: 2021-04-06 07:50:17 UTC

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New package MultiHorizonSPA with initial version 1.0.0
Package: MultiHorizonSPA
Title: Multi Horizon Superior Predictive Ability
Version: 1.0.0
Authors@R: c(person("Luca", "Barbaglia", email = "luc.barbaglia@gmail.com", role = c("cre", "aut")))
Maintainer: Luca Barbaglia <luc.barbaglia@gmail.com>
Description: Run the Multi Horizon Superior Predictive Ability test to compare the predictive performance of two distinct models when jointly considering all horizons of a forecast path.
Depends: R (>= 3.5.0)
Imports: matlab, stats
License: GPL-3
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2021-04-02 07:30:47 UTC; barbalu
Author: Luca Barbaglia [cre, aut]
Repository: CRAN
Date/Publication: 2021-04-06 08:00:09 UTC

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New package multifear with initial version 0.1.1
Package: multifear
Title: Multiverse Analyses for Conditioning Data
Version: 0.1.1
Authors@R: c(person(given = "Angelos-Miltiadis", family = "Krypotos", role = c("aut", "cre", "cph"), email = "amkrypotos@gmail.com"))
Maintainer: Angelos-Miltiadis Krypotos <amkrypotos@gmail.com>
Description: A suite of functions for performing analyses, based on a multiverse approach, for conditioning data. Specifically, given the appropriate data, the functions are able to perform t-tests, analyses of variance, and mixed models for the provided data and return summary statistics and plots. The function is also able to return for all those tests p-values, confidence intervals, and Bayes factors. The methods are described in Lonsdorf, Gerlicher, Klingelhofer-Jens, & Krypotos <doi:10.31234/osf.io/2z6pd>.
Depends: R (>= 3.6.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
URL: https://github.com/AngelosPsy/multifear
BugReports: https://github.com/AngelosPsy/multifear/issues
Imports: dplyr (>= 0.8.4), purrr (>= 0.3.3), stats (>= 3.6.2), ez (>= 4.4.0), stringr (>= 1.4.0), reshape2 (>= 1.4.3), tibble (>= 2.1.3), ggplot2 (>= 3.2.1), effsize (>= 0.7.8), nlme (>= 3.1.144), BayesFactor (>= 0.9.12.4.2), bayestestR (>= 0.5.2), broom (>= 0.5.5), effectsize (>= 0.4.1), esc (>= 0.5.1), forestplot (>= 1.10), bootstrap (>= 2019.6)
Suggests: gridExtra (>= 2.3), fastDummies (>= 1.6.1), vctrs (>= 0.3.1), tidyselect (>= 1.0.0), tidyr (>= 1.0.2), plyr (>= 1.8.6), ggraph (>= 2.0.1), igraph (>= 1.2.4.2), testthat (>= 2.1.0), cowplot (>= 1.0.0), covr
NeedsCompilation: no
Packaged: 2021-04-02 10:10:49 UTC; angeloskrypotos
Author: Angelos-Miltiadis Krypotos [aut, cre, cph]
Repository: CRAN
Date/Publication: 2021-04-06 07:30:19 UTC

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Package HistDat updated to version 0.2.0 with previous version 0.1.0 dated 2021-04-02

Title: Summary Statistics for Histogram/Count Data
Description: In some cases you will have data in a histogram format, where you have a vector of all possible observations, and a vector of how many times each observation appeared. You could expand this into a single 1D vector, but this may not be advisable if the counts are extremely large. 'HistDat' allows for the calculation of summary statistics without the need for expanding your data.
Author: Michael Milton
Maintainer: Michael Milton <michael.r.milton@gmail.com>

Diff between HistDat versions 0.1.0 dated 2021-04-02 and 0.2.0 dated 2021-04-06

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Package fddm updated to version 0.3-3 with previous version 0.3-1 dated 2021-03-22

Title: Fast Implementation of the Diffusion Decision Model
Description: Provides the probability density function (PDF) of the diffusion decision model (DDM; e.g., Ratcliff & McKoon, 2008, <doi:10.1162/neco.2008.12-06-420>) with across-trial variability in the drift rate. Because the PDF of the DDM contains an infinite sum, it needs to be approximated. 'fddm' implements all published approximations (Navarro & Fuss, 2009, <doi:10.1016/j.jmp.2009.02.003>; Gondan, Blurton, & Kesselmeier, 2014, <doi:10.1016/j.jmp.2014.05.002>) plus new approximations. All approximations are implemented purely in 'C++' providing faster speed than existing packages.
Author: Kendal B. Foster [aut], Henrik Singmann [ctb, cre] (<https://orcid.org/0000-0002-4842-3657>)
Maintainer: Henrik Singmann <singmann@gmail.com>

Diff between fddm versions 0.3-1 dated 2021-03-22 and 0.3-3 dated 2021-04-06

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New package fcci with initial version 1.0.0
Package: fcci
Title: Feldman-Cousins Confidence Intervals
Version: 1.0.0
Authors@R: person(given = "Valerio", family = "Gherardi", role = c("aut", "cre"), email = "vgherard@sissa.it", comment = c(ORCID = "0000-0002-8215-3013"))
Maintainer: Valerio Gherardi <vgherard@sissa.it>
Description: Provides support for building Feldman-Cousins confidence intervals [G. J. Feldman and R. D. Cousins (1998) <doi:10.1103/PhysRevD.57.3873>].
License: GPL (>= 3)
Encoding: UTF-8
LinkingTo: Rcpp
Imports: Rcpp, assertthat, rlang
SystemRequirements: C++11
URL: https://github.com/vgherard/fcci
BugReports: https://github.com/vgherard/fcci/issues
Suggests: covr, testthat (>= 3.0.0)
NeedsCompilation: yes
Packaged: 2021-04-02 14:37:06 UTC; vale
Author: Valerio Gherardi [aut, cre] (<https://orcid.org/0000-0002-8215-3013>)
Repository: CRAN
Date/Publication: 2021-04-06 07:50:20 UTC

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Package ctrdata updated to version 1.5.2 with previous version 1.5.1 dated 2021-03-21

Title: Retrieve and Analyze Clinical Trials in Public Registers
Description: Provides functions for querying, retrieving and analyzing protocol- and results-related information on clinical trials from two public registers, the 'European Union Clinical Trials Register' ('EUCTR', <https://www.clinicaltrialsregister.eu/>) and 'ClinicalTrials.gov' ('CTGOV', <https://clinicaltrials.gov/>). The trial information is transformed and stored in a database ('SQLite' or 'MongoDB', via 'nodbi'). Functions are provided to identify de- duplicated records, to easily find and extract variables (fields) of interest even from complex nesting as used by the registers, and to update previous queries that users retrieved in a database. The package can be used for meta analysis and trend-analysis of the design and conduct as well as results of clinical trials.
Author: Ralf Herold [aut, cre] (<https://orcid.org/0000-0002-8148-6748>)
Maintainer: Ralf Herold <ralf.herold@mailbox.org>

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Package BoomSpikeSlab updated to version 1.2.4 with previous version 1.2.3 dated 2020-05-01

Title: MCMC for Spike and Slab Regression
Description: Spike and slab regression with a variety of residual error distributions corresponding to Gaussian, Student T, probit, logit, SVM, and a few others. Spike and slab regression is Bayesian regression with prior distributions containing a point mass at zero. The posterior updates the amount of mass on this point, leading to a posterior distribution that is actually sparse, in the sense that if you sample from it many coefficients are actually zeros. Sampling from this posterior distribution is an elegant way to handle Bayesian variable selection and model averaging. See <DOI:10.1504/IJMMNO.2014.059942> for an explanation of the Gaussian case.
Author: Steven L. Scott <steve.the.bayesian@gmail.com>
Maintainer: Steven L. Scott <steve.the.bayesian@gmail.com>

Diff between BoomSpikeSlab versions 1.2.3 dated 2020-05-01 and 1.2.4 dated 2021-04-06

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Package Mega2R (with last version 1.0.8) was removed from CRAN

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

2020-10-01 1.0.8
2020-05-19 1.0.7
2020-05-15 1.0.6
2019-02-28 1.0.5
2018-06-18 1.0.4
2018-05-22 1.0.3
2018-04-03 1.0.2
2017-11-02 1.0.0

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Package mlquantify (with last version 0.1.4) was removed from CRAN

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

2020-09-23 0.1.4

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Package readrba updated to version 0.1.1 with previous version 0.1.0 dated 2020-12-16

Title: Download and Tidy Data from the Reserve Bank of Australia
Description: Download up-to-date data from the Reserve Bank of Australia in a tidy data frame. Package includes functions to download current and historical statistical tables (<https://www.rba.gov.au/statistics/tables/>) and forecasts (<https://www.rba.gov.au/publications/smp/forecasts-archive.html>). Data includes a broad range of Australian macroeconomic and financial time series.
Author: Matt Cowgill [aut, cre] (<https://orcid.org/0000-0003-0422-3300>)
Maintainer: Matt Cowgill <mattcowgill@gmail.com>

Diff between readrba versions 0.1.0 dated 2020-12-16 and 0.1.1 dated 2021-04-06

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