Fri, 26 Jun 2020

Package tidytable updated to version 0.5.2 with previous version 0.5.1 dated 2020-05-29

Title: Tidy Interface to 'data.table'
Description: Tidy interface to 'data.table'. 'rlang' compatible, which allows the user to build custom functions much like they would in the tidyverse.
Author: Mark Fairbanks [aut, cre], Tyson Barrett [ctb], Ivan Leung [ctb], Ross Kennedy [ctb], Lionel Henry [ctb], Matt Carlson [ctb]
Maintainer: Mark Fairbanks <mark.t.fairbanks@gmail.com>

Diff between tidytable versions 0.5.1 dated 2020-05-29 and 0.5.2 dated 2020-06-26

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Package sarsop updated to version 0.6.3 with previous version 0.6.2 dated 2020-06-26

Title: Approximate POMDP Planning Software
Description: A toolkit for Partially Observed Markov Decision Processes (POMDP). Provides bindings to C++ libraries implementing the algorithm SARSOP (Successive Approximations of the Reachable Space under Optimal Policies) and described in Kurniawati et al (2008), <doi:10.15607/RSS.2008.IV.009>. This package also provides a high-level interface for generating, solving and simulating POMDP problems and their solutions.
Author: Carl Boettiger [cre, aut, cph] (<https://orcid.org/0000-0002-1642-628X>), Jeroen Ooms [aut], Milad Memarzadeh [aut], Hanna Kurniawati [ctb, cph], David Hsu [ctb, cph], Hanna Kurniawati [ctb, cph], Wee Sun Lee [ctb, cph], Yanzhu Du [ctb], Xan Huang [ctb], Trey Smith [ctb, cph], Tony Cassandra [ctb, cph], Lee Thomason [ctb, cph], Carl Kindman [ctb, cph], Le Trong Dao [ctb, cph], Amit Jain [ctb, cph], Rong Nan [ctb, cph], Ulrich Drepper [ctb], Free Software Foundation [cph], Tyge Lovset [ctb, cph], Yves Berquin [ctb, cph], Benjamin Grüdelbach [ctb], RSA Data Security, Inc. [cph]
Maintainer: Carl Boettiger <cboettig@gmail.com>

Diff between sarsop versions 0.6.2 dated 2020-06-26 and 0.6.3 dated 2020-06-26

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New package lolR with initial version 2.1
Package: lolR
Type: Package
Title: Linear Optimal Low-Rank Projection
Version: 2.1
Date: 2020-06-20
Authors@R: c(person("Eric", "Bridgeford", role = c("aut", "cre"), email = "ericwb95@gmail.com"), person("Minh", "Tang", role="ctb", email="minh@jhu.edu"), person("Jason", "Yim", role = "ctb", email = "jasonkyuyim@gmail.com"), person("Joshua", "Vogelstein", role = "ths", email = "jovo@jhu.edu"))
Maintainer: Eric Bridgeford <ericwb95@gmail.com>
Description: Supervised learning techniques designed for the situation when the dimensionality exceeds the sample size have a tendency to overfit as the dimensionality of the data increases. To remedy this High dimensionality; low sample size (HDLSS) situation, we attempt to learn a lower-dimensional representation of the data before learning a classifier. That is, we project the data to a situation where the dimensionality is more manageable, and then are able to better apply standard classification or clustering techniques since we will have fewer dimensions to overfit. A number of previous works have focused on how to strategically reduce dimensionality in the unsupervised case, yet in the supervised HDLSS regime, few works have attempted to devise dimensionality reduction techniques that leverage the labels associated with the data. In this package and the associated manuscript Vogelstein et al. (2017) <arXiv:1709.01233>, we provide several methods for feature extraction, some utilizing labels and some not, along with easily extensible utilities to simplify cross-validative efforts to identify the best feature extraction method. Additionally, we include a series of adaptable benchmark simulations to serve as a standard for future investigative efforts into supervised HDLSS. Finally, we produce a comprehensive comparison of the included algorithms across a range of benchmark simulations and real data applications.
Depends: R (>= 3.4.0)
License: GPL-2
URL: https://github.com/neurodata/lol
Imports: ggplot2, abind, MASS, irlba, pls, robust, robustbase
Encoding: UTF-8
LazyData: true
VignetteBuilder: knitr
RoxygenNote: 7.1.0
Suggests: knitr, rmarkdown, parallel, randomForest, latex2exp, testthat, covr
NeedsCompilation: no
Packaged: 2020-06-25 18:56:31 UTC; eric
Author: Eric Bridgeford [aut, cre], Minh Tang [ctb], Jason Yim [ctb], Joshua Vogelstein [ths]
Repository: CRAN
Date/Publication: 2020-06-26 22:30:03 UTC

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Package hmma updated to version 1.1.0 with previous version 1.0.0 dated 2020-04-08

Title: Constructs Asymmetric Hidden Markov Models
Description: Asymmetric hidden Markov model (HMM-A) learning. HMM-As are similar to regular HMMs, but use Bayesian Networks (BNs) in their emission distribution. The HMM-As can therefore offer more problem insight [Bueno et al. 2017, <doi:10.1016/j.ijar.2017.05.011>].
Author: Marcos L.P Bueno [aut], Arjen Hommersom [aut, cre], Joop Thibaudier [aut], Marco Scutari [ctb], Robert Ness [ctb], Robert Gentleman and Ross Ihaka [cph], The R Development Core Team [cph], The R Foundation [cph]
Maintainer: Arjen Hommersom <arjen.hommersom@ou.nl>

Diff between hmma versions 1.0.0 dated 2020-04-08 and 1.1.0 dated 2020-06-26

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New package deTestSet with initial version 1.1.7.2
Package: deTestSet
Version: 1.1.7.2
Title: Test Set for Differential Equations
Authors@R: c(person("Karline","Soetaert", role = c("aut","cre"), email = "karline.soetaert@nioz.nl"), person("Jeff","Cash", role = "aut", email = "j.cash@imperial.ac.uk"), person("Francesca","Mazzia", role = "aut", email = "mazzia@dm.uniba.it"), person("Ernst","Hairer", role = "ctb", comment = "files dopri8.f, dopri6.f"), person("Gerard","Wanner", role = "ctb", comment = "files dopri8.f, dopri6.f"), person("T.","Abdulla", role = "ctb", comment = "file mebdfi.f"), person("Cecilia","Magherini", role = "ctb", comment = "files bimd.f, bimda.f"), person("Luigi","Brugnano", role = "ctb", comment = "files bimd.f, bimda.f"), person("Cleve","Moler", role = "ctb", comment = "file bimda.f") )
Maintainer: Karline Soetaert <karline.soetaert@nioz.nl>
Author: Karline Soetaert [aut, cre], Jeff Cash [aut], Francesca Mazzia [aut], Ernst Hairer [ctb] (files dopri8.f, dopri6.f), Gerard Wanner [ctb] (files dopri8.f, dopri6.f), T. Abdulla [ctb] (file mebdfi.f), Cecilia Magherini [ctb] (files bimd.f, bimda.f), Luigi Brugnano [ctb] (files bimd.f, bimda.f), Cleve Moler [ctb] (file bimda.f)
Depends: R (>= 2.01), deSolve
Imports: graphics, grDevices, stats
Description: Solvers and test set for stiff and non-stiff differential equations, and differential algebraic equations. See Mazzia, F., Cash, J.R., and K. Soetaert (2012) <DOI:10.1016/j.cam.2012.03.014>.
License: GPL
Copyright: inst/COPYRIGHTS
LazyData: yes
NeedsCompilation: yes
Packaged: 2020-06-25 17:06:16 UTC; karlines
Repository: CRAN
Date/Publication: 2020-06-26 22:50:07 UTC

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Package shinyobjects updated to version 0.1.1 with previous version 0.1.0 dated 2020-05-12

Title: Access Reactive Data Interactively
Description: Troubleshooting reactive data in 'shiny' can be difficult. These functions will convert reactive data frames into functions and load all assigned objects into your local environment. If you create a dummy input object, as the function will suggest, you will be able to test your server and ui functions interactively.
Author: Jake Riley [aut, cre]
Maintainer: Jake Riley <rjake@sas.upenn.edu>

Diff between shinyobjects versions 0.1.0 dated 2020-05-12 and 0.1.1 dated 2020-06-26

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Package SSDforR updated to version 1.5.17 with previous version 1.5.16 dated 2020-06-09

Title: Functions to Analyze Single System Data
Description: Functions to visually and statistically analyze single system data.
Author: Charles Auerbach [aut, cre], Wendy Zeitlin [aut]
Maintainer: Charles Auerbach <auerbach@yu.edu>

Diff between SSDforR versions 1.5.16 dated 2020-06-09 and 1.5.17 dated 2020-06-26

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Package RXshrink updated to version 1.4 with previous version 1.3.3 dated 2020-04-26

Title: Maximum Likelihood Shrinkage using Generalized Ridge or Least Angle Regression Methods
Description: Functions are provided to calculate and display ridge TRACEs for various shrinkage Paths. They determine the m-Extent of shrinkage most likely, under Normal-theory, to produce optimally biased estimates of regression beta-coefficients with minimum MSE Risk. The new unr.ridge() function implements the "Unrestricted Path" introduced in "Ridge TRACE Diagnostics" <arXiv:2005.14291>. This Path appears more efficient than the Paths used by the qm.ridge(), aug.lars() and uc.lars() functions. In-Sample predictions can be made using RXpredict() for all five types of RXshrink linear model TRACE diagnostics. New functions MLboot(), MLcalc(), MLhist() and MLtrue() provide insights into the true bias and MSE risk characteristics of non-linear Shrinkage estimators. The correct.signs() function provides estimates with "correct" numerical signs when ill-conditioned (nearly multicollinear) models yield OLS estimates that disagree with the signs of the observed correlations between the y-outcome and the selected x-predictor variables.
Author: Bob Obenchain
Maintainer: Bob Obenchain <wizbob@att.net>

Diff between RXshrink versions 1.3.3 dated 2020-04-26 and 1.4 dated 2020-06-26

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Package revdbayes updated to version 1.3.7 with previous version 1.3.6 dated 2019-12-02

Title: Ratio-of-Uniforms Sampling for Bayesian Extreme Value Analysis
Description: Provides functions for the Bayesian analysis of extreme value models. The 'rust' package <https://cran.r-project.org/package=rust> is used to simulate a random sample from the required posterior distribution. The functionality of 'revdbayes' is similar to the 'evdbayes' package <https://cran.r-project.org/package=evdbayes>, which uses Markov Chain Monte Carlo ('MCMC') methods for posterior simulation. Also provided are functions for making inferences about the extremal index, using the K-gaps model of Suveges and Davison (2010) <doi:10.1214/09-AOAS292>. Also provided are d,p,q,r functions for the Generalised Extreme Value ('GEV') and Generalised Pareto ('GP') distributions that deal appropriately with cases where the shape parameter is very close to zero.
Author: Paul J. Northrop [aut, cre, cph]
Maintainer: Paul J. Northrop <p.northrop@ucl.ac.uk>

Diff between revdbayes versions 1.3.6 dated 2019-12-02 and 1.3.7 dated 2020-06-26

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Package emmeans updated to version 1.4.8 with previous version 1.4.7 dated 2020-05-25

Title: Estimated Marginal Means, aka Least-Squares Means
Description: Obtain estimated marginal means (EMMs) for many linear, generalized linear, and mixed models. Compute contrasts or linear functions of EMMs, trends, and comparisons of slopes. Plots and other displays. Least-squares means are discussed, and the term "estimated marginal means" is suggested, in Searle, Speed, and Milliken (1980) Population marginal means in the linear model: An alternative to least squares means, The American Statistician 34(4), 216-221 <doi:10.1080/00031305.1980.10483031>.
Author: Russell Lenth [aut, cre, cph], Henrik Singmann [ctb], Jonathon Love [ctb], Paul Buerkner [ctb], Maxime Herve [ctb]
Maintainer: Russell Lenth <russell-lenth@uiowa.edu>

Diff between emmeans versions 1.4.7 dated 2020-05-25 and 1.4.8 dated 2020-06-26

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More information about emmeans at CRAN
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Package volcano3D updated to version 1.0.1 with previous version 1.0.0 dated 2020-06-04

Title: Interactive Plotting of Three-Way Differential Expression Analysis
Description: Differential expression (DE) analysis can be used to discover quantitative changes in expression levels between experimental groups. Such results are typically visualised using volcano plots, however in cases where more than two experimental groups are involved, visualising results can become convoluted and it quickly becomes difficult to see the wood for the trees. This package provides easy-to-use functions to extract and visualise outputs from DE between three groups (primarily aimed at 'limma' and 'DESeq2' outputs). We present novel methods to map DE results into polar coordinates to enable users to combine and simultaneously view three sets of results. These graphics also possess optional 'plotly' outputs for interactive and three-dimensional functionality, as seen in Lewis et. al. (2019) <doi:10.1016/j.celrep.2019.07.091>.
Author: Katriona Goldmann [aut, cre], Myles Lewis [aut, ctb]
Maintainer: Katriona Goldmann <k.goldmann@qmul.ac.uk>

Diff between volcano3D versions 1.0.0 dated 2020-06-04 and 1.0.1 dated 2020-06-26

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Package OCNet updated to version 0.3.1 with previous version 0.3.0 dated 2020-05-12

Title: Optimal Channel Networks
Description: Generate and analyze Optimal Channel Networks (OCNs): oriented spanning trees reproducing all scaling features characteristic of real, natural river networks. As such, they can be used in a variety of numerical experiments in the fields of hydrology, ecology and epidemiology. See Carraro et al. (2020) <doi:10.1101/2020.02.17.948851> for a presentation of the package; Rinaldo et al. (2014) <doi:10.1073/pnas.1322700111> for a theoretical overview on the OCN concept; Furrer and Sain (2010) <doi:10.18637/jss.v036.i10> for the construct used.
Author: Luca Carraro [aut, cre], Florian Altermatt [ctb], Emanuel A. Fronhofer [ctb], Reinhard Furrer [ctb], Isabelle Gounand [ctb], Andrea Rinaldo [ctb], Enrico Bertuzzo [aut]
Maintainer: Luca Carraro <luca.carraro@hotmail.it>

Diff between OCNet versions 0.3.0 dated 2020-05-12 and 0.3.1 dated 2020-06-26

 DESCRIPTION               |    6 +++---
 MD5                       |   18 +++++++++---------
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More information about OCNet at CRAN
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Package ImpactEffectsize updated to version 0.5.0 with previous version 0.4.1 dated 2020-06-04

Title: Calculation and Visualization of the Impact Effect Size Measure
Description: A non-parametric effect size measure capturing changes in central tendency or shape of data distributions. The package provides the necessary functions to calculate and plot the Impact effect size measure between two groups.
Author: Jorn Lotsch[aut,cre], Alfred Ultsch[aut]
Maintainer: Jorn Lotsch <j.loetsch@em.uni-frankfurt.de>

Diff between ImpactEffectsize versions 0.4.1 dated 2020-06-04 and 0.5.0 dated 2020-06-26

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Permanent link

New package HSAR with initial version 0.5
Package: HSAR
Type: Package
Title: Hierarchical Spatial Autoregressive Model
Version: 0.5
Date: 2020-6-1
Author: Guanpeng Dong, Richard Harris, Angelos Mimis
Maintainer: Angelos Mimis <mimis@panteion.gr>
Description: A Hierarchical Spatial Autoregressive Model (HSAR), based on a Bayesian Markov Chain Monte Carlo (MCMC) algorithm (Dong and Harris (2014) <doi:10.1111/gean.12049>). The creation of this package was supported by the Economic and Social Research Council (ESRC) through the Applied Quantitative Methods Network: Phase II, grant number ES/K006460/1.
License: GPL (>= 2)
Depends: R (>= 3.5.0)
Imports: spdep, spatialreg, Rcpp
LinkingTo: Rcpp, RcppArmadillo
Suggests: sf, tidyverse, maptools ,rgdal, rgeos, RColorBrewer, classInt, markdown, knitr
VignetteBuilder: knitr
NeedsCompilation: yes
Repository: CRAN
RoxygenNote: 7.1.0
Packaged: 2020-06-26 15:54:45 UTC; angelos
Date/Publication: 2020-06-26 17:20:16 UTC

More information about HSAR at CRAN
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New package antitrust with initial version 0.99.14
Package: antitrust
Type: Package
Title: Tools for Antitrust Practitioners
Version: 0.99.14
Date: 2020-06-25
Author: Charles Taragin and Michael Sandfort
Maintainer: Charles Taragin <ctaragin@ftc.gov>
Imports: methods, MASS, evd, BB, numDeriv
Suggests: ggplot2, bookdown, knitr
VignetteBuilder: knitr
Encoding: UTF-8
Description: A collection of tools for antitrust practitioners, including the ability to calibrate different consumer demand systems and simulate the effects of mergers under different competitive regimes.
License: Unlimited
LazyLoad: yes
Collate: 'AntitrustClasses.R' 'BertrandClasses.R' 'BargainingClasses.R' 'BertrandRUMClasses.R' 'AuctionClasses.R' 'VerticalClasses.R' 'CournotClasses.R' 'OwnershipMethods.R' 'SummaryMethods.R' 'ShowMethods.R' 'AuctionCapMethods.R' 'PricesMethods.R' 'CostMethods.R' 'MarginsMethods.R' 'ParamsMethods.R' 'PriceDeltaMethods.R' 'PSMethods.R' 'OutputMethods.R' 'PlotMethods.R' 'HypoMonMethods.R' 'HHIMethods.R' 'UPPMethods.R' 'DiversionMethods.R' 'ElastMethods.R' 'CMCRMethods.R' 'CVMethods.R' 'DiagnosticsMethods.R' 'AIDSFunctions.R' 'Antitrust_Shiny.R' 'AntitrustPackage.R' 'Auction2ndCapFunctions.R' 'Auction2ndLogitFunctions.R' 'BertrandFunctions.R' 'CESFunctions.R' 'CMCRBertrandFunctions.R' 'CMCRCournotFunctions.R' 'CournotFunctions.R' 'HHIFunctions.R' 'LinearFunctions.R' 'LogitFunctions.R' 'SimFunctions.R' 'VerticalFunctions.R' 'antitrust-deprecated.R'
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-06-25 15:02:39 UTC; ctara
Repository: CRAN
Date/Publication: 2020-06-26 17:20:07 UTC

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Package loon.ggplot updated to version 1.0.1 with previous version 1.0.0 dated 2020-06-17

Title: Making 'ggplot2' Plots Interactive with 'loon' and Vice Versa
Description: It provides a bridge between the 'loon' and 'ggplot2' packages. Data analysts who value the grammar pipeline provided by 'ggplot2' can turn these static plots into interactive 'loon' plots. Conversely, data analysts who explore data interactively with 'loon' can turn any 'loon' plot into a 'ggplot2' plot structure. The function 'loon.ggplot()' is applied to one plot structure will return the other.
Author: Zehao Xu [aut, cre], R. Wayne Oldford [aut]
Maintainer: Zehao Xu <z267xu@uwaterloo.ca>

Diff between loon.ggplot versions 1.0.0 dated 2020-06-17 and 1.0.1 dated 2020-06-26

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Permanent link

Package gRim updated to version 0.2.4 with previous version 0.2.3 dated 2020-06-20

Title: Graphical Interaction Models
Description: Provides the following types of models: Models for contingency tables (i.e. log-linear models) Graphical Gaussian models for multivariate normal data (i.e. covariance selection models) Mixed interaction models. Documentation about 'gRim' is provided by vignettes included in this package and the book by Højsgaard, Edwards and Lauritzen (2012, <doi:10.1007/978-1-4614-2299-0>); see 'citation("gRim")' for details.
Author: Søren Højsgaard <sorenh@math.aau.dk>
Maintainer: Søren Højsgaard <sorenh@math.aau.dk>

Diff between gRim versions 0.2.3 dated 2020-06-20 and 0.2.4 dated 2020-06-26

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New package gesisdata with initial version 0.1.0
Package: gesisdata
Type: Package
Title: Reproducible Data Retrieval from the GESIS Data Archive
Version: 0.1.0
Date: 2020-06-23
Authors@R: c( person("Frederick", "Solt", email = "frederick-solt@uiowa.edu", role = c("aut", "cre", "cph")))
URL: https://github.com/fsolt/gesisdata
BugReports: https://github.com/fsolt/gesisdata/issues
Description: Reproducible, programmatic retrieval of datasets from the GESIS Data Archive. The GESIS Data Archive <https://search.gesis.org> makes available thousands of invaluable datasets, but researchers using these datasets are caught in a bind. The archive's terms and conditions bar dissemination of downloaded datasets to third parties, but to ensure that one's work can be reproduced, assessed, and built upon by others, one must provide access to the raw data one has employed. The 'gesisdata' package cuts this knot by providing registered users with programmatic, reproducible access to GESIS datasets from within 'R'.
License: MIT + file LICENSE
LazyData: TRUE
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
Imports: magrittr, rio, RSelenium (>= 1.7.1), stringr, dplyr, tools, utils
Encoding: UTF-8
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-06-26 12:39:25 UTC; fredsolt
Author: Frederick Solt [aut, cre, cph]
Maintainer: Frederick Solt <frederick-solt@uiowa.edu>
Repository: CRAN
Date/Publication: 2020-06-26 16:10:03 UTC

More information about gesisdata at CRAN
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Package ARpLMEC updated to version 1.1 with previous version 1.0 dated 2019-01-09

Title: Fitting Autoregressive Censored Mixed-Effects Models
Description: It fits left, right or intervalar censored mixed-effects linear model with autoregressive errors of order p using the EM algorithm. It provides estimates, standard errors of the parameters and prediction of future observations. Florin Vaida and Lin Liu (2009) <doi:10.1198/jcgs.2009.07130>.
Author: Rommy C. Olivari,Aldo M. Garay and Victor H. Lachos
Maintainer: Rommy C. Olivari <rco1@de.ufpe.br>

Diff between ARpLMEC versions 1.0 dated 2019-01-09 and 1.1 dated 2020-06-26

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New package zfit with initial version 0.1.0
Package: zfit
Type: Package
Title: Fit Models in a Pipe
Version: 0.1.0
Author: Magnus Thor Torfason
Maintainer: Magnus Thor Torfason <m@zulutime.net>
Description: The goal of 'zfit' is to improve the usage of basic model fitting functions within a piped work flow, in particular when passing and processing a data.frame using 'dplyr' or similar packages.
License: MIT + file LICENSE
Language: en-US
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
Suggests: testthat, dplyr
Imports: magrittr
NeedsCompilation: no
Packaged: 2020-06-26 13:36:03 UTC; magnus
Repository: CRAN
Date/Publication: 2020-06-26 16:00:02 UTC

More information about zfit at CRAN
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New package tiledb with initial version 0.7.0
Package: tiledb
Type: Package
Version: 0.7.0
Title: Sparse and Dense Multidimensional Array Storage Engine for Data Science
Author: TileDB, Inc.
Copyright: TileDB, Inc.
Maintainer: Dirk Eddelbuettel <dirk@tiledb.com>
Description: The data science storage engine 'TileDB' introduces a powerful on-disk format for multi-dimensional arrays. It supports dense and sparse arrays, dataframes and key-values stores, cloud storage ('S3', 'GCS', 'Azure'), chunked arrays, multiple compression, encryption and checksum filters, uses a fully multi-threaded implementation, supports parallel I/O, data versioning ('time travel'), metadata and groups. It is implemented as an embeddable cross-platform C++ library with APIs from several languages, and integrations.
License: MIT + file LICENSE
URL: https://github.com/TileDB-Inc/TileDB-R
BugReports: https://github.com/TileDB-Inc/TileDB-R/issues
SystemRequirements: cmake, curl, git
OS_type: unix
Imports: methods, Rcpp, nanotime
LinkingTo: Rcpp
Suggests: testthat, rmarkdown, knitr, BiocStyle
VignetteBuilder: knitr
RoxygenNote: 7.1.0
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2020-06-26 11:26:05.587211 UTC; edd
Repository: CRAN
Date/Publication: 2020-06-26 16:00:06 UTC

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Package sofa updated to version 0.4.0 with previous version 0.3.0 dated 2018-01-03

Title: Connector to 'CouchDB'
Description: Provides an interface to the 'NoSQL' database 'CouchDB' (<http://couchdb.apache.org>). Methods are provided for managing databases within 'CouchDB', including creating/deleting/updating/transferring, and managing documents within databases. One can connect with a local 'CouchDB' instance, or a remote 'CouchDB' databases such as 'Cloudant'. Documents can be inserted directly from vectors, lists, data.frames, and 'JSON'. Targeted at 'CouchDB' v2 or greater.
Author: Scott Chamberlain [aut, cre] (<https://orcid.org/0000-0003-1444-9135>), rOpenSci [fnd] (https://ropensci.org/)
Maintainer: Scott Chamberlain <myrmecocystus@gmail.com>

Diff between sofa versions 0.3.0 dated 2018-01-03 and 0.4.0 dated 2020-06-26

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Package raster updated to version 3.3-6 with previous version 3.1-5 dated 2020-04-19

Title: Geographic Data Analysis and Modeling
Description: Reading, writing, manipulating, analyzing and modeling of spatial data. The package implements basic and high-level functions for raster data and for vector data operations such as intersections. See the manual and tutorials on <https://rspatial.org/> to get started.
Author: Robert J. Hijmans [cre, aut] (<https://orcid.org/0000-0001-5872-2872>), Jacob van Etten [ctb], Michael Sumner [ctb], Joe Cheng [ctb], Dan Baston [ctb], Andrew Bevan [ctb], Roger Bivand [ctb], Lorenzo Busetto [ctb], Mort Canty [ctb], David Forrest [ctb], Aniruddha Ghosh [ctb], Duncan Golicher [ctb], Josh Gray [ctb], Jonathan A. Greenberg [ctb], Paul Hiemstra [ctb], Kassel Hingee [ctb], Institute for Mathematics Applied Geosciences [cph], Charles Karney [ctb], Matteo Mattiuzzi [ctb], Steven Mosher [ctb], Jakub Nowosad [ctb], Edzer Pebesma [ctb], Oscar Perpinan Lamigueiro [ctb], Etienne B. Racine [ctb], Barry Rowlingson [ctb], Ashton Shortridge [ctb], Bill Venables [ctb], Rafael Wueest [ctb]
Maintainer: Robert J. Hijmans <r.hijmans@gmail.com>

Diff between raster versions 3.1-5 dated 2020-04-19 and 3.3-6 dated 2020-06-26

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More information about raster at CRAN
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New package mmaqshiny with initial version 1.0.0
Package: mmaqshiny
Title: Explore Air-Quality Mobile-Monitoring Data
Version: 1.0.0
Authors@R: c( person(given = "Adithi R.", family = "Upadhya", email = "adithi@ilklabs.com", role = c("aut", "cre", "cph")), person(given = "Pratyush", family = "Agrawal", email = "pratyush@ilklabs.com", role = "dtc"), person(given = "Sreekanth", family = "Vakacherla", email = "sree.hcu@gmail.com", role = c("aui", "ctb")), person(given = "Meenakshi", family = "Kushwaha", email = "meenakshi@ilklabs.com", role = c("aut", "cph")))
Description: Mobile-monitoring or "sensors on a mobile platform", is an increasingly popular approach to measure high-resolution pollution data at the street level. Coupled with location data, spatial visualisation of air-quality parameters helps detect localized areas of high air-pollution, also called hotspots. In this approach, portable sensors are mounted on a vehicle and driven on predetermined routes to collect high frequency data (1 Hz). 'mmaqshiny' is for analysing, visualising and spatial mapping of high-resolution air-quality data collected by specific devices installed on a moving platform. 1 Hz data of PM2.5 (mass concentrations of particulate matter with size less than 2.5 microns), Black carbon mass concentrations (BC), ultra-fine particle number concentrations, carbon dioxide along with GPS coordinates and relative humidity (RH) data collected by popular portable instruments (TSI DustTrak-8530, Aethlabs microAeth-AE51, TSI CPC3007, LICOR Li-830, Garmin GPSMAP 64s, Omega USB RH probe respectively). It incorporates device specific cleaning and correction algorithms. RH correction is applied to DustTrak PM2.5 following the Chakrabarti et al., (2004) <doi:10.1016/j.atmosenv.2004.03.007>. Provision is given to add linear regression coefficients for correcting the PM2.5 data (if required). BC data will be cleaned for the vibration generated noise, by adopting the statistical procedure as explained in Apte et al., (2011) <doi:10.1016/j.atmosenv.2011.05.028>, followed by a loading correction as suggested by Ban-Weiss et al., (2009) <doi:10.1021/es8021039>. For the number concentration data, provision is given for dilution correction factor (if a diluter is used with CPC3007; default value is 1). The package joins the raw, cleaned and corrected data from the above said instruments and outputs as a downloadable csv file.
Depends: R (>= 3.5.0)
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: htmltools, Cairo, xts, lubridate, zoo, caTools, ggplot2, data.table, DT, dplyr, leaflet, stringr, shiny, XML, shinyjs, plotly
Suggests: testthat, devtools, usethis, shinytest
RoxygenNote: 7.1.0
URL: https://github.com/meenakshi-kushwaha/mmaqshiny
BugReports: https://github.com/meenakshi-kushwaha/mmaqshiny/issues
NeedsCompilation: no
Packaged: 2020-06-26 13:14:05 UTC; ILK Consultancy
Author: Adithi R. Upadhya [aut, cre, cph], Pratyush Agrawal [dtc], Sreekanth Vakacherla [aui, ctb], Meenakshi Kushwaha [aut, cph]
Maintainer: Adithi R. Upadhya <adithi@ilklabs.com>
Repository: CRAN
Date/Publication: 2020-06-26 16:00:23 UTC

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Package localIV updated to version 0.3.1 with previous version 0.3.0 dated 2020-04-01

Title: Estimation of Marginal Treatment Effects using Local Instrumental Variables
Description: In the generalized Roy model, the marginal treatment effect (MTE) can be used as a building block for constructing conventional causal parameters such as the average treatment effect (ATE) and the average treatment effect on the treated (ATT). Given a treatment selection equation and an outcome equation, the function mte() estimates the MTE via the semiparametric local instrumental variables method or the normal selection model. The function mte_at() evaluates MTE at different values of the latent resistance u with a given X = x, and the function mte_tilde_at() evaluates MTE projected onto the estimated propensity score. The function ace() estimates population-level average causal effects such as ATE, ATT, or the marginal policy relevant treatment effect.
Author: Xiang Zhou [aut, cre]
Maintainer: Xiang Zhou <xiang_zhou@fas.harvard.edu>

Diff between localIV versions 0.3.0 dated 2020-04-01 and 0.3.1 dated 2020-06-26

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Package littler updated to version 0.3.11 with previous version 0.3.10 dated 2020-06-03

Title: R at the Command-Line via 'r'
Description: A scripting and command-line front-end is provided by 'r' (aka 'littler') as a lightweight binary wrapper around the GNU R language and environment for statistical computing and graphics. While R can be used in batch mode, the r binary adds full support for both 'shebang'-style scripting (i.e. using a hash-mark-exclamation-path expression as the first line in scripts) as well as command-line use in standard Unix pipelines. In other words, r provides the R language without the environment.
Author: Dirk Eddelbuettel and Jeff Horner
Maintainer: Dirk Eddelbuettel <edd@debian.org>

Diff between littler versions 0.3.10 dated 2020-06-03 and 0.3.11 dated 2020-06-26

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Package kit updated to version 0.0.3 with previous version 0.0.2 dated 2020-05-24

Title: Data Manipulation Functions Implemented in C
Description: Basic functions, implemented in C, for large data manipulation. Fast vectorised ifelse()/nested if()/switch() functions, psum()/pprod() functions equivalent to pmin()/pmax() plus others which are missing from base R. Most of these functions are callable at C level.
Author: Morgan Jacob [aut, cre, cph]
Maintainer: Morgan Jacob <morgan.emailbox@gmail.com>

Diff between kit versions 0.0.2 dated 2020-05-24 and 0.0.3 dated 2020-06-26

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Package cobalt updated to version 4.2.2 with previous version 4.2.1 dated 2020-06-20

Title: Covariate Balance Tables and Plots
Description: Generate balance tables and plots for covariates of groups preprocessed through matching, weighting or subclassification, for example, using propensity scores. Includes integration with 'MatchIt', 'twang', 'Matching', 'optmatch', 'CBPS', 'ebal', 'WeightIt', 'cem', 'sbw', and 'designmatch' for assessing balance on the output of their preprocessing functions. Users can also specify data for balance assessment not generated through the above packages. Also included are methods for assessing balance in clustered or multiply imputed data sets or data sets with longitudinal treatments.
Author: Noah Greifer [aut, cre] (<https://orcid.org/0000-0003-3067-7154>)
Maintainer: Noah Greifer <noah.greifer@gmail.com>

Diff between cobalt versions 4.2.1 dated 2020-06-20 and 4.2.2 dated 2020-06-26

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New package bellreg with initial version 0.0.1
Package: bellreg
Title: Count Regression Models Based on the Bell Distribution
Version: 0.0.1
Authors@R: c(person(given = "Fabio", family = "Demarqui", email = "fndemarqui@est.ufmg.br", role = c("aut", "cre"), comment = c(ORCID = "0000-0001-9236-1986")), person(given = "Marcos", family = "Prates", role = "ctb", comment = c(ORCID = "0000-0001-8077-4898")), person(given = "Fredy", family = "Caceres", role = "ctb", comment = c(ORCID = "0000-0001-8077-4898")))
Description: Bell regression models for count data with overdispersion. The implemented models account for ordinary and zero-inflated regression models under both frequentist and Bayesian approaches. Theoretical details regarding the models implemented in the package can be found in Castellares et al. (2018) <doi:10.1016/j.apm.2017.12.014> and Lemonte et al. (2020) <doi:10.1080/02664763.2019.1636940>.
License: GPL (>= 2)
URL: https://github.com/fndemarqui/bellreg
BugReports: https://github.com/fndemarqui/bellreg/issues
Encoding: UTF-8
LazyData: true
Biarch: true
Depends: R (>= 3.4.0)
Imports: extraDistr, Formula, magic, MASS, methods, numbers, Rcpp (>= 0.12.0), Rdpack, rstan (>= 2.18.1), rstantools (>= 2.0.0)
RdMacros: Rdpack
LinkingTo: BH (>= 1.66.0), Rcpp (>= 0.12.0), RcppEigen (>= 0.3.3.3.0), rstan (>= 2.18.1), StanHeaders (>= 2.18.0)
SystemRequirements: GNU make
RoxygenNote: 7.1.0
Suggests: testthat
NeedsCompilation: yes
Packaged: 2020-06-26 11:31:10 UTC; fndemarqui
Author: Fabio Demarqui [aut, cre] (<https://orcid.org/0000-0001-9236-1986>), Marcos Prates [ctb] (<https://orcid.org/0000-0001-8077-4898>), Fredy Caceres [ctb] (<https://orcid.org/0000-0001-8077-4898>)
Maintainer: Fabio Demarqui <fndemarqui@est.ufmg.br>
Repository: CRAN
Date/Publication: 2020-06-26 16:00:27 UTC

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Package sadists updated to version 0.2.4 with previous version 0.2.3 dated 2017-03-20

Title: Some Additional Distributions
Description: Provides the density, distribution, quantile and generation functions of some obscure probability distributions, including the doubly non-central t, F, Beta, and Eta distributions; the lambda-prime and K-prime; the upsilon distribution; the (weighted) sum of non-central chi-squares to a power; the (weighted) sum of log non-central chi-squares; the product of non-central chi-squares to powers; the product of doubly non-central F variables; the product of independent normals.
Author: Steven E. Pav [aut, cre] (<https://orcid.org/0000-0002-4197-6195>)
Maintainer: Steven E. Pav <shabbychef@gmail.com>

Diff between sadists versions 0.2.3 dated 2017-03-20 and 0.2.4 dated 2020-06-26

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Package RMPSH updated to version 1.1.1 with previous version 1.1.0 dated 2020-06-25

Title: Recursive Modified Pattern Search on Hyper-Rectangle
Description: Optimization of any Black-Box/Non-Convex Function on Hyper-Rectangular Parameter Space. It uses a Variation of Pattern Search Technique. Described in the paper : Das (2016) <arXiv:1604.08616> .
Author: Priyam Das [cre, aut], Debsurya De [aut]
Maintainer: Priyam Das <pdas@ncsu.edu>

Diff between RMPSH versions 1.1.0 dated 2020-06-25 and 1.1.1 dated 2020-06-26

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Package predictoR updated to version 1.1.2 with previous version 1.1.0 dated 2019-06-24

Title: Predictive Data Analysis System
Description: Perform a supervised data analysis on a database through a 'shiny' graphical interface. It includes methods such as K-Nearest Neighbors, Decision Trees, ADA Boosting, Extreme Gradient Boosting, Random Forest, Neural Networks, Deep Learning, Support Vector Machines and Bayesian Methods.
Author: Oldemar Rodriguez R. with contributions from Diego Jimenez A. and Andres Navarro D.
Maintainer: Oldemar Rodriguez <oldemar.rodriguez@ucr.ac.cr>

Diff between predictoR versions 1.1.0 dated 2019-06-24 and 1.1.2 dated 2020-06-26

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New package MinBAR with initial version 1.1.1
Type: Package
Package: MinBAR
Title: Determining the Minimal Background Area for Species Distribution Models
Version: 1.1.1
Authors@R: c( person("Xavier", "Rotllan-Puig", email = "xavier.rotllan.puig@aster-projects.cat", role = c("aut", "cre")), person("Anna", "Traveset", email = "atraveset@imedea.uib-csic.es", role = c("aut")))
Description: A versatile tool that aims at (1) defining what is the minimum background extent necessary to fit good partial species distribution models and/or (2) determining if the background area used to fit a partial species distribution model is reliable enough to extract ecologically relevant conclusions from it. See Rotllan-Puig, X. & Traveset, A. (2019) <doi:10.1101/571182>.
Depends: R (>= 3.4.0)
Imports: raster, rgdal, sp, maxnet, dismo (>= 1.1-4), ecospat (>= 2.2.0), geosphere (>= 1.5-5), lattice, latticeExtra
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
URL: https://github.com/xavi-rp/MinBAR
BugReports: https://github.com/xavi-rp/MinBAR/issues
NeedsCompilation: no
Packaged: 2020-06-26 11:09:58 UTC; xavi_rp
Author: Xavier Rotllan-Puig [aut, cre], Anna Traveset [aut]
Maintainer: Xavier Rotllan-Puig <xavier.rotllan.puig@aster-projects.cat>
Repository: CRAN
Date/Publication: 2020-06-26 14:30:06 UTC

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Package lamW updated to version 1.3.3 with previous version 1.3.2 dated 2020-05-25

Title: Lambert-W Function
Description: Implements both real-valued branches of the Lambert-W function (Corless et al, 1996) <doi:10.1007/BF02124750> without the need for installing the entire GSL.
Author: Avraham Adler [aut, cph, cre] (<https://orcid.org/0000-0002-3039-0703>)
Maintainer: Avraham Adler <Avraham.Adler@gmail.com>

Diff between lamW versions 1.3.2 dated 2020-05-25 and 1.3.3 dated 2020-06-26

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Package inventorize updated to version 1.0.5 with previous version 1.0.4 dated 2020-06-25

Title: Inventory Analytics and Cost Calculations
Description: Simulate inventory policies, facilitate inventory analysis calculations such as stock levels and re-order points,pricing and promotions calculations. The package includes calculations of inventory metrics, stock-out calculations and ABC analysis calculations. The package includes revenue management techniques such as Multi-product optimization,logit model optimization. The functions are referenced from : 1-Harris, Ford W. (1913). "How many parts to make at once". Factory, The Magazine of Management. <isbn10: 135–136, 152>. 2- Nahmias, S. Production and Operations Analysis. McGraw-Hill International Edition. <isbn: 0-07- 2231265-3. Chapter 4>. 3-Silver, E.A., Pyke, D.F., Peterson, R. Inventory Management and Production Planning and Scheduling. <isbn: 978-0471119470>. 4-Ballou, R.H. Business Logistics Management. <isbn: 978-0130661845>. Chapter 9. 5-MIT Micromasters Program. 6- Columbia University course for supply and demand analysis. 8- Price Elasticity of Demand MATH 104,Mark Mac Lean (with assistance from Patrick Chan) 2011W For further details or correspondence :<www.linkedin.com/in/haythamomar>, <www.rescaleanalytics.com>.
Author: Haytham Omar [aut, cre]
Maintainer: Haytham Omar <haytham@rescaleanalytics.com>

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Package influential updated to version 1.1.2 with previous version 1.1.1 dated 2020-06-24

Title: Identification and Classification of the Most Influential Nodes
Description: Contains functions for the classification and ranking of top candidate features, reconstruction of networks from adjacency matrices and data frames, analysis of the topology of the network and calculation of centrality measures, and identification of the most influential nodes. Also, a function is provided for running SIRIR model, which is the combination of leave-one-out cross validation technique and the conventional SIR model, on a network to unsupervisedly rank the true influence of vertices. Additionally, some functions have been provided for the assessment of dependence and correlation of two network centrality measures as well as the conditional probability of deviation from their corresponding means in opposite direction. Fred Viole and David Nawrocki (2013, ISBN:1490523995). Csardi G, Nepusz T (2006). "The igraph software package for complex network research." InterJournal, Complex Systems, 1695. Adopted algorithms and sources are referenced in function document.
Author: Adrian (Abbas) Salavaty [aut, cre], Mirana Ramialison [ths], Peter D. Currie [ths]
Maintainer: Adrian Salavaty <abbas.salavaty@gmail.com>

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Package hybridModels updated to version 0.3.7 with previous version 0.3.6 dated 2020-04-16

Title: An R Package for the Stochastic Simulation of Disease Spreading in Dynamic Networks
Description: Simulates stochastic hybrid models for transmission of infectious diseases in dynamic networks. It is a metapopulation model in which each node in the network is a sub-population and disease spreads within nodes and among them, combining two approaches: stochastic simulation algorithm (<doi:10.1146/annurev.physchem.58.032806.104637>) and individual-based approach, respectively. Equations that models spread within nodes are customizable and there are two link types among nodes: migration and influence (commuting). More information in Fernando S. Marques, Jose H. H. Grisi-Filho, Marcos Amaku et al. (2020) <doi:10.18637/jss.v094.i06>.
Author: Fernando S. Marques [aut, cre], Jose H. H. Grisi-Filho [aut], Marcos Amaku [aut]
Maintainer: Fernando S. Marques <fernandosix@gmail.com>

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Package discoveR updated to version 1.2.7 with previous version 1.2.4 dated 2020-01-13

Title: Exploratory Data Analysis System
Description: Performs an exploratory data analysis through a 'shiny' interface. It includes basic methods such as the mean, median, mode, normality test, among others. It also includes clustering techniques such as Principal Components Analysis, Hierarchical Clustering and the K-Means Method.
Author: Oldemar Rodriguez R. with contributions from Diego Jimenez A. and Andres Navarro D.
Maintainer: Oldemar Rodriguez <oldemar.rodriguez@ucr.ac.cr>

Diff between discoveR versions 1.2.4 dated 2020-01-13 and 1.2.7 dated 2020-06-26

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Package aricode updated to version 1.0.0 with previous version 0.1.2 dated 2019-06-29

Title: Efficient Computations of Standard Clustering Comparison Measures
Description: Implements an efficient O(n) algorithm based on bucket-sorting for fast computation of standard clustering comparison measures. Available measures include adjusted Rand index (ARI), normalized information distance (NID), normalized mutual information (NMI), adjusted mutual information (AMI), normalized variation information (NVI) and entropy, as described in Vinh et al (2009) <doi:10.1145/1553374.1553511>. Include AMI (Adjusted Mutual Information) since version 0.1.2, a modified version of ARI (MARI) and simple Chi-square distance since version 1.0.0.
Author: Julien Chiquet [aut, cre] (<https://orcid.org/0000-0002-3629-3429>), Guillem Rigaill [aut], Martina Sundqvist [aut], Valentin Dervieux [ctb]
Maintainer: Julien Chiquet <julien.chiquet@inrae.fr>

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Package FCPS updated to version 1.2.3 with previous version 1.2.2 dated 2020-06-07

Title: Fundamental Clustering Problems Suite
Description: Many conventional clustering algorithms are provided in this package with consistent input and output, which enables the user to try out algorithms swiftly. Additionally, 26 statistical approaches for the estimation of the number of clusters as well as the the mirrored density plot (MD-plot) of clusterability are implemented. Moreover, the fundamental clustering problems suite (FCPS) offers a variety of clustering challenges any algorithm should handle when facing real world data, see Thrun, M.C., Ultsch A.: "Clustering Benchmark Datasets Exploiting the Fundamental Clustering Problems" (2020), Data in Brief, <DOI:10.1016/j.dib.2020.105501>.
Author: Michael Thrun [aut, cre, cph] (<https://orcid.org/0000-0001-9542-5543>), Quirin Stier [ctb, rev], Peter Nahrgang [ctr, ctb], Felix Pape [ctr, ctb], Vasyl Pihur [ctb], Guy Brock [ctb], Susmita Datta [ctb], Somnath Datta [ctb], Luis Winckelmann [com], Alfred Ultsch [dtc, ctb]
Maintainer: Michael Thrun <m.thrun@gmx.net>

Diff between FCPS versions 1.2.2 dated 2020-06-07 and 1.2.3 dated 2020-06-26

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New package sever with initial version 0.0.4
Package: sever
Title: Customise 'Shiny' Disconnected Screens and Error Messages
Version: 0.0.4
Date: 2020-06-22
Authors@R: person(given = "John", family = "Coene", role = c("aut", "cre"), email = "jcoenep@gmail.com")
Description: Customise 'Shiny' disconnected screens as well as sanitize error messages to make them clearer and friendlier to the user.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0.9000
Imports: cli, shiny
URL: http://sever.john-coene.com/
BugReports: https://github.com/JohnCoene/sever/issues
NeedsCompilation: no
Packaged: 2020-06-23 20:52:17 UTC; jp
Author: John Coene [aut, cre]
Maintainer: John Coene <jcoenep@gmail.com>
Repository: CRAN
Date/Publication: 2020-06-26 11:50:02 UTC

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New package guaguas with initial version 0.1.0
Package: guaguas
Title: Nombres Inscritos en Chile (1920 - 2019)
Version: 0.1.0
Authors@R: person(given = "Riva", family = "Quiroga", role = c("aut", "cre"), email = "riva.quiroga@uc.cl", comment = c(ORCID = "0000-0002-1147-4135"))
Description: Datos de nombres inscritos en Chile entre 1920 y 2019, de acuerdo al Servicio de Registro Civil. Este paquete incluye todos los nombres con al menos 15 ocurrencias anuales. English: Chilean baby names registered in the Civil Registry Service. This package contains all names used at least 15 times per year, from 1920 to 2019.
License: CC0
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
Depends: R (>= 2.10)
Imports: tibble
URL: https://github.com/rivaquiroga/guaguas
BugReports: https://github.com/rivaquiroga/guaguas/issues
NeedsCompilation: no
Packaged: 2020-06-24 02:32:53 UTC; ciruelo
Author: Riva Quiroga [aut, cre] (<https://orcid.org/0000-0002-1147-4135>)
Maintainer: Riva Quiroga <riva.quiroga@uc.cl>
Repository: CRAN
Date/Publication: 2020-06-26 12:00:02 UTC

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New package GInSARCorW with initial version 1.15.6
Package: GInSARCorW
Type: Package
Title: GACOS InSAR Correction Workflow
Version: 1.15.6
Date: 2020-06-24
Author: Subhadip Datta
Maintainer: Subhadip Datta <subhadipdatta007@gmail.com>
Description: A workflow for correction of Differential Interferometric Synthetic Aperture Radar (DInSAR) atmospheric delay base on Generic Atmospheric Correction Online Service for InSAR (GACOS) data and correction algorithms proposed by Chen Yu. You can find atmospheric delay data here: <http://ceg-research.ncl.ac.uk/v2/gacos>.This package calculate the Both Zenith and LOS direction (User Depend). You have to just download GACOS product on your area and preprocessed D-InSAR unwrapped images. Cite those references and this package in your work, when using this framework. References: Yu, C., N. T. Penna, and Z. Li (2017) <doi:10.1016/j.rse.2017.10.038>. Yu, C., Li, Z., & Penna, N. T. (2017) <doi:10.1016/j.rse.2017.10.038>. Yu, C., Penna, N. T., and Li, Z. (2017) <doi:10.1002/2016JD025753>.
License: GPL-3
URL: <https://subhadipdatta007.wixsite.com/profile/post/ginsarcorw-gacos-insar-correction-workflow>
Repository: CRAN
Depends: raster, circular
Imports: rgdal, rgeos, sp
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-06-24 09:11:09 UTC; subha
Date/Publication: 2020-06-26 12:00:06 UTC

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New package colorDF with initial version 0.1.0
Package: colorDF
Title: Colorful Data Frames in R Terminal
Version: 0.1.0
Authors@R: person(given = "January", family = "Weiner", role = c("aut", "cre"), email = "january.weiner@gmail.com", comment = c(ORCID = "0000-0003-1438-7819"))
Description: Colorful Data Frames in the terminal. The new class does change the behaviour of any of the objects, but adds a style definition and a print method. Using ANSI escape codes, it colors the terminal output of data frames. Some column types (such as p-values and identifiers) are automatically recognized.
Depends: R (>= 2.10)
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: purrr,crayon
Suggests: knitr, rmarkdown, fansi, tidyverse, data.table, testthat (>= 2.1.0)
VignetteBuilder: knitr
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-06-23 20:29:33 UTC; january
Author: January Weiner [aut, cre] (<https://orcid.org/0000-0003-1438-7819>)
Maintainer: January Weiner <january.weiner@gmail.com>
Repository: CRAN
Date/Publication: 2020-06-26 11:50:06 UTC

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New package riskCommunicator with initial version 0.1.0
Package: riskCommunicator
Title: G-Computation to Estimate Interpretable Epidemiological Effects
Version: 0.1.0
Authors@R: c( person(given = "Jessica", family = "Grembi", role = c("aut", "cre", "cph"), email = "jess.grembi@gmail.com", comment = c(ORCID = "0000-0001-6142-4913")), person("Elizabeth", "Rogawski McQuade", role = "ctb", comment = c(ORCID = "0000-0002-4942-3747")))
Depends: R (>= 3.5)
Imports: boot, dplyr, ggplot2, gridExtra, magrittr, purrr, stats, rlang, tidyr, tidyselect, tidyverse
Description: Estimates flexible epidemiological effect measures including both differences and ratios using the parametric G-formula developed as an alternative to inverse probability weighting. It is useful for estimating the impact of interventions in the presence of treatment-confounder-feedback. G-computation was originally described by Robbins (1986) <doi:10.1016/0270-0255(86)90088-6> and has been described in detail by Ahern, Hubbard, and Galea (2009) <doi:10.1093/aje/kwp015>; Snowden, Rose, and Mortimer (2011) <doi:10.1093/aje/kwq472>; and Westreich et al. (2012) <doi:10.1002/sim.5316>.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
Suggests: knitr, rmarkdown, testthat, printr
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-06-23 06:01:48 UTC; JGrembi
Author: Jessica Grembi [aut, cre, cph] (<https://orcid.org/0000-0001-6142-4913>), Elizabeth Rogawski McQuade [ctb] (<https://orcid.org/0000-0002-4942-3747>)
Maintainer: Jessica Grembi <jess.grembi@gmail.com>
Repository: CRAN
Date/Publication: 2020-06-26 10:10:02 UTC

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New package RcmdrPlugin.WorldFlora with initial version 1.0
Package: RcmdrPlugin.WorldFlora
Type: Package
Title: R Commander Plug-in for the 'WorldFlora' Package
Version: 1.0
Date: 2020-6-13
Author: Roeland Kindt
Maintainer: Roeland Kindt <R.KINDT@CGIAR.ORG>
Depends: R (>= 3.5.0), WorldFlora (>= 1.6)
Imports: Rcmdr (>= 2.4-0)
Description: An R Commander plug-in for the 'WorldFlora' package. It was mainly developed to show workflows and scripts for first-time users.
License: GPL-2
Suggests: data.table, utils, stringr
Packaged: 2020-06-23 05:53:05 UTC; RKINDT
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2020-06-26 10:10:10 UTC

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New package qtl2 with initial version 0.22-8
Package: qtl2
Version: 0.22-8
Date: 2020-06-22
Title: Quantitative Trait Locus Mapping in Experimental Crosses
Description: Provides a set of tools to perform quantitative trait locus (QTL) analysis in experimental crosses. It is a reimplementation of the 'R/qtl' package to better handle high-dimensional data and complex cross designs. Broman et al. (2018) <doi:10.1534/genetics.118.301595>.
Author: Karl W Broman [aut, cre] (<https://orcid.org/0000-0002-4914-6671>), R Core Team [ctb]
Maintainer: Karl W Broman <broman@wisc.edu>
Authors@R: c(person("Karl W", "Broman", role=c("aut", "cre"), email="broman@wisc.edu", comment=c(ORCID = "0000-0002-4914-6671")), person("R Core Team", role="ctb"))
Copyright: Code for Brent's method for univariate function optimization was taken from R 3.2.2 (Copyright (c) 1995, 1996 Robert Gentleman and Ross Ihaka, Copyright (C) 2003-2004 The R Foundation, Copyright (C) 1998-2014 The R Core Team).
Depends: R (>= 3.1.0)
Imports: Rcpp (>= 0.12.12), yaml (>= 2.1.13), jsonlite (>= 0.9.17), data.table (>= 1.10.4-3), parallel, stats, utils, graphics, grDevices, RSQLite
Suggests: testthat, devtools, roxygen2, vdiffr, qtl
License: GPL-3
URL: https://kbroman.org/qtl2, https://github.com/rqtl/qtl2
BugReports: https://github.com/rqtl/qtl2/issues
LazyData: true
Encoding: UTF-8
ByteCompile: true
LinkingTo: Rcpp, RcppEigen
RoxygenNote: 7.1.0
NeedsCompilation: yes
Packaged: 2020-06-22 11:12:00 UTC; kbroman
Repository: CRAN
Date/Publication: 2020-06-26 10:40:02 UTC

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New package epca with initial version 1.0.0
Package: epca
Type: Package
Title: Exploratory Principal Component Analysis
Version: 1.0.0
Date: 2020-06-20
Authors@R: person(given = "Fan", family = "Chen", role = c("aut", "cre"), email = "fan.chen@wisc.edu", comment = c(ORCID = "0000-0003-4508-6023"))
Description: Exploratory principal component analysis for large-scale dataset, including sparse principal component analysis and sparse matrix approximation.
URL: https://github.com/fchen365/epca
BugReports: https://github.com/fchen365/epca/issues
License: GPL-3
Depends: R (>= 3.5),
Imports: clue, irlba, imager, matlab, Matrix, RSpectra, tidyverse, GPArotation,
Suggests: elasticnet, ggcorrplot, rmarkdown, markdown, reshape2, matlabr, knitr, PMA,
VignetteBuilder: knitr, rmarkdown
Encoding: UTF-8
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-06-23 06:05:43 UTC; fanchen
Author: Fan Chen [aut, cre] (<https://orcid.org/0000-0003-4508-6023>)
Maintainer: Fan Chen <fan.chen@wisc.edu>
Repository: CRAN
Date/Publication: 2020-06-26 10:10:06 UTC

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New package ecorest with initial version 1.0.0
Package: ecorest
Title: Conducts Analyses Informing Ecosystem Restoration Decisions
Version: 1.0.0
Authors@R: c(person(given = "S. Kyle", family = "McKay", role = c("aut", "cre"), email = "kyle.mckay@usace.army.mil", comment = c(ORCID = "0000-0003-2703-3841")), person(given = "Darixa D.", family = "Hernandez-Abrams", role = c("aut"), email = "darixa.d.hernandez-abrams@erdc.dren.mil"))
Description: Three sets of data and functions for informing ecosystem restoration decisions, particularly in the context of the U.S. Army Corps of Engineers. First, model parameters are compiled as a data set and associated metadata for over 500 habitat suitability models developed by the U.S. Fish and Wildlife Service (USFWS 1980) <https://www.fws.gov/policy/ESMindex.html>. Second, functions for conducting habitat suitability analyses both for the models described above as well as generic user-specified model parameterizations. Third, a suite of decision support tools for conducting cost-effectiveness and incremental cost analyses (Robinson et al. 1995) <https://www.iwr.usace.army.mil/Portals/70/docs/iwrreports/95-R-1.pdf>.
Depends: R (>= 3.5.0)
License: CC0
Encoding: UTF-8
LazyData: true
Imports: viridis, stats, graphics, grDevices
RoxygenNote: 7.0.2
NeedsCompilation: no
Packaged: 2020-06-23 11:14:27 UTC; u4eevskm
Author: S. Kyle McKay [aut, cre] (<https://orcid.org/0000-0003-2703-3841>), Darixa D. Hernandez-Abrams [aut]
Maintainer: S. Kyle McKay <kyle.mckay@usace.army.mil>
Repository: CRAN
Date/Publication: 2020-06-26 10:50:03 UTC

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Package SimilaR updated to version 1.0.8 with previous version 1.0.7 dated 2020-04-06

Title: R Source Code Similarity Evaluation
Description: An implementation of a novel method to quantify the similarity of the code-base of R functions by means of program dependence graphs. Possible use cases include detection of code clones for improving software quality and of plagiarism amongst students' assignments.
Author: Maciej Bartoszuk [aut, cre] (<https://orcid.org/0000-0001-6088-8273>), Marek Gagolewski [aut] (<https://orcid.org/0000-0003-0637-6028>)
Maintainer: Maciej Bartoszuk <bartoszuk@rexamine.com>

Diff between SimilaR versions 1.0.7 dated 2020-04-06 and 1.0.8 dated 2020-06-26

 SimilaR-1.0.7/SimilaR/R/SimilaR_fromTwoFunctions.R                   |only
 SimilaR-1.0.7/SimilaR/man/SimilaR_fromTwoFunctions.Rd                |only
 SimilaR-1.0.8/SimilaR/DESCRIPTION                                    |   17 
 SimilaR-1.0.8/SimilaR/MD5                                            |   24 
 SimilaR-1.0.8/SimilaR/R/SimilaR_fromDirectory.R                      |  109 +
 SimilaR-1.0.8/SimilaR/R/SimilaR_general.R                            |    2 
 SimilaR-1.0.8/SimilaR/R/antiplagiarism.R                             |    2 
 SimilaR-1.0.8/SimilaR/R/load.R                                       |   17 
 SimilaR-1.0.8/SimilaR/R/similar-package.R                            |    4 
 SimilaR-1.0.8/SimilaR/man/SimilaR-package.Rd                         |    3 
 SimilaR-1.0.8/SimilaR/man/SimilaR_fromDirectory.Rd                   |   90 +
 SimilaR-1.0.8/SimilaR/tests/testthat/test-SimilaR_fromDirectory.R    |   44 
 SimilaR-1.0.8/SimilaR/tests/testthat/test-SimilaR_fromTwoFunctions.R |   64 -
 SimilaR-1.0.8/SimilaR/tests/testthat/test-algorithm.R                |  638 ++++------
 14 files changed, 566 insertions(+), 448 deletions(-)

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New package scDIFtest with initial version 0.1.0
Package: scDIFtest
Type: Package
Title: Item-Wise Score-Based DIF Detection
Version: 0.1.0
Authors@R: c( person("Dries", "Debeer", email = "debeer.dries@gmail.com", role = c("cre", "aut")))
Description: Detection of item-wise Differential Item Functioning (DIF) in fitted 'mirt', 'multipleGroup' or 'bfactor' models using score-based structural change tests. Under the hood the sctest() function from the 'strucchange' package is used.
Imports: sandwich, strucchange, mirt, zoo,
Suggests: mvtnorm, psychotree, knitr, rmarkdown, testthat
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-06-25 13:30:55 UTC; u0067731
Author: Dries Debeer [cre, aut]
Maintainer: Dries Debeer <debeer.dries@gmail.com>
Repository: CRAN
Date/Publication: 2020-06-26 09:10:03 UTC

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New package rMorningStar with initial version 1.0.6
Package: rMorningStar
Title: Mutual Funds Performance Metrics
Version: 1.0.6
Authors@R: person(given = "Anurag", family = "Agrawal", role = c("aut", "cre"), email = "agrawalanurag1999@gmail.com", comment = c(ORCID = "0000-0003-2272-8273"))
Description: Collection of functions to calculate performance metrics of mutual funds/exchange traded funds. This package aids investors in researching mutual funds/exchange traded funds for their investment decision. Also, this package contains tools to manage a portfolio of different mutual fund/exchange traded funds. For more information see Bruce J. Feibel [2003, ISBN:978-0471445630].
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
Imports: PerformanceAnalytics, quantmod, xts, stringr, rvest, xml2, readr, purrr, tidyr, stringi, ggplot2, dplyr
NeedsCompilation: no
Packaged: 2020-06-25 17:29:28 UTC; Kanhaiiya Agrawal
Author: Anurag Agrawal [aut, cre] (<https://orcid.org/0000-0003-2272-8273>)
Maintainer: Anurag Agrawal <agrawalanurag1999@gmail.com>
Repository: CRAN
Date/Publication: 2020-06-26 09:20:02 UTC

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Package officer updated to version 0.3.12 with previous version 0.3.11 dated 2020-05-18

Title: Manipulation of Microsoft Word and PowerPoint Documents
Description: Access and manipulate 'Microsoft Word' and 'Microsoft PowerPoint' documents from R. The package focuses on tabular and graphical reporting from R; it also provides two functions that let users get document content into data objects. A set of functions lets add and remove images, tables and paragraphs of text in new or existing documents. When working with 'PowerPoint' presentations, slides can be added or removed; shapes inside slides can also be added or removed. When working with 'Word' documents, a cursor can be used to help insert or delete content at a specific location in the document. The package does not require any installation of Microsoft products to be able to write Microsoft files.
Author: David Gohel [aut, cre], Frank Hangler [ctb] (function body_replace_all_text), Liz Sander [ctb] (several documentation fixes), Anton Victorson [ctb] (fixes xml structures), Jon Calder [ctb] (update vignettes), John Harrold [ctb] (fuction annotate_base), John Muschelli [ctb] (google doc compatibility)
Maintainer: David Gohel <david.gohel@ardata.fr>

Diff between officer versions 0.3.11 dated 2020-05-18 and 0.3.12 dated 2020-06-26

 officer-0.3.11/officer/man/sections.Rd                           |only
 officer-0.3.12/officer/DESCRIPTION                               |    6 
 officer-0.3.12/officer/MD5                                       |   35 -
 officer-0.3.12/officer/NAMESPACE                                 |    2 
 officer-0.3.12/officer/NEWS                                      |   17 
 officer-0.3.12/officer/R/docx_add.R                              |   15 
 officer-0.3.12/officer/R/docx_section.R                          |  270 +++++-----
 officer-0.3.12/officer/R/knitr_utils.R                           |   11 
 officer-0.3.12/officer/R/read_docx.R                             |    4 
 officer-0.3.12/officer/README.md                                 |    6 
 officer-0.3.12/officer/build/vignette.rds                        |binary
 officer-0.3.12/officer/inst/doc/overview.html                    |   29 +
 officer-0.3.12/officer/inst/template/template.docx               |binary
 officer-0.3.12/officer/man/body_add.Rd                           |   12 
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 officer-0.3.12/officer/man/body_end_section_continuous.Rd        |only
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 officer-0.3.12/officer/man/body_end_section_portrait.Rd          |only
 officer-0.3.12/officer/tests/testthat/test-docx-add.R            |   22 
 officer-0.3.12/officer/tests/testthat/test-docx-misc.R           |    8 
 22 files changed, 272 insertions(+), 165 deletions(-)

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Package jmv updated to version 1.2.23 with previous version 1.2.5 dated 2020-02-17

Title: The 'jamovi' Analyses
Description: A suite of common statistical methods such as descriptives, t-tests, ANOVAs, regression, correlation matrices, proportion tests, contingency tables, and factor analysis. This package is also useable from the 'jamovi' statistical spreadsheet (see <https://www.jamovi.org> for more information).
Author: Ravi Selker, Jonathon Love, Damian Dropmann
Maintainer: Jonathon Love <jon@thon.cc>

Diff between jmv versions 1.2.5 dated 2020-02-17 and 1.2.23 dated 2020-06-26

 DESCRIPTION                  |   14 ++--
 MD5                          |  142 +++++++++++++++++++++----------------------
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 R/anovanp.h.R                |    3 
 R/anovaonew.b.R              |    9 +-
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 R/anovarm.b.R                |   25 +++++--
 R/anovarm.h.R                |    9 +-
 R/anovarmnp.h.R              |    3 
 R/cfa.h.R                    |    3 
 R/conttables.h.R             |    3 
 R/conttablespaired.h.R       |    3 
 R/corrmatrix.b.R             |    4 -
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 R/descriptives.b.R           |   50 ++++++++-------
 R/descriptives.h.R           |    3 
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 man/anovaRMNP.Rd             |   10 ++-
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 man/propTest2.Rd             |   19 ++++-
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 man/ttestOneS.Rd             |   39 +++++++++--
 man/ttestPS.Rd               |   36 ++++++++--
 tests/testthat/testanovarm.R |   31 +++++++++
 tests/testthat/testttestis.R |   12 ++-
 vignettes/new-syntax.Rmd     |    6 -
 72 files changed, 1295 insertions(+), 474 deletions(-)

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New package GPSeqClus with initial version 1.0.0
Package: GPSeqClus
Type: Package
Title: Sequential Clustering Algorithm for Location Data
Version: 1.0.0
Date: 2020-05-28
Author: Clapp, J. G.
Maintainer: Justin Clapp <justin.clapp@wyo.gov>
Description: Applies sequential clustering algorithm to animal location data based on user-defined parameters and appends results to the dataframe. Plots interactive cluster maps and provides a summary dataframe with attributes for each cluster commonly used as covariates in subsequent modeling efforts. Additional functions provide individual keyhole markup language plots for quick assessment, and export global positioning system exchange format files for navigation purposes.
Depends: R (>= 3.5)
Imports: geosphere, leaflet, leaflet.extras, plotKML, plyr, purrr, rgdal, sp, spacetime, stats, suncalc, tcltk, utils
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
NeedsCompilation: no
Packaged: 2020-06-22 19:13:55 UTC; jugclapp
Repository: CRAN
Date/Publication: 2020-06-26 10:00:15 UTC

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New package depigner with initial version 0.8.1
Package: depigner
Title: A Utility Package to Help you Deal with "Pignas"
Version: 0.8.1
Authors@R: person(given = "Corrado", family = "Lanera", role = c("aut", "cre", "cph"), email = "corrado.lanera@gmail.com")
Description: Pigna [_pìn'n'a_] is the Italian word for pine cone. In jargon, it is used to identify a task which is boring, banal, annoying, painful, frustrating and maybe even with a not so beautiful or rewarding result, just like the obstinate act of trying to challenge yourself in extracting pine nuts from a pine cone, provided that, in the end, you will find at least one inside it. Here you can find a backpack of functions to be used to solve small everyday problems of coding or analyzing (clinical) data, which would be normally solved using quick-and-dirty patches. You will be able to convert 'Hmisc' and 'rms' summary()es into data.frames ready to be rendered by 'pander' and 'knitr'. You can access easy-to-use wrappers to activate essential but useful progress bars (from 'progress') into your loops or functionals. Easy setup and control Telegram's bots (from 'telegram.bot') to send messages or to divert error messages to a Telegram's chat. You also have some utilities helping you in the development of packages, like the activation of the same user interface of 'usethis' into your package, or call polite functions to ask a user to install other packages. Finally, you find a set of thematic sets of packages you may use to set up new environments quickly, installing them in a single call.
License: GPL-3
URL: https://corradolanera.github.io/depigner/, https://github.com/CorradoLanera/depigner
BugReports: https://github.com/CorradoLanera/depigner/issues
Depends: R (>= 3.6)
Imports: broom (>= 0.5.0), desc, dplyr (>= 0.7.7), fs, ggplot2 (>= 3.1.0), Hmisc (>= 4.2.0), magrittr (>= 1.5), progress (>= 1.2.0), purrr (>= 0.2.5), rlang (>= 0.2.2), rprojroot, stats, stringr (>= 1.3.1), telegram.bot (>= 2.3.0), tibble (>= 1.4.2), tidyr (>= 0.8.1), usethis (>= 1.5.0), utils
Suggests: covr (>= 3.1.0), rms (>= 5.1.2), spelling, survival, testthat (>= 2.1.0), withr
Encoding: UTF-8
Language: en-US
LazyData: true
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-06-25 17:56:58 UTC; corrado
Author: Corrado Lanera [aut, cre, cph]
Maintainer: Corrado Lanera <corrado.lanera@gmail.com>
Repository: CRAN
Date/Publication: 2020-06-26 09:10:07 UTC

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New package vlda with initial version 1.1.5
Package: vlda
Type: Package
Title: Visualization of Multidimensional Longitudinal Data
Version: 1.1.5
Authors@R: c(person("Seongwon", "Ryu", email = "seongwon6154@gmail.com", role = c("aut", "cre")), person("Bohui", "Lee", email = "leebh@pusan.ac.kr", role = c("aut")), person("Yongseok", "Choi", email = "yschoi@pusan.ac.kr", role = c("ctb")))
Author: Seongwon Ryu [aut, cre], Bohui Lee [aut], Yongseok Choi [ctb]
Maintainer: Seongwon Ryu <seongwon6154@gmail.com>
Depends: R (>= 3.6.0)
Imports: dplyr, ggrepel, ggplot2, ggiraph, ggsci
Description: Assists in producing a plot that more effectively expresses changes over time for two different types (long format and wide format) using a consistent calling scheme for longitudinal data. It provides the ability to projection supplementary information (supplementary objects and variables) that can often occur in longitudinal data to graphs, as well as provides a new interactive implementation to perform the additional interpretation, so it is also useful for longitudinal data visuals analysis (see <http://lib.pusan.ac.kr/resource/e-article/?app=eds&mod=detail&record_id=edsker.000004649097&db_id=edsker> for more information).
License: MIT + file LICENSE
URL: https://github.com/pnuwon/vlda
BugReports: https://github.com/pnuwon/vlda/issues
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
NeedsCompilation: yes
Packaged: 2020-06-26 03:48:17 UTC; Ryu
Repository: CRAN
Date/Publication: 2020-06-26 08:50:02 UTC

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New package tidytuesdayR with initial version 1.0.0
Package: tidytuesdayR
Type: Package
Title: Access the Weekly 'TidyTuesday' Project Dataset
Version: 1.0.0
Authors@R: c( person( given = "Ellis", family = "Hughes", email = "ellishughes@live.com", role = c("aut", "cre") ), person( given = "Jon", family = "Harmon", email = "jonthegeek@gmail.com", role = "ctb" ), person( given = "Thomas", family = "Mock", email = "j.thomasmock@gmail.com", role = "ctb" ), person( given = "R4DS Online Learning Community", email = "rfordatasci@gmail.com", role = "dtc" ) )
Description: 'TidyTuesday' is a project by the 'R4DS Online Learning Community' in which they post a weekly dataset onto post a weekly dataset in a public data repository (<https://github.com/rfordatascience/tidytuesday>) for people to analyze and visualize. This package provides the tools to easily download this data and the description of the source.
License: MIT + file LICENSE
URL: https://github.com/thebioengineer/tidytuesdayR
BugReports: https://github.com/thebioengineer/tidytuesdayR/issues
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
Depends: R (>= 3.4.0)
Suggests: testthat (>= 2.1.0), covr, pkgdown, tibble
Imports: readxl (>= 1.0.0), rvest (>= 0.3.2), tools (>= 3.1.0), lubridate (>= 1.7.0), purrr (>= 0.2.5), readr (>= 1.0.0), rstudioapi (>= 0.2), xml2 (>= 1.2.0), httr, jsonlite, magrittr
NeedsCompilation: no
Packaged: 2020-06-25 22:23:52 UTC; ehhughes
Author: Ellis Hughes [aut, cre], Jon Harmon [ctb], Thomas Mock [ctb], R4DS Online Learning Community [dtc]
Maintainer: Ellis Hughes <ellishughes@live.com>
Repository: CRAN
Date/Publication: 2020-06-26 09:00:03 UTC

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New package sarsop with initial version 0.6.2
Package: sarsop
Type: Package
Title: Approximate POMDP Planning Software
Version: 0.6.2
Authors@R: c( person("Carl", "Boettiger", email = "cboettig@gmail.com", role = c("cre", "aut", "cph"), comment = c(ORCID = "0000-0002-1642-628X")), person("Jeroen", "Ooms", role = c("aut")), person("Milad", "Memarzadeh", role = "aut"), person("Hanna", "Kurniawati", role = c("ctb", "cph")), person("David", "Hsu", role = c("ctb", "cph")), person("Hanna", "Kurniawati", role = c("ctb", "cph")), person("Wee", "Sun Lee", role = c("ctb", "cph")), person("Yanzhu", "Du", role = "ctb"), person("Xan", "Huang", role = "ctb"), person("Trey", "Smith", role = c("ctb", "cph")), person("Tony", "Cassandra", role = c("ctb", "cph")), person("Lee", "Thomason", role = c("ctb", "cph")), person("Carl", "Kindman", role = c("ctb", "cph")), person("Le", "Trong Dao", role = c("ctb", "cph")), person("Amit", "Jain", role= c("ctb", "cph")), person("Rong", "Nan", role = c("ctb", "cph")), person("Ulrich", "Drepper", role = c("ctb")), person("", "Free Software Foundation", role = "cph"), person("Tyge", "Lovset", role = c("ctb", "cph")), person("Yves", "Berquin", role = c("ctb", "cph")), person("Benjamin", "Grüdelbach", role = "ctb"), person("", "RSA Data Security, Inc.", role = "cph") )
Description: A toolkit for Partially Observed Markov Decision Processes (POMDP). Provides bindings to C++ libraries implementing the algorithm SARSOP (Successive Approximations of the Reachable Space under Optimal Policies) and described in Kurniawati et al (2008), <doi:10.15607/RSS.2008.IV.009>. This package also provides a high-level interface for generating, solving and simulating POMDP problems and their solutions.
License: GPL-2
URL: https://github.com/boettiger-lab/sarsop
BugReports: https://github.com/boettiger-lab/sarsop/issues
RoxygenNote: 7.1.0
Imports: xml2, parallel, processx, digest, Matrix
Suggests: testthat, roxygen2, knitr, tidyverse, covr, spelling
LinkingTo: BH
Encoding: UTF-8
Language: en-US
NeedsCompilation: yes
Packaged: 2020-06-25 23:33:11 UTC; cboettig
Author: Carl Boettiger [cre, aut, cph] (<https://orcid.org/0000-0002-1642-628X>), Jeroen Ooms [aut], Milad Memarzadeh [aut], Hanna Kurniawati [ctb, cph], David Hsu [ctb, cph], Hanna Kurniawati [ctb, cph], Wee Sun Lee [ctb, cph], Yanzhu Du [ctb], Xan Huang [ctb], Trey Smith [ctb, cph], Tony Cassandra [ctb, cph], Lee Thomason [ctb, cph], Carl Kindman [ctb, cph], Le Trong Dao [ctb, cph], Amit Jain [ctb, cph], Rong Nan [ctb, cph], Ulrich Drepper [ctb], Free Software Foundation [cph], Tyge Lovset [ctb, cph], Yves Berquin [ctb, cph], Benjamin Grüdelbach [ctb], RSA Data Security, Inc. [cph]
Maintainer: Carl Boettiger <cboettig@gmail.com>
Repository: CRAN
Date/Publication: 2020-06-26 08:50:09 UTC

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New package metools with initial version 1.0.0
Package: metools
Title: Macroeconomics Tools
Version: 1.0.0
Authors@R: c(person(given = "João Victor", family = "Gomes de Araujo Santana", email = "jvg.santana@gmail.com", role = c("aut", "cre")))
Description: Provides a number of functions to facilitate the handling and production of reports using time series data. The package was developed to be understandable for beginners, so some functions aim to transform processes that would be complex into functions with a few lines. The main advantage of using the 'metools' package is the ease of producing reports and working with time series using a few lines of code, so the code is clean and easy to understand/maintain. Learn more about the 'metools' at <https://metoolsr.wordpress.com>.
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: ggplot2, scales, stringr, tibble, lubridate, tidyr
RoxygenNote: 7.1.0
URL: https://metoolsr.wordpress.com,https://github.com/jvg0mes/metools,https://jvg0mes.github.io/metoolsr
NeedsCompilation: no
Packaged: 2020-06-26 07:50:54 UTC; João Victor
Author: João Victor Gomes de Araujo Santana [aut, cre]
Maintainer: João Victor Gomes de Araujo Santana <jvg.santana@gmail.com>
Repository: CRAN
Date/Publication: 2020-06-26 08:50:14 UTC

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New package frenchCurve with initial version 0.1.0
Package: frenchCurve
Type: Package
Title: Generate Open or Closed Interpolating Curves
Version: 0.1.0
Author: Bill Venables
Maintainer: Bill Venables <Bill.Venables@gmail.com>
Description: Functions for finding smooth interpolating curves connecting a series of points in the plane. Curves may be open or closed, that is, with the first and last point of the curve at the initial point.
License: GPL-2
Imports: graphics, stats, sp
Depends: grDevices
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-06-21 06:55:44 UTC; bill
Repository: CRAN
Date/Publication: 2020-06-26 08:40:02 UTC

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New package bayesbr with initial version 0.0.0.1
Package: bayesbr
Title: Beta Regression on a Bayesian Model
Version: 0.0.0.1
Authors@R: c(person(given = "Joao", family = "Melo", role = c("aut", "cre"), email = "pjoao266@gmail.com"), person(given = "Vinicius", family = "Mayrink", role = "aut", email = "vdinizm@gmail.com"))
Description: Applies the Beta regression model on the Bayesian statistical view, the Beta regression is used when the response variable is a proportion variable, that is, it only accepts values between 0 and 1. The package 'bayesbr' uses the package 'rstan' to build the Bayesian statistical models. The main function of the package receives as a parameter a form informing the independent variable and the co-variables of the model to be made, as output it returns a list with the results of the model. For more details see Ferrari and Cribari-Neto (2004) <doi:10.1080/0266476042000214501> and Hoffman and Gelman (2014) <arXiv:1111.4246>.
Encoding: UTF-8
LazyData: true
Biarch: true
Depends: R (>= 3.4.0)
Imports: methods, Rcpp (>= 0.12.0), rstan (>= 2.18.1), rstantools (>= 2.0.0), coda, tidyr, dplyr, stringr, ggplot2, magrittr, fdrtool (>= 1.2.15), Formula(>= 1.2-3), loo(>= 2.2.0), RcppParallel
LinkingTo: BH (>= 1.66.0), Rcpp (>= 0.12.0), RcppEigen (>= 0.3.3.3.0), rstan (>= 2.18.1), StanHeaders (>= 2.18.0), RcppParallel
SystemRequirements: GNU make
License: GPL-2
RoxygenNote: 7.1.0
URL: https://github.com/pjoao266/bayesbr
BugReports: https://github.com/pjoao266/bayesbr/issues
NeedsCompilation: yes
Packaged: 2020-06-25 19:26:13 UTC; pjoao
Author: Joao Melo [aut, cre], Vinicius Mayrink [aut]
Maintainer: Joao Melo <pjoao266@gmail.com>
Repository: CRAN
Date/Publication: 2020-06-26 09:00:06 UTC

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New package BasketballAnalyzeR with initial version 0.5.0
Package: BasketballAnalyzeR
Type: Package
Title: Analysis and Visualization of Basketball Data
Version: 0.5.0
Author: Marco Sandri, Paola Zuccolotto, Marica Manisera
Maintainer: Marco Sandri <basketballanalyzer.help@unibs.it>
Description: Contains data and code to accompany the book P. Zuccolotto and M. Manisera (2020) Basketball Data Science. Applications with R. CRC Press. ISBN 9781138600799.
License: GPL (>= 2.0)
Encoding: UTF-8
LazyData: true
URL: https://github.com/sndmrc/BasketballAnalyzeR
Contact: <basketballanalyzer.help@unibs.it>
Depends: R (>= 3.4), ggplot2 (>= 2.2.0)
Imports: hexbin (>= 1.27), plyr (>= 1.8.4), dplyr (>= 0.7.6), tidyr (>= 0.8.1), rlang (>= 0.4.3), magrittr (>= 1.5), ggrepel (>= 0.8), gridExtra (>= 2.3), scales (>= 1.0), MASS (>= 7.3), directlabels (>= 2018.05), corrplot (>= 0.80), ggplotify (>= 0.0.3), network (>= 1.13.0), sna (>= 2.4), dendextend (>= 1.8), circlize (>= 0.4), PBSmapping (>= 2.70), sp (>= 1.3), operators (>= 0.1), stringr (>= 1.3), GGally (>= 1.4), statnet.common (>= 4.2), ggnetwork (>= 0.5), readr (>= 1.3), stats, grDevices, graphics
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-06-25 21:53:39 UTC; sndmr
Repository: CRAN
Date/Publication: 2020-06-26 09:00:11 UTC

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Package twoway updated to version 0.6.3 with previous version 0.6.2 dated 2018-08-24

Title: Analysis of Two-Way Tables
Description: Carries out analyses of two-way tables with one observation per cell, together with graphical displays for an additive fit and a diagnostic plot for removable 'non-additivity' via a power transformation of the response. It implements Tukey's Exploratory Data Analysis (1973) <ISBN: 978-0201076165> methods, including a 1-degree-of-freedom test for row*column 'non-additivity', linear in the row and column effects.
Author: Michael Friendly [aut, cre] (<https://orcid.org/0000-0002-3237-0941>), Richard M. Heiberger [aut], John Fox [ctb]
Maintainer: Michael Friendly <friendly@yorku.ca>

Diff between twoway versions 0.6.2 dated 2018-08-24 and 0.6.3 dated 2020-06-26

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Package rgdal updated to version 1.5-12 with previous version 1.5-10 dated 2020-06-09

Title: Bindings for the 'Geospatial' Data Abstraction Library
Description: Provides bindings to the 'Geospatial' Data Abstraction Library ('GDAL') (>= 1.11.4) and access to projection/transformation operations from the 'PROJ' library. Use is made of classes defined in the 'sp' package. Raster and vector map data can be imported into R, and raster and vector 'sp' objects exported. The 'GDAL' and 'PROJ' libraries are external to the package, and, when installing the package from source, must be correctly installed first; it is important that 'GDAL' < 3 be matched with 'PROJ' < 6. From 'rgdal' 1.5-8, installed with to 'GDAL' >=3, 'PROJ' >=6 and 'sp' >= 1.4, coordinate reference systems use 'WKT2_2019' strings, not 'PROJ' strings. 'Windows' and 'macOS' binaries (including 'GDAL', 'PROJ' and their dependencies) are provided on 'CRAN'.
Author: Roger Bivand [cre, aut] (<https://orcid.org/0000-0003-2392-6140>), Tim Keitt [aut], Barry Rowlingson [aut, ctb], Edzer Pebesma [ctb], Michael Sumner [ctb], Robert Hijmans [ctb], Even Rouault [cph, ctb], Frank Warmerdam [cph, ctb], Jeroen Ooms [ctb], Colin Rundel [ctb]
Maintainer: Roger Bivand <Roger.Bivand@nhh.no>

Diff between rgdal versions 1.5-10 dated 2020-06-09 and 1.5-12 dated 2020-06-26

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Package renv updated to version 0.11.0 with previous version 0.10.0 dated 2020-05-06

Title: Project Environments
Description: A dependency management toolkit for R. Using 'renv', you can create and manage project-local R libraries, save the state of these libraries to a 'lockfile', and later restore your library as required. Together, these tools can help make your projects more isolated, portable, and reproducible.
Author: Kevin Ushey [aut, cre], RStudio [cph]
Maintainer: Kevin Ushey <kevin@rstudio.com>

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Package fpc updated to version 2.2-7 with previous version 2.2-6 dated 2020-06-24

Title: Flexible Procedures for Clustering
Description: Various methods for clustering and cluster validation. Fixed point clustering. Linear regression clustering. Clustering by merging Gaussian mixture components. Symmetric and asymmetric discriminant projections for visualisation of the separation of groupings. Cluster validation statistics for distance based clustering including corrected Rand index. Standardisation of cluster validation statistics by random clusterings and comparison between many clustering methods and numbers of clusters based on this. Cluster-wise cluster stability assessment. Methods for estimation of the number of clusters: Calinski-Harabasz, Tibshirani and Walther's prediction strength, Fang and Wang's bootstrap stability. Gaussian/multinomial mixture fitting for mixed continuous/categorical variables. Variable-wise statistics for cluster interpretation. DBSCAN clustering. Interface functions for many clustering methods implemented in R, including estimating the number of clusters with kmeans, pam and clara. Modality diagnosis for Gaussian mixtures. For an overview see package?fpc.
Author: Christian Hennig <christian.hennig@unibo.it>
Maintainer: Christian Hennig <christian.hennig@unibo.it>

Diff between fpc versions 2.2-6 dated 2020-06-24 and 2.2-7 dated 2020-06-26

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Package dataframeexplorer updated to version 0.1.7 with previous version 0.1.6 dated 2020-04-17

Title: Familiarity with Dataframes Before Data Manipulation
Description: Real life data is muddy, fuzzy and unpredictable. This makes data manipulations tedious and bringing the data to right shape alone is a major chunk of work. Functions in this package help us get an understanding of dataframes to dramatically reduces data coding time.
Author: Ashrith Reddy [aut, cre]
Maintainer: Ashrith Reddy <ashrithssreddy@gmail.com>

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Package regplot updated to version 1.1 with previous version 1.0 dated 2020-01-30

Title: Enhanced Regression Nomogram Plot
Description: A function to plot a regression nomogram of regression objects. Covariate distributions are superimposed on nomogram scales and the plot can be animated to allow on-the-fly changes to distribution representation and to enable outcome calculation.
Author: Roger Marshall [aut, cre]
Maintainer: Roger Marshall <rj.marshall@auckland.ac.nz>

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Package SubtypeDrug updated to version 0.1.1 with previous version 0.1.0 dated 2020-05-16

Title: Prioritization of Candidate Cancer Subtype Specific Drugs
Description: A systematic biology tool was developed to prioritize cancer subtype-specific drugs by integrating genetic perturbation, drug action, biological pathway, and cancer subtype. The capabilities of this tool include inferring patient-specific subpathway activity profiles in the context of gene expression profiles with subtype labels, calculating differentially expressed subpathways based on cultured human cells treated with drugs in the 'cMap' (connectivity map) database, prioritizing cancer subtype specific drugs according to drug-disease reverse association score based on subpathway, and visualization of results (Castelo (2013) <doi:10.1186/1471-2105-14-7>; Han et al (2019) <doi:10.1093/bioinformatics/btz894>; Lamb and Justin (2006) <DOI:10.1126/science.1132939>).
Author: Xudong Han, Junwei Han, Chonghui Liu
Maintainer: Junwei Han <hanjunwei1981@163.com>

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