Sun, 24 Jan 2021

New package migest with initial version 1.8.3
Package: migest
Type: Package
Title: Methods for the Indirect Estimation of Bilateral Migration
Version: 1.8.3
Authors@R: c(person(c("Guy", "J."), "Abel", role = c("aut", "cre"), email = "g.j.abel@gmail.com", comment = c(ORCID = "0000-0002-4893-5687")))
Maintainer: Guy J. Abel <g.j.abel@gmail.com>
Description: Indirect methods for estimating bilateral migration flows in the presence of partial or missing data, including the estimation of bilateral migration flows from changes in bilateral migrant stock tables (e.g. Abel (2013) <doi:10.4054/DemRes.2013.28.18>).
URL: https://github.com/guyabel/migest/
BugReports: https://github.com/guyabel/migest/issues
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
Imports: dplyr, purrr, tidyr, stringr, magrittr, stats, tibble, utils
NeedsCompilation: no
Packaged: 2021-01-23 07:48:53 UTC; Guy
Author: Guy J. Abel [aut, cre] (<https://orcid.org/0000-0002-4893-5687>)
Repository: CRAN
Date/Publication: 2021-01-24 17:00:09 UTC

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New package BIGL with initial version 1.6.1
Package: BIGL
Type: Package
Title: Biochemically Intuitive Generalized Loewe Model
Version: 1.6.1
Date: 2021-01-24
Author: Heather Turner, Annelies Tourny, Olivier Thas, Maxim Nazarov, Rytis Bagdziunas, Stijn Hawinkel
Maintainer: Maxim Nazarov <maxim.nazarov@openanalytics.eu>
Description: Response surface methods for drug synergy analysis. Available methods include generalized and classical Loewe formulations as well as Highest Single Agent methodology. Response surfaces can be plotted in an interactive 3-D plot and formal statistical tests for presence of synergistic effects are available. Implemented methods and tests are described in the article "BIGL: Biochemically Intuitive Generalized Loewe null model for prediction of the expected combined effect compatible with partial agonism and antagonism" by Koen Van der Borght, Annelies Tourny, Rytis Bagdziunas, Olivier Thas, Maxim Nazarov, Heather Turner, Bie Verbist & Hugo Ceulemans (2017) <doi:10.1038/s41598-017-18068-5>.
License: GPL-3
Depends: R (>= 3.5)
Imports: ggplot2, MASS, methods, minpack.lm, numDeriv, parallel, progress, rgl, robustbase, scales, nleqslv,
Suggests: knitr, rmarkdown, testthat, shiny, DT
VignetteBuilder: knitr, rmarkdown
LazyData: true
URL: https://github.com/openanalytics/BIGL
BugReports: https://github.com/openanalytics/BIGL/issues
Encoding: UTF-8
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2021-01-24 15:01:53 UTC; maxim
Repository: CRAN
Date/Publication: 2021-01-24 17:00:13 UTC

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Fri, 22 Jan 2021

New package circglmbayes with initial version 1.3.0
Package: circglmbayes
Type: Package
Date: 2021-01-22
Title: Bayesian Analysis of a Circular GLM
Version: 1.3.0
Authors@R: person("Kees", "Mulder", email = "keestimmulder@gmail.com", role = c("aut", "cre"))
Maintainer: Kees Mulder <keestimmulder@gmail.com>
Description: Perform a Bayesian analysis of a circular outcome General Linear Model (GLM), which allows regressing a circular outcome on linear and categorical predictors. Posterior samples are obtained by means of an MCMC algorithm written in 'C++' through 'Rcpp'. Estimation and credible intervals are provided, as well as hypothesis testing through Bayes Factors. See Mulder and Klugkist (2017) <doi:10.1016/j.jmp.2017.07.001>.
License: GPL-3
Encoding: UTF-8
ByteCompile: true
URL: https://github.com/keesmulder/circglmbayes
BugReports: https://github.com/keesmulder/circglmbayes/issues
LazyData: true
Depends: R (>= 2.10)
LinkingTo: Rcpp, BH, RcppArmadillo
Imports: Rcpp, stats, graphics, shiny, grDevices, ggplot2, reshape2, coda
RoxygenNote: 7.1.1
NeedsCompilation: yes
Packaged: 2021-01-22 12:26:03 UTC; keest
Author: Kees Mulder [aut, cre]
Repository: CRAN
Date/Publication: 2021-01-22 13:10:02 UTC

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New package heemod with initial version 0.14.2
Package: heemod
Title: Markov Models for Health Economic Evaluations
Version: 0.14.2
Authors@R: c( person("Kevin", "Zarca", email = "kevin.zarca@gmail.com", role = c("aut", "cre")), person("Antoine", "Filipovic-Pierucci", role = "aut"), person("Matthew", "Wiener", role = "ctb"), person("Zdenek", "Kabat", role = "ctb"), person("Vojtech", "Filipec", role = "ctb"), person("Jordan", "Amdahl", role=c("ctb")), person("Yonatan", "Carranza Alarcon", role=c("ctb")), person("Vince", "Daniels", role=c("ctb")) )
Description: An implementation of the modelling and reporting features described in reference textbook and guidelines (Briggs, Andrew, et al. Decision Modelling for Health Economic Evaluation. Oxford Univ. Press, 2011; Siebert, U. et al. State-Transition Modeling. Medical Decision Making 32, 690-700 (2012).): deterministic and probabilistic sensitivity analysis, heterogeneity analysis, time dependency on state-time and model-time (semi-Markov and non-homogeneous Markov models), etc.
Depends: R (>= 3.3.0)
Imports: dplyr (>= 0.7.2), ggplot2 (>= 2.2.0), lazyeval (>= 0.2.0), memoise (>= 1.1.0), mvnfast (>= 0.2.2), plyr (>= 1.8.0), pryr (>= 0.1.2), tibble (>= 1.3.0), rlang (>= 0.3), purrr (>= 0.3)
License: GPL (>= 3)
LazyData: true
VignetteBuilder: knitr
RoxygenNote: 7.1.1
Suggests: BCEA, diagram, flexsurv, knitr, logitnorm, lpSolve, mgcv, optimx, parallel, readxl, rgho, rmarkdown, stringr, survival, testthat, triangle, magrittr, cli
BugReports: https://github.com/pierucci/heemod/issues
NeedsCompilation: no
Packaged: 2021-01-22 11:59:21 UTC; kevin
Author: Kevin Zarca [aut, cre], Antoine Filipovic-Pierucci [aut], Matthew Wiener [ctb], Zdenek Kabat [ctb], Vojtech Filipec [ctb], Jordan Amdahl [ctb], Yonatan Carranza Alarcon [ctb], Vince Daniels [ctb]
Maintainer: Kevin Zarca <kevin.zarca@gmail.com>
Repository: CRAN
Date/Publication: 2021-01-22 13:00:02 UTC

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New package ECTTDNN with initial version 0.1.0
Package: ECTTDNN
Type: Package
Title: Cointegration Based Timedelay Neural Network Model
Version: 0.1.0
Authors@R: c(person("Pankaj", "Das", role = c("aut","cre"),email="pankaj.das2@icar.gov.in"),person("Achal", "Lama", role = "aut",email="achal.lama@icar.gov.in"), person("Girish Kumar", "Jha", role = "aut",email="grish.stat@gmail.com"))
Author: Pankaj Das [aut, cre], Achal Lama [aut], Girish Kumar Jha [aut]
Maintainer: Pankaj Das <pankaj.das2@icar.gov.in>
Depends: R (>= 3.3.0),urca,forecast,vars
Description: This cointegration based Time Delay Neural Network Model hybrid model allows the researcher to make use of the information extracted by the cointegrating vector as an input in the neural network model.
Encoding: UTF-8
LazyData: true
License: GPL-3
NeedsCompilation: no
Packaged: 2021-01-21 12:08:07 UTC; USER
Repository: CRAN
Date/Publication: 2021-01-22 11:20:02 UTC

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New package spatstat.core with initial version 1.65-0
Package: spatstat.core
Version: 1.65-0
Date: 2021-01-07
Title: Core Functionality of the 'spatstat' Package
Authors@R: c(person("Adrian", "Baddeley", role = c("aut", "cre"), email = "Adrian.Baddeley@curtin.edu.au"), person("Rolf", "Turner", role = "aut", email="r.turner@auckland.ac.nz"), person("Ege", "Rubak", role = "aut", email = "rubak@math.aau.dk"), person("Kasper", "Klitgaard Berthelsen", role = "ctb"), person("Ottmar", "Cronie", role = "ctb"), person("Tilman", "Davies", role = "ctb"), person("Yongtao", "Guan", role = "ctb"), person("Ute", "Hahn", role = "ctb"), person("Abdollah", "Jalilian", role = "ctb"), person("Marie-Colette", "van Lieshout", role = "ctb"), person("Greg", "McSwiggan", role = "ctb"), person("Tuomas", "Rajala", role = "ctb"), person("Suman", "Rakshit", role = "ctb"), person("Dominic", "Schuhmacher", role = "ctb"), person("Rasmus", "Plenge Waagepetersen", role = "ctb"), person("Hangsheng", "Wang", role = "ctb"))
Maintainer: Adrian Baddeley <Adrian.Baddeley@curtin.edu.au>
Depends: R (>= 3.5.0), spatstat.data (>= 1.6-1), spatstat.geom, stats, graphics, grDevices, utils, methods, nlme, rpart
Imports: spatstat.utils (>= 1.18-0), spatstat.sparse, mgcv, Matrix, abind, tensor, goftest (>= 1.2-2)
Suggests: sm, maptools (>= 0.9-9), gsl, locfit, spatial, RandomFields (>= 3.1.24.1), RandomFieldsUtils(>= 0.3.3.1), fftwtools (>= 0.9-8), spatstat.linnet
Description: This is a subset of the original 'spatstat' package, containing all of the user-level code from 'spatstat', except for the code for linear networks.
License: GPL (>= 2)
URL: http://spatstat.org/
LazyData: true
NeedsCompilation: yes
ByteCompile: true
BugReports: https://github.com/spatstat/spatstat.core/issues
Packaged: 2021-01-09 00:33:34 UTC; adrian
Author: Adrian Baddeley [aut, cre], Rolf Turner [aut], Ege Rubak [aut], Kasper Klitgaard Berthelsen [ctb], Ottmar Cronie [ctb], Tilman Davies [ctb], Yongtao Guan [ctb], Ute Hahn [ctb], Abdollah Jalilian [ctb], Marie-Colette van Lieshout [ctb], Greg McSwiggan [ctb], Tuomas Rajala [ctb], Suman Rakshit [ctb], Dominic Schuhmacher [ctb], Rasmus Plenge Waagepetersen [ctb], Hangsheng Wang [ctb]
Repository: CRAN
Date/Publication: 2021-01-22 10:50:02 UTC

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New package sdmApp with initial version 0.0.1
Package: sdmApp
Title: A User-Friendly Application for Species Distribution Modeling
Version: 0.0.1
Authors@R: c(person(given = "Aboubacar", family = "HEMA", role = c("aut", "cre"), email = "aboubacarhema94@gmail.com"), person(given = "Babacar", family = "NDAO", role = "ctb", email = "babacar.ndao@cse.sn"), person(given = "Louise", family = "LEROUX", role = "aut", email = "louise.leroux@cirad.fr"), person(given = "Abdoul Aziz", family = "DIOUF", role = "ctb", email = "aziz.diouf@cse.sn"))
Author: Aboubacar HEMA [aut, cre], Babacar NDAO [ctb], Louise LEROUX [aut], Abdoul Aziz DIOUF [ctb]
Maintainer: Aboubacar HEMA <aboubacarhema94@gmail.com>
Description: A 'shiny' application that allows non-expert 'R' users to easily model species distribution. It offers a reproducible work flow for species distribution modeling into a single and user friendly environment. 'sdmApp' takes 'raster' data (in format supported by the 'raster package') and species occurrence data (several format supported) as input argument. It provides an interactive graphical user interface (GUI).
License: GPL-3
URL: https://github.com/Abson-dev/sdmApp
BugReports: https://github.com/Abson-dev/sdmApp/issues
Depends: R (>= 3.5.0)
Imports: raster (>= 2.6.7), sp (>= 1.2.0), biomod2 (>= 3.4.6), blockCV (>= 2.1.1), CENFA (>= 1.1.0), dismo (>= 1.0.12), DT, kernlab (>= 0.9-29), randomForest (>= 4.6.10), readxl (>= 1.3.1), rhandsontable (>= 0.3.7), sf, shiny (>= 0.12.2), shinyBS (>= 0.61), shinyFiles (>= 0.7.0), SSDM (>= 0.2.8), ggcorrplot (>= 0.1.3), ggplot2 (>= 3.1.1), ggpubr (>= 0.4.0), haven (>= 2.3.1), tidyverse (>= 1.3.0), data.table, rgeos (>= 0.3-8), rJava (>= 0.9-13)
Suggests: covr, grDevices, knitr, rmarkdown, stats, testthat, utils, rgdal (>= 1.5-8), automap (>= 1.0-14), graphics, future.apply
VignetteBuilder: knitr, rmarkdown
Encoding: UTF-8
Language: en-US
LazyData: true
RoxygenNote: 7.1.1
SystemRequirements: Java (>= 8)
NeedsCompilation: no
Packaged: 2021-01-21 10:05:28 UTC; DELLDRAMOMO
Repository: CRAN
Date/Publication: 2021-01-22 10:40:03 UTC

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New package healthyR.ts with initial version 0.1.0
Package: healthyR.ts
Title: The Time Series Modeling Companion to 'healthyR'
Version: 0.1.0
Authors@R: c( person("Steven","Sanderson", email = "spsanderson@gmail.com", role = c("aut","cre")), person("Steven Sanderson", role = "cph"))
Description: Hospital time series data analysis workflow tools, modeling, and automations. This library provides many useful tools to review common administrative time series hospital data. Some of these include average length of stay, and readmission rates. The aim is to provide a simple and consistent verb framework that takes the guesswork out of everything.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
URL: https://github.com/spsanderson/healthyR.ts
BugReports: https://github.com/spsanderson/healthyR.ts/issues
Suggests: knitr, rmarkdown, roxygen2, scales
VignetteBuilder: knitr
Imports: magrittr, rlang (>= 0.1.2), tibble, timetk, modeltime, modeltime.ensemble, modeltime.resample, dplyr, purrr, ggplot2, tidyquant, healthyR.data, lubridate, stringr, plotly
NeedsCompilation: no
Packaged: 2021-01-21 03:30:57 UTC; Steve
Author: Steven Sanderson [aut, cre], Steven Sanderson [cph]
Maintainer: Steven Sanderson <spsanderson@gmail.com>
Repository: CRAN
Date/Publication: 2021-01-22 10:40:06 UTC

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New package GFisher with initial version 0.1.0
Package: GFisher
Type: Package
Title: Generalized Fisher's Combination Tests Under Dependence
Version: 0.1.0
Author: Hong Zhang
Maintainer: Hong Zhang <hzhang@wpi.edu>
Description: Accurate and computationally efficient p-value calculation methods for a general family of Fisher type statistics (GFisher). The GFisher covers Fisher's combination, Good's statistic, Lancaster's statistic, weighted Z-score combination, etc. It allows a flexible weighting scheme, as well as an omnibus procedure that automatically adapts proper weights and degrees of freedom to a given data. The new p-value calculation methods are based on novel ideas of moment-ratio matching and joint-distribution approximation. The technical details can be found in Hong Zhang and Zheyang Wu (2020) <arXiv:2003.01286>.
License: GPL-2
Imports: stats, Matrix, mvtnorm
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2021-01-20 22:12:49 UTC; consi
Repository: CRAN
Date/Publication: 2021-01-22 10:40:12 UTC

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New package cinaRgenesets with initial version 0.1.1
Package: cinaRgenesets
Type: Package
Title: Ready-to-Use Curated Gene Sets for 'cinaR'
Version: 0.1.1
Authors@R: c(person(given = "Onur", family = "Karakaslar", role = c("aut", "cre"), email = "eonurkara@gmail.com"), person(given = "Duygu", family = "Ucar", role = "aut", comment = c(ORCID = "0000-0002-9772-3066")) )
Description: Immune related gene sets provided along with the 'cinaR' package.
License: GPL-3
Encoding: UTF-8
LazyData: true
URL: https://github.com/eonurk/cinaR-genesets
BugReports: https://github.com/eonurk/cinaR-genesets/issues/
biocViews:
Depends: R (>= 3.5.0)
Imports:
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2021-01-20 18:04:39 UTC; karako
Author: Onur Karakaslar [aut, cre], Duygu Ucar [aut] (<https://orcid.org/0000-0002-9772-3066>)
Maintainer: Onur Karakaslar <eonurkara@gmail.com>
Repository: CRAN
Date/Publication: 2021-01-22 10:40:09 UTC

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New package bayesforecast with initial version 0.0.1
Package: bayesforecast
Title: Bayesian Time Series Modeling with Stan
Version: 0.0.1
Authors@R: c(person("Asael","Alonzo Matamoros", role = c("aut", "cre"),email = "asael.alonzo@gmail.com"), person("Cristian","Cruz Torres", role = 'aut', email = "cristian.cruz@unah.edu.hn"), person("Rob", "Hyndman", email="Rob.Hyndman@monash.edu", role = "ctb"), person("Mitchell", "O'Hara-Wild", role = "ctb") )
Description: Fit Bayesian time series models using 'Stan' for full Bayesian inference. A wide range of distributions and models are supported, allowing users to fit Seasonal ARIMA, ARIMAX, Dynamic Harmonic Regression, GARCH, t-student innovation GARCH models, asymmetric GARCH, Random Walks, stochastic volatility models for univariate time series. Prior specifications are flexible and explicitly encourage users to apply prior distributions that actually reflect their beliefs. Model fit can easily be assessed and compared with typical visualization methods, information criteria such as loglik, AIC, BIC WAIC, Bayes factor and leave-one-out cross-validation methods. References: Hyndman (2017) <doi:10.18637/jss.v027.i03>; Carpenter et al. (2017) <doi:10.18637/jss.v076.i01>.
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Biarch: true
Depends: R (>= 4.0.0)
Imports: bayesplot (>= 1.5.0), methods, gridExtra, ggplot2, forecast, loo (>= 2.2.0), Rcpp (>= 0.12.0), rstan (>= 2.18.1), rstantools (>= 2.0.0), RcppParallel (>= 5.0.1), bridgesampling (>= 0.3-0), MASS, StanHeaders, astsa,lubridate, prophet,zoo
Suggests: knitr, rmarkdown,ggfortify
LinkingTo: BH (>= 1.66.0), Rcpp (>= 0.12.0), RcppParallel (>= 5.0.1), RcppEigen (>= 0.3.3.3.0), rstan (>= 2.18.1), StanHeaders (>= 2.18.0)
SystemRequirements: GNU make
Collate: 'autoplot.R' 'auto_sarima.R' 'bayes_factor.R' 'bayesforecast-package.R' 'Birth.R' 'Fit.R' 'forecast.R' 'garch.R' 'get_params.R' 'ipc.R' 'log_lik.R' 'Misc.R' 'model.R' 'naive.R' 'posterior_intervals.R' 'posterior_predict.R' 'predictive_error.R' 'print.R' 'prior.R' 'report.R' 'Sarima.R' 'summary.R' 'ssm.R' 'stanmodels.R' 'SVM.R' 'varstan.R' 'stan_models.R'
NeedsCompilation: yes
Packaged: 2021-01-20 20:24:19 UTC; asael
Author: Asael Alonzo Matamoros [aut, cre], Cristian Cruz Torres [aut], Rob Hyndman [ctb], Mitchell O'Hara-Wild [ctb]
Maintainer: Asael Alonzo Matamoros <asael.alonzo@gmail.com>
Repository: CRAN
Date/Publication: 2021-01-22 10:20:02 UTC

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New package MixTwice with initial version 1.1
Package: MixTwice
Type: Package
Title: MixTwice--a Package for Large-Scale Hypothesis Testing
Version: 1.1
Imports: alabama, ashr, fdrtool
Date: 2021-01-14
Author: Zihao Zheng and Michael A.Newton
Maintainer: Zihao Zheng <zihao.zheng@wisc.edu>
Description: Implements large-scale hypothesis testing by variance mixing. It takes two statistics per testing unit -- an estimated effect and its associated squared standard error -- and fits a nonparametric, shape-constrained mixture separately on two latent parameters. It reports local false discovery rates (lfdr) and local false sign rates (lfsr). Manuscript describing algorithm of MixTwice: Zheng et al(2020) <arXiv:2011.07420>.
License: GPL-2
NeedsCompilation: no
Packaged: 2021-01-20 15:34:05 UTC; appli
Depends: R (>= 3.5.0)
Repository: CRAN
Date/Publication: 2021-01-22 09:40:05 UTC

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New package margins with initial version 0.3.26
Package: margins
Type: Package
Title: Marginal Effects for Model Objects
Description: An R port of Stata's 'margins' command, which can be used to calculate marginal (or partial) effects from model objects.
License: MIT + file LICENSE
Version: 0.3.26
Date: 2021-01-10
Authors@R: c(person("Thomas J.", "Leeper", role = c("aut", "cre"), email = "thosjleeper@gmail.com", comment = c(ORCID = "0000-0003-4097-6326")), person("Jeffrey", "Arnold", role = c("ctb"), email = "jeffrey.arnold@gmail.com"), person("Vincent", "Arel-Bundock", role = c("ctb")), person("Jacob A.", "Long", role = c("ctb"), email = "long.1377@osu.edu", comment = c(ORCID = "0000-0002-1582-6214")) )
URL: https://github.com/leeper/margins
BugReports: https://github.com/leeper/margins/issues
Imports: utils, stats, prediction (>= 0.3.6), data.table, graphics, grDevices, MASS
Suggests: methods, knitr, rmarkdown, testthat, ggplot2, gapminder, sandwich, stargazer, lme4
Enhances: AER, betareg, nnet, ordinal, survey
ByteCompile: true
VignetteBuilder: knitr
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2021-01-21 22:48:36 UTC; THOMAS
Author: Thomas J. Leeper [aut, cre] (<https://orcid.org/0000-0003-4097-6326>), Jeffrey Arnold [ctb], Vincent Arel-Bundock [ctb], Jacob A. Long [ctb] (<https://orcid.org/0000-0002-1582-6214>)
Maintainer: Thomas J. Leeper <thosjleeper@gmail.com>
Repository: CRAN
Date/Publication: 2021-01-22 09:20:02 UTC

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New package deepMOU with initial version 0.1.0
Package: deepMOU
Title: Clustering of Short Texts by Mixture of Unigrams and Its Deep Extensions
Version: 0.1.0
Authors@R: c( person("Martin", "D'Ippolito", email = "martinmy69@gmail.com", role = c("aut","cre")), person("Anderlucci", "Laura", email = "laura.anderlucci@unibo.it", role = "aut"), person("Cinzia", "Viroli", email = "cinzia.viroli@unibo.it", role = "aut"))
Description: Functions providing an easy and intuitive way for fitting and clusters data using the Mixture of Unigrams models by means the Expectation-Maximization algorithm (Nigam, K. et al. (2000). <doi:10.1023/A:1007692713085>), Mixture of Dirichlet-Multinomials estimated by Gradient Descent (Anderlucci, Viroli (2020) <doi:10.1007/s11634-020-00399-3>) and Deep Mixture of Multinomials whose estimates are obtained with Gibbs sampling scheme (Viroli, Anderlucci (2020) <arXiv:1902.06615v2>). There are also functions for graphical representation of clusters obtained.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Imports: skmeans, extraDistr, dplyr, Rfast, entropy, ggplot2, RColorBrewer, stats, graphics, MASS
NeedsCompilation: no
Packaged: 2021-01-20 15:19:45 UTC; dippolitom
Author: Martin D'Ippolito [aut, cre], Anderlucci Laura [aut], Cinzia Viroli [aut]
Maintainer: Martin D'Ippolito <martinmy69@gmail.com>
Depends: R (>= 3.5.0)
Repository: CRAN
Date/Publication: 2021-01-22 09:40:02 UTC

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New package cmprskcoxmsm with initial version 0.1.0
Package: cmprskcoxmsm
Type: Package
Title: Use IPW to Estimate Treatment Effect under Competing Risks
Version: 0.1.0
Author: Yiran Zhang
Maintainer: Yiran Zhang <yiz038@health.ucsd.edu>
Description: Uses inverse probability weighting methods to estimate treatment effect under marginal structure model for the cause-specific hazard of competing risk events. Estimates also the cumulative incidence function (i.e. risk) of the potential outcomes, and provides inference on risk difference and risk ratio. Reference: Kalbfleisch & Prentice (2002)<doi:10.1002/9781118032985>; Hernan et al (2001)<doi:10.1198/016214501753168154>.
License: GPL (>= 2)
Imports: ggplot2, survival, stats, twang, graphics, sandwich
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-01-20 18:48:13 UTC; yiran
Repository: CRAN
Date/Publication: 2021-01-22 09:50:02 UTC

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New package Biostatistics with initial version 1.0.0
Package: Biostatistics
Type: Package
Title: Statistics Tutorials for Biologists
Version: 1.0.0
Author: Rob Knell
Maintainer: Rob Knell <r.knell@qmul.ac.uk>
Description: Tutorials for statistics, aimed at biological scientists. Subjects range from basic descriptive statistics through to complex linear modelling. The tutorials include text, videos, interactive coding exercises and multiple choice quizzes. The package also includes 19 datasets which are used in the tutorials.
Encoding: UTF-8
LazyData: true
Imports: learnr
Suggests: ggplot2, car, plotrix, knitr, rmarkdown
License: GPL-3
VignetteBuilder: knitr
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2021-01-20 17:37:47 UTC; ugbt794
Depends: R (>= 3.5.0)
Repository: CRAN
Date/Publication: 2021-01-22 09:40:08 UTC

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New package autoharp with initial version 0.0.4
Package: autoharp
Title: Semi-Automatic Grading of R and Rmd Scripts
Version: 0.0.4
Authors@R: c( person("Vik", "Gopal", email="vik.gopal@nus.edu.sg", role=c("aut", "cre")), person("Samuel", "Seah", email="samuelseah@u.nus.edu", role="aut"), person("Viknesh", "Jeya Kumar", email="viknesh@u.nus.edu", role="aut"), person("Gabriel", "Ang", email="gabrielang@u.nus.edu", role="aut"), person("Ruofan", "Liu", email="kelseyliu1998@gmail.com", role="ctb"), person("National University of Singapore", role="cph"))
Description: A customisable set of tools for assessing and grading R or R-markdown scripts from students. It allows for checking correctness of code output, runtime statistics and static code analysis. The latter feature is made possible by representing R expressions using a tree structure.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Imports: magrittr, dplyr, stringr, rlang, tidyr, tibble, knitr, rmarkdown, pryr, shiny, lintr, methods, igraph, testthat
Collate: 'treeharp.R' 'th_getter-length.R' 'as.matrix.R' 'check_correctness.R' 'check_rmd.R' 'check_runtime.R' 'count_lints.R' 'env_size.R' 'examplify_to_r.R' 'forestharp.R' 'forestharp_helpers.R' 'generate_thumbnails.R' 'join_treeharp.R' 'lang_2_tree.R' 'lang_2_tree_helpers.R' 'log_summary.R' 'lum_local_match.R' 'nlp_related.R' 'populate_soln_env.R' 'render_one.R' 'reset_path.R' 'run_tuner.R' 'to_BFS.R' 'tree_kernel.R' 'tree_routines.R' 'utils-pipe.R' 'utils.R' 'write_html.R' 'zzz.R'
Suggests: readxl, xml2, rvest, formatR
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-01-20 12:23:52 UTC; viknesh
Author: Vik Gopal [aut, cre], Samuel Seah [aut], Viknesh Jeya Kumar [aut], Gabriel Ang [aut], Ruofan Liu [ctb], National University of Singapore [cph]
Maintainer: Vik Gopal <vik.gopal@nus.edu.sg>
Repository: CRAN
Date/Publication: 2021-01-22 09:20:06 UTC

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New package SPlit with initial version 1.0
Package: SPlit
Type: Package
Title: Split a Dataset for Training and Testing
Version: 1.0
Date: 2021-01-11
Authors@R: c(person("Akhil", "Vakayil", role = c("aut", "cre"), email = "akhilv@gatech.edu"), person("Roshan", "Joseph", role = c("aut", "ths")), person("Simon", "Mak", role = "aut"))
Description: Procedure to optimally split a dataset for training and testing. 'SPlit' is based on the method of support points, which is independent of modeling methods. Please see Joseph and Vakayil (2020) <arXiv:2012.10945> for details. This work is supported by U.S. National Science Foundation grant CBET-1921873.
LazyData: TRUE
License: GPL (>= 2)
Imports: Rcpp (>= 1.0.4)
LinkingTo: Rcpp, RcppArmadillo
RoxygenNote: 7.1.0
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2021-01-19 20:13:32 UTC; akhil
Author: Akhil Vakayil [aut, cre], Roshan Joseph [aut, ths], Simon Mak [aut]
Maintainer: Akhil Vakayil <akhilv@gatech.edu>
Repository: CRAN
Date/Publication: 2021-01-22 08:30:05 UTC

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New package SAMtool with initial version 1.0.0
Package: SAMtool
Type: Package
Title: Stock Assessment Methods Toolkit
Version: 1.0.0
Authors@R: c(person("Quang", "Huynh", email = "quang@bluematterscience.com", role = c("aut", "cre")), person("Tom", "Carruthers", email = "tom@bluematterscience.com", role = "aut"), person("Adrian", "Hordyk", email = "adrian@bluematterscience.com", role = "aut"))
Date: 2021-01-19
Maintainer: Quang Huynh <quang@bluematterscience.com>
Description: Simulation tools for closed-loop simulation are provided for the 'MSEtool' operating model to inform data-rich fisheries. 'SAMtool' provides a conditioning model, assessment models of varying complexity with standardized reporting, model-based management procedures, and diagnostic tools for evaluating assessments inside closed-loop simulation.
License: GPL-3
Depends: R (>= 3.5.0), MSEtool (>= 3.0.0)
Imports: TMB, corpcor, dplyr, gplots, grDevices, graphics, methods, snowfall, stats, utils, rmarkdown
LinkingTo: TMB, RcppEigen
Suggests: knitr, testthat, shiny, mvtnorm, reshape2
LazyData: yes
LazyLoad: yes
RoxygenNote: 7.1.1
Encoding: UTF-8
VignetteBuilder: knitr
URL: https://github.com/Blue-Matter/SAMtool
BugReports: https://github.com/Blue-Matter/SAMtool/issues
NeedsCompilation: yes
Packaged: 2021-01-19 23:41:00 UTC; qhuynh
Author: Quang Huynh [aut, cre], Tom Carruthers [aut], Adrian Hordyk [aut]
Repository: CRAN
Date/Publication: 2021-01-22 08:50:06 UTC

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New package rtables with initial version 0.3.6
Package: rtables
Title: Reporting Tables
Date: 2020-12-21
Version: 0.3.6
Authors@R: c( person("Gabriel", "Becker", email = "gabembecker@gmail.com", role = c("aut", "cre")), person("Adrian", "Waddell", email = "adrian.waddell@roche.com", role = "aut"), person("Daniel", "Sabanés Bové", email = "daniel.sabanes_bove@roche.com", role = "ctb"), person("Maximilian", "Mordig", email = "maximilian_oliver.mordig@roche.com", role = "ctb") )
Description: Reporting tables often have structure that goes beyond simple rectangular data. The 'rtables' package provides a framework for declaring complex multi-level tabulations and then applying them to data. This framework models both tabulation and the resulting tables as hierarchical, tree-like objects which support sibling sub-tables, arbitrary splitting or grouping of data in row and column dimensions, cells containing multiple values, and the concept of contextual summary computations. A convenient pipe-able interface is provided for declaring table layouts and the corresponding computations, and then applying them to data.
Depends: methods, magrittr, R (>= 2.10)
Imports: stats, htmltools
Suggests: dplyr, tibble, tidyr, testthat, xml2, knitr, rmarkdown
License: Apache License 2.0 | file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
VignetteBuilder: knitr
URL: https://github.com/roche/rtables, https://roche.github.io/rtables/
BugReports: https://github.com/roche/rtables/issues
Collate: '00tabletrees.R' 'Viewer.R' 'argument_conventions.R' 'as_html.R' 'utils.R' 'colby_constructors.R' 'compare_rtables.R' 'deprecated.R' 'format_rcell.R' 'indent.R' 'make_subset_expr.R' 'prune.R' 'rtable.R' 'simple_analysis.R' 'split_funs.R' 'summary.R' 'tree_accessors.R' 'tt_afun_utils.R' 'tt_compare_tables.R' 'tt_compatibility.R' 'tt_deprecated.R' 'tt_dotabulation.R' 'tt_paginate.R' 'tt_pos_and_access.R' 'tt_showmethods.R' 'tt_sort.R' 'tt_test_afuns.R' 'tt_toString.R' 'labels.R' 'zzz_constants.R'
NeedsCompilation: no
Packaged: 2021-01-19 20:33:45 UTC; gabrielbecker
Author: Gabriel Becker [aut, cre], Adrian Waddell [aut], Daniel Sabanés Bové [ctb], Maximilian Mordig [ctb]
Maintainer: Gabriel Becker <gabembecker@gmail.com>
Repository: CRAN
Date/Publication: 2021-01-22 08:40:02 UTC

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New package mifa with initial version 0.2.0
Package: mifa
Title: Multiple Imputation for Exploratory Factor Analysis
Version: 0.2.0
Authors@R: c( person("Vahid", "Nassiri", role = "aut"), person("Anikó", "Lovik", role = "aut"), person("Geert ", "Molenberghs", role = "aut"), person("Geert ", "Verbeke", role = "aut"), person("Tobias", "Busch", email = "teebusch@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "https://orcid.org/0000-0002-8390-7892")) )
URL: https://github.com/teebusch/mifa
BugReports: https://github.com/teebusch/mifa/issues
Imports: stats, mice, dplyr, checkmate
Suggests: psych, testthat, knitr, rmarkdown, ggplot2, tidyr, covr
Description: Impute the covariance matrix of incomplete data so that factor analysis can be performed. Imputations are made using multiple imputation by Multivariate Imputation with Chained Equations (MICE) and combined with Rubin's rules. Parametric Fieller confidence intervals and nonparametric bootstrap confidence intervals can be obtained for the variance explained by different numbers of principal components. The method is described in Nassiri et al. (2018) <doi:10.3758/s13428-017-1013-4>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2021-01-19 21:44:47 UTC; teebu
Author: Vahid Nassiri [aut], Anikó Lovik [aut], Geert Molenberghs [aut], Geert Verbeke [aut], Tobias Busch [aut, cre] (<https://orcid.org/0000-0002-8390-7892>)
Maintainer: Tobias Busch <teebusch@gmail.com>
Repository: CRAN
Date/Publication: 2021-01-22 08:40:08 UTC

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New package ggx with initial version 0.1.1
Package: ggx
Type: Package
Title: A Natural Language Interface to 'ggplot2'
Version: 0.1.1
Authors@R: person("Andreas M.", "Brandmaier", email = "andy@brandmaier.de", role = c("aut", "cre"))
Description: The 'ggplot2' package is the state-of-the-art toolbox for creating and formatting graphs. However, it is easy to forget how certain formatting commands are named and sometimes users find themselves asking: How do you rotate the x-axis labels again? Or how do you hide the legend...? This package allows users to issue natural language commands related to theme-related styling of plots (colors, font size and such), which then are translated into valid 'ggplot2' commands.
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: sets, ggplot2
RoxygenNote: 7.1.0
VignetteBuilder: knitr
Suggests: knitr, rmarkdown, markdown
NeedsCompilation: no
Packaged: 2021-01-19 17:02:42 UTC; brandmaier
Author: Andreas M. Brandmaier [aut, cre]
Maintainer: Andreas M. Brandmaier <andy@brandmaier.de>
Repository: CRAN
Date/Publication: 2021-01-22 08:30:02 UTC

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New package ggshadow with initial version 0.0.2
Package: ggshadow
Title: Shadow and Glow Geoms for 'ggplot2'
Version: 0.0.2
Authors@R: person("Marc", "Menem", email = "marc.menem@m4x.org", role = c("aut", "cre"))
Description: A collection of Geoms for R's 'ggplot2' library. geom_shadowpath(), geom_shadowline(), geom_shadowstep() and geom_shadowpoint() functions draw a shadow below lines to make busy plots more aesthetically pleasing. geom_glowpath(), geom_glowline(), geom_glowstep() and geom_glowpoint() add a neon glow around lines to get a steampunk style.
Depends: R (>= 3.4.0)
Imports: ggplot2 (>= 3.3.0), grid, scales, rlang, glue
Suggests: rmarkdown, knitr
VignetteBuilder: knitr
License: GPL-2
Encoding: UTF-8
LazyData: true
URL: https://github.com/marcmenem/ggshadow/
BugReports: https://github.com/marcmenem/ggshadow/issues
RoxygenNote: 7.1.0
Collate: 'geom-glowpath.r' 'geom-glowpoint.r' 'geom-shadowpath.r' 'geom-shadowpoint.r' 'internal-doc.r' 'scale-shadow.r'
NeedsCompilation: no
Packaged: 2021-01-19 20:58:13 UTC; marc
Author: Marc Menem [aut, cre]
Maintainer: Marc Menem <marc.menem@m4x.org>
Repository: CRAN
Date/Publication: 2021-01-22 08:50:03 UTC

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New package FMM with initial version 0.1.1
Package: FMM
Type: Package
Title: Rhythmic Patterns Modeling by FMM Models
Version: 0.1.1
Author: Adrian Lamela, Itziar Fernandez, Yolanda Larriba, Alejandro Rodriguez, Cristina Rueda
Maintainer: Itziar Fernandez <itziar.fernandez@uva.es>
Description: Provides a collection of functions to fit and explore single, multi-component and restricted Frequency Modulated Moebius (FMM) models. 'FMM' is a nonlinear parametric regression model capable of fitting non-sinusoidal shapes in rhythmic patterns. Details about the mathematical formulation of 'FMM' models can be found in Rueda et al. (2019) <doi:10.1038/s41598-019-54569-1>.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.5)
Imports: methods, foreach, iterators, parallel, doParallel
Suggests: ggplot2, RColorBrewer, testthat
NeedsCompilation: no
RoxygenNote: 7.1.1
Packaged: 2021-01-19 22:31:32 UTC; Buhardilla
Repository: CRAN
Date/Publication: 2021-01-22 09:00:12 UTC

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New package aweSOM with initial version 1.0
Package: aweSOM
Title: Interactive Self-Organizing Maps
Version: 1.0
Date: 2021-01-19
Authors@R: c(person("Julien", "Boelaert", role= c("aut", "cre"), email="julien.boelaert@univ-lille.fr"), person("Etienne", "Ollion", role= "aut"), person("Jan", "Sodoge", role= "aut"), person("Mohamed", "Megdoud", role= "ctb"), person("Otmane", "Naji", role= "ctb"), person("Arnaud", "Lemba Kote", role= "ctb"), person("Theo", "Renoud", role= "ctb"), person("Samuel", "Hym", role= "ctb"))
Description: Self-organizing maps (also known as SOM, see Kohonen (2001) <doi:10.1007/978-3-642-56927-2>) are a method for dimensionality reduction and clustering of continuous data. This package introduces interactive (html) graphics for easier analysis of SOM results. It also features an interactive interface, for push-button training and visualization of SOM, as well as tools to evaluate the quality of SOM.
License: GPL (>= 2)
Depends: R (>= 3.1.0)
Imports: kohonen, shiny, htmlwidgets, rmarkdown, htmltools, rclipboard, RColorBrewer, viridis, data.table, DT, kernlab, stats, cluster, e1071, haven, foreign, readxl
Suggests: knitr
VignetteBuilder: knitr
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2021-01-19 15:42:54 UTC; bart
Author: Julien Boelaert [aut, cre], Etienne Ollion [aut], Jan Sodoge [aut], Mohamed Megdoud [ctb], Otmane Naji [ctb], Arnaud Lemba Kote [ctb], Theo Renoud [ctb], Samuel Hym [ctb]
Maintainer: Julien Boelaert <julien.boelaert@univ-lille.fr>
Repository: CRAN
Date/Publication: 2021-01-22 08:10:10 UTC

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New package cropDemand with initial version 1.0.0
Package: cropDemand
Type: Package
Title: Spatial Crop Water Demand for Brazil
Version: 1.0.0
Authors@R: c(person(given = "Roberto", family = "Filgueiras", role = c("aut","cre"), email = "betofilgueiras@gmail.com", comment = c(ORCID = "0000-0002-0186-8907")), person(given = "Luan P.", family = "Venancio", role = ("aut"), comment = c(ORCID = "0000-0002-5544-8588")), person(given = "Catariny C.", family = "Aleman", role = ("aut"), comment = c(ORCID = "0000-0002-3894-3077")), person(given = "Fernando F.", family = "da Cunha", role = ("aut"), comment = c(ORCID = "0000-0002-1671-1021")))
Description: Estimation of crop water demand can be processed via this package. As example, the data from 'TerraClimate' dataset (<http://www.climatologylab.org/terraclimate.html>) calibrated with automatic weather stations of National Meteorological Institute of Brazil is available in a coarse spatial resolution to do the crop water demand. However, the user have also the option to download the variables directly from 'TerraClimate' repository with the download.terraclimate function and access the original 'TerraClimate' products. If the user believes that is necessary calibrate the variables, there is another function to do it. Lastly, the estimation of the crop water demand present in this package can be run for all the Brazilian territory with 'TerraClimate' dataset.
License: CC BY 4.0
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.2.0),
Imports: dplyr(>= 0.3.0.1), ggplot2(>= 3.3.2), extrafont, raster, rgdal, tidyr, ncdf4
BugReports: https://github.com/FilgueirasR/cropDemand/issues
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2021-01-19 16:07:36 UTC; betof
Author: Roberto Filgueiras [aut, cre] (<https://orcid.org/0000-0002-0186-8907>), Luan P. Venancio [aut] (<https://orcid.org/0000-0002-5544-8588>), Catariny C. Aleman [aut] (<https://orcid.org/0000-0002-3894-3077>), Fernando F. da Cunha [aut] (<https://orcid.org/0000-0002-1671-1021>)
Maintainer: Roberto Filgueiras <betofilgueiras@gmail.com>
Repository: CRAN
Date/Publication: 2021-01-22 08:00:02 UTC

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Thu, 21 Jan 2021

New package SPARSEMODr with initial version 1.0.1
Package: SPARSEMODr
Title: SPAtial Resolution-SEnsitive Models of Outbreak Dynamics
Version: 1.0.1
URL: https://github.com/NAU-CCL/SPARSEMODr
BugReports: https://github.com/NAU-CCL/SPARSEMODr/issues
Authors@R: c( person("Joseph", "Mihaljevic", email="Joseph.Mihaljevic@nau.edu", role=c("aut", "cre"), comment="C code, package development"), person("Toby", "Hocking", email="toby.hocking@r-project.org", role=c("ctb"), comment="R package interface"), person("Seth", "Borkovec", email="stb224@nau.edu", role=c("ctb"), comment="package development"))
Description: Implementation of spatially-explicit, stochastic disease models with customizable time windows that describe how parameter values fluctuate during outbreaks (e.g., in response to public health or conservation interventions).
License: GPL (>= 2)
Imports: Rcpp (>= 1.0.4), future.apply, data.table, future, tidyverse, lubridate, viridis, geosphere
Suggests: knitr, rmarkdown, testthat
VignetteBuilder: knitr
LinkingTo: Rcpp
Depends: R (>= 3.5.0)
NeedsCompilation: yes
Packaged: 2021-01-15 19:18:54 UTC; jrm84
Author: Joseph Mihaljevic [aut, cre] (C code, package development), Toby Hocking [ctb] (R package interface), Seth Borkovec [ctb] (package development)
Maintainer: Joseph Mihaljevic <Joseph.Mihaljevic@nau.edu>
Repository: CRAN
Date/Publication: 2021-01-21 23:30:06 UTC

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New package opentimsr with initial version 1.0.3
Encoding: UTF-8
Package: opentimsr
Type: Package
Title: An Open-Source Loader for Bruker's timsTOF Data Files
Version: 1.0.3
Date: 2021-01-19
Authors@R: c(person(given="Michał Piotr", family="Startek", role=c("aut","cre","cph"), email="michal.startek@mimuw.edu.pl", comment=c(ORCID="0000-0001-5227-3447")), person(given="Mateusz Krzysztof", family="Łącki", role=c("aut","cph"), comment=c(ORCID="0000-0001-7415-4748")) )
Maintainer: Michał Piotr Startek <michal.startek@mimuw.edu.pl>
Description: A free, open-source package designed for handling .tdf data files produced by Bruker's 'timsTOF' mass spectrometers, as described <https://www.bruker.com/service/support-upgrades/software-downloads/mass-spectrometry.html> (after registering). Fast, free, crossplatform, with no reading through EULAs or messing with binary .dll files involved.
License: GPL-3
URL: https://github.com/michalsta/opentims
Depends: R (>= 3.0.0)
Imports: Rcpp (>= 0.12.0), methods, DBI, RSQLite
LazyData: no
LinkingTo: Rcpp
NeedsCompilation: yes
SystemRequirements: C++14
RoxygenNote: 7.1.1
Packaged: 2021-01-19 20:11:42 UTC; mist
Author: Michał Piotr Startek [aut, cre, cph] (<https://orcid.org/0000-0001-5227-3447>), Mateusz Krzysztof Łącki [aut, cph] (<https://orcid.org/0000-0001-7415-4748>)
Repository: CRAN
Date/Publication: 2021-01-21 23:20:18 UTC

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New package fastkmedoids with initial version 1.2
Package: fastkmedoids
Type: Package
Title: Faster K-Medoids Clustering Algorithms: FastPAM, FastCLARA, FastCLARANS
Version: 1.2
Date: 2021-01-13
Author: Xun Li
Maintainer: Xun Li <lixun910@gmail.com>
Description: R wrappers of C++ implementation of Faster K-Medoids clustering algorithms (FastPAM, FastCLARA and FastCLARANS) proposed in Erich Schubert, Peter J. Rousseeuw 2019 <doi:10.1007/978-3-030-32047-8_16>.
Depends: methods
License: GPL (>= 2)
Collate: RcppExports.R KmedoidsResult.R
Encoding: UTF-8
Imports: Rcpp (>= 1.0.1)
LinkingTo: Rcpp
RoxygenNote: 7.1.1
SystemRequirements: C++11
NeedsCompilation: yes
Packaged: 2021-01-13 16:13:14 UTC; xun
Repository: CRAN
Date/Publication: 2021-01-21 17:20:06 UTC

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New package doc2vec with initial version 0.1.1
Package: doc2vec
Type: Package
Title: Distributed Representations of Sentences and Documents
Version: 0.1.1
Authors@R: c( person('Jan', 'Wijffels', role = c('aut', 'cre', 'cph'), email = 'jwijffels@bnosac.be', comment = "R wrapper"), person('BNOSAC', role = 'cph', comment = "R wrapper"), person('hiyijian', role = c('ctb', 'cph'), comment = "Code in src/doc2vec"))
Maintainer: Jan Wijffels <jwijffels@bnosac.be>
Description: Learn vector representations of sentences, paragraphs or documents by using the 'Paragraph Vector' algorithms, namely the distributed bag of words ('PV-DBOW') and the distributed memory ('PV-DM') model. The techniques in the package are detailed in the paper "Distributed Representations of Sentences and Documents" by Mikolov et al. (2014), available at <arXiv:1405.4053>.
URL: https://github.com/bnosac/doc2vec
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Depends: R (>= 2.10)
Imports: Rcpp (>= 0.11.5), stats
LinkingTo: Rcpp
Suggests: tokenizers.bpe
NeedsCompilation: yes
Packaged: 2021-01-21 08:42:35 UTC; jwijffels
Author: Jan Wijffels [aut, cre, cph] (R wrapper), BNOSAC [cph] (R wrapper), hiyijian [ctb, cph] (Code in src/doc2vec)
Repository: CRAN
Date/Publication: 2021-01-21 17:20:09 UTC

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New package usmap with initial version 0.5.2
Package: usmap
Version: 0.5.2
Title: US Maps Including Alaska and Hawaii
Description: Obtain United States map data frames of varying region types (e.g. county, state). The map data frames include Alaska and Hawaii conveniently placed to the bottom left, as they appear in most maps of the US. Convenience functions for plotting choropleths and working with FIPS codes are also provided.
Authors@R: person("Paolo", "Di Lorenzo", email = "paolo@dilorenzo.pl", role = c("aut", "cre"))
Depends: R (>= 3.5.0)
License: GPL-3 | file LICENSE
Encoding: UTF-8
LazyData: true
URL: https://usmap.dev
BugReports: https://github.com/pdil/usmap/issues
Imports: utils
Suggests: covr, ggplot2, ggrepel, knitr, maptools, proto, rgdal, rmarkdown, scales, sp, stringr, testthat
RoxygenNote: 7.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-01-21 15:33:11 UTC; paolo
Author: Paolo Di Lorenzo [aut, cre]
Maintainer: Paolo Di Lorenzo <paolo@dilorenzo.pl>
Repository: CRAN
Date/Publication: 2021-01-21 16:20:03 UTC

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New package shapr with initial version 0.1.4
Package: shapr
Version: 0.1.4
Title: Prediction Explanation with Dependence-Aware Shapley Values
Description: Complex machine learning models are often hard to interpret. However, in many situations it is crucial to understand and explain why a model made a specific prediction. Shapley values is the only method for such prediction explanation framework with a solid theoretical foundation. Previously known methods for estimating the Shapley values do, however, assume feature independence. This package implements the method described in Aas, Jullum and Løland (2019) <arXiv:1903.10464>, which accounts for any feature dependence, and thereby produces more accurate estimates of the true Shapley values.
Authors@R: c( person("Nikolai", "Sellereite", email = "nikolaisellereite@gmail.com", role = "aut", comment = c(ORCID = "0000-0002-4671-0337")), person("Martin", "Jullum", email = "Martin.Jullum@nr.no", role = c("cre", "aut"), comment = c(ORCID = "0000-0003-3908-5155")), person("Anders", "Løland", email = "Anders.Loland@nr.no", role = "ctb"), person("Jens Christian", "Wahl", email = "Jens.Christian.Wahl@nr.no", role = "ctb"), person("Camilla", "Lingjærde", role = "ctb"), person("Norsk Regnesentral", role = c("cph", "fnd")) )
URL: https://norskregnesentral.github.io/shapr/, https://github.com/NorskRegnesentral/shapr
BugReports: https://github.com/NorskRegnesentral/shapr/issues
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
ByteCompile: true
Language: en-US
RoxygenNote: 7.1.1
Depends: R (>= 3.5.0)
Imports: stats, data.table, Rcpp (>= 0.12.15), condMVNorm, mvnfast, Matrix
Suggests: ranger, xgboost, mgcv, testthat, knitr, rmarkdown, roxygen2, MASS, ggplot2, gbm
LinkingTo: RcppArmadillo, Rcpp
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2021-01-21 14:53:36 UTC; jullum
Author: Nikolai Sellereite [aut] (<https://orcid.org/0000-0002-4671-0337>), Martin Jullum [cre, aut] (<https://orcid.org/0000-0003-3908-5155>), Anders Løland [ctb], Jens Christian Wahl [ctb], Camilla Lingjærde [ctb], Norsk Regnesentral [cph, fnd]
Maintainer: Martin Jullum <Martin.Jullum@nr.no>
Repository: CRAN
Date/Publication: 2021-01-21 16:20:07 UTC

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New package envalysis with initial version 0.4.1
Package: envalysis
Type: Package
Title: Miscellaneous Functions for Environmental Analyses
Version: 0.4.1
Date: 2021-01-21
Authors@R: c(person("Zacharias", "Steinmetz", role = c("aut", "cre"), email = "steinmetz-z@uni-landau.de", comment = c(ORCID = "0000-0001-6675-5033")))
Maintainer: Zacharias Steinmetz <steinmetz-z@uni-landau.de>
Description: Small toolbox for data analyses in environmental chemistry and ecotoxicology. Provides, for example, calibration() to calculate calibration curves and corresponding limits of detection (LODs) and quantification (LOQs) according to German DIN 32645:2008-11. texture() makes it easy to estimate soil particle size distributions from hydrometer measurements (ASTM D422-63(2007)e2).
URL: https://github.com/zsteinmetz/envalysis
BugReports: https://github.com/zsteinmetz/envalysis/issues
Encoding: UTF-8
License: GPL-3
LazyLoad: yes
LazyData: yes
VignetteBuilder: knitr
Depends: R (>= 4.0.0)
Imports: drc, ggplot2
Suggests: knitr, rmarkdown, testthat, MASS, data.table, tibble, soiltexture
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2021-01-21 14:45:14 UTC; steinmetz-z
Author: Zacharias Steinmetz [aut, cre] (<https://orcid.org/0000-0001-6675-5033>)
Repository: CRAN
Date/Publication: 2021-01-21 16:20:10 UTC

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New package KRIS with initial version 1.1.6
Package: KRIS
Type: Package
Title: Keen and Reliable Interface Subroutines for Bioinformatic Analysis
Version: 1.1.6
Authors@R: c(person(given = "Kridsadakorn", family = "Chaichoompu", email = "kridsadakorn@biostatgen.org", role = c("aut", "cre")),person(given = "Kristel", family = 'Van Steen', role = "aut"),person(given = "Fentaw", family = "Abegaz", role = "aut"),person(given = "Sissades", family = "Tongsima", role = "aut"),person(given = "Philip", family = "James Shaw", role = "aut"),person(given = "Anavaj", family = "Sakuntabhai", role = "aut"),person(given = "Luisa", family = "Pereira", role = "aut"))
Description: Provides useful functions which are needed for bioinformatic analysis such as calculating linear principal components from numeric data and Single-nucleotide polymorphism (SNP) dataset, calculating fixation index (Fst) using Hudson method, creating scatter plots in 3 views, handling with PLINK binary file format, detecting rough structures and outliers using unsupervised clustering, and calculating matrix multiplication in the faster way for big data.
Depends: R (>= 3.5.0)
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Imports: rARPACK,grDevices,graphics,stats,utils
Suggests: testthat
BugReports: https://gitlab.com/kris.ccp/kris/-/issues
URL: https://gitlab.com/kris.ccp/kris
NeedsCompilation: no
Packaged: 2021-01-20 15:02:56 UTC; kris
Author: Kridsadakorn Chaichoompu [aut, cre], Kristel Van Steen [aut], Fentaw Abegaz [aut], Sissades Tongsima [aut], Philip James Shaw [aut], Anavaj Sakuntabhai [aut], Luisa Pereira [aut]
Maintainer: Kridsadakorn Chaichoompu <kridsadakorn@biostatgen.org>
Repository: CRAN
Date/Publication: 2021-01-21 12:10:02 UTC

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New package RsSimulx with initial version 1.0.0
Package: RsSimulx
Type: Package
Title: R Speaks 'Simulx'
Version: 1.0.0
Authors@R: c(person(given = "Clemence", family = "Pinaud", role = c("aut", "cre"), email = "clemence.pinaud@lixoft.com"), person(given = "Jonathan", family = "Chauvin", role = "aut", email = "clemence.pinaud@lixoft.com"), person(given = "Marc", family = "Lavielle", role = "ctb", email = "Marc.Lavielle@inria.fr"))
Maintainer: Clemence Pinaud <clemence.pinaud@lixoft.com>
Description: Provide useful tools which supplement the use of Simulx software and R connectors (Monolix Suite). 'Simulx' is an easy, efficient and flexible application for clinical trial simulations. You need 'Simulx' software to be installed in order to use 'RsSimulx' package. Among others tasks, 'RsSimulx' provides the same functions as package 'mlxR' does with a compatibility with 'Simulx' software.
SystemRequirements: 'Simulx' (<http://simulx.lixoft.com/>)
Depends: R (>= 3.0.0), ggplot2
Imports: gridExtra, utils, stats, grDevices
Encoding: UTF-8
Collate: catplotmlx.R ggplotmlx.R kmplotmlx.R prctilemlx.R simulxR.R smlx-checks.R smlx-init.R smlx-tools.R data.R smlx-connectors.R writeData.R zzz.R exposure.R shinymlx.R statmlx.R stoolsmlx.R simpop.R utils.R
LazyData: true
License: BSD_2_clause + file LICENSE
Copyright: LIXOFT
RoxygenNote: 7.1.1.9000
Suggests: testthat
NeedsCompilation: no
Packaged: 2021-01-19 10:26:39 UTC; clemence
Author: Clemence Pinaud [aut, cre], Jonathan Chauvin [aut], Marc Lavielle [ctb]
Repository: CRAN
Date/Publication: 2021-01-21 11:10:06 UTC

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New package groupedstats with initial version 2.0.1
Type: Package
Package: groupedstats
Title: Grouped Statistical Analyses in a Tidy Way
Version: 2.0.1
Authors@R: person(given = "Indrajeet", family = "Patil", role = c("aut", "cre", "cph"), email = "patilindrajeet.science@gmail.com", comment = c(ORCID = "0000-0003-1995-6531", Twitter = "@patilindrajeets"))
Maintainer: Indrajeet Patil <patilindrajeet.science@gmail.com>
Description: Collection of functions to run statistical tests across all combinations of multiple grouping variables.
License: GPL-3 | file LICENSE
URL: https://indrajeetpatil.github.io/groupedstats/, https://github.com/IndrajeetPatil/groupedstats/
BugReports: https://github.com/IndrajeetPatil/groupedstats/issues/
Depends: R (>= 3.6.0)
Imports: broomExtra, dplyr, effectsize, glue, lme4, magrittr, parameters, purrr, rlang, skimr, stats, tibble, tidyr
Suggests: gapminder, ggplot2, knitr, rmarkdown
Encoding: UTF-8
Language: en-US
LazyData: true
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2021-01-21 11:06:42 UTC; inp099
Author: Indrajeet Patil [aut, cre, cph] (<https://orcid.org/0000-0003-1995-6531>, @patilindrajeets)
Repository: CRAN
Date/Publication: 2021-01-21 11:40:15 UTC

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New package faux with initial version 0.0.1.6
Package: faux
Title: Simulation for Factorial Designs
Version: 0.0.1.6
Date: 2021-01-05
Authors@R: c( person( given = "Lisa", family = "DeBruine", role = c("aut", "cre"), email = "debruine@gmail.com", comment = c(ORCID = "0000-0002-7523-5539") ), person( given = "Anna", family = "Krystalli", role = c("ctb"), email = "annakrystalli@googlemail.com", comment = c(ORCID = "0000-0002-2378-4915") ), person( given = "Andrew", family = "Heiss", role = c("ctb"), email = "andrew@andrewheiss.com", comment = c(ORCID = "0000-0002-3948-3914") ))
Description: Create datasets with factorial structure through simulation by specifying variable parameters. Extended documentation at <https://debruine.github.io/faux/>. Described in DeBruine (2020) <doi:10.5281/zenodo.2669586>.
Depends: R (>= 3.2.4)
Imports: lme4, dplyr, ggplot2 (>= 3.3.0), jsonlite, truncnorm
License: MIT + file LICENSE
Suggests: testthat (>= 2.1.0), tidyr, knitr, rmarkdown, roxygen2, covr, cowplot, ggExtra, purrr, broom, broom.mixed, psych
VignetteBuilder: knitr
RoxygenNote: 7.1.1
Encoding: UTF-8
LazyData: true
URL: https://github.com/debruine/faux
BugReports: https://github.com/debruine/faux/issues
NeedsCompilation: no
Packaged: 2021-01-18 16:13:24 UTC; lisad
Author: Lisa DeBruine [aut, cre] (<https://orcid.org/0000-0002-7523-5539>), Anna Krystalli [ctb] (<https://orcid.org/0000-0002-2378-4915>), Andrew Heiss [ctb] (<https://orcid.org/0000-0002-3948-3914>)
Maintainer: Lisa DeBruine <debruine@gmail.com>
Repository: CRAN
Date/Publication: 2021-01-21 11:20:02 UTC

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New package circularEV with initial version 0.1.0
Package: circularEV
Type: Package
Title: Extreme Value Analysis for Circular Data
Version: 0.1.0
Date: 2021-01-19
Depends: R (>= 3.6)
Imports: parallel, foreach, doParallel, mgcv, circular, NPCirc, ggplot2, utils, stats
Author: Evandro Konzen
Maintainer: Evandro Konzen <e.konzen@reading.ac.uk>
Description: General functions for performing extreme value analysis on a circular domain as part of the statistical methodology in the paper by Konzen, E., Neves, C., and Jonathan, P. (2020+). Modelling non-stationary extremes of storm severity: comparing parametric and semi-parametric inference. Environmetrics (to appear).
Acknowledgements: This work was supported by the EPSRC UKRI Innovation Fellowship (grant number EP/S001263/1)
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
Suggests: plotly, testthat, knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-01-19 10:36:27 UTC; evandro
Repository: CRAN
Date/Publication: 2021-01-21 11:10:02 UTC

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New package TRMF with initial version 0.0.2
Package: TRMF
Type: Package
Title: Temporally Regularized Matrix Factorization
Version: 0.0.2
Author: Chad Hammerquist [aut, cre], Scentsy Inc [cph]
Maintainer: Chad Hammerquist <chammerquist@scentsy.com>
Description: Use alternating least squares to estimate a Temporally Regularized Matrix Factorization (Yu, Hsiang-Fu, Nikhil Rao, and Inderjit S. Dhillon, 2015) <arXiv:1509.08333v3> (possibly) in the presence of missing values.
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: Matrix,limSolve,generics
Suggests: magrittr, knitr,rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-01-18 22:25:43 UTC; chammerquist
Repository: CRAN
Date/Publication: 2021-01-21 10:20:09 UTC

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New package shiny.worker with initial version 0.0.1
Package: shiny.worker
Type: Package
Title: Delegate Jobs for Shiny Web Applications
Version: 0.0.1
Authors@R: c(person("Paweł", "Przytuła", email = "paweł@appsilon.com", role = c("aut")), person("Dominik", "Krzemiński", email = "dominik@appsilon.com", role = c("cre")), person(family = "Appsilon", role = c("cph")) )
Description: It allows you to delegate heavy computation tasks to a separate process, such that it does not freeze your Shiny app.
Encoding: UTF-8
LazyData: true
License: MIT + file LICENSE
Imports: future, shiny, R6
RoxygenNote: 7.1.1
Suggests: testthat, covr
NeedsCompilation: no
Packaged: 2021-01-19 10:05:26 UTC; dominik
Author: Paweł Przytuła [aut], Dominik Krzemiński [cre], Appsilon [cph]
Maintainer: Dominik Krzemiński <dominik@appsilon.com>
Repository: CRAN
Date/Publication: 2021-01-21 11:00:02 UTC

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New package LSMRealOptions with initial version 0.1.0
Package: LSMRealOptions
Title: Value American and Real Options Through LSM Simulation
Version: 0.1.0
Authors@R: c(person("Thomas", "Aspinall", email = "tomaspinall2512@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-6968-1989")), person("Adrian", "Gepp", email = "adgepp@bond.edu.au", role = c("aut"), comment = c(ORCID = "0000-0003-1666-5501")), person("Geoff", "Harris", email = "gharris@bond.edu.au", role = c("aut"), comment = c(ORCID = "0000-0003-4284-8619")), person("Simone", "Kelly", email = "skelly@bond.edu.au", role = c("aut"), comment = c(ORCID = "0000-0002-6528-8557")), person("Colette", "Southam", email = "csoutham@bond.edu.au", role = c("aut"), comment = c(ORCID = "0000-0001-7263-2347")), person("Bruce", "Vanstone", email = "bvanston@bond.edu.au", role = c("aut"), comment = c(ORCID = "0000-0002-3977-2468")) )
Description: The least-squares Monte Carlo (LSM) simulation method is a popular method for the approximation of the value of early and multiple exercise options. 'LSMRealOptions' provides implementations of the LSM simulation method to value American option products and capital investment projects through real options analysis. 'LSMRealOptions' values capital investment projects with cash flows dependent upon underlying state variables that are stochastically evolving, providing analysis into the timing and critical values at which investment is optimal. 'LSMRealOptions' provides flexibility in the stochastic processes followed by underlying assets, the number of state variables, basis functions and underlying asset characteristics to allow a broad range of assets to be valued through the LSM simulation method. Real options projects are further able to be valued whilst considering construction periods, time-varying initial capital expenditures and path-dependent operational flexibility including the ability to temporarily shutdown or permanently abandon projects after initial investment has occurred. The LSM simulation method was first presented in the prolific work of Longstaff and Schwartz (2001) <doi:10.1093/rfs/14.1.113>.
Depends: R (>= 3.5.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1.9000
Suggests: knitr, rmarkdown, ggplot2, dplyr, scales, NFCP
Imports: stats
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-01-19 07:29:28 UTC; Thomas Aspinall
Author: Thomas Aspinall [aut, cre] (<https://orcid.org/0000-0002-6968-1989>), Adrian Gepp [aut] (<https://orcid.org/0000-0003-1666-5501>), Geoff Harris [aut] (<https://orcid.org/0000-0003-4284-8619>), Simone Kelly [aut] (<https://orcid.org/0000-0002-6528-8557>), Colette Southam [aut] (<https://orcid.org/0000-0001-7263-2347>), Bruce Vanstone [aut] (<https://orcid.org/0000-0002-3977-2468>)
Maintainer: Thomas Aspinall <tomaspinall2512@gmail.com>
Repository: CRAN
Date/Publication: 2021-01-21 11:00:13 UTC

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New package interacCircos with initial version 1.0.0
Package: interacCircos
Type: Package
Title: The Visualization of Interactive Circos Plot
Description: Implement in an efficient approach to display the genomic data, relationship, information in an interactive circular genome(Circos) plot. 'interacCircos' are inspired by 'circosJS', 'BioCircos.js' and 'NG-Circos' and we integrate the modules of 'circosJS', 'BioCircos.js' and 'NG-Circos' into this R package, based on 'htmlwidgets' framework.
Version: 1.0.0
Author: Zhe Cui
Maintainer: Zhe Cui <mrcuizhe@gmail.com>
License: GPL-3
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.5.0)
Imports: RColorBrewer, htmlwidgets, jsonlite, plyr, grDevices
RoxygenNote: 7.1.0
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-01-19 06:49:21 UTC; cuizhe
Repository: CRAN
Date/Publication: 2021-01-21 10:40:06 UTC

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New package gwaRs with initial version 0.1.0
Type: Package
Package: gwaRs
Title: Manhattan, Q-Q, and PCA Plots using 'ggplot2'
Version: 0.1.0
Authors@R: person(given = "Lindokuhle", family = "Nkambule", role = c("aut", "cre"), email = "lindonkambule116@gmail.com", comment = c(ORCID = "0000-0002-5682-2834"))
Description: Generate Manhattan, Q-Q, and PCA plots from GWAS and PCA results using 'ggplot2'.
License: MIT + file LICENCE
Encoding: UTF-8
LazyData: true
Imports: RColorBrewer (>= 1.1.2), ggplot2, ggrepel, dplyr, tidyr, data.table, scales, stats, grDevices
RoxygenNote: 7.1.1
Depends: R (>= 2.10)
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
URL: https://github.com/LindoNkambule/gwaRs
BugReports: https://github.com/LindoNkambule/gwaRs/issues
NeedsCompilation: no
Packaged: 2021-01-19 07:08:12 UTC; lindokuhle
Author: Lindokuhle Nkambule [aut, cre] (<https://orcid.org/0000-0002-5682-2834>)
Maintainer: Lindokuhle Nkambule <lindonkambule116@gmail.com>
Repository: CRAN
Date/Publication: 2021-01-21 10:40:11 UTC

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New package chronicle with initial version 0.1.0
Package: chronicle
Type: Package
Title: Grammar for Creating R Markdown Reports
Version: 0.1.0
Authors@R: person("Philippe", "Heymans Smith", email = "pheymanss@gmail.com", role = c("aut", "cre"))
Description: A system for creating beautiful and interactive R Markdown reports by adding modules like plots and tables to an empty header.
Depends: R (>= 3.5.0), data.table, magrittr, rlang
License: GPL (>= 3)
Encoding: UTF-8
Imports: DT, dygraphs, ggplot2, glue, knitr, plotly, prettydoc, purrr, RColorBrewer, readr, rmarkdown, scales, stats, viridis, zoo
Suggests: devtools
LazyData: true
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2021-01-19 03:06:50 UTC; pheym
Author: Philippe Heymans Smith [aut, cre]
Maintainer: Philippe Heymans Smith <pheymanss@gmail.com>
Repository: CRAN
Date/Publication: 2021-01-21 10:30:02 UTC

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New package BTYDplus with initial version 1.2.0
Package: BTYDplus
Type: Package
Title: Probabilistic Models for Assessing and Predicting your Customer Base
Version: 1.2.0
Authors@R: person("Michael", "Platzer", email = "michael.platzer@gmail.com", role = c("aut", "cre"))
Description: Provides advanced statistical methods to describe and predict customers' purchase behavior in a non-contractual setting. It uses historic transaction records to fit a probabilistic model, which then allows to compute quantities of managerial interest on a cohort- as well as on a customer level (Customer Lifetime Value, Customer Equity, P(alive), etc.). This package complements the BTYD package by providing several additional buy-till-you-die models, that have been published in the marketing literature, but whose implementation are complex and non-trivial. These models are: NBD [Ehrenberg (1959) <doi:10.2307/2985810>], MBG/NBD [Batislam et al (2007) <doi:10.1016/j.ijresmar.2006.12.005>], (M)BG/CNBD-k [Reutterer et al (2020) <doi:10.1016/j.ijresmar.2020.09.002>], Pareto/NBD (HB) [Abe (2009) <doi:10.1287/mksc.1090.0502>] and Pareto/GGG [Platzer and Reutterer (2016) <doi:10.1287/mksc.2015.0963>].
URL: https://github.com/mplatzer/BTYDplus#readme
BugReports: https://github.com/mplatzer/BTYDplus/issues
License: GPL-3
LinkingTo: Rcpp
Depends: R (>= 3.2.0)
Imports: Rcpp, BTYD (>= 2.3), coda, data.table, mvtnorm, bayesm, stats, graphics
Suggests: testthat, covr, knitr, rmarkdown, gsl, lintr (>= 1.0.0)
RoxygenNote: 7.1.1
LazyData: true
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2021-01-20 17:16:22 UTC; mplatzer
Author: Michael Platzer [aut, cre]
Maintainer: Michael Platzer <michael.platzer@gmail.com>
Repository: CRAN
Date/Publication: 2021-01-21 11:00:16 UTC

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New package autoMrP with initial version 0.98
Package: autoMrP
Type: Package
Title: Improving MrP with Ensemble Learning
Version: 0.98
Authors@R: c( person(given = "Reto", family = "Wüest", role = c("aut"), email = "wuest.reto@gmail.com", comment = c(ORCID = "0000-0002-7502-6489")), person(given = "Lucas", family = "Leemann", role = c("aut"), email = "leemann@ipz.uzh.ch", comment = c(ORCID = "0000-0001-5201-869X")), person(given = "Philipp", family = "Broniecki", role = c("aut", "cre"), email = "philippbroniecki@gmail.com", comment = c(ORCID = "0000-0001-9214-4404")), person(given = "Hadley", family = "Wickham", role = "ctb", email = "hadley@rstudio.com"))
Description: A tool that improves the prediction performance of multilevel regression with post-stratification (MrP) by combining a number of machine learning methods. For information on the method, please refer to Broniecki, Wüest, Leemann (2020) ''Improving Multilevel Regression with Post-Stratification Through Machine Learning (autoMrP)'' forthcoming in 'Journal of Politics'. Final pre-print version: <https://lucasleemann.files.wordpress.com/2020/07/automrp-r2pa.pdf>.
URL: https://github.com/retowuest/autoMrP
BugReports: https://github.com/retowuest/autoMrP/issues
Depends: R (>= 3.6)
Imports: rlang (>= 0.4.5), dplyr (>= 1.0.2), lme4 (>= 1.1), gbm (>= 2.1.5), e1071 (>= 1.7-3), tibble (>= 3.0.1), glmmLasso (>= 1.5.1), EBMAforecast (>= 1.0.0), foreach (>= 1.5.0), doParallel (>= 1.0.15), doRNG (>= 1.8.2), ggplot2 (>= 3.3.2), knitr (>= 1.29), tidyr (>= 1.1.2), purrr (>= 0.3.4)
Suggests: rmarkdown, R.rsp
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
VignetteBuilder: R.rsp
NeedsCompilation: no
Packaged: 2021-01-19 10:11:26 UTC; Philipp
Author: Reto Wüest [aut] (<https://orcid.org/0000-0002-7502-6489>), Lucas Leemann [aut] (<https://orcid.org/0000-0001-5201-869X>), Philipp Broniecki [aut, cre] (<https://orcid.org/0000-0001-9214-4404>), Hadley Wickham [ctb]
Maintainer: Philipp Broniecki <philippbroniecki@gmail.com>
Repository: CRAN
Date/Publication: 2021-01-21 11:00:09 UTC

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New package targets with initial version 0.0.2
Package: targets
Title: Dynamic Function-Oriented 'Make'-Like Declarative Workflows
Description: As a pipeline toolkit for Statistics and data science in R, the 'targets' package brings together function-oriented programming and 'Make'-like declarative workflows. It analyzes the dependency relationships among the tasks of a workflow, skips steps that are already up to date, runs the necessary computation with optional parallel workers, abstracts files as R objects, and provides tangible evidence that the results match the underlying code and data. The methodology in this package borrows from GNU 'Make' (2015, ISBN:978-9881443519) and 'drake' (2018, <doi:10.21105/joss.00550>).
Version: 0.0.2
License: MIT + file LICENSE
URL: https://docs.ropensci.org/targets/, https://github.com/ropensci/targets
BugReports: https://github.com/ropensci/targets/issues
Authors@R: c( person( given = c("William", "Michael"), family = "Landau", role = c("aut", "cre"), email = "will.landau@gmail.com", comment = c(ORCID = "0000-0003-1878-3253") ), person( given = c("Matthew", "T."), family = "Warkentin", role = "ctb" ), person( given = "Samantha", family = "Oliver", role = "rev", comment = c(ORCID = "0000-0001-5668-1165") ), person( given = "Tristan", family = "Mahr", role = "rev", comment = c(ORCID = "0000-0002-8890-5116") ), person( family = "Eli Lilly and Company", role = "cph" ))
Depends: R (>= 3.5.0)
Imports: callr (>= 3.4.3), cli (>= 2.0.2), codetools (>= 0.2.16), data.table (>= 1.12.8), digest (>= 0.6.25), igraph (>= 1.2.5), R6 (>= 2.4.1), rlang (>= 0.4.5), tibble (>= 3.0.1), tidyselect (>= 1.1.0), utils, vctrs (>= 0.2.4), withr (>= 2.1.2)
Suggests: aws.s3 (>= 0.3.21), bs4Dash(>= 0.5.0), clustermq (>= 0.8.9), curl (>= 4.3), dplyr (>= 1.0.0), fst (>= 0.9.2), future (>= 1.19.1), keras (>= 2.2.5.0), knitr (>= 1.30), rmarkdown (>= 2.4), pingr (>= 2.0.1), pkgload (>= 1.1.0), qs (>= 0.23.2), rstudioapi (>= 0.11), shiny (>= 1.5.0), shinycssloaders (>= 1.0.0), testthat (>= 3.0.0), torch (>= 0.1.0), usethis (>= 1.6.3), visNetwork (>= 2.0.9)
Encoding: UTF-8
Language: en-US
VignetteBuilder: knitr
Config/testthat/edition: 3
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2021-01-18 13:17:37 UTC; c240390
Author: William Michael Landau [aut, cre] (<https://orcid.org/0000-0003-1878-3253>), Matthew T. Warkentin [ctb], Samantha Oliver [rev] (<https://orcid.org/0000-0001-5668-1165>), Tristan Mahr [rev] (<https://orcid.org/0000-0002-8890-5116>), Eli Lilly and Company [cph]
Maintainer: William Michael Landau <will.landau@gmail.com>
Repository: CRAN
Date/Publication: 2021-01-21 09:20:03 UTC

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New package LPDynR with initial version 1.0.1
Package: LPDynR
Title: Land Productivity Dynamics Indicator
Version: 1.0.1
Authors@R: c( person("Xavier", "Rotllan-Puig", email = "xavier.rotllan.puig@aster-projects.cat", role = c("aut", "cre")), person("Eva", "Ivits", email = "", role = c("aut")), person("Michael", "Cherlet", email = "", role = c("aut")))
Description: It uses 'phenological' and productivity-related variables derived from time series of vegetation indexes, such as the Normalized Difference Vegetation Index, to assess ecosystem dynamics and change, which eventually might drive to land degradation. The final result of the Land Productivity Dynamics indicator is a categorical map with 5 classes of land productivity dynamics, ranging from declining to increasing productivity. See <https://github.com/xavi-rp/LPD/blob/master/ATBD/LPD_ATBD.pdf> for a description of the methods used in the package to calculate the indicator.
Depends: R (>= 3.6.0)
Imports: raster, dplyr, stats, data.table, virtualspecies, magrittr, rgdal, parallel
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
URL: https://github.com/xavi-rp/LPDynR
BugReports: https://github.com/xavi-rp/LPDynR/issues
NeedsCompilation: no
Packaged: 2021-01-18 12:12:42 UTC; xavi_rp
Author: Xavier Rotllan-Puig [aut, cre], Eva Ivits [aut], Michael Cherlet [aut]
Maintainer: Xavier Rotllan-Puig <xavier.rotllan.puig@aster-projects.cat>
Repository: CRAN
Date/Publication: 2021-01-21 09:10:05 UTC

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New package GenomeAdmixR with initial version 1.1.2
Type: Package
Package: GenomeAdmixR
Title: Simulate Admixture of Genomes
Version: 1.1.2
Authors@R: c(person(given = "Thijs", family = "Janzen", role = c("aut", "cre"), email = "thijsjanzen@gmail.com"), person(given = "Fernando", family = "Diaz G.", role = "ctb", email = "ferdiazfer@gmail.com"), person(given = "Richèl J.C.", family = "Bilderbeek", role = "ctb"))
Description: Individual-based simulations forward in time, simulating how patterns in ancestry along the genome change after admixture. Full description can be found in Janzen (2020) <doi:10.1101/2020.10.19.343491>.
License: GPL (>= 2)
URL: https://github.com/thijsjanzen/GenomeAdmixR
BugReports: https://github.com/thijsjanzen/GenomeAdmixR/issues
Imports: hierfstat, methods, Rcpp, tibble, ggplot2, rlang, ggridges
Suggests: covr, dplyr, junctions, magrittr, rmarkdown, testit, testthat, knitr
LinkingTo: Rcpp, RcppArmadillo
VignetteBuilder: knitr
Encoding: UTF-8
RoxygenNote: 7.1.1
SystemRequirements: C++14, GNU make
NeedsCompilation: yes
Packaged: 2021-01-18 13:43:47 UTC; p251362
Author: Thijs Janzen [aut, cre], Fernando Diaz G. [ctb], Richèl J.C. Bilderbeek [ctb]
Maintainer: Thijs Janzen <thijsjanzen@gmail.com>
Repository: CRAN
Date/Publication: 2021-01-21 09:10:09 UTC

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New package DesignCTPB with initial version 0.4.0
Package: DesignCTPB
Type: Package
Title: Design Clinical Trials with Potential Biomarker Effect
Version: 0.4.0
Authors@R: c(person("Yitao", "Lu", email = "yitaolu@uvic.ca", role = c("aut","cre"),comment = c(ORCID = "0000-0002-0523-7416")), person("Belaid", email = "bmoa@uvic.ca", role = c("aut")), person("Julie","Zhou", email = "jzhou@uvic.ca", role = c("aut")), person("Li","Xing", email = "li.xing@math.usask.ca", role = c("aut"),comment = c(ORCID = "0000-0002-4186-7909")), person("Xuekui","Zhang", email = "xuekui@uvic.ca", role = c("aut"),comment = c(ORCID = "0000-0003-4728-2343")))
Description: Applying 'CUDA' 'GPUs' via 'Numba' for optimal clinical design. It allows the user to utilize a 'reticulate' 'Python' environment and run intensive Monte Carlo simulation to get the optimal cutoff for the clinical design with potential biomarker effect, which can guide the realistic clinical trials.
License: GPL (>= 2)
URL: https://github.com/ubcxzhang/DesignCTPB, Y Lu (2020) <doi:10.1002/sim.8868>
BugReports: https://github.com/ubcxzhang/DesignCTPB/issues
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
NeedsCompilation: no
Config/reticulate: list( packages = list( list(package = "scipy", pip = TRUE), list(package = "numba", pip = TRUE), list(package = "pandas", pip = TRUE) ) )
Packaged: 2021-01-18 13:11:05 UTC; michael
Imports: reticulate, mnormt, fields, magrittr
Suggests: knitr, rmarkdown, dplyr, plotly,
VignetteBuilder: knitr
Depends: R (>= 2.10)
SystemRequirements: NVIDIA CUDA GPU with compute capability 3.0 or above and NVIDIA CUDA Toolkit 9.0 or above
Author: Yitao Lu [aut, cre] (<https://orcid.org/0000-0002-0523-7416>), Belaid [aut], Julie Zhou [aut], Li Xing [aut] (<https://orcid.org/0000-0002-4186-7909>), Xuekui Zhang [aut] (<https://orcid.org/0000-0003-4728-2343>)
Maintainer: Yitao Lu <yitaolu@uvic.ca>
Repository: CRAN
Date/Publication: 2021-01-21 09:10:12 UTC

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New package reportfactory with initial version 0.1.1
Package: reportfactory
Title: Lightweight Infrastructure for Handling Multiple R Markdown Documents
Version: 0.1.1
Authors@R: c( person("Thibaut", "Jombart", role = "aut", email = "thibautjombart@gmail.com"), person("Zhian N.", "Kamvar", role = "aut", email = "zkamvar@gmail.com"), person("Amy", "Gimma", role = "ctb", email = "amyg225@gmail.com"), person("Tim", "Taylor", role =c("aut", "cre"), email = "tim.taylor@hiddenelephants.co.uk", comment = c(ORCID = "0000-0002-8587-7113")) )
Description: Provides an infrastructure for handling multiple R Markdown reports, including automated curation and time-stamping of outputs, parameterisation and provision of helper functions to manage dependencies.
License: MIT + file LICENSE
URL: https://github.com/reconhub/reportfactory
BugReports: https://github.com/reconhub/reportfactory/issues
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Suggests: testthat, covr
Imports: rprojroot, fs, rmarkdown, utils, checkpoint, yaml, callr
Config/testthat/edition: 3
NeedsCompilation: no
Packaged: 2021-01-18 10:19:14 UTC; tim
Author: Thibaut Jombart [aut], Zhian N. Kamvar [aut], Amy Gimma [ctb], Tim Taylor [aut, cre] (<https://orcid.org/0000-0002-8587-7113>)
Maintainer: Tim Taylor <tim.taylor@hiddenelephants.co.uk>
Repository: CRAN
Date/Publication: 2021-01-21 09:00:02 UTC

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New package pwt10 with initial version 10.0-0
Package: pwt10
Version: 10.0-0
Date: 2021-01-18
Title: Penn World Table (Version 10.x)
Authors@R: person(given = "Achim", family = "Zeileis", role = c("aut", "cre"), email = "Achim.Zeileis@R-project.org", comment = c(ORCID = "0000-0003-0918-3766"))
Description: The Penn World Table 10.x (<http://www.ggdc.net/pwt/>) provides information on relative levels of income, output, input, and productivity for 183 countries between 1950 and 2019.
LazyData: yes
LazyDataCompression: xz
Depends: R (>= 3.6.0)
License: GPL-2 | GPL-3
NeedsCompilation: no
Packaged: 2021-01-18 03:14:53 UTC; zeileis
Author: Achim Zeileis [aut, cre] (<https://orcid.org/0000-0003-0918-3766>)
Maintainer: Achim Zeileis <Achim.Zeileis@R-project.org>
Repository: CRAN
Date/Publication: 2021-01-21 08:30:02 UTC

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New package GenHMM1d with initial version 0.1.0
Package: GenHMM1d
Type: Package
Title: Goodness-of-Fit for Univariate Hidden Markov Models
Version: 0.1.0
Authors@R: c( person(c("Bouchra","R."), "Nasri", role = c("aut", "cre","cph"), email = "bouchra.nasri@umontreal.ca"), person("Mamadou Yamar", "Thioub", role = c("aut","cph")))
Description: Inference, goodness-of-fit tests, and predictions for continuous and discrete univariate Hidden Markov Models (HMM). The goodness-of-fit test is based on a Cramer-von Mises statistic and uses parametric bootstrap to estimate the p-value. The description of the methodology is taken from Nasri et al (2020) <doi:10.1029/2019WR025122>.
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: actuar, EnvStats, extraDistr, ggplot2, matrixcalc, parallel, reshape2, rmutil, ssdtools, VaRES, VGAM
Depends: doParallel, foreach, stats
Suggests: gamlss.dist, GeneralizedHyperbolic, gld, GLDEX, sgt, skewt, sn, stabledist
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2021-01-17 23:13:20 UTC; 49009427
Author: Bouchra R. Nasri [aut, cre, cph], Mamadou Yamar Thioub [aut, cph]
Maintainer: Bouchra R. Nasri <bouchra.nasri@umontreal.ca>
Repository: CRAN
Date/Publication: 2021-01-21 08:20:03 UTC

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New package GEInter with initial version 0.1.0
Package: GEInter
Type: Package
Title: Robust Gene-Environment Interaction Analysis
Version: 0.1.0
Authors@R: c(person("Mengyun", "Wu", role=c("aut"), email = "wu.mengyun@mail.shufe.edu.cn"), person("Xing", "Qin", role=c("aut","cre"), email = "qin.xing@163.sufe.edu.cn"), person("Shuangge", "Ma", role=c("aut"), email = "shuangge.ma@yale.edu"))
Maintainer: Xing Qin <qin.xing@163.sufe.edu.cn>
Description: For the risk, progression, and response to treatment of many complex diseases, it has been increasingly recognized that gene-environment interactions play important roles beyond the main genetic and environmental effects. In practical interaction analyses, outliers in response variables and covariates are not uncommon. In addition, missingness in environmental factors is routinely encountered in epidemiological studies. The developed package consists of four robust approaches to address the outliers problems, among which two approaches can also accommodate missingness in environmental factors. Both continuous and right censored responses are considered. The proposed approaches are based on penalization and sparse boosting techniques for identifying important interactions, which are realized using efficient algorithms. Beyond the gene-environment analysis, the developed package can also be adopted to conduct analysis on interactions between other types of low-dimensional and high-dimensional data. (Mengyun Wu et al (2017), <doi:10.1080/00949655.2018.1523411>; Mengyun Wu et al (2017), <doi:10.1002/gepi.22055>; Yaqing Xu et al (2018), <doi:10.1080/00949655.2018.1523411>; Yaqing Xu et al (2019), <doi:10.1016/j.ygeno.2018.07.006>).
License: GPL-2
Encoding: UTF-8
LazyData: true
Imports: survAUC, MASS, splines, pcaPP, Hmisc, survival, quantreg, reshape2, ggplot2, stats, graphics
RoxygenNote: 7.1.1
Depends: R (>= 2.10)
NeedsCompilation: no
Packaged: 2021-01-18 02:39:53 UTC; qx
Author: Mengyun Wu [aut], Xing Qin [aut, cre], Shuangge Ma [aut]
Repository: CRAN
Date/Publication: 2021-01-21 08:20:06 UTC

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Wed, 20 Jan 2021

New package rGEDI with initial version 0.1.11
Package: rGEDI
Type: Package
Title: NASA's Global Ecosystem Dynamics Investigation (GEDI) Data Visualization and Processing
Version: 0.1.11
Authors@R: c( person("Carlos Alberto", "Silva", email = "carlos_engflorestal@outlook.com", role = c("aut", "cre", "cph")), person("Caio", "Hamamura", email = "caiohamamura@gmail.com", role = c("aut", "cph")), person("Ruben", "Valbuena", email = "r.valbuena@bangor.ac.uk", role = c("aut","ctb")), person("Steven", "Hancock", email = "steven.hancock@ed.ac.uk", role = c("aut","ctb")), person("Adrian", "Cardil", email = "adriancardil@gmail.com", role = c("aut","ctb")), person("Eben North", "Broadbent", email = "eben@ufl.edu", role = c("aut","ctb")), person("Danilo Roberti Alves de", "Almeida", email = "daniloflorestas@gmail.com", role = c("aut","ctb")), person("Celso H. L.", "Silva Junior", email = "celso.junior@inpe.br", role = c("aut","ctb")), person("Carine", "Klauberg", email = "carine_klauberg@hotmail.com", role = c("aut","ctb")), person("Burton", "Garbow", email = "", role = ("cph"), comment = "Is the author of the MINPACK-1 Least Squares Fitting Library"), person("Kenneth", "Hillstrom", email = "", role = ("cph"), comment = "Is the author of the MINPACK-1 Least Squares Fitting Library"), person("Jorge", "More", email = "", role = ("cph"), comment = "Is the author of the MINPACK-1 Least Squares Fitting Library"), person("Craig", "Markwardt", email = "", role = ("cph"), comment = "Is the author of the enhanced MINPACK-1 Least Squares Fitting Library"))
Maintainer: Carlos Alberto Silva <carlos_engflorestal@outlook.com>
Description: Set of tools for downloading, reading, visualizing and processing GEDI Level1B, Level2A and Level2B data.
License: GPL-3
Encoding: UTF-8
LazyData: true
Depends: methods
Imports: bit64, curl, data.table, fs, getPass, ggplot2, hdf5r, jsonlite, lazyeval, raster, rgdal, rgeos, RColorBrewer, sp, stats
Suggests: lattice, leaflet, leafsync, lidR, plot3D, rasterVis, viridis
SystemRequirements: GNU Scientific Library (>= 2.1), HDF5 (>= 1.8.13), libgeotiff (>= 1.4.0), szip (>= 2.1), zlib (>= 1.2)
NeedsCompilation: yes
RoxygenNote: 7.1.0
BugReports: https://groups.yahoo.com/neo/groups/rGEDI
URL: https://github.com/carlos-alberto-silva/rGEDI
Copyright: inst/COPYRIGHTS
Author: Carlos Alberto Silva [aut, cre, cph], Caio Hamamura [aut, cph], Ruben Valbuena [aut, ctb], Steven Hancock [aut, ctb], Adrian Cardil [aut, ctb], Eben North Broadbent [aut, ctb], Danilo Roberti Alves de Almeida [aut, ctb], Celso H. L. Silva Junior [aut, ctb], Carine Klauberg [aut, ctb], Burton Garbow [cph] (Is the author of the MINPACK-1 Least Squares Fitting Library), Kenneth Hillstrom [cph] (Is the author of the MINPACK-1 Least Squares Fitting Library), Jorge More [cph] (Is the author of the MINPACK-1 Least Squares Fitting Library), Craig Markwardt [cph] (Is the author of the enhanced MINPACK-1 Least Squares Fitting Library)
Repository: CRAN
Repository/R-Forge/Project: rgedi
Repository/R-Forge/Revision: 38
Repository/R-Forge/DateTimeStamp: 2021-01-19 13:58:51
Date/Publication: 2021-01-20 17:10:03 UTC
Packaged: 2021-01-19 14:17:31 UTC; rforge

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New package trainR with initial version 0.0.1
Package: trainR
Title: An Interface to the National Rail Enquiries Systems
Version: 0.0.1
Authors@R: person(given = "Roberto", family = "Villegas-Diaz", role = c("aut", "cre"), email = "villegas.roberto@hotmail.com", comment = c(ORCID = "0000-0001-5036-8661"))
Description: The goal of 'trainR' is to provide a simple interface to the National Rail Enquiries (NRE) systems. There are few data feeds available, the simplest of them is Darwin, which provides real-time arrival and departure predictions, platform numbers, delay estimates, schedule changes and cancellations. Other data feeds provide historical data, Historic Service Performance (HSP), and much more. 'trainR' simplifies the data retrieval, so that the users can focus on their analyses. For more details visit <https://www.nationalrail.co.uk/46391.aspx>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Depends: R (>= 2.10)
URL: https://github.com/villegar/trainR/, https://villegar.github.io/trainR/
BugReports: https://github.com/villegar/trainR/issues/
Language: en-GB
Imports: RCurl, dplyr, glue, lubridate, magrittr, purrr, stringr, tibble, tidyr, usethis, xml2
NeedsCompilation: no
Packaged: 2021-01-16 20:13:24 UTC; roberto.villegas-diaz
Author: Roberto Villegas-Diaz [aut, cre] (<https://orcid.org/0000-0001-5036-8661>)
Maintainer: Roberto Villegas-Diaz <villegas.roberto@hotmail.com>
Repository: CRAN
Date/Publication: 2021-01-20 11:10:02 UTC

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New package njtr1 with initial version 0.1.0
Package: njtr1
Title: Download and Analyze New Jersey Car Crash Data
Version: 0.1.0
Authors@R: person(given = "Gavin", family = "Rozzi", role = c("aut", "cre"), email = "gr@gavinrozzi.com", comment = c(ORCID = "0000-0002-9969-8175"))
Description: Download and analyze crash data published by the New Jersey Department of Transportation. The data in this package is collected through the filing of NJTR-1 form by police officers, which provide a standardized way of documenting a crash that took place within New Jersey.
License: GPL-3
Encoding: UTF-8
URL: https://gavinrozzi.github.io/njtr1/, https://github.com/gavinrozzi/njtr1/, https://www.gavinrozzi.com/project/njtr1/
BugReports: https://github.com/gavinrozzi/njtr1/issues/
LazyData: true
Depends: R (>= 3.5.0), stringr, lubridate, readr
Suggests: knitr, rmarkdown, markdown
RoxygenNote: 7.1.1
VignetteBuilder: knitr, rmarkdown
NeedsCompilation: no
Packaged: 2021-01-17 17:50:23 UTC; shore
Author: Gavin Rozzi [aut, cre] (<https://orcid.org/0000-0002-9969-8175>)
Maintainer: Gavin Rozzi <gr@gavinrozzi.com>
Repository: CRAN
Date/Publication: 2021-01-20 12:00:02 UTC

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New package mongopipe with initial version 0.1.1
Package: mongopipe
Title: Query MongoDB Documents with R
Version: 0.1.1
Authors@R: person(given = "Oliver", family = "Haag", role = c("aut", "cre"), email = "oliver_haag@e.mail.de")
Maintainer: Oliver Haag <oliver_haag@e.mail.de>
Description: Translate R code into MongoDB aggregation pipelines.
URL: https://rpkgs.gitlab.io/mongopipe, https://gitlab.com/rpkgs/mongopipe
BugReports: https://gitlab.com/rpkgs/mongopipe/-/issues
License: MIT + file LICENSE
Suggests: testthat (>= 3.0.0), mongolite (>= 2.2.0), nycflights13
Config/testthat/edition: 3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Imports: magrittr, jsonlite, rlang
NeedsCompilation: no
Packaged: 2021-01-17 15:45:05 UTC; olli
Author: Oliver Haag [aut, cre]
Repository: CRAN
Date/Publication: 2021-01-20 11:50:06 UTC

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New package mobilityIndexR with initial version 0.2.1
Package: mobilityIndexR
Type: Package
Title: Calculates Transition Matrices and Mobility Indices
Version: 0.2.1
Author: Brett Mullins and Trevor Harkreader
Maintainer: Brett Mullins <brettcmullins@gmail.com>
Description: Measures mobility in a population through transition matrices and mobility indices. Relative, mixed, and absolute transition matrices are supported. The Prais-Bibby, Absolute Movement, Origin Specific, and Weighted Group Mobility indices are supported. Example income and grade data are included.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Depends: R (>= 2.10)
Imports: stats
Suggests: testthat (>= 2.1.0), covr, knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-01-16 22:14:14 UTC; brettm
Repository: CRAN
Date/Publication: 2021-01-20 11:50:09 UTC

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New package circletyper with initial version 1.0.0
Package: circletyper
Type: Package
Title: Curve Text Elements in 'Shiny' Using 'CircleType.js'
Version: 1.0.0
Authors@R: person(given = "Etienne", family = "Bacher", role = c("aut", "cre", "cph"), email = "etienne.bacher@protonmail.com")
Description: Enables curving text elements in 'Shiny' apps.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: shiny
RoxygenNote: 7.1.1
URL: https://github.com/etiennebacher/circletyper
BugReports: https://github.com/etiennebacher/circletyper/issues
Suggests: testthat (>= 3.0.0), spelling
Config/testthat/edition: 3
Language: en-US
NeedsCompilation: no
Packaged: 2021-01-17 17:52:12 UTC; etienne
Author: Etienne Bacher [aut, cre, cph]
Maintainer: Etienne Bacher <etienne.bacher@protonmail.com>
Repository: CRAN
Date/Publication: 2021-01-20 12:00:05 UTC

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New package pestr with initial version 0.8.2
Package: pestr
Title: Interface to Download Data on Pests and Hosts from 'EPPO'
Version: 0.8.2
Authors@R: person(given = "Michal Jan", family = "Czyz", role = c("aut", "cre"), email = "m.czyz.j@gmail.com", comment = c(ORCID = "0000-0001-7156-4530"))
Description: Set of tools to automatize extraction of data on pests from 'EPPO Data Services' and 'EPPO Global Database' and to put them into tables with human readable format. Those function use 'EPPO database API', thus you first need to register on <https://data.eppo.int> (free of charge). Additional helpers allow to download, check and connect to 'SQLite EPPO database'.
Depends: R (>= 3.6.0)
Imports: curl, DBI, dplyr (>= 1.0.0), httr, jsonlite, magrittr, readr, rlang, RSQLite, tidyr (>= 1.0.0), utils
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Suggests: knitr, mockr, rmarkdown, roxygen2, testthat
URL: https://github.com/mczyzj/pestr
BugReports: https://github.com/mczyzj/pestr/issues
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-01-16 11:40:02 UTC; michal
Author: Michal Jan Czyz [aut, cre] (<https://orcid.org/0000-0001-7156-4530>)
Maintainer: Michal Jan Czyz <m.czyz.j@gmail.com>
Repository: CRAN
Date/Publication: 2021-01-20 11:00:02 UTC

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Tue, 19 Jan 2021

New package ftrCOOL with initial version 1.1.2
Package: ftrCOOL
Type: Package
Title: Feature Extraction from Biological Sequences
Version: 1.1.2
Author: Sare Amerifar
Maintainer: Sare Amerifar <sare.ameri.01@gmail.com>
Description: Extracts features from biological sequences. It contains most features which are presented in related work and also includes features which have never been introduced before. It extracts numerous features from nucleotide and peptide sequences. Each feature converts the input sequences to discrete numbers in order to use them as predictors in machine learning models. There are many features and information which are hidden inside a sequence. Utilizing the package, users can convert biological sequences to discrete models based on chosen properties. References: 'iLearn' 'Z. Chen et al.' (2019) <DOI:10.1093/bib/bbz041>. 'iFeature' 'Z. Chen et al.' (2018) <DOI:10.1093/bioinformatics/bty140>. <https://CRAN.R-project.org/package=rDNAse>. 'PseKRAAC' 'Y. Zuo et al.' 'PseKRAAC: a flexible web server for generating pseudo K-tuple reduced amino acids composition' (2017) <DOI:10.1093/bioinformatics/btw564>. 'iDNA6mA-PseKNC' 'P. Feng et al.' 'iDNA6mA-PseKNC: Identifying DNA N6-methyladenosine sites by incorporating nucleotide physicochemical properties into PseKNC' (2019) <DOI:10.1016/j.ygeno.2018.01.005>. 'I. Dubchak et al.' 'Prediction of protein folding class using global description of amino acid sequence' (1995) <DOI:10.1073/pnas.92.19.8700>. 'W. Chen et al.' 'Identification and analysis of the N6-methyladenosine in the Saccharomyces cerevisiae transcriptome' (2015) <DOI:10.1038/srep13859>.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
Imports: stats, utils
Suggests: testthat
NeedsCompilation: no
Packaged: 2021-01-18 17:18:29 UTC; sareameri
Repository: CRAN
Date/Publication: 2021-01-19 17:00:02 UTC

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New package RGENERATEPREC with initial version 1.2.8
Package: RGENERATEPREC
Maintainer: Emanuele Cordano <emanuele.cordano@gmail.com>
License: GPL (>= 2)
Title: Tools to Generate Daily-Precipitation Time Series
Type: Package
Author: Emanuele Cordano
Description: The method 'generate()' is extended for spatial multi-site stochastic generation of daily precipitation. It generates precipitation occurrence in several sites using logit regression (Generalized Linear Models) and the approach by D.S. Wilks (1998) <doi:10.1016/S0022-1694(98)00186-3> .
Version: 1.2.8
Repository: CRAN
Date: 2021-01-19
Depends: R (>= 3.0), copula, RGENERATE, blockmatrix, Matrix, stringr
Imports: RMAWGEN
Suggests: knitr,rmarkdown,lubridate,leaflet,lmom,ggplot2,reshape2,RefManageR
VignetteBuilder: knitr
URL: https://github.com/ecor/RGENERATEPREC
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2021-01-19 14:04:34 UTC; ecor
Date/Publication: 2021-01-19 15:40:19 UTC

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New package unstruwwel with initial version 0.1.0
Package: unstruwwel
Title: Detect and Parse Historic Dates
Version: 0.1.0
Authors@R: person('Stefanie Schneider', email = 'stefanie.schneider@itg.uni-muenchen.de', role = c('cre', 'aut'), comment = c(ORCID = "0000-0003-4915-6949"))
Maintainer: Stefanie Schneider <stefanie.schneider@itg.uni-muenchen.de>
Description: Automatically converts language-specific verbal information, e.g., "1st half of the 19th century," to its standardized numerical counterparts, e.g., "1801-01-01/1850-12-31." It follows the recommendations of the 'MIDAS' ('Marburger Informations-, Dokumentations- und Administrations-System'), see <doi:10.11588/artdok.00003770>.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
URL: https://github.com/stefanieschneider/unstruwwel
BugReports: https://github.com/stefanieschneider/unstruwwel/issues
Suggests: testthat, roxygen2
Imports: R6, assertthat, lubridate, magrittr, stringr, tibble, tidyr, purrr, dplyr, rlang
Depends: R (>= 2.10)
NeedsCompilation: no
Packaged: 2021-01-15 20:08:09 UTC; sschneider
Author: Stefanie Schneider [cre, aut] (<https://orcid.org/0000-0003-4915-6949>)
Repository: CRAN
Date/Publication: 2021-01-19 10:10:02 UTC

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New package R6P with initial version 0.1.1
Package: R6P
Type: Package
Title: Design Patterns in R
URL: https://tidylab.github.io/R6P/, https://github.com/tidylab/R6P
BugReports: https://github.com/tidylab/R6P/issues
Version: 0.1.1
Date: 2021-01-01
Authors@R: c( person("Harel", "Lustiger", email = "tidylab@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0003-2953-9598")) )
Maintainer: Harel Lustiger <tidylab@gmail.com>
Description: Build robust and maintainable software with object-oriented design patterns in R. Design patterns abstract and present in neat, well-defined components and interfaces the experience of many software designers and architects over many years of solving similar problems. These are solutions that have withstood the test of time with respect to re-usability, flexibility, and maintainability. 'R6P' provides abstract base classes with examples for a few known design patterns. The patterns were selected by their applicability to analytic projects in R. Using these patterns in R projects have proven effective in dealing with the complexity that data-driven applications possess.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Language: en-GB
Depends: R (>= 3.5)
Suggests: testthat, collections, dplyr, DBI, RSQLite, tibble, pryr
Imports: R6, purrr, stringr
Config/testthat/edition: 3
NeedsCompilation: no
Packaged: 2021-01-16 06:53:00 UTC; Alpha
Author: Harel Lustiger [aut, cre] (<https://orcid.org/0000-0003-2953-9598>)
Repository: CRAN
Date/Publication: 2021-01-19 10:20:02 UTC

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New package ubms with initial version 1.0.1
Package: ubms
Version: 1.0.1
Date: 2021-01-15
Title: Bayesian Models for Data from Unmarked Animals using 'Stan'
Authors@R: person("Ken", "Kellner", email="contact@kenkellner.com", role=c("cre","aut"))
Depends: R (>= 3.4.0), unmarked
Imports: ggplot2 (>= 2.0.0), gridExtra, lme4, loo, Matrix, methods, Rcpp (>= 0.12.0), rstan (>= 2.18.1), rstantools (>= 2.0.0), stats
Suggests: covr, devtools, knitr, pkgdown, raster, rmarkdown, roxygen2, testthat
VignetteBuilder: knitr
Description: Fit Bayesian hierarchical models of animal abundance and occurrence via the 'rstan' package, the R interface to the 'Stan' C++ library. Supported models include single-season occupancy, dynamic occupancy, and N-mixture abundance models. Covariates on model parameters are specified using a formula-based interface similar to package 'unmarked', while also allowing for estimation of random slope and intercept terms. References: Carpenter et al. (2017) <doi:10.18637/jss.v076.i01>; Fiske and Chandler (2011) <doi:10.18637/jss.v043.i10>.
License: GPL (>= 3)
URL: https://kenkellner.com/ubms/
BugReports: https://github.com/kenkellner/ubms/issues
Encoding: UTF-8
RoxygenNote: 7.1.1
Biarch: true
LinkingTo: BH (>= 1.66.0), Rcpp (>= 0.12.0), RcppArmadillo (>= 0.9.300.2.0), RcppEigen (>= 0.3.3.3.0), rstan (>= 2.18.1), StanHeaders (>= 2.18.0)
SystemRequirements: GNU make
Collate: 'RcppExports.R' 'submodel.R' 'response.R' 'inputs.R' 'fit.R' 'posterior_predict.R' 'posterior_linpred.R' 'fitted.R' 'gof.R' 'occu.R' 'colext.R' 'missing.R' 'distamp.R' 'fitlist.R' 'occuRN.R' 'mb_chisq.R' 'multinomPois.R' 'occuTTD.R' 'pcount.R' 'plot_marginal.R' 'predict.R' 'ranef.R' 'residuals.R' 'stanmodels.R' 'ubms-package.R' 'ubmsFit-methods.R' 'ubmsFitList-methods.R' 'umf.R' 'utils.R'
NeedsCompilation: yes
Packaged: 2021-01-15 18:00:03 UTC; ken
Author: Ken Kellner [cre, aut]
Maintainer: Ken Kellner <contact@kenkellner.com>
Repository: CRAN
Date/Publication: 2021-01-19 09:30:03 UTC

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New package torchdatasets with initial version 0.0.1
Package: torchdatasets
Title: Ready to Use Extra Datasets for Torch
Version: 0.0.1
Authors@R: c( person(given = "Daniel", family = "Falbel", role = c("aut", "cre"), email = "daniel@rstudio.com" ), person(family = "RStudio", role = c("cph")) )
Description: Provides datasets in a format that can be easily consumed by torch 'dataloaders'. Handles data downloading from multiple sources, caching and pre-processing so users can focus only on their model implementations.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Imports: torch, fs, zip, pins, torchvision, stringr
Suggests: testthat, readr
URL: https://mlverse.github.io/torchdatasets/, https://github.com/mlverse/torchdatasets
BugReports: https://github.com/mlverse/torchdatasets/issues
NeedsCompilation: no
Packaged: 2021-01-15 19:00:00 UTC; dfalbel
Author: Daniel Falbel [aut, cre], RStudio [cph]
Maintainer: Daniel Falbel <daniel@rstudio.com>
Repository: CRAN
Date/Publication: 2021-01-19 09:40:02 UTC

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New package sgstar with initial version 0.1.0
Package: sgstar
Type: Package
Title: Seasonal Generalized Space Time Autoregressive (S-GSTAR) Model
Version: 0.1.0
Authors@R: c(person("M. Yoga Satria Utama","Developer", role = c("aut","cre"),email = "221709801@stis.ac.id"), person("Ernawati Pasaribu","Developer",role = "aut"))
Description: A set of function that implements for seasonal multivariate time series analysis based on Seasonal Generalized Space Time Autoregressive with Seemingly Unrelated Regression (S-GSTAR-SUR) Model by Setiawan(2016)<https://www.researchgate.net/publication/316517889_S-GSTAR-SUR_model_for_seasonal_spatio_temporal_data_forecasting>.
License: GPL-3
Imports: dplyr,ggplot2,nlme,tidyr
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
Suggests: knitr,rmarkdown
Depends: R (>= 3.4)
URL: https://github.com/yogasatria30/sgstar
BugReports: https://github.com/yogasatria30/sgstar/issues
NeedsCompilation: no
Packaged: 2021-01-15 17:00:16 UTC; Lenovo
Author: M. Yoga Satria Utama Developer [aut, cre], Ernawati Pasaribu Developer [aut]
Maintainer: M. Yoga Satria Utama Developer <221709801@stis.ac.id>
Repository: CRAN
Date/Publication: 2021-01-19 09:20:03 UTC

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New package safetyData with initial version 1.0.0
Package: safetyData
Title: Clinical Trial Data
Description: Example clinical trial data sets formatted for easy use in R.
Version: 1.0.0
Authors@R: c( person( given = "Jeremy", family = "Wildfire", role = c("aut", "cre"), email = "jwildfire@gmail.com" ), person( given = "Renan", family = "Escalante Chong", role = c("aut"), email = "raescalan@gmail.com" ) )
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Depends: R (>= 3.0)
NeedsCompilation: no
Packaged: 2021-01-15 19:37:09 UTC; jeremy
Author: Jeremy Wildfire [aut, cre], Renan Escalante Chong [aut]
Maintainer: Jeremy Wildfire <jwildfire@gmail.com>
Repository: CRAN
Date/Publication: 2021-01-19 09:50:02 UTC

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New package randChecks with initial version 0.1.0
Package: randChecks
Type: Package
Title: Covariate Balance Checks: Randomization Tests and Graphical Diagnostics
Version: 0.1.0
Author: Zach Branson
Maintainer: Zach Branson <zach@stat.cmu.edu>
Description: Provides randomization tests and graphical diagnostics for assessing randomized assignment and covariate balance for a binary treatment variable. See Branson (2021) <arXiv:1804.08760> for details.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2021-01-15 16:25:12 UTC; zjbranson
Depends: R (>= 3.5.0)
Repository: CRAN
Date/Publication: 2021-01-19 09:50:06 UTC

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New package qut with initial version 2.2
Package: qut
Type: Package
Title: Quantile Universal Threshold
Version: 2.2
Authors@R: c(person("Jairo", "Diaz-Rodriguez", role = c("aut", "cre","cph"), email = "adjairo@uninorte.edu.co"), person("Sylvain", "Sardy", role = c("aut", "ths"), email = "sylvain.sardy@unige.ch"), person("Caroline", "Giacobino", role = c("aut")), person("Nick", "Hengartner", role = c("aut")))
Description: Thresholding based tests for null hypothesis of the form A beta =c, and the Quantile Universal Threshold (QUT) for lasso regularization of Generalized Linear Models (GLM) and square-root lasso to obtain a sparse model with a good compromise between high true positive rate and low false discovery rate. Giacobino et al. (2017) <doi:10.1214/17-EJS1366>. Sardy et al. (2017) <arXiv:1708.02908>.
License: GPL-2
Depends: Matrix, glmnet, lars, flare
NeedsCompilation: no
Packaged: 2021-01-15 19:40:31 UTC; jairo
Author: Jairo Diaz-Rodriguez [aut, cre, cph], Sylvain Sardy [aut, ths], Caroline Giacobino [aut], Nick Hengartner [aut]
Maintainer: Jairo Diaz-Rodriguez <adjairo@uninorte.edu.co>
Repository: CRAN
Date/Publication: 2021-01-19 10:00:02 UTC

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New package MOSS with initial version 0.1.0
Package: MOSS
Title: Multi-Omic Integration via Sparse Singular Value Decomposition
Version: 0.1.0
Authors@R: c( person("Agustin", "Gonzalez-Reymundez", email = "agugonrey@gmail.com", role = c("aut","cre")), person("Alexander", "Grueneberg", email = "cran@agrueneberg.info", role = c("aut")), person("Ana", "Vazquez", email = "avazquez@msu.edu", role = c("ctb")))
Description: High dimensionality, noise and heterogeneity among samples and features challenge the omic integration task. Here we present an omic integration method based on sparse singular value decomposition (SVD) to deal with these limitations, by: a. obtaining the main axes of variation of the combined omics, b. imposing sparsity constraints at both subjects (rows) and features (columns) levels using Elastic Net type of shrinkage, and d. allowing both linear and non-linear projections (via t-Stochastic Neighbor Embedding) of the omic data to detect clusters in very convoluted data (Gonzalez-Reymundez & Vazquez, 2020) <doi:10.1038/s41598-020-65119-5>.
License: GPL-2
URL: https://github.com/agugonrey/MOSS
BugReports: https://github.com/agugonrey/MOSS/issues
Imports: cluster, dbscan, Rtsne, stats
Suggests: annotate, bigparallelr, bigstatsr, clValid, ComplexHeatmap, fpc, ggplot2, ggpmisc, ggthemes, gridExtra, irlba, knitr, MASS, rmarkdown, testthat, viridis
VignetteBuilder: knitr
Encoding: UTF-8
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2021-01-15 17:18:02 UTC; epibio
Author: Agustin Gonzalez-Reymundez [aut, cre], Alexander Grueneberg [aut], Ana Vazquez [ctb]
Maintainer: Agustin Gonzalez-Reymundez <agugonrey@gmail.com>
Repository: CRAN
Date/Publication: 2021-01-19 09:20:06 UTC

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New package httpgd with initial version 1.0.0
Package: httpgd
Type: Package
Title: A 'HTTP' Server Graphics Device
Version: 1.0.0
Authors@R: c( person(given = "Florian", family = "Rupprecht", email = "floruppr@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-1795-8624")), person(given = "Kun", family = "Ren", role = "ctb", email = "mail@renkun.me"), person("Jeroen", "Ooms", role = c("ctb"), email = "jeroen@berkeley.edu", comment = c(ORCID = "0000-0002-4035-0289")), person("Hadley", "Wickham", email = "hadley@rstudio.com", role = "cph", comment = "Author of included svglite code"), person("Lionel", "Henry", email = "lionel@rstudio.com", role = "cph", comment = "Author of included svglite code"), person("Thomas Lin", "Pedersen", email = "thomas.pedersen@rstudio.com", role = "cph", comment = "Author and creator of included svglite code"), person("T Jake", "Luciani", email = "jake@apache.org", role = "cph", comment = "Author of included svglite code"), person("Matthieu", "Decorde", email = "matthieu.decorde@ens-lyon.fr", role = "cph", comment = "Author of included svglite code"), person("Vaudor", "Lise", email = "lise.vaudor@ens-lyon.fr", role = "cph", comment = "Author of included svglite code"), person("Tony", "Plate", role = "cph", comment = "Contributor to included svglite code"), person("David", "Gohel", role = "cph", comment = "Contributor to included svglite code"), person("Yixuan", "Qiu", role = "cph", comment = "Contributor to included svglite code"), person("Håkon", "Malmedal", role = "cph", comment = "Contributor to included svglite code"), person("RStudio", role = "cph", comment = "Copyright holder of included svglite code"), person("Brett", "Robinson", role = "cph", comment = "Author of included belle library"), person("Google", role = "cph", comment = "Copyright holder of included material design icons"), person("Victor", "Zverovich", role = "cph", comment = "Author of included fmt library") )
Description: A graphics device for R that is accessible via network protocols. This package was created to make it easier to embed live R graphics in integrated development environments and other applications. The included 'HTML/JavaScript' client (plot viewer) aims to provide a better overall user experience when dealing with R graphics. The device asynchronously serves 'SVG' graphics via 'HTTP' and 'WebSockets'.
License: GPL (>= 2)
Depends: R (>= 4.0.0)
Imports: cpp11 (>= 0.2.4), later (>= 1.1.0), systemfonts (>= 0.2.3)
LinkingTo: cpp11, BH (>= 1.75.0), later, systemfonts
Suggests: testthat, xml2 (>= 1.0.0), fontquiver (>= 0.2.0)
RoxygenNote: 7.1.1
Encoding: UTF-8
SystemRequirements: C++17, libpng
URL: https://github.com/nx10/httpgd
BugReports: https://github.com/nx10/httpgd/issues
NeedsCompilation: yes
Packaged: 2021-01-15 16:58:31 UTC; floru
Author: Florian Rupprecht [aut, cre] (<https://orcid.org/0000-0002-1795-8624>), Kun Ren [ctb], Jeroen Ooms [ctb] (<https://orcid.org/0000-0002-4035-0289>), Hadley Wickham [cph] (Author of included svglite code), Lionel Henry [cph] (Author of included svglite code), Thomas Lin Pedersen [cph] (Author and creator of included svglite code), T Jake Luciani [cph] (Author of included svglite code), Matthieu Decorde [cph] (Author of included svglite code), Vaudor Lise [cph] (Author of included svglite code), Tony Plate [cph] (Contributor to included svglite code), David Gohel [cph] (Contributor to included svglite code), Yixuan Qiu [cph] (Contributor to included svglite code), Håkon Malmedal [cph] (Contributor to included svglite code), RStudio [cph] (Copyright holder of included svglite code), Brett Robinson [cph] (Author of included belle library), Google [cph] (Copyright holder of included material design icons), Victor Zverovich [cph] (Author of included fmt library)
Maintainer: Florian Rupprecht <floruppr@gmail.com>
Repository: CRAN
Date/Publication: 2021-01-19 09:10:02 UTC

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New package ccmReportR with initial version 0.0.2
Package: ccmReportR
Title: Wraps 'CCM' with Utility Functions
Version: 0.0.2
Authors@R: person(given = "James", family = "Lane", role = c("aut", "cre"), email = "lanejames35@gmail.com")
Description: Provides a set of functions to perform queries against the 'CCM' API <https://mohcontacttracing.my.salesforce.com>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Imports: dplyr (>= 1.0.2), httr (>= 1.4.2), jsonlite (>= 1.7.1), keyring (>= 1.1.0), lubridate (>= 1.7.9), purrr (>= 0.3.4)
NeedsCompilation: no
Packaged: 2021-01-15 14:41:52 UTC; lane_j
Author: James Lane [aut, cre]
Maintainer: James Lane <lanejames35@gmail.com>
Repository: CRAN
Date/Publication: 2021-01-19 09:40:05 UTC

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New package logitr with initial version 0.1.0
Package: logitr
Title: Logit Models w/Preference & WTP Space Utility Parameterizations
Version: 0.1.0
Authors@R: c( person(given = "John", family = "Helveston", role = c("aut", "cre", "cph"), email = "john.helveston@gmail.com", comment = c(ORCID = "0000-0002-2657-9191")))
Description: Estimation of multinomial (MNL) and mixed logit (MXL) models in R. Models can be estimated using "Preference" space or "Willingness-to-pay" (WTP) space utility parameterizations. An option is available to run a multistart optimization loop with random starting points in each iteration, which is useful for non-convex problems like MXL models or models with WTP space utility parameterizations. The main optimization loop uses the 'nloptr' package to minimize the negative log-likelihood function. Additional functions are available for computing and comparing WTP from both preference space and WTP space models and for simulating the expected shares of a set of alternatives using an estimated model. MXL models assume uncorrelated heterogeneity covariances and are estimated using maximum simulated likelihood based on the algorithms in Train (2009) "Discrete Choice Methods with Simulation, 2nd Edition" <doi:10.1017/CBO9780511805271>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
VignetteBuilder: knitr
Depends: R (>= 3.5.0)
Suggests: knitr, rmarkdown, here, ggplot2
Imports: nloptr, stats, randtoolbox, MASS
URL: https://github.com/jhelvy/logitr
BugReports: https://github.com/jhelvy/logitr/issues
NeedsCompilation: no
Packaged: 2021-01-15 13:02:49 UTC; jhelvy
Author: John Helveston [aut, cre, cph] (<https://orcid.org/0000-0002-2657-9191>)
Maintainer: John Helveston <john.helveston@gmail.com>
Repository: CRAN
Date/Publication: 2021-01-19 08:40:03 UTC

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New package feamiR with initial version 0.1.0
Package: feamiR
Type: Package
Title: Classification and Feature Selection for microRNA/mRNA Interactions
Version: 0.1.0
Authors@R: c(person(given = "Eleanor", family = "Williams", role = c("aut","cre"), email = "ecw63@cam.ac.uk"), person(given="Irina", family = "Mohorianu", role = c("aut"), email = "iim22@cam.ac.uk"))
Maintainer: Eleanor Williams <ecw63@cam.ac.uk>
Description: Comprises a pipeline for predicting microRNA/mRNA interactions, as detailed in Williams, Calinescu, Mohorianu (2020) <doi:10.1101/2020.12.23.424130>. Its input consists of [a] a messenger RNA (mRNA) dataset (either in fasta format, focused on 3' UTRs or in gtf format; for the latter, the sequences of the 3’ UTRs are generated using the genomic coordinates), [b] a microRNA dataset (in fasta format, retrieved from miRBase, <http://www.mirbase.org/>) and [c] an interaction dataset (in csv format, from miRTarBase <http://mirtarbase.cuhk.edu.cn/php/index.php>). To characterise and predict microRNA/mRNA interactions, we use [a] statistical analyses based on Chi-squared and Fisher exact tests and [b] Machine Learning classifiers (decision trees, random forests and support vector machines). To enhance the accuracy of the classifiers we also employ feature selection approaches used in on conjunction with the classifiers. The feature selection approaches include a voting scheme for decision trees, a measure based on Gini index for random forests, forward feature selection and Genetic Algorithms on SVMs. The pipeline also includes a novel approach based on embryonic Genetic Algorithms which combines and optimises the forward feature selection and Genetic Algorithms. All analyses, including the classification and feature selection, are applicable on the microRNA seed features (default), on the full microRNA features and/or flanking features on the mRNA. The sets of features can be combined.
Encoding: UTF-8
Depends: R (>= 3.1.2)
Imports: stringr, randomForest, rpart, rpart.plot, GA, e1071, ggplot2, magrittr, tibble, dplyr, reticulate
Config/reticulate: list( packages = list( list(package = "os"), list(package = "argparse"), list(package = "gzip"), list(package = "pandas"), list(package = "numpy"), list(package = "math"), list(package = "scipy.stats"), list(package = "matplotlib.pyplot"), list(package = "seaborn"), list(package = "statistics"), list(package = "logging"), list(package = "Bio") ) )
Suggests: parallel, doParallel
SystemRequirements: Python (>=3.6) sreformat patman
URL: https://github.com/Core-Bioinformatics/feamiR
BugReports: https://github.com/Core-Bioinformatics/feamiR/issues
LazyData: true
RoxygenNote: 7.1.1.9000
License: GPL-2
NeedsCompilation: no
Packaged: 2021-01-15 12:03:40 UTC; ecw63
Author: Eleanor Williams [aut, cre], Irina Mohorianu [aut]
Repository: CRAN
Date/Publication: 2021-01-19 08:30:02 UTC

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New package eemdTDNN with initial version 0.1.0
Package: eemdTDNN
Type: Package
Title: EEMD and Its Variant Based Time Delay Neural Network Model
Version: 0.1.0
Authors@R: c(person(given = "Kapil", family = "Choudhary", role = c("aut", "cre"), email = "choudharykapil832@gmail.com"), person(given = "Girish Kumar", family = "Jha", role = c("aut", "ths", "ctb")), person(given = "Rajeev Ranjan", family = "Kumar", role = c("aut", "ctb")), person(given = "Ronit", family = "Jaiswal", role = "ctb"))
Maintainer: Kapil Choudhary <choudharykapil832@gmail.com>
Description: Forecasting univariate time series with different decomposition based time delay neural network models. For method details see Yu L, Wang S, Lai KK (2008). <doi:10.1016/j.eneco.2008.05.003>.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Imports: forecast, Rlibeemd
Depends: R (>= 2.10)
NeedsCompilation: no
Packaged: 2021-01-15 13:53:56 UTC; Rajeev-PC
Author: Kapil Choudhary [aut, cre], Girish Kumar Jha [aut, ths, ctb], Rajeev Ranjan Kumar [aut, ctb], Ronit Jaiswal [ctb]
Repository: CRAN
Date/Publication: 2021-01-19 09:00:02 UTC

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Mon, 18 Jan 2021

New package AzureCosmosR with initial version 1.0.0
Package: AzureCosmosR
Title: Interface to the 'Azure Cosmos DB' 'NoSQL' Database Service
Version: 1.0.0
Authors@R: c( person("Hong", "Ooi", , "hongooi73@gmail.com", role=c("aut", "cre")), person("Andrew", "Liu", role="ctb", comment="Assistance with Cosmos DB"), person("Microsoft", role="cph") )
Description: An interface to 'Azure CosmosDB': <https://azure.microsoft.com/en-us/services/cosmos-db/>. On the admin side, 'AzureCosmosR' provides functionality to create and manage 'Cosmos DB' instances in Microsoft's 'Azure' cloud. On the client side, it provides an interface to the 'Cosmos DB' SQL API, letting the user store and query documents and attachments in 'Cosmos DB'. Part of the 'AzureR' family of packages.
URL: https://github.com/Azure/AzureCosmosR https://github.com/Azure/AzureR
BugReports: https://github.com/Azure/AzureCosmosR/issues
License: MIT + file LICENSE
VignetteBuilder: knitr
Depends: R (>= 3.3)
Imports: utils, AzureRMR (>= 2.3.3), curl, openssl, jsonlite, httr, uuid, vctrs (>= 0.3.0)
Suggests: AzureTableStor, mongolite, DBI, odbc, dplyr, testthat, knitr, rmarkdown
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2021-01-18 21:39:24 UTC; hongo
Author: Hong Ooi [aut, cre], Andrew Liu [ctb] (Assistance with Cosmos DB), Microsoft [cph]
Maintainer: Hong Ooi <hongooi73@gmail.com>
Repository: CRAN
Date/Publication: 2021-01-18 23:50:05 UTC

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New package RAEN with initial version 0.1
Package: RAEN
Title: Random Approximate Elastic Net (RAEN) Variable Selection Method
Version: 0.1
Encoding: UTF-8
Description: The Proportional Subdistribution Hazard (PSH) model has been popular for estimating the effects of the covariates on the cause of interest in Competing Risks analysis. The fast accumulation of large scale datasets has posed a challenge to classical statistical methods. Current penalized variable selection methods show unsatisfactory performance in ultra-high dimensional data. We propose a novel method, the Random Approximate Elastic Net (RAEN), with a robust and generalized solution to the variable selection problem for the PSH model. Our method shows improved sensitivity for variable selection compared with current methods.
Author: Han Sun and Xiaofeng Wang
Maintainer: Han Sun <han.sunny@gmail.com>
URL: https://github.com/saintland/RAEN
Imports: boot, foreach, doParallel,glmnet, fastcmprsk
Depends: R(>= 3.5.0), lars
Suggests: testthat, knitr, rmarkdown
License: GPL (>= 2)
RoxygenNote: 7.1.0
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-01-15 06:23:38 UTC; sunh
Repository: CRAN
Date/Publication: 2021-01-18 16:50:15 UTC

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New package partR2 with initial version 0.9.1
Package: partR2
Title: Partitioning R2 in GLMMs
Version: 0.9.1
Depends: R (>= 3.5.0)
Authors@R: c(person(given = "Martin A.", family = "Stoffel", role = c("aut", "cre"), email = "martin.adam.stoffel@gmail.com"), person(given = "Shinichi", family = "Nakagawa", role = c("aut"), email = "s.nakagawa@unsw.edu.au"), person(given = "Holger", family = "Schielzeth", role = c("aut"), email = "holger.schielzeth@uni-jena.de"))
Description: Partitioning the R2 of GLMMs into variation explained by each predictor and combination of predictors using semi-partial (part) R2 and inclusive R2. Methods are based on the R2 for GLMMs described in Nakagawa & Schielzeth (2013) <doi:10.1111/j.2041-210x.2012.00261.x> and Nakagawa, Johnson & Schielzeth (2017) <doi:10.1098/rsif.2017.0213>.
License: GPL (>= 2)
URL: https://github.com/mastoffel/partR2
BugReports: https://github.com/mastoffel/partR2/issues
Imports: methods, stats, lme4 (>= 1.1-21), pbapply (>= 1.4-2), dplyr (>= 0.8.3), purrr (>= 0.3.3), rlang (>= 0.4.2), tibble (>= 2.1.3), magrittr (>= 1.5), ggplot2 (>= 3.3.0), tidyr (>= 1.1)
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Suggests: testthat, future, furrr, knitr, rmarkdown, patchwork, covr
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-01-14 18:45:39 UTC; mstoffel
Author: Martin A. Stoffel [aut, cre], Shinichi Nakagawa [aut], Holger Schielzeth [aut]
Maintainer: Martin A. Stoffel <martin.adam.stoffel@gmail.com>
Repository: CRAN
Date/Publication: 2021-01-18 16:30:04 UTC

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New package panelr with initial version 0.7.5
Package: panelr
Title: Regression Models and Utilities for Repeated Measures and Panel Data
Version: 0.7.5
Authors@R: person("Jacob A.", "Long", email = "jacob.long@sc.edu", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-1582-6214"))
Description: Provides an object type and associated tools for storing and wrangling panel data. Implements several methods for creating regression models that take advantage of the unique aspects of panel data. Among other capabilities, automates the "within-between" (also known as "between-within" and "hybrid") panel regression specification that combines the desirable aspects of both fixed effects and random effects econometric models and fits them as multilevel models (Allison, 2009 <doi:10.4135/9781412993869.d33>; Bell & Jones, 2015 <doi:10.1017/psrm.2014.7>). These models can also be estimated via generalized estimating equations (GEE; McNeish, 2019 <doi:10.1080/00273171.2019.1602504>) and Bayesian estimation is (optionally) supported via 'Stan'. Supports estimation of asymmetric effects models via first differences (Allison, 2019 <doi:10.1177/2378023119826441>) as well as a generalized linear model extension thereof using GEE.
URL: https://panelr.jacob-long.com
BugReports: https://github.com/jacob-long/panelr
Depends: R (>= 3.4.0), lme4
Imports: crayon, dplyr, Formula, ggplot2, jtools (>= 2.0.1), lmerTest, magrittr, methods, purrr, rlang (>= 0.3.0), stringr, tibble (>= 2.0.0)
Suggests: brms, broom.mixed, car, clubSandwich, geepack, generics, nlme, plm, sandwich, skimr, tidyr (>= 0.8.3), testthat, covr, knitr, rmarkdown
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-01-18 04:00:06 UTC; jacoblong
Author: Jacob A. Long [aut, cre] (<https://orcid.org/0000-0002-1582-6214>)
Maintainer: Jacob A. Long <jacob.long@sc.edu>
Repository: CRAN
Date/Publication: 2021-01-18 17:00:02 UTC

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New package memify with initial version 0.1.1
Package: memify
Type: Package
Title: Constructing Functions That Keep State
Version: 0.1.1
Author: Bert Gunter
Maintainer: Bert Gunter <bgunter.4567@gmail.com>
Description: A simple way to construct and maintain functions that keep state i.e. remember their argument lists. This can be useful when one needs to repeatedly invoke the same function with only a small number of argument changes at each invocation.
Depends: R (>= 4.0)
Imports: utils
License: GPL-3
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2021-01-14 20:39:19 UTC; bgunter
Repository: CRAN
Date/Publication: 2021-01-18 16:40:09 UTC

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New package Inflect with initial version 1.0.3
Package: Inflect
Type: Package
Title: Melt Curve Fitting and Melt Shift Analysis
Version: 1.0.3
Authors@R: c(person("Neil", "McCracken", email = "namccrac@iu.edu",role = c("aut")), person("Aruna", "Wijeratne", role = c("ctb")), person("Amber", "Mosley", email = "almosley@iu.edu",role = c("cre")))
Description: This program analyzes raw abundance data from a cellular thermal shift experiment and calculates melt temperatures and melt shifts for each protein in the experiment. Reference to software development can be found at <doi:10.1101/2020.10.31.363523>.
License: GPL-2
Encoding: UTF-8
LazyData: true
Imports: readxl, writexl, optimr, data.table, plotrix, tidyr, ggplot2
Suggests: knitr, rmarkdown,
VignetteBuilder: knitr
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2021-01-15 00:45:13 UTC; namccrac
Config/testthat/edition: 3
Author: Neil McCracken [aut], Aruna Wijeratne [ctb], Amber Mosley [cre]
Maintainer: Amber Mosley <almosley@iu.edu>
Repository: CRAN
Date/Publication: 2021-01-18 16:40:12 UTC

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New package GSDA with initial version 1.0
Package: GSDA
Type: Package
Title: Gene Set Distance Analysis (GSDA)
Version: 1.0
Date: 2021-01-014
Authors@R: c(person("Xueyuan", "Cao", email = "xcao12@uthsc.edu", role = c("aut", "cre")), person("Stanley", "Pounds", email = "stanley.pounds@stjude.org", role = c("aut")))
Description: The gene-set distance analysis of omic data is implemented by generalizing distance correlations to evaluate the association of a gene set with categorical and censored event-time variables.
Depends: R (>= 3.5.0),msigdbr
License: GPL (>= 2)
biocViews: Microarray, Bioinformatics, Gene expression
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
LazyLoad: yes
NeedsCompilation: no
Packaged: 2021-01-14 17:30:56 UTC; xcao12
Author: Xueyuan Cao [aut, cre], Stanley Pounds [aut]
Maintainer: Xueyuan Cao <xcao12@uthsc.edu>
Repository: CRAN
Date/Publication: 2021-01-18 16:20:27 UTC

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New package bigmds with initial version 0.0.1
Package: bigmds
Title: Multidimensional Scaling for Big Data
Version: 0.0.1
Authors@R: c( person(given = "Cristian", family = "Pachón García", role = c("aut", "cre"), email = "cc.pachon@gmail.com", comment = c(ORCID = "0000-0001-9518-4874")), person(given = "Pedro", family = "Delicado", role = c("aut"), email = "pedro.delicado@upc.edu", comment = c(ORCID = "0000-0003-3933-4852")) )
Description: We present a set of algorithms for Multidimensional Scaling (MDS) to be used with large datasets. MDS is a statistic tool for reduction of dimensionality, using as input a distance matrix of dimensions n × n. When n is large, classical algorithms suffer from computational problems and MDS configuration can not be obtained. With this package, we address these problems by means of three algorithms: Divide and Conquer MDS, Fast MDS and MDS based on Gower interpolation. The main idea of these methods is based on partitioning the dataset into small pieces, where classical methods can work.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Imports: MCMCpack, stats, pdist
Suggests: testthat (>= 3.0.0)
Config/testthat/edition: 3
URL: https://github.com/pachoning/bigmds
BugReports: https://github.com/pachoning/bigmds/issues
NeedsCompilation: no
Packaged: 2021-01-14 17:39:05 UTC; cristianpachongarcia
Author: Cristian Pachón García [aut, cre] (<https://orcid.org/0000-0001-9518-4874>), Pedro Delicado [aut] (<https://orcid.org/0000-0003-3933-4852>)
Maintainer: Cristian Pachón García <cc.pachon@gmail.com>
Repository: CRAN
Date/Publication: 2021-01-18 16:20:10 UTC

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New package sims with initial version 0.0.2
Package: sims
Title: Simulate Data from R or 'JAGS' Code
Version: 0.0.2
Authors@R: c(person(given = "Audrey", family = "Beliveau", role = "aut", email = "audrey.beliveau@uwaterloo.ca"), person(given = "Joe", family = "Thorley", role = c("aut", "cre"), email = "joe@poissonconsulting.ca", comment = c(ORCID = "0000-0002-7683-4592")))
Description: Generates data from R or 'JAGS' code for use in simulation studies. The data are returned as an 'nlist::nlists' object and/or saved to file as individual '.rds' files. Parallelization is implemented using the 'future' package. Progress is reported using the 'progressr' package.
License: MIT + file LICENSE
Depends: R (>= 3.6)
Imports: chk, future.apply, nlist, parallel, stats, yesno
Suggests: covr, future, knitr, progressr, rjags, rmarkdown, testthat
VignetteBuilder: knitr
Encoding: UTF-8
Language: en-US
LazyData: true
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2021-01-14 15:52:52 UTC; joe
Author: Audrey Beliveau [aut], Joe Thorley [aut, cre] (<https://orcid.org/0000-0002-7683-4592>)
Maintainer: Joe Thorley <joe@poissonconsulting.ca>
Repository: CRAN
Date/Publication: 2021-01-18 15:50:02 UTC

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New package spNetwork with initial version 0.1.0
Package: spNetwork
Type: Package
Title: Spatial Analysis on Network
Version: 0.1.0
Authors@R: c( person("Jeremy", "Gelb", email = "jeremy.gelb@ucs.inrs.ca",role = c("aut", "cre")), person("Philippe", "Apparicio", email="philippe.apparicio@ucs.inrs.ca", role=c("ctb")))
Description: Perform spatial analysis on network. Allow to calculate Network Kernel Density Estimate, and to build spatial matrices ('listw' objects like in 'spdep' package) to conduct any kind of traditional spatial analysis with spatial weights based on reticular distances. K functions on network are also available but still experimental. References: Okabe et al (2019) <doi:10.1080/13658810802475491>; Okabe et al (2012, ISBN:978-0470770818);Baddeley el al (2015, ISBN:9781482210200).
License: GPL-2
Encoding: UTF-8
LazyData: true
Imports: spdep (>= 1.1.2), maptools (>= 0.9-5), rgeos (>= 0.5-2), sp (>= 1.3-1), sf (>= 0.9-0), raster (>= 3.0-12), igraph (>= 1.2.4.2), cubature (>= 2.0.4.1), future.apply (>= 1.4.0), methods (>= 1.7.1), ggplot2 (>= 3.3.0), progressr (>= 0.4.0), data.table (>= 1.12.8), SearchTrees (>= 0.5.2), Rcpp (>= 1.0.4.6)
Depends: R (>= 3.6)
Suggests: future (>= 1.16.0), testthat (>= 3.0.0), knitr (>= 1.28), kableExtra (>= 1.1.0), rmarkdown (>= 2.1), RColorBrewer (>= 1.1-2), classInt (>= 0.4-3), reshape2 (>= 1.4.3), dplyr (>= 0.8.3), rlang (>= 0.4.6), rgdal (>= 1.5-18), plot3D (>= 1.3)
RoxygenNote: 7.1.1
VignetteBuilder: knitr
URL: https://github.com/JeremyGelb/spNetwork
BugReports: https://github.com/JeremyGelb/spNetwork/issues
LinkingTo: Rcpp, RcppProgress, RcppArmadillo
SystemRequirements: C++11
NeedsCompilation: yes
Packaged: 2021-01-14 14:32:32 UTC; gelbj
Author: Jeremy Gelb [aut, cre], Philippe Apparicio [ctb]
Maintainer: Jeremy Gelb <jeremy.gelb@ucs.inrs.ca>
Repository: CRAN
Date/Publication: 2021-01-18 10:10:07 UTC

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New package aghq with initial version 0.1.0
Package: aghq
Type: Package
Title: Adaptive Gauss Hermite Quadrature for Bayesian Inference
Version: 0.1.0
Author: Alex Stringer
Maintainer: Alex Stringer <alex.stringer@mail.utoronto.ca>
Description: Adaptive Gauss Hermite Quadrature for Bayesian inference. The AGHQ method for normalizing posterior distributions and making Bayesian inferences based on them. Functions are provided for doing quadrature and marginal Laplace approximations, and summary methods are provided for making inferences based on the results. See Stringer (2021). "Implementing Adaptive Quadrature for Bayesian Inference: the aghq Package" <arXiv:2101.04468>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Depends: R (>= 3.5.0)
Imports: methods, mvQuad, matrixStats, Matrix, stringr, magrittr, dplyr, tidyr, tidyselect, rlang, polynom, tibble, purrr
Suggests: trustOptim, trust, numDeriv, testthat (>= 2.1.0), knitr, rmarkdown, ggplot2
VignetteBuilder: knitr
Language: en-US
NeedsCompilation: no
Packaged: 2021-01-14 14:59:42 UTC; alexstringer
Repository: CRAN
Date/Publication: 2021-01-18 10:30:02 UTC

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New package torchaudio with initial version 0.1.1.0
Package: torchaudio
Title: R Interface to 'pytorch''s 'torchaudio'
Version: 0.1.1.0
Authors@R: c( person(given = "Athos", family = "Damiani", role = c("aut", "cre"), email = "athos.damiani@gmail.com" ) )
Description: Provides access to datasets, models and preprocessing facilities for deep learning in audio.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Suggests: testthat, monitoR, tuneR, knitr, rmarkdown, stringr, numbers, purrr, scales, httr, viridis
Imports: torch (>= 0.2.0), fs, rlang, rappdirs, utils, tools, glue
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-01-14 14:08:35 UTC; athos
Author: Athos Damiani [aut, cre]
Maintainer: Athos Damiani <athos.damiani@gmail.com>
Repository: CRAN
Date/Publication: 2021-01-18 10:00:02 UTC

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New package parallelPlot with initial version 0.1.0
Package: parallelPlot
Title: 'Htmlwidget' for a Parallel Coordinates Plot
Version: 0.1.0
Authors@R: c( person("Mike", "Bostock", role = c("aut", "cph"), comment = "d3.js library in htmlwidgets/lib, http://d3js.org"), person("David", "Chazalviel", email = "david.chazalviel@club-internet.fr", role = c("aut", "cre")), person("Benoit", "Lehman", email = "benoit.lehman@tech-advantage.com", role = c("aut")) )
Description: Create a parallel coordinates plot, using 'htmlwidgets' package and 'd3.js'.
URL: https://gitlab.com/drti/parallelplot
BugReports: https://gitlab.com/drti/parallelplot/-/issues
Depends: R (>= 3.5.0)
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Imports: htmlwidgets
Suggests: testthat, shiny, knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-01-14 11:02:53 UTC; cuckooland
Author: Mike Bostock [aut, cph] (d3.js library in htmlwidgets/lib, http://d3js.org), David Chazalviel [aut, cre], Benoit Lehman [aut]
Maintainer: David Chazalviel <david.chazalviel@club-internet.fr>
Repository: CRAN
Date/Publication: 2021-01-18 09:10:03 UTC

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New package noah with initial version 0.1.0
Package: noah
Title: Create Unique Pseudonymous Animal Names
Version: 0.1.0
Authors@R: person(given = "Tobias", family = "Busch", role = c("aut", "cre"), email = "teebusch@gmail.com", comment = c(ORCID = "https://orcid.org/0000-0002-8390-7892"))
Description: Generate pseudonymous animal names that are delightful and easy to remember like the Likable Leech and the Proud Chickadee. A unique pseudonym can be created for every unique element in a vector or row in a data frame. Pseudonyms can be customized and tracked over time, so that the same input is always assigned the same pseudonym.
License: MIT + file LICENSE
Suggests: testthat, covr
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
URL: https://github.com/Teebusch/noah
BugReports: https://github.com/Teebusch/noah/issues
Imports: R6, hash, digest, assertthat, purrr, dplyr, magrittr, crayon, rlang, stringr
Depends: R (>= 3.1.0)
NeedsCompilation: no
Packaged: 2021-01-14 10:47:54 UTC; teebu
Author: Tobias Busch [aut, cre] (<https://orcid.org/0000-0002-8390-7892>)
Maintainer: Tobias Busch <teebusch@gmail.com>
Repository: CRAN
Date/Publication: 2021-01-18 09:10:06 UTC

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New package kittyR with initial version 1.0.0
Type: Package
Package: kittyR
Title: Kitty Pictures and Meows from R Console
Version: 1.0.0
Authors@R: person(given = "Indrajeet", family = "Patil", role = c("aut", "cre", "cph"), email = "patilindrajeet.science@gmail.com", comment = c(ORCID = "0000-0003-1995-6531", Twitter = "@patilindrajeets"))
Maintainer: Indrajeet Patil <patilindrajeet.science@gmail.com>
Description: Get pictures of cats and their meows from your R console.
License: MIT + file LICENSE
URL: https://github.com/IndrajeetPatil/kittyR
BugReports: https://github.com/IndrajeetPatil/kittyR/issues
Depends: R (>= 3.6.0)
Imports: beepr, dplyr, graphics, imager, magrittr, purrr, rvest, stringr, tibble
Suggests: spelling, testthat
Encoding: UTF-8
Language: en-US
LazyData: true
RoxygenNote: 7.1.1
Config/testthat/edition: 3
Config/testthat/parallel: true
NeedsCompilation: no
Packaged: 2021-01-14 12:11:24 UTC; inp099
Author: Indrajeet Patil [aut, cre, cph] (<https://orcid.org/0000-0003-1995-6531>, @patilindrajeets)
Repository: CRAN
Date/Publication: 2021-01-18 09:30:02 UTC

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New package geysertimes with initial version 0.1.2
Package: geysertimes
Title: Geyser Data from GeyserTimes.org
Version: 0.1.2
Imports: jsonlite, lubridate, rappdirs, readr, tools, utils
Suggests: curl, dplyr, knitr, rmarkdown
Authors@R: person(given = "Stephen", family = "Kaluzny", role = c("aut", "cre"), email = "spkaluzny@gmail.com")
Description: Download geyser eruption and observation data from the GeyserTimes site (<https://geysertimes.org>) and optionally store it locally. The vignette shows the a simple analysis of downloading, accessing, and summarizing the data.
License: MIT + file LICENSE
URL: https://github.com/geysertimes/geysertimes-r-package
BugReports: https://github.com/geysertimes/geysertimes-r-package/issues
VignetteBuilder: knitr, rmarkdown
LazyData: yes
NeedsCompilation: no
Packaged: 2021-01-13 17:14:28 UTC; spk
Author: Stephen Kaluzny [aut, cre]
Maintainer: Stephen Kaluzny <spkaluzny@gmail.com>
Repository: CRAN
Date/Publication: 2021-01-18 09:00:02 UTC

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New package coder with initial version 0.13.5
Package: coder
Type: Package
Title: Deterministic Categorization of Items Based on External Code Data
Version: 0.13.5
Authors@R: c( person("Erik", "Bulow", email = "eriklgb@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-9973-456X")), person("Emely C", "Zabore", role = "rev", comment = "Emily reviewed the package (v. 0.12.1) for rOpenSci, see <https://github.com/ropensci/software-review/issues/381>"), person("David", "Robinson", role = "rev", comment = "David reviewed the package (v. 0.12.1) for rOpenSci, see <https://github.com/ropensci/software-review/issues/381>") )
Description: Fast categorization of items based on external code data identified by regular expressions. A typical use case considers patient with medically coded data, such as codes from the International Classification of Diseases ('ICD') or the Anatomic Therapeutic Chemical ('ATC') classification system. Functions of the package relies on a triad of objects: (1) case data with unit id:s and possible dates of interest; (2) external code data for corresponding units in (1) and with optional dates of interest and; (3) a classification scheme ('classcodes' object) with regular expressions to identify and categorize relevant codes from (2). It is easy to introduce new classification schemes ('classcodes' objects) or to use default schemes included in the package. Use cases includes patient categorization based on 'comorbidity indices' such as 'Charlson', 'Elixhauser', 'RxRisk V', or the 'comorbidity-polypharmacy' score (CPS), as well as adverse events after hip and knee replacement surgery.
License: GPL-2
Depends: R (>= 3.3)
Suggests: covr, testthat, knitr, rmarkdown, writexl
Imports: data.table, decoder, generics, methods, tibble
LazyData: TRUE
RoxygenNote: 7.1.1
VignetteBuilder: knitr
URL: https://docs.ropensci.org/coder/
BugReports: https://github.com/ropensci/coder/issues
Encoding: UTF-8
Language: en-US
NeedsCompilation: no
Packaged: 2021-01-14 10:07:41 UTC; erikbulow
Author: Erik Bulow [aut, cre] (<https://orcid.org/0000-0002-9973-456X>), Emely C Zabore [rev] (Emily reviewed the package (v. 0.12.1) for rOpenSci, see <https://github.com/ropensci/software-review/issues/381>), David Robinson [rev] (David reviewed the package (v. 0.12.1) for rOpenSci, see <https://github.com/ropensci/software-review/issues/381>)
Maintainer: Erik Bulow <eriklgb@gmail.com>
Repository: CRAN
Date/Publication: 2021-01-18 09:00:05 UTC

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New package cecs with initial version 0.1.0
Package: cecs
Title: R Interface for the C Implementation of CEC Benchmark Functions
Version: 0.1.0
Authors@R: c( person("Eryk", "Warchulski", role = c("aut", "cre"), email = "ewarchul@gmail.com"), person("Dariusz", "Jagodziński", role = c("cph"), email = "d.jagodzinski@elka.pw.edu.pl"), person("Yasser", "Gonzalez-Fernandez", role = c("cph"), email = "yasser@yassergonzalez.com"), person("Mauricio", "Zambrano-Bigiarini", role = c("cph"), email = "mzb.devel@gmail.com") )
Description: Goal of this package is to provide access to benchmark functions defined for the Special Session and Competition on Real-Parameter Single Objective Optimization in one place. The package contains functions from following years: 2013, 2014, 2017, 2021 (<https://github.com/P-N-Suganthan>). Implementations of CEC-2013 (Y. Gonzalez-Fernandez & M. Zambrano-Bigiarini) and CEC2017 (D. Jagodziński) are taken from existed R packages. Also, the original C source code has been cleaned and reorganized for better readability.
License: GPL (>= 3)
BugReports: https://github.com/ewarchul/cecs/issues
URL: https://github.com/ewarchul/cecs
Depends: R (>= 3.6.0)
Imports: stringr (>= 1.4.0)
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Suggests: testthat (>= 3.0.0), purrr (>= 0.3.4)
Config/testthat/edition: 3
NeedsCompilation: yes
Packaged: 2021-01-13 19:40:41 UTC; ewarchul
Author: Eryk Warchulski [aut, cre], Dariusz Jagodziński [cph], Yasser Gonzalez-Fernandez [cph], Mauricio Zambrano-Bigiarini [cph]
Maintainer: Eryk Warchulski <ewarchul@gmail.com>
Repository: CRAN
Date/Publication: 2021-01-18 08:40:02 UTC

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New package cachem with initial version 1.0.0
Package: cachem
Version: 1.0.0
Title: Cache R Objects with Automatic Pruning
Description: Key-value stores with automatic pruning. Caches can limit either their total size or the age of the oldest object (or both), automatically pruning objects to maintain the constraints.
Authors@R: c( person("Winston", "Chang", , "winston@rstudio.com", c("aut", "cre")), person(family = "RStudio", role = c("cph", "fnd")))
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
ByteCompile: true
URL: https://cachem.r-lib.org/, https://github.com/r-lib/cachem
Imports: rlang, fastmap
Suggests: testthat
RoxygenNote: 7.1.1
NeedsCompilation: yes
Packaged: 2021-01-13 20:52:01 UTC; winston
Author: Winston Chang [aut, cre], RStudio [cph, fnd]
Maintainer: Winston Chang <winston@rstudio.com>
Repository: CRAN
Date/Publication: 2021-01-18 08:50:02 UTC

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Sat, 16 Jan 2021

New package thematic with initial version 0.1.1
Package: thematic
Title: Unified and Automatic 'Theming' of 'ggplot2', 'lattice', and 'base' R Graphics
Version: 0.1.1
Authors@R: c( person("Carson", "Sievert", role = c("aut", "cre"), email = "carson@rstudio.com", comment = c(ORCID = "0000-0002-4958-2844")), person("Barret", "Schloerke", email = "barret@rstudio.com", role = "aut", comment = c(ORCID = "0000-0001-9986-114X")), person("Joe", "Cheng", role = "aut", email = "joe@rstudio.com"), person(family = "RStudio", role = "cph") )
Description: Theme 'ggplot2', 'lattice', and 'base' graphics based on a few choices, including foreground color, background color, accent color, and font family. Fonts that aren't available on the system, but are available via download on 'Google Fonts', can be automatically downloaded, cached, and registered for use with the 'showtext' and 'ragg' packages.
URL: https://rstudio.github.io/thematic/, https://github.com/rstudio/thematic#readme
Depends: R (>= 3.0.0)
Imports: utils, graphics, grDevices, grid, farver, rlang, scales, rstudioapi (>= 0.8), rappdirs, ggplot2 (>= 3.3.0)
Suggests: lattice, stats, withr, sysfonts, showtext, Cairo, systemfonts, ragg, knitr, rmarkdown, htmltools, shiny (>= 1.5.0), testthat, vdiffr, svglite, jsonlite, curl
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Collate: 'auto.R' 'base.R' 'cache.R' 'gfonts.R' 'ggplot.R' 'globals.R' 'hooks.R' 'imports.R' 'knitr.R' 'lattice.R' 'onLoad.R' 'thematic-save-plot.R' 'thematic.R' 'utils.R' 'view-shinytest.R'
NeedsCompilation: no
Packaged: 2021-01-15 22:16:59 UTC; cpsievert
Author: Carson Sievert [aut, cre] (<https://orcid.org/0000-0002-4958-2844>), Barret Schloerke [aut] (<https://orcid.org/0000-0001-9986-114X>), Joe Cheng [aut], RStudio [cph]
Maintainer: Carson Sievert <carson@rstudio.com>
Repository: CRAN
Date/Publication: 2021-01-16 10:30:02 UTC

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New package eltr with initial version 0.1.0
Package: eltr
Title: Utilise Catastrophe Model Event Loss Table Outputs
Version: 0.1.0
Authors@R: person(given = "Randhir", family = "Bilkhu", role = c("aut", "cre"), email = "rbilkhu7@gmail.com")
Description: Provides a tool to run Monte Carlo simulation of catastrophe model event loss tables, using a Poisson frequency and Beta severity distribution.
License: LGPL (>= 2.1)
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Suggests: testthat, covr, knitr, rmarkdown
Imports: data.table
VignetteBuilder: knitr
Depends: R (>= 2.10)
URL: https://randhirbilkhu.github.io/eltr/, https://github.com/RandhirBilkhu/eltr
BugReports: https://github.com/RandhirBilkhu/eltr/issues
NeedsCompilation: no
Packaged: 2021-01-13 20:17:23 UTC; randz
Author: Randhir Bilkhu [aut, cre]
Maintainer: Randhir Bilkhu <rbilkhu7@gmail.com>
Repository: CRAN
Date/Publication: 2021-01-16 10:20:02 UTC

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New package visae with initial version 0.1.0
Package: visae
Type: Package
Title: Visualization of Adverse Events
Version: 0.1.0
Authors@R: c(person("Marcio A. Diniz", role = c("aut", "cre","cph"), email = "marcio.diniz@cshs.org"), person("Michael Luu", role = "aut"))
Description: Implementation of Shiny app to visualize adverse events based on the Common Terminology Criteria for Adverse Events using stacked correspondence analysis as described in Diniz et. al (2021) <arXiv:2101.03454>.
BugReports: https://github.com/dnzmarcio/visae/issues
License: GPL (>= 2)
Depends: shiny (>= 1.4.0), dplyr (>= 1.0.0), ggplot2 (>= 3.3.0), magrittr (>= 1.5.0)
Imports: shinyjs (>= 1.1), ca (>= 0.71), tidyr (>= 1.1.0), ggrepel (>= 0.8.2), rlang (>= 0.4.6), DT (>= 0.13)
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2021-01-12 17:39:45 UTC; DinizMA
Author: Marcio A. Diniz [aut, cre, cph], Michael Luu [aut]
Maintainer: Marcio A. Diniz <marcio.diniz@cshs.org>
Repository: CRAN
Date/Publication: 2021-01-16 09:40:02 UTC

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New package SkeweDF with initial version 0.1.0
Package: SkeweDF
Title: Optimization of Skewed Distributions with Birth-Death Processes
Version: 0.1.0
Authors@R: person(given = "Andre", family = "Grageda", role = c("aut", "cre"), email = "gragedaa@upstate.edu")
Description: Implementations of models which follow the Kolmogorov Birth-Death process framework and functions which utilize these Kolmogorov Birth-Death process models for analysis of skewed distribution functions.
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: Rcpp (>= 1.0.5), dplyr (>= 1.0.2), parallel (>= 3.6.3), zipfR (>= 0.6-66), optimr (>= 2019-12.4), purrr (>= 0.3.4), matrixStats (>= 0.56.0), stringr (>= 1.4.0), methods (>= 3.6.3), grDevices (>= 3.6.3), graphics (>= 3.6.3), utils (>= 3.6.3)
RoxygenNote: 7.1.1
LinkingTo: Rcpp
NeedsCompilation: yes
Packaged: 2021-01-11 18:51:53 UTC; grage
Author: Andre Grageda [aut, cre]
Maintainer: Andre Grageda <gragedaa@upstate.edu>
Repository: CRAN
Date/Publication: 2021-01-16 09:40:05 UTC

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Fri, 15 Jan 2021

New package SpatMCA with initial version 1.0.2.0
Package: SpatMCA
Type: Package
Title: Regularized Spatial Maximum Covariance Analysis
Version: 1.0.2.0
Date: 2021-01-06
URL: https://github.com/egpivo/SpatMCA
BugReports: https://github.com/egpivo/SpatMCA/issues
Description: Provide regularized maximum covariance analysis incorporating smoothness, sparseness and orthogonality of couple patterns by using the alternating direction method of multipliers algorithm. The method can be applied to either regularly or irregularly spaced data, including 1D, 2D, and 3D (Wang and Huang, 2017 <doi:10.1002/env.2481>).
License: GPL-2
Imports: Rcpp, RcppParallel (>= 0.11.2), fields, MASS
LinkingTo: Rcpp, RcppArmadillo, RcppParallel
Suggests: testthat (>= 2.1.0), RColorBrewer, plot3D, pracma, spTimer, maps
SystemRequirements: GNU make
NeedsCompilation: yes
Author: Wen-Ting Wang [aut, cre], Hsin-Cheng Huang [aut]
Maintainer: Wen-Ting Wang <egpivo@gmail.com>
Encoding: UTF-8
RoxygenNote: 7.1.1
Packaged: 2021-01-12 14:31:12 UTC; wen-tingwang
Repository: CRAN
Date/Publication: 2021-01-16 00:50:08 UTC

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New package GLMcat with initial version 0.1.1
Package: GLMcat
Title: Generalized Linear Models for Categorical Responses
Version: 0.1.1
Authors@R: c(person(given = "Lorena", family = "León",role = c("aut", "cre"), email = "ylorenaleonv@gmail.com"), person(given = "Jean", family = "Peyhardi", email = "jean.peyhardi@umontpellier.fr", role = "aut"), person(given = "Catherine", family = "Trottier", email = "catherine.trottier@umontpellier.fr", role = "aut"))
Description: In statistical modeling, there is a wide variety of regression models for categorical dependent variables (nominal or ordinal data); yet, there is no software embracing all these models together in a uniform and generalized format. Following the methodology proposed by Peyhardi, Trottier, and Guédon (2015) <doi:10.1093/biomet/asv042>, we introduce 'GLMcat', an R package to estimate generalized linear models implemented under the unified specification (r, F, Z). Where r represents the ratio of probabilities (reference, cumulative, adjacent, or sequential), F the cumulative distribution function for the linkage, and Z, the design matrix.
License: GPL-3
Encoding: UTF-8
Depends: R (>= 2.10)
LazyData: true
RoxygenNote: 7.0.2
LinkingTo: Rcpp, BH, RcppEigen
Imports: Rcpp, stats
Suggests: knitr, rmarkdown, testthat, dplyr, ggplot2, gridExtra, gtools, tidyr
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2021-01-12 22:07:45 UTC; leonvelasco
Author: Lorena León [aut, cre], Jean Peyhardi [aut], Catherine Trottier [aut]
Maintainer: Lorena León <ylorenaleonv@gmail.com>
Repository: CRAN
Date/Publication: 2021-01-16 00:50:11 UTC

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New package extRatum with initial version 1.0.3
Package: extRatum
Title: Summary Statistics for Geospatial Features
Version: 1.0.3
Authors@R: c( person("Nikos", "Patias", email = "n.patias@liverpool.ac.uk", role = c("aut","cre"), comment = c(ORCID = "0000-0002-6542-2330")), person("Francisco", "Rowe", email = "fcorowe@liverpool.ac.uk", role = ("aut")) )
Description: Provides summary statistics of local geospatial features within a given geographic area. It does so by calculating the area covered by a target geospatial feature (i.e. buildings, parks, lakes, etc.). The geospatial features can be of any type of geospatial data, including point, polygon or line data.
License: MIT + file LICENSE
Depends: R (>= 4.0.0)
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
SystemRequirements: C++11, GDAL (>= 2.0.1), GEOS (>= 3.4.0), PROJ (>= 4.8.0)
Date/Publication: 2021-01-16 00:50:02 UTC
Imports: sf (>= 0.9.5), dplyr (>= 1.0.0), tidyr (>= 1.1.0)
NeedsCompilation: no
Packaged: 2021-01-13 15:04:09 UTC; User
Author: Nikos Patias [aut, cre] (<https://orcid.org/0000-0002-6542-2330>), Francisco Rowe [aut]
Maintainer: Nikos Patias <n.patias@liverpool.ac.uk>
Repository: CRAN

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New package shiny.router with initial version 0.2.1
Package: shiny.router
Type: Package
Title: Basic Routing for Shiny Web Applications
Version: 0.2.1
Authors@R: c(person("Filip", "Stachura", email = "filip@appsilon.com", role = c("aut")), person("Dominik", "Krzemiński", email = "dominik@appsilon.com", role = c("cre", "aut")), person("Krystian", "Igras", email = "krystian@appsilon.com", role = c("aut")), person(family = "Appsilon", role = c("cph")) )
Description: It is a simple router for your Shiny apps. The router allows you to create dynamic web applications with real-time User Interface and easily share url to pages within your Shiny apps.
Encoding: UTF-8
LazyData: true
License: MIT + file LICENSE
Imports: magrittr, shiny, htmltools
RoxygenNote: 7.1.1
Suggests: testthat, covr
NeedsCompilation: no
Packaged: 2021-01-15 13:41:23 UTC; dominik
Author: Filip Stachura [aut], Dominik Krzemiński [cre, aut], Krystian Igras [aut], Appsilon [cph]
Maintainer: Dominik Krzemiński <dominik@appsilon.com>
Repository: CRAN
Date/Publication: 2021-01-15 16:00:02 UTC

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New package spatstat.geom with initial version 1.65-5
Package: spatstat.geom
Version: 1.65-5
Date: 2021-01-12
Title: Geometrical Functionality of the 'spatstat' Package
Authors@R: c(person("Adrian", "Baddeley", role = c("aut", "cre"), email = "Adrian.Baddeley@curtin.edu.au"), person("Rolf", "Turner", role = "aut", email="r.turner@auckland.ac.nz"), person("Ege", "Rubak", role = "aut", email = "rubak@math.aau.dk"), person("Tilman", "Davies", role = "ctb"), person("Ute", "Hahn", role = "ctb"), person("Abdollah", "Jalilian", role = "ctb"), person("Suman", "Rakshit", role = "ctb"), person("Dominic", "Schuhmacher", role = "ctb"), person("Rasmus", "Plenge Waagepetersen", role = "ctb"))
Maintainer: Adrian Baddeley <Adrian.Baddeley@curtin.edu.au>
Depends: R (>= 3.5.0), spatstat.data (>= 1.6-1), stats, graphics, grDevices, utils, methods
Imports: spatstat.utils (>= 1.18-0), spatstat.sparse, deldir (>= 0.0-21), polyclip (>= 1.10-0)
Suggests: spatstat.core, spatstat.linnet, maptools (>= 0.9-9), spatial, fftwtools (>= 0.9-8)
Description: This is a subset of the original 'spatstat' package, containing the user-level code from 'spatstat' which performs geometrical operations, except for the geometry of linear networks.
License: GPL (>= 2)
URL: http://spatstat.org/
LazyData: true
NeedsCompilation: yes
ByteCompile: true
BugReports: https://github.com/spatstat/spatstat.geom/issues
Packaged: 2021-01-12 10:41:35 UTC; adrian
Author: Adrian Baddeley [aut, cre], Rolf Turner [aut], Ege Rubak [aut], Tilman Davies [ctb], Ute Hahn [ctb], Abdollah Jalilian [ctb], Suman Rakshit [ctb], Dominic Schuhmacher [ctb], Rasmus Plenge Waagepetersen [ctb]
Repository: CRAN
Date/Publication: 2021-01-15 13:40:06 UTC

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New package Rthingsboard with initial version 0.2.2
Package: Rthingsboard
Type: Package
Title: 'ThingsBoard' API
Version: 0.2.2
Date: 2021-01-13
Authors@R: person(given = "David", family = "Dorchies", role = c("aut", "cre"), email = "david.dorchies@inrae.fr", comment = c(ORCID = "0000-0002-6595-7984"))
Description: The goal of 'Rthingsboard' is to provide interaction with the API of 'ThingsBoard' (<https://thingsboard.io/>), an open-source IoT platform for device management, data collection, processing and visualization.
License: AGPL-3
Encoding: UTF-8
LazyData: true
Imports: httr, logger, methods, dplyr
Suggests: ggplot2, testthat
RoxygenNote: 7.1.1
URL: https://github.com/DDorch/Rthingsboard
BugReports: https://github.com/DDorch/Rthingsboard/issues
NeedsCompilation: no
Packaged: 2021-01-13 16:24:25 UTC; david.dorchies
Author: David Dorchies [aut, cre] (<https://orcid.org/0000-0002-6595-7984>)
Maintainer: David Dorchies <david.dorchies@inrae.fr>
Repository: CRAN
Date/Publication: 2021-01-15 10:30:03 UTC

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New package IDF with initial version 2.0.0
Package: IDF
Type: Package
Title: Estimation and Plotting of IDF Curves
Version: 2.0.0
Date: 2021-01-15
Authors@R: c(person("Jana", "Ulrich", email = "jana.ulrich@met.fu-berlin.de", role = c("aut", "cre")), person("Laura","Mack", email= "laura.mack@fu-berlin.de",role="ctb"), person("Oscar E.","Jurado", email= "jurado@zedat.fu-berlin.de",role="ctb"), person("Christoph", "Ritschel", role = "aut"), person("Carola", "Detring", role = "ctb"), person("Sarah", "Joedicke", role = "ctb"))
Description: Intensity-duration-frequency (IDF) curves are a widely used analysis-tool in hydrology to assess extreme values of precipitation [e.g. Mailhot et al., 2007, <doi:10.1016/j.jhydrol.2007.09.019>]. The package 'IDF' provides functions to estimate IDF parameters for given precipitation time series on the basis of a duration-dependent generalized extreme value distribution [Koutsoyiannis et al., 1998, <doi:10.1016/S0022-1694(98)00097-3>].
Author: Jana Ulrich [aut, cre], Laura Mack [ctb], Oscar E. Jurado [ctb], Christoph Ritschel [aut], Carola Detring [ctb], Sarah Joedicke [ctb]
Maintainer: Jana Ulrich <jana.ulrich@met.fu-berlin.de>
Imports: stats, evd, ismev, RcppRoll, pbapply, fastmatch
License: GPL (>= 2)
Encoding: UTF-8
URL: https://gitlab.met.fu-berlin.de/Rpackages/idf_package
LazyData: true
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2021-01-15 09:59:13 UTC; janaulrich
Repository: CRAN
Date/Publication: 2021-01-15 10:20:05 UTC

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New package ExhaustiveSearch with initial version 1.0.0
Package: ExhaustiveSearch
Type: Package
Title: A Fast and Scalable Exhaustive Feature Selection Framework
Version: 1.0.0
Authors@R: c(person(given = "Rudolf", family = "Jagdhuber", role = c("aut", "cre"), email = "r.jagdhuber@gmail.com"), person(given = "Jorge", family = "Nocedal", role = "cph", comment = "lbfgs c library"), person(given = "Naoaki", family = "Okazaki", role = "cph", comment = "lbfgs c library"))
Description: The goal of this package is to provide an easy to use, fast and scalable exhaustive search framework. Exhaustive feature selections typically require a very large number of models to be fitted and evaluated. Execution speed and memory management are crucial factors here. This package provides solutions for both. Execution speed is optimized by using a multi-threaded C++ backend, and memory issues are solved by by only storing the best results during execution and thus keeping memory usage constant.
License: GPL (>= 3)
Encoding: UTF-8
Imports: Rcpp
LinkingTo: Rcpp, RcppArmadillo
RoxygenNote: 7.1.1
URL: https://github.com/RudolfJagdhuber/ExhaustiveSearch
BugReports: https://github.com/RudolfJagdhuber/ExhaustiveSearch/issues
Suggests: mlbench
NeedsCompilation: yes
Packaged: 2021-01-13 14:41:58 UTC; Rudi
Author: Rudolf Jagdhuber [aut, cre], Jorge Nocedal [cph] (lbfgs c library), Naoaki Okazaki [cph] (lbfgs c library)
Maintainer: Rudolf Jagdhuber <r.jagdhuber@gmail.com>
Repository: CRAN
Date/Publication: 2021-01-15 10:20:09 UTC

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New package ExamPAData with initial version 0.2.0
Package: ExamPAData
Type: Package
Title: Data Sets for Predictive Analytics Exam
Version: 0.2.0
Authors@R: c( person("Guanglai", "Li", email = "liguanglai@gmail.com", role = c("aut", "cre")), person("Sam", "Castillo", role = "aut") )
Date: 2021-01-12
Description: Contains all data sets for Exam PA: Predictive Analytics at <https://exampa.net/>.
URL: https://github.com/sdcastillo/ExamPAData
BugReports: https://github.com/sdcastillo/ExamPAData/issues
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.5.0)
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2021-01-12 21:46:36 UTC; gl
Author: Guanglai Li [aut, cre], Sam Castillo [aut]
Maintainer: Guanglai Li <liguanglai@gmail.com>
Repository: CRAN
Date/Publication: 2021-01-15 10:20:12 UTC

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New package bmabasket with initial version 0.1.0
Package: bmabasket
Type: Package
Title: Bayesian Model Averaging for Basket Trials
Version: 0.1.0
Date: 2021-01-09
Authors@R: c( person("Matt", "Psioda", email = "matt_psioda@unc.edu", role = "cre"), person("Ethan", "Alt", email = "ethanalt@live.unc.edu", role = "aut"))
Maintainer: Matt Psioda <matt_psioda@unc.edu>
Description: An implementation of the Bayesian model averaging method of Psioda and others (2019) <doi:10.1093/biostatistics/kxz014> for basket trials. Contains a user-friendly wrapper for simulating basket trials under conditions and analyzing them with a Bayesian model averaging approach.
License: GPL (>= 2)
Depends: R (>= 3.5.0)
Imports: Rcpp (>= 1.0.3), partitions
LinkingTo: Rcpp, RcppArmadillo
Encoding: UTF-8
URL: https://github.com/ethan-alt/bmabasket
BugReports: https://github.com/ethan-alt/bmabasket/issues
RoxygenNote: 7.1.1
NeedsCompilation: yes
Packaged: 2021-01-12 20:17:40 UTC; ethanalt
Author: Matt Psioda [cre], Ethan Alt [aut]
Repository: CRAN
Date/Publication: 2021-01-15 10:20:02 UTC

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New package sparsevb with initial version 0.1.0
Package: sparsevb
Type: Package
Title: Spike-and-Slab Variational Bayes for Linear and Logistic Regression
Version: 0.1.0
Date: 2021-1-04
Authors@R: c(person("Gabriel", "Clara", email = "gabriel.j.clara@gmail.com", role = c("aut", "cre")), person("Botond", "Szabo", role = "aut"), person("Kolyan", "Ray", role = "aut"))
Author: Gabriel Clara [aut, cre], Botond Szabo [aut], Kolyan Ray [aut]
Maintainer: Gabriel Clara <gabriel.j.clara@gmail.com>
Description: Implements variational Bayesian algorithms to perform scalable variable selection for sparse, high-dimensional linear and logistic regression models. Features include a novel prioritized updating scheme, which uses a preliminary estimator of the variational means during initialization to generate an updating order prioritizing large, more relevant, coefficients. Sparsity is induced via spike-and-slab priors with either Laplace or Gaussian slabs. By default, the heavier-tailed Laplace density is used. Formal derivations of the algorithms and asymptotic consistency results may be found in Kolyan Ray and Botond Szabo (2020) <doi:10.1080/01621459.2020.1847121> and Kolyan Ray, Botond Szabo, and Gabriel Clara (2020) <arXiv:2010.11665>.
BugReports: https://gitlab.com/gclara/varpack/-/issues
License: GPL (>= 3)
Imports: Rcpp (>= 1.0.5), selectiveInference (>= 1.2.5), glmnet (>= 4.0-2), stats
LinkingTo: Rcpp, RcppArmadillo, RcppEnsmallen
SystemRequirements: C++11
Encoding: UTF-8
RoxygenNote: 7.1.1
NeedsCompilation: yes
Packaged: 2021-01-12 04:11:21 UTC; gclara
Repository: CRAN
Date/Publication: 2021-01-15 09:20:02 UTC

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New package eFRED with initial version 0.1.0
Package: eFRED
Title: Fetch Data from the Federal Reserve Economic Database
Version: 0.1.0
Author: Chris Mann <cmann3@unl.edu>
Maintainer: Chris Mann <cmann3@unl.edu>
Description: Interact with the FRED API, <https://fred.stlouisfed.org/docs/api/fred/>, to fetch observations across economic series; find information about different economic sources, releases, series, etc.; conduct searches by series name, attributes, or tags; and determine the latest updates. Includes functions for creating panels of related variables with minimal effort and datasets containing data sources, releases, and popular FRED tags.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: jsonlite, httr, R (>= 2.10)
Suggests: knitr, rmarkdown, datasets
VignetteBuilder: knitr
LazyData: true
RoxygenNote: 7.0.2
NeedsCompilation: no
Packaged: 2021-01-12 13:01:24 UTC; chris
Repository: CRAN
Date/Publication: 2021-01-15 09:40:13 UTC

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New package autostsm with initial version 1.0
Package: autostsm
Type: Package
Title: Automatic Structural Time Series Models
Version: 1.0
Date: 2021-01-11
Author: Alex Hubbard
Maintainer: Alex Hubbard <hubbard.alex@gmail.com>
Description: Automatic model selection for structural time series decomposition into trend, cycle, and seasonal components using the Kalman filter. See Koopman, Siem Jan and Marios Ooms (2012) "Forecasting Economic Time Series Using Unobserved Components Time Series Models <doi:10.1093/oxfordhb/9780195398649.013.0006>.
License: GPL (>= 2)
Imports: Matrix (>= 1.2), maxLik (>= 1.4), seastests (>= 0.14), forecast (>= 8.13), lubridate (>= 1.7), tsutils (>= 0.9), ggplot2 (>= 3.3), gridExtra (>= 2.3), strucchange (>= 1.5), imputeTS (>= 3.1), foreach (>= 1.5), doSNOW (>= 1.0), parallel (>= 4.0), zoo (>= 1.8)
Depends: R (>= 3.5.0), data.table (>= 1.13)
LinkingTo: Rcpp, RcppArmadillo
RoxygenNote: 7.1.1
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2021-01-12 16:27:39 UTC; alex.hubbard
Repository: CRAN
Date/Publication: 2021-01-15 10:00:05 UTC

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New package arcpullr with initial version 0.1
Package: arcpullr
Type: Package
Title: Pull Data from an ArcGIS REST API
Version: 0.1
Authors@R: c(person(given = "Paul", family = "Frater", role = c("aut", "cre"), email = "paul.frater@wisconsin.gov", comment = c(ORCID = "0000-0002-7237-6563")), person("Zac", "Driscoll", email = "zdriscoll@mmsd.com", role = c("aut", "ctb"), comment = c(ORCID = "0000-0002-8233-0980")))
License: GPL-3
Encoding: UTF-8
LazyData: true
Description: Functions to efficiently query ArcGIS REST APIs <https://developers.arcgis.com/rest/>. Both spatial and SQL queries can be used to retrieve data. Simple Feature (sf) objects are utilized to perform spatial queries. This package was neither produced nor is maintained by Esri.
Depends: R (>= 3.6.0)
Imports: httr (>= 1.4.1), jsonlite (>= 1.6.1), sf (>= 0.9.5), dplyr (>= 1.0.2), ggplot2 (>= 3.3.0), tidyr (>= 1.0.2), rlang (>= 0.4.7)
RoxygenNote: 7.1.1
Suggests: testthat, knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-01-12 15:26:55 UTC; fratepnd
Author: Paul Frater [aut, cre] (<https://orcid.org/0000-0002-7237-6563>), Zac Driscoll [aut, ctb] (<https://orcid.org/0000-0002-8233-0980>)
Maintainer: Paul Frater <paul.frater@wisconsin.gov>
Repository: CRAN
Date/Publication: 2021-01-15 10:00:08 UTC

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New package activatr with initial version 0.1.0
Package: activatr
Type: Package
Title: Utilities for Parsing and Plotting Activities
Version: 0.1.0
Authors@R: person("Daniel", "Schafer", email = "dan.schafer@gmail.com", role = c("aut", "cre"))
Description: This contains helpful functions for parsing, managing, plotting, and visualizing activities, most often from GPX (GPS Exchange Format) files recorded by GPS devices. It allows easy parsing of the source files into standard R data formats, along with functions to compute derived data for the activity, and to plot the activity in a variety of ways.
License: MIT + file LICENSE
URL: https://github.com/dschafer/activatr
BugReports: https://github.com/dschafer/activatr/issues
Encoding: UTF-8
LazyData: true
Depends: R (>= 4.0.0)
Imports: dplyr (>= 1.0.0), geosphere (>= 1.5), ggmap (>= 3.0.0), glue (>= 1.4.0), httr (>= 1.4.0), lubridate (>= 1.7.0), magrittr (>= 2.0.0), rlang (>= 0.4.0), tibble (>= 3.0.0), timetk (>= 2.6.0), xml2 (>= 1.3.2)
RoxygenNote: 7.1.1
Suggests: covr (>= 3.5.0), ggplot2 (>= 3.3.0), knitr (>= 1.30), mockery (>= 0.4.2), rmarkdown (>= 2.6), roxygen2 (>= 7.1.0), testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-01-12 04:41:36 UTC; dschafer
Author: Daniel Schafer [aut, cre]
Maintainer: Daniel Schafer <dan.schafer@gmail.com>
Repository: CRAN
Date/Publication: 2021-01-15 09:20:05 UTC

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New package SeuratObject with initial version 4.0.0
Package: SeuratObject
Type: Package
Title: Data Structures for Single Cell Data
Version: 4.0.0
Date: 2021-01-07
Authors@R: c( person(given = 'Rahul', family = 'Satija', email = 'rsatija@nygenome.org', role = 'aut', comment = c(ORCID = '0000-0001-9448-8833')), person(given = 'Andrew', family = 'Butler', email = 'abutler@nygenome.org', role = 'aut', comment = c(ORCID = '0000-0003-3608-0463')), person(given = 'Paul', family = 'Hoffman', email = 'nygcSatijalab@nygenome.org', role = c('aut', 'cre'), comment = c(ORCID = '0000-0002-7693-8957')), person(given = 'Tim', family = 'Stuart', email = 'tstuart@nygenome.org', role = 'aut', comment = c(ORCID = '0000-0002-3044-0897')), person(given = 'Jeff', family = 'Farrell', email = 'jfarrell@g.harvard.edu', role = 'ctb'), person(given = 'Shiwei', family = 'Zheng', email = 'szheng@nygenome.org', role = 'ctb', comment = c(ORCID = '0000-0001-6682-6743')), person(given = 'Christoph', family = 'Hafemeister', email = 'chafemeister@nygenome.org', role = 'ctb', comment = c(ORCID = '0000-0001-6365-8254')), person(given = 'Patrick', family = 'Roelli', email = 'proelli@nygenome.org', role = 'ctb'), person(given = "Yuhan", family = "Hao", email = 'yhao@nygenome.org', role = 'ctb', comment = c(ORCID = '0000-0002-1810-0822')) )
Description: Defines S4 classes for single-cell genomic data and associated information, such as dimensionality reduction embeddings, nearest-neighbor graphs, and spatially-resolved coordinates. Provides data access methods and R-native hooks to ensure the Seurat object is familiar to other R users. See Satija R, Farrell J, Gennert D, et al (2015) <doi:10.1038/nbt.3192>, Macosko E, Basu A, Satija R, et al (2015) <doi:10.1016/j.cell.2015.05.002>, and Stuart T, Butler A, et al (2019) <doi:10.1016/j.cell.2019.05.031> for more details.
URL: https://satijalab.org/seurat, https://github.com/mojaveazure/seurat-object
BugReports: https://github.com/mojaveazure/seurat-object/issues
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Depends: R (>= 3.5.0)
Imports: grDevices, grid, Matrix (>= 1.2.18), methods, Rcpp (>= 1.0.5), rlang (>= 0.4.7), sctransform, stats, tools, utils
Suggests: tinytest
Collate: 'RcppExports.R' 'utils.R' 'zzz.R' 'generics.R' 'assay.R' 'command.R' 'data.R' 'default.R' 'jackstraw.R' 'dimreduc.R' 'graph.R' 'neighbor.R' 'spatial.R' 'seurat.R'
LinkingTo: Rcpp, RcppEigen
NeedsCompilation: yes
Packaged: 2021-01-11 19:28:57 UTC; paul
Author: Rahul Satija [aut] (<https://orcid.org/0000-0001-9448-8833>), Andrew Butler [aut] (<https://orcid.org/0000-0003-3608-0463>), Paul Hoffman [aut, cre] (<https://orcid.org/0000-0002-7693-8957>), Tim Stuart [aut] (<https://orcid.org/0000-0002-3044-0897>), Jeff Farrell [ctb], Shiwei Zheng [ctb] (<https://orcid.org/0000-0001-6682-6743>), Christoph Hafemeister [ctb] (<https://orcid.org/0000-0001-6365-8254>), Patrick Roelli [ctb], Yuhan Hao [ctb] (<https://orcid.org/0000-0002-1810-0822>)
Maintainer: Paul Hoffman <nygcSatijalab@nygenome.org>
Repository: CRAN
Date/Publication: 2021-01-15 08:50:02 UTC

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Thu, 14 Jan 2021

New package icesVocab with initial version 1.1.9
Package: icesVocab
Title: ICES Vocabularies Database Web Services
Date: 2021-01-14
Version: 1.1.9
Authors@R: c(person("Colin", "Millar", email = "colin.millar@ices.dk", role = c("aut","cre")), person("Arni", "Magnusson", role = "aut"))
Imports: utils, xml2
Description: R interface to access the RECO POX web services of the ICES (International Council for the Exploration of the Sea) Vocabularies database <https://vocab.ices.dk/services/POX.aspx>.
License: GPL-3
URL: https://vocab.ices.dk/services/POX.aspx
RoxygenNote: 7.1.1
Encoding: UTF-8
BugReports: https://github.com/ices-tools-prod/icesVocab/issues
Suggests: testthat
NeedsCompilation: no
Packaged: 2021-01-14 22:26:56 UTC; colin
Author: Colin Millar [aut, cre], Arni Magnusson [aut]
Maintainer: Colin Millar <colin.millar@ices.dk>
Repository: CRAN
Date/Publication: 2021-01-15 00:00:02 UTC

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New package datapackage.r with initial version 1.3.2
Package: datapackage.r
Type: Package
Title: Data Package 'Frictionless Data'
Version: 1.3.2
Date: 2021-01-14
Authors@R: c(person("Kleanthis", "Koupidis", email = "koupidis.okfgr@gmail.com", role = c("aut", "cre")), person("Lazaros", "Ioannidis", email = "larjohn@gmail.com", role = "aut"), person("Charalampos", "Bratsas", email = "cbratsas@math.auth.gr", role = "aut"), person("Open Knowledge International", email = "info@okfn.org", role = "cph"))
Maintainer: Kleanthis Koupidis <koupidis.okfgr@gmail.com>
Description: Work with 'Frictionless Data Packages' (<https://specs.frictionlessdata.io//data-package/>). Allows to load and validate any descriptor for a data package profile, create and modify descriptors and provides expose methods for reading and streaming data in the package. When a descriptor is a 'Tabular Data Package', it uses the 'Table Schema' package (<https://CRAN.R-project.org/package=tableschema.r>) and exposes its functionality, for each resource object in the resources field.
URL: https://github.com/frictionlessdata/datapackage-r
License: MIT + file LICENSE
BugReports: https://github.com/frictionlessdata/datapackage-r/issues
Encoding: UTF-8
LazyData: true
Imports: config, future, httr, iterators, jsonlite, jsonvalidate, purrr, R6, R.utils, readr, rlist, stringr, tableschema.r, tools, urltools, utils, V8
Suggests: covr, curl, data.table, DBI, devtools, foreach, httptest, knitr, rmarkdown, RSQLite, testthat
Collate: 'DataPackageError.R' 'Package.R' 'helpers.R' 'profile.R' 'binary.readable.connection.r' 'binary.readable.r' 'datapackage.r.R' 'infer.R' 'is.valid.R' 'resource.R' 'validate.R'
RoxygenNote: 7.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-01-14 15:55:28 UTC; akis_
Author: Kleanthis Koupidis [aut, cre], Lazaros Ioannidis [aut], Charalampos Bratsas [aut], Open Knowledge International [cph]
Repository: CRAN
Date/Publication: 2021-01-14 22:10:11 UTC

More information about datapackage.r at CRAN
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New package seasonalclumped with initial version 0.3.2
Package: seasonalclumped
Title: Toolbox for Clumped Isotope Seasonality Reconstructions
Version: 0.3.2
Authors@R: person(given = "Niels", family = "de Winter", role = c("aut", "cre"), email = "niels_de_winter@live.nl", comment = c(ORCID = "0000-0002-1453-5407"))
Description: Compiles a set of functions and dummy data that simplify reconstructions of seasonal temperature variability in the geological past from stable isotope and clumped isotope records in sub–annually resolved carbonate archives (e.g. mollusk shells, corals and speleothems). For more information, see de Winter et al., 2020 (Climate of the Past Discussions, <doi:10.5194/cp-2020-118>).
Imports: ggplot2, gridExtra, TTR, magrittr
License: GPL-3
URL: https://github.com/nielsjdewinter/seasonalclumped
BugReports: https://github.com/nielsjdewinter/seasonalclumped/issues
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Depends: R (>= 3.5.0)
Suggests: knitr, rmarkdown
NeedsCompilation: no
Packaged: 2021-01-11 17:17:54 UTC; Convernaum
Author: Niels de Winter [aut, cre] (<https://orcid.org/0000-0002-1453-5407>)
Maintainer: Niels de Winter <niels_de_winter@live.nl>
Repository: CRAN
Date/Publication: 2021-01-14 10:20:02 UTC

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New package remap with initial version 0.2.0
Package: remap
Type: Package
Title: Regional Spatial Modeling with Continuous Borders
Version: 0.2.0
Authors@R: person("Jadon", "Wagstaff", email = "jadonw@gmail.com", role = c("aut", "cre"))
Description: Automatically creates separate regression models for different spatial regions. The prediction surface is smoothed using a novel method developed by the package creator. If regional models are continuous, the resulting prediction surface is continuous across the spatial dimensions, even at region borders.
License: GPL-3
URL: https://github.com/jadonwagstaff/remap
BugReports: https://github.com/jadonwagstaff/remap/issues
Encoding: UTF-8
LazyData: true
Imports: graphics (>= 3.6.0), parallel (>= 3.6.0), sf (>= 0.9.6), stats (>= 3.6.0), units (>= 0.6.7), utils (>= 3.6.0)
RoxygenNote: 7.1.1
Suggests: dplyr (>= 1.0.2), ggplot2 (>= 3.3.2), knitr (>= 1.30), lwgeom (>= 0.2.5), magrittr (>= 2.0.1), maps (>= 3.3.0), mgcv (>= 1.8.33), rmarkdown (>= 2.5), tibble (>= 3.0.4)
VignetteBuilder: knitr
Depends: R (>= 3.6.0)
NeedsCompilation: no
Packaged: 2021-01-11 17:29:49 UTC; Jadon
Author: Jadon Wagstaff [aut, cre]
Maintainer: Jadon Wagstaff <jadonw@gmail.com>
Repository: CRAN
Date/Publication: 2021-01-14 10:30:02 UTC

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New package VAM with initial version 0.4.0
Package: VAM
Type: Package
Title: Variance-Adjusted Mahalanobis
Version: 0.4.0
Author: H. Robert Frost
Maintainer: H. Robert Frost <rob.frost@dartmouth.edu>
Description: Contains logic for cell-specific gene set scoring of single cell RNA sequencing data.
Depends: R (>= 3.6.0), MASS, Matrix
Suggests: Seurat (>= 3.1.4)
License: GPL (>= 2)
Copyright: Dartmouth College
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2021-01-11 14:14:17 UTC; robfrost
Repository: CRAN
Date/Publication: 2021-01-14 09:30:05 UTC

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New package tabnet with initial version 0.1.0
Package: tabnet
Title: Fit 'TabNet' Models for Classification and Regression
Version: 0.1.0
Authors@R: c( person(given = "Daniel", family = "Falbel", role = c("aut", "cre"), email = "daniel@rstudio.com"), person(family = "RStudio", role = c("cph")) )
Description: Implements the 'TabNet' model by Sercan O. Arik et al (2019) <arXiv:1908.07442> and provides a consistent interface for fitting and creating predictions. It's also fully compatible with the 'tidymodels' ecosystem.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Imports: torch, hardhat, magrittr, glue, progress, rlang, methods, tibble, vctrs
Suggests: testthat, modeldata, recipes, parsnip, dials, withr, knitr, rmarkdown, vip, tidyverse
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-01-11 13:47:17 UTC; dfalbel
Author: Daniel Falbel [aut, cre], RStudio [cph]
Maintainer: Daniel Falbel <daniel@rstudio.com>
Repository: CRAN
Date/Publication: 2021-01-14 09:30:02 UTC

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New package sisireg with initial version 0.7.0
Package: sisireg
Title: Sign-Simplicity-Regression-Solver
Version: 0.7.0
Authors@R: person(given = "Lars", family = "Metzner", role = c("aut", "cre"), email = "lars.metzner@ppi.de")
Description: Implementation of the SSR-Algorithm. The Sign-Simplicity-Regression model is a nonparametric statistical model which is based on residual signs and simplicity assumptions on the regression function. Goal is to calculate the most parsimonious regression function satisfying the statistical adequacy requirements. Theory and functions are specified in Metzner (2020, ISBN: 9798682394203, "Trendbasierte Prognostik") and Metzner (2021, ISBN: 9798593470270, "Adäquates Maschinelles Lernen").
License: GPL (>= 2)
Encoding: UTF-8
Imports: zoo, raster
RoxygenNote: 7.1.1
NeedsCompilation: yes
Packaged: 2021-01-11 13:31:57 UTC; lme
Author: Lars Metzner [aut, cre]
Maintainer: Lars Metzner <lars.metzner@ppi.de>
Repository: CRAN
Date/Publication: 2021-01-14 09:40:02 UTC

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New package shinyRadioMatrix with initial version 0.2.0
Package: shinyRadioMatrix
Type: Package
Title: Create a Matrix with Radio Buttons
Version: 0.2.0
Authors@R: c(person("Zsolt", "Szelepcsényi", email = "szelepcsenyi.zsolt@gmail.com", role = c("aut", "cre")), person("Zoltán", "Szelepcsényi", email = "szelepcsenyi.zoltan@gmail.com", role = "aut"))
Maintainer: Zsolt Szelepcsényi <szelepcsenyi.zsolt@gmail.com>
Description: An input controller for R Shiny: a matrix with radio buttons, where only one option per row can be selected.
Imports: shiny
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Depends: R (>= 2.10)
NeedsCompilation: no
Packaged: 2021-01-11 16:35:29 UTC; evista
Author: Zsolt Szelepcsényi [aut, cre], Zoltán Szelepcsényi [aut]
Repository: CRAN
Date/Publication: 2021-01-14 10:00:02 UTC

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New package mecor with initial version 0.9.0
Package: mecor
Type: Package
Title: Measurement Error Correction in Linear Models with a Continuous Outcome
Version: 0.9.0
Author: Linda Nab
Maintainer: Linda Nab <lindanab4@gmail.com>
Description: Covariate measurement error correction is implemented by means of regression calibration by Carroll RJ, Ruppert D, Stefanski LA & Crainiceanu CM (2006, ISBN:1584886331), efficient regression calibration by Spiegelman D, Carroll RJ & Kipnis V (2001) <doi:10.1002/1097-0258(20010115)20:1%3C139::AID-SIM644%3E3.0.CO;2-K> and maximum likelihood estimation by Bartlett JW, Stavola DBL & Frost C (2009) <doi:10.1002/sim.3713>. Outcome measurement error correction is implemented by means of the method of moments by Buonaccorsi JP (2010, ISBN:1420066560) and efficient method of moments by Keogh RH, Carroll RJ, Tooze JA, Kirkpatrick SI & Freedman LS (2014) <doi:10.1002/sim.7011>. Standard error estimation of the corrected estimators is implemented by means of the Delta method by Rosner B, Spiegelman D & Willett WC (1990) <doi:10.1093/oxfordjournals.aje.a115715> and Rosner B, Spiegelman D & Willett WC (1992) <doi:10.1093/oxfordjournals.aje.a116453>, the Fieller method described by Buonaccorsi JP (2010, ISBN:1420066560), and the Bootstrap by Carroll RJ, Ruppert D, Stefanski LA & Crainiceanu CM (2006, ISBN:1584886331).
Depends: R (>= 2.10)
License: GPL-3
Encoding: UTF-8
LazyData: true
URL: https://github.com/LindaNab/mecor
Imports: lme4, lmerTest, numDeriv
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2021-01-11 09:35:55 UTC; lindanab
Repository: CRAN
Date/Publication: 2021-01-14 09:20:02 UTC

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New package MARSANNhybrid with initial version 0.1.0
Package: MARSANNhybrid
Type: Package
Title: MARS Based ANN Hybrid Model
Version: 0.1.0
Authors@R: c(person("Pankaj", "Das", role = c("aut","cre"),email="pankaj.das2@icar.gov.in"),person("Achal", "Lama", role = "aut",email="achal.lama@icar.gov.in"), person("Girish Kumar", "Jha", role = "aut",email="grish.stat@gmail.com"))
Author: Pankaj Das [aut, cre], Achal Lama [aut], Girish Kumar Jha [aut]
Maintainer: Pankaj Das <pankaj.das2@icar.gov.in>
Depends: R (>= 3.3.0),neuralnet,earth,stats
Description: Multivariate Adaptive Regression Spline (MARS) based Artificial Neural Network (ANN) hybrid model is combined Machine learning hybrid approach which selects important variables using MARS and then fits ANN on the extracted important variables.
Encoding: UTF-8
LazyData: true
License: GPL-3
NeedsCompilation: no
Packaged: 2021-01-11 10:45:22 UTC; USER
Repository: CRAN
Date/Publication: 2021-01-14 09:40:11 UTC

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New package log with initial version 1.1.0
Package: log
Title: Record Events and Issues
Version: 1.1.0
Authors@R: c( person(given = "John", family = "Coene", role = c("aut", "cre"), email = "john@opifex.org"), person(family = "Opifex", role = c("cph"), email = "john@opifex.org") )
Description: Logger to keep track of informational events and errors useful for debugging.
License: AGPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1.9000
Imports: R6, cli, crayon
Suggests: shiny, plumber, testthat (>= 3.0.0), covr
Config/testthat/edition: 3
NeedsCompilation: no
Packaged: 2021-01-10 22:11:22 UTC; jp
Author: John Coene [aut, cre], Opifex [cph]
Maintainer: John Coene <john@opifex.org>
Repository: CRAN
Date/Publication: 2021-01-14 09:10:02 UTC

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New package ICSsmoothing with initial version 1.2.5
Package: ICSsmoothing
Type: Package
Title: Data Smoothing by Interpolating Cubic Splines
Version: 1.2.5
Authors@R: c( person("Juraj", "Hudak", role = c("aut")), person("Viliam", "Kacala", email = "viliam.kacala.ml@gmail.com", role = c("cre")), person("Csaba", "Torok", email = "csaba.torok@upjs.sk", role = c("ctb")))
Description: We construct the explicit form of clamped cubic interpolating spline (both uniform - knots are equidistant and non-uniform - knots are arbitrary). Using this form, we propose a linear regression model suitable for real data smoothing. This package is based on a diploma thesis Hudak (2017) <https://opac.crzp.sk/?fn=detailBiblioForm&sid=7FE4E0810F66E41DF9A9CA23557F&seo=CRZP-detail-kniha>.
Depends: R (>= 3.5.0), polynom, ggplot2
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Suggests: knitr, rmarkdown, testthat
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-01-11 07:59:46 UTC; vildibald
Author: Juraj Hudak [aut], Viliam Kacala [cre], Csaba Torok [ctb]
Maintainer: Viliam Kacala <viliam.kacala.ml@gmail.com>
Repository: CRAN
Date/Publication: 2021-01-14 09:10:09 UTC

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New package ggOceanMaps with initial version 1.0.9
Package: ggOceanMaps
Type: Package
Title: Plot Data on Oceanographic Maps using 'ggplot2'
Version: 1.0.9
Date: 2021-01-08
Authors@R: c(person("Mikko", "Vihtakari", email = "mikko.vihtakari@hi.no", role = c("aut", "cre"), comment = c(affiliation = "Institute of Marine Research", ORCID = "0000-0003-0371-4319")), person("Hadley", "Wickham", role = "ctb"), person("Simon", "O'Hanlon", role = "ctb"), person("Roger", "Bivand", role = "ctb") )
URL: https://mikkovihtakari.github.io/ggOceanMaps/
BugReports: https://github.com/MikkoVihtakari/ggOceanMaps/issues
Description: Allows plotting data on bathymetric maps using 'ggplot2'. Plotting oceanographic spatial data is made as simple as feasible, but also flexible for custom modifications. Data that contain geographic information from anywhere around the globe can be plotted on maps generated by the basemap() function using 'ggplot2' layers separated by the '+' operator. The package uses spatial shapefiles stored in the 'ggOceanMapsData' package, geospatial packages for R to manipulate, and the 'ggspatial' package to help to plot these shapefiles.
Depends: R (>= 3.5.0), ggplot2, ggspatial
Imports: sp, raster, rgdal, rgeos, methods, utils, sf, stars, smoothr, units, dplyr, parallel
Suggests: ggOceanMapsData, cowplot, knitr, rmarkdown, scales
Additional_repositories: https://mikkovihtakari.github.io/drat
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-01-11 10:25:24 UTC; a22357
Author: Mikko Vihtakari [aut, cre] (Institute of Marine Research, <https://orcid.org/0000-0003-0371-4319>), Hadley Wickham [ctb], Simon O'Hanlon [ctb], Roger Bivand [ctb]
Maintainer: Mikko Vihtakari <mikko.vihtakari@hi.no>
Repository: CRAN
Date/Publication: 2021-01-14 09:40:05 UTC

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New package faviconPlease with initial version 0.1.1
Package: faviconPlease
Title: Find the URL to the 'Favicon' for a Website
Version: 0.1.1
Authors@R: person(given = "John", family = "Blischak", role = c("aut", "cre"), email = "jdblischak@gmail.com")
Description: Finds the URL to the 'favicon' for a website. This is useful if you want to display the 'favicon' in an HTML document or web application, especially if the website is behind a firewall.
URL: https://github.com/jdblischak/faviconPlease
BugReports: https://github.com/jdblischak/faviconPlease/issues
Imports: utils, xml2
Suggests: httr, tinytest, ttdo
License: MIT + file LICENSE
Encoding: UTF-8
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2021-01-11 15:12:22 UTC; jdblischak
Author: John Blischak [aut, cre]
Maintainer: John Blischak <jdblischak@gmail.com>
Repository: CRAN
Date/Publication: 2021-01-14 09:40:08 UTC

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New package eCAR with initial version 0.1.0
Package: eCAR
Type: Package
Title: Eigenvalue CAR Models
Version: 0.1.0
Authors@R: c( person(given = "Garritt", family = "L. Page", email = "page@stat.byu.edu", role = c("aut", "cre")), person(given = "Massimo", family = "Ventrucci", email = "massimo.ventrucci@unibo.it", role = c("aut")), person(given = "S. McKay", family = "Curtis", email = "s.mckay.curtis@gmail.com", role = c("cph")), person(given = "Radford", family = "M. Neal", role = c("cph")))
Maintainer: Garritt L. Page <page@stat.byu.edu>
Description: Fits Leroux model in spectral domain to estimate causal spatial effect as detailed in Guan, Y; Page, G.L.; Reich, B.J.; Ventrucci, M.; Yang, S; (2020) <arXiv:2012.11767>. Both the parametric and semi-parametric models are available. The semi-parametric model relies on 'INLA'. The 'INLA' package can be obtained from <https://www.r-inla.org/>.
License: GPL
Encoding: UTF-8
Depends: R (>= 3.5.0)
Suggests: INLA
Imports: Matrix
LazyData: true
RoxygenNote: 7.1.1
Additional_repositories: https://inla.r-inla-download.org/R/stable/
URL: https://github.com/gpage2990/eCAR
NeedsCompilation: yes
Packaged: 2021-01-11 15:30:29 UTC; gpage
Author: Garritt L. Page [aut, cre], Massimo Ventrucci [aut], S. McKay Curtis [cph], Radford M. Neal [cph]
Repository: CRAN
Date/Publication: 2021-01-14 09:50:02 UTC

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New package DIFshiny with initial version 0.1.0
Package: DIFshiny
Type: Package
Title: Differential Item Functioning via Shiny Application
Version: 0.1.0
Author: Huseyin Yildiz [aut, cre]
Maintainer: Huseyin Yildiz <huseyinyildiz35@gmail.com>
Description: Differential Item Functioning (DIF) Analysis with shiny application interfaces. You can run the functions in this package without any arguments and perform your DIF analysis using user-friendly interfaces.
Depends: R (>= 3.4.0)
License: GPL-2
RoxygenNote: 7.1.1
Imports: shiny, shinydashboard, difR, stats, readxl
Encoding: UTF-8
LazyData: true
Suggests: testthat
NeedsCompilation: no
Packaged: 2021-01-11 13:14:47 UTC; husey
Repository: CRAN
Date/Publication: 2021-01-14 09:20:06 UTC

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New package utilities with initial version 0.1.0
Package: utilities
Type: Package
Title: Data Utility Functions
Version: 0.1.0
Date: 2021-01-07
Authors@R: person("Ben", "O'Neill", email = "ben.oneill@hotmail.com", role = c("aut", "cre"))
Author: Ben O'Neill [aut, cre]
Maintainer: Ben O'Neill <ben.oneill@hotmail.com>
Description: Data utility functions for use in probability and statistics. Includes functions for computing higher-moments for samples and their decompositions. Also includes utilities to examine functional mappings between factor variables and other variables in a data set.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: stats
Suggests: ggplot2, ggdag
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2021-01-11 02:39:00 UTC; nfultz
Repository: CRAN
Date/Publication: 2021-01-14 08:30:02 UTC

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New package node2vec with initial version 0.1.0
Package: node2vec
Title: Algorithmic Framework for Representational Learning on Graphs
Version: 0.1.0
Authors@R: c( person(given = "Yang", family = "Tian", role = c("aut", "cre"), email = "tianyang1211@126.com"), person(given="Xu", family="Li", role="aut"), person(given="Jing", family="Ren", role="aut") )
Description: Given any graph, the 'node2vec' algorithm can learn continuous feature representations for the nodes, which can then be used for various downstream machine learning tasks.The techniques are detailed in the paper "node2vec: Scalable Feature Learning for Networks" by Aditya Grover, Jure Leskovec(2016),available at <arXiv:1607.00653>.
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
Imports: data.table, igraph, word2vec, rlist, dplyr, vctrs, vegan
Depends: R (>= 2.10)
NeedsCompilation: no
Packaged: 2020-12-27 15:31:28 UTC; Administrator
Author: Yang Tian [aut, cre], Xu Li [aut], Jing Ren [aut]
Maintainer: Yang Tian <tianyang1211@126.com>
Repository: CRAN
Date/Publication: 2021-01-14 09:00:02 UTC

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New package EMDANNhybrid with initial version 0.1.0
Package: EMDANNhybrid
Type: Package
Title: Ensemble Machine Learning Hybrid Model
Version: 0.1.0
Authors@R: c(person("Pankaj", "Das", role = c("aut","cre"),email="pankaj.das2@icar.gov.in"),person("Achal", "Lama", role = "aut",email="achal.lama@icar.gov.in"), person("Girish", "Jha", role = "aut",email="grish.stat@gmail.com"))
Author: Pankaj Das [aut, cre], Achal Lama [aut], Girish Jha [aut]
Maintainer: Pankaj Das <pankaj.das2@icar.gov.in>
Depends: R (>= 3.3.0),EMD,nnfor,forecast
Description: The researchers can use this package to fit Empirical Mode Decomposition and Artificial Neural Network based hybrid model for nonlinear and non stationary time series data.
Encoding: UTF-8
LazyData: true
License: GPL-3
NeedsCompilation: no
Packaged: 2021-01-11 04:42:31 UTC; USER
Repository: CRAN
Date/Publication: 2021-01-14 08:30:05 UTC

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New package EEMDelm with initial version 0.1.0
Package: EEMDelm
Type: Package
Title: Ensemble Empirical Mode Decomposition and Its Variant Based ELM Model
Version: 0.1.0
Authors@R: c(person(given = "Girish Kumar", family = "Jha", role = c("aut", "cre"), email = "girish.stat@gmail.com"), person(given = "Kapil", family = "Choudhary", role = c("aut", "ctb")), person(given = "Rajeev Ranjan", family = "Kumar", role = "ctb"), person(given = "Ronit", family = "Jaiswal", role = "ctb"))
Maintainer: Girish Kumar Jha <girish.stat@gmail.com>
Description: Forecasting univariate time series with different decomposition based Extreme Learning Machine models. For method details see Yu L, Wang S, Lai KK (2008). <doi:10.1016/j.eneco.2008.05.003>, Parida M, Behera MK, Nayak N (2018). <doi:10.1109/ICSESP.2018.8376723>.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Imports: forecast, nnfor, Rlibeemd
Depends: R (>= 2.10)
NeedsCompilation: no
Packaged: 2021-01-09 06:58:46 UTC; Rajeev-PC
Author: Girish Kumar Jha [aut, cre], Kapil Choudhary [aut, ctb], Rajeev Ranjan Kumar [ctb], Ronit Jaiswal [ctb]
Repository: CRAN
Date/Publication: 2021-01-14 08:50:03 UTC

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New package bayesian with initial version 0.0.2
Package: bayesian
Type: Package
Version: 0.0.2
Title: Bindings for Bayesian TidyModels
Authors@R: c(person(given = "Hamada S.", family = "Badr", role = c("aut", "cre"), email = "badr@jhu.edu", comment = c(ORCID = "0000-0002-9808-2344")))
Description: Fit Bayesian models using 'brms'/'Stan' with 'parsnip'/'tidymodels'. 'tidymodels' is a collection of packages for machine learning, developed by Wickham (2020) <https://www.tidymodels.org>). The technical details of 'brms' and 'Stan' are described in Bürkner (2017) <doi:10.18637/jss.v080.i01>, Bürkner (2018) <doi:10.32614/RJ-2018-017>, and Carpenter et al. (2017) <doi:10.18637/jss.v076.i01>.
License: MIT + file LICENSE
URL: https://hsbadr.github.io/bayesian/, https://github.com/hsbadr/bayesian
BugReports: https://github.com/hsbadr/bayesian/issues
Depends: brms (>= 2.14.4), parsnip (>= 0.1.4), R (>= 2.10)
Imports: dplyr, purrr, rlang, stats, tibble, utils
Suggests: covr, devtools, knitr, rmarkdown, roxygen2, spelling, testthat
VignetteBuilder: knitr
Encoding: UTF-8
RoxygenNote: 7.1.1
Collate: 'bayesian_init.R' 'bayesian_load.R' 'bayesian_make.R' 'bayesian.R'
LazyData: yes
LazyLoad: yes
Language: en-US
NeedsCompilation: no
Packaged: 2021-01-11 00:10:40 UTC; runner
Author: Hamada S. Badr [aut, cre] (<https://orcid.org/0000-0002-9808-2344>)
Maintainer: Hamada S. Badr <badr@jhu.edu>
Repository: CRAN
Date/Publication: 2021-01-14 08:20:02 UTC

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Wed, 13 Jan 2021

New package lmQCM with initial version 0.2.2
Package: lmQCM
Type: Package
Title: An Algorithm for Gene Co-Expression Analysis
Version: 0.2.2
Date: 2021-01-13
Authors@R: c(person("Zhi", "Huang", email = "huang898@purdue.edu", role = c("aut", "cre")), person("Jie", "Zhang", email = "jizhan@iu.edu", role = c("aut", "ctb")), person("Kun", "Huang", email = "kunhuang@iu.edu", role = c("aut", "ctb")), person("Zhi", "Han", email = "zhihan@iu.edu", role = c("aut", "ctb")) )
Author: Zhi Huang [aut, cre], Jie Zhang [aut, ctb], Kun Huang [aut, ctb], Zhi Han [aut, ctb]
Maintainer: Zhi Huang <huang898@purdue.edu>
Description: Implementation based on Zhang, Jie & Huang, Kun (2014) <doi:10.4137/CIN.S14021> Normalized ImQCM: An Algorithm for Detecting Weak Quasi-Cliques in Weighted Graph with Applications in Gene Co-Expression Module Discovery in Cancers. Cancer informatics, 13, CIN-S14021.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: genefilter, Biobase, progress, stats, methods
Suggests: devtools, roxygen2
LazyData: true
RoxygenNote: 7.1.1
URL: https://github.com/huangzhii/lmQCM/
BugReports: https://github.com/huangzhii/lmQCM/issues/
NeedsCompilation: no
Packaged: 2021-01-13 19:10:40 UTC; zhihuan
Repository: CRAN
Date/Publication: 2021-01-14 00:10:02 UTC

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New package shinyIRT with initial version 0.1
Package: shinyIRT
Type: Package
Title: Item Response Theory Analysis with a 'shiny' Application
Version: 0.1
Author: Huseyin Yildiz [aut, cre]
Maintainer: Huseyin Yildiz <huseyinyildiz35@gmail.com>
Description: Performing Item Response Theory analysis such as parameter estimation, ability estimation, item and model fit analyse, local independence assumption, dimensionality assumption, characteristic and information curves under various models with a user friendly 'shiny' interface.
Imports: magrittr, shiny, shinydashboard, shinycssloaders, readxl, stats, mirt, psych, irtoys
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2021-01-10 14:16:03 UTC; husey
Repository: CRAN
Date/Publication: 2021-01-13 18:30:02 UTC

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New package valmetrics with initial version 1.0.0
Package: valmetrics
Type: Package
Title: Metrics and Plots for Model Evaluation
Version: 1.0.0
Authors@R: c(person("Kristin", "Piikki", email = "kristin.piikki@slu.se", role = c("aut", "cre", "cph") ), person("Johanna", "Wetterlind", email = "johanna.wetterlind@slu.se", role = c("aut", "cph") ), person("Mats", "Soderstrom", email = "mats.soderstrom@slu.se", role = c("aut", "cph") ), person("Bo", "Stenberg", email = "bo.stenberg@slu.se", role = c("aut", "cph") ) )
Maintainer: Kristin Piikki <kristin.piikki@slu.se>
Description: Functions for metrics and plots for model evaluation. Based on vectors of observed and predicted values. Method: Kristin Piikki, Johanna Wetterlind, Mats Soderstrom and Bo Stenberg (2021). <doi:10.1111/SUM.12694>.
Depends: R (>= 4.0.0)
Suggests: roxygen2, knitr, markdown
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-01-09 16:51:10 UTC; piikki
Author: Kristin Piikki [aut, cre, cph], Johanna Wetterlind [aut, cph], Mats Soderstrom [aut, cph], Bo Stenberg [aut, cph]
Repository: CRAN
Date/Publication: 2021-01-13 15:30:02 UTC

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New package listcompr with initial version 0.1.0
Package: listcompr
Version: 0.1.0
Date: 2021-01-10
Title: List Comprehension for R
Author: Patrick Roocks <mail@p-roocks.de>
Maintainer: Patrick Roocks <mail@p-roocks.de>
Description: Syntactic shortcuts for creating synthetic lists, vectors, and data frames using list comprehension.
URL: https://github.com/patrickroocks/listcompr
Depends: R (>= 3.1.2)
License: GPL (>= 2)
LazyData: true
Suggests: testthat, rmarkdown, knitr
Collate: 'listcompr.r' 'gen-list.r'
VignetteBuilder: knitr
RoxygenNote: 7.1.1
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2021-01-10 12:09:52 UTC; patrick
Repository: CRAN
Date/Publication: 2021-01-13 16:00:02 UTC

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New package html5 with initial version 0.1.0
Package: html5
Type: Package
Title: Generates HTML Tag Strings for HTML5 Elements Included in Mozilla's Documentation of HTML5
Version: 0.1.0
Author: Timothy Conwell
Maintainer: Timothy Conwell <timconwell@gmail.com>
Description: Generates HTML tag strings for HTML5 elements included in Mozilla's documentation of HTML5. Attributes are passed as parameters. If the attribute name is a reserved R word, the attribute is suffixed with _attr (ex: for_attr). To declare a DOCTYPE, wrap html with function html_doc(). Mozilla's documentation for HTML5 is available here: <https://developer.mozilla.org/en-US/docs/Web/HTML/Element>. Elements marked as obsolete are not included.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2021-01-09 22:54:08 UTC; tim
Repository: CRAN
Date/Publication: 2021-01-13 15:50:02 UTC

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New package ggvenn with initial version 0.1.8
Package: ggvenn
Title: Draw Venn Diagram by 'ggplot2'
Version: 0.1.8
Authors@R: person(given = "Linlin", family = "Yan", role = c("aut", "cre"), email = "yanlinlin82@gmail.com", comment = c(ORCID = "0000-0002-4990-6239"))
Author: Linlin Yan [aut, cre] (<https://orcid.org/0000-0002-4990-6239>)
Maintainer: Linlin Yan <yanlinlin82@gmail.com>
Description: An easy-to-use way to draw pretty venn diagram by 'ggplot2'.
Depends: dplyr, grid, ggplot2
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2021-01-09 16:07:45 UTC; yanll
Repository: CRAN
Date/Publication: 2021-01-13 15:30:09 UTC

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New package LTRCtrees with initial version 1.1.1
Package: LTRCtrees
Type: Package
Title: Survival Trees to Fit Left-Truncated and Right-Censored and Interval-Censored Survival Data
Version: 1.1.1
Description: Recursive partition algorithms designed for fitting survival tree with left-truncated and right censored (LTRC) data, as well as interval-censored data. The LTRC trees can also be used to fit survival tree with time-varying covariates.
Imports: partykit (>= 1.2.0), rpart, survival, inum, icenReg, Icens, interval
biocViews:
Suggests: Formula, rpart.plot, knitr, rmarkdown
Depends: R (>= 3.2.0)
License: GPL-3
LazyData: TRUE
Author: Wei Fu, Jeffrey Simonoff, Wenbo Jing
Maintainer: Wenbo Jing <wj2093@stern.nyu.edu>
VignetteBuilder: knitr, rmarkdown
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2021-01-11 01:31:53 UTC; WENBO JING
Repository: CRAN
Date/Publication: 2021-01-13 13:00:02 UTC

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New package VancouvR with initial version 0.1.2
Package: VancouvR
Type: Package
Title: Access the 'City of Vancouver' Open Data API
Version: 0.1.2
Author: Jens von Bergmann
Maintainer: Jens von Bergmann <jens@mountainmath.ca>
Description: Wrapper around the 'City of Vancouver' Open Data API <https://opendata.vancouver.ca/api/v2/console> to simplify and standardize access to 'City of Vancouver' open data. Functionality to list the data catalogue and access data and geographic records.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
RoxygenNote: 7.1.0.9000
Imports: dplyr, httr, rlang, urltools, readr, digest, sf, tibble, purrr
Suggests: knitr, rmarkdown, ggplot2, lwgeom, tidyr
VignetteBuilder: knitr
URL: https://github.com/mountainMath/VancouvR, https://mountainmath.github.io/VancouvR/
BugReports: https://github.com/mountainMath/VancouvR/issues
Packaged: 2021-01-12 22:42:18 UTC; jens
Repository: CRAN
Date/Publication: 2021-01-13 11:10:05 UTC

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New package SparseTSCGM with initial version 4.0
Package: SparseTSCGM
Type: Package
Title: Sparse Time Series Chain Graphical Models
Authors@R: c(person("Fentaw", "Abegaz", role=c("aut","cre"), email="f.abegaz.yazew@rug.nl"), person("Ernst", "Wit", role = "aut"))
Version: 4.0
Date: 2021-01-12
Depends: R(>= 3.3.2)
Imports: glasso,longitudinal, huge, MASS, mvtnorm, network, abind, stats
Author: Fentaw Abegaz [aut, cre], Ernst Wit [aut]
Maintainer: Fentaw Abegaz <f.abegaz.yazew@rug.nl>
Description: Computes sparse vector autoregressive coefficients and precision matrices for time series chain graphical models. Fentaw Abegaz and Ernst Wit (2013) <doi:10.1093/biostatistics/kxt005>.
License: GPL (>= 3)
NeedsCompilation: yes
Packaged: 2021-01-12 22:59:20 UTC; Fentaw
Repository: CRAN
Date/Publication: 2021-01-13 11:10:08 UTC

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New package NFCP with initial version 0.1.0
Package: NFCP
Title: N-Factor Commodity Pricing Through Term Structure Estimation
Version: 0.1.0
Authors@R: c(person("Thomas", "Aspinall", email = "tomaspinall2512@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-6968-1989")), person("Adrian", "Gepp", email = "adgepp@bond.edu.au", role = c("aut"), comment = c(ORCID = "0000-0003-1666-5501")), person("Geoff", "Harris", email = "gharris@bond.edu.au", role = c("aut"), comment = c(ORCID = "0000-0003-4284-8619")), person("Simone", "Kelly", email = "skelly@bond.edu.au", role = c("aut"), comment = c(ORCID = "0000-0002-6528-8557")), person("Colette", "Southam", email = "csoutham@bond.edu.au", role = c("aut"), comment = c(ORCID = "0000-0001-7263-2347")), person("Bruce", "Vanstone", email = "bvanston@bond.edu.au", role = c("aut"), comment = c(ORCID = "0000-0002-3977-2468")) )
Description: Commodity pricing models are (systems of) stochastic differential equations that are utilized for the valuation and hedging of commodity contingent claims (i.e. derivative products on the commodity) and other commodity related investments. Commodity pricing models that capture market dynamics are of great importance to commodity market participants in order to exercise sound investment and risk-management strategies. Parameters of commodity pricing models are estimated through maximum likelihood estimation, using available term structure futures data of a commodity. 'NFCP' (n-factor commodity pricing) provides a framework for the modeling, parameter estimation, probabilistic forecasting, option valuation and simulation of commodity prices through state space and Monte Carlo methods, risk-neutral valuation and Kalman filtering. 'NFCP' allows the commodity pricing model to consist of n correlated factors, with both random walk and mean-reverting elements. The n-factor commodity pricing model framework was first presented in the work of Cortazar and Naranjo (2006) <doi:10.1002/fut.20198>. Examples presented in 'NFCP' replicate the two-factor crude oil commodity pricing model presented in the prolific work of Schwartz and Smith (2000) <doi:10.1287/mnsc.46.7.893.12034> with the approximate term structure futures data applied within this study provided in the 'NFCP' package.
Depends: R (>= 3.5.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1.9000
RdMacros: mathjaxr, Rdpack
Suggests: OptionPricing, knitr, rmarkdown
Imports: FKF.SP, MASS, numDeriv, parallel, rgenoud, stats, mathjaxr, Rdpack, curl
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-01-09 04:05:01 UTC; Thomas Aspinall
Author: Thomas Aspinall [aut, cre] (<https://orcid.org/0000-0002-6968-1989>), Adrian Gepp [aut] (<https://orcid.org/0000-0003-1666-5501>), Geoff Harris [aut] (<https://orcid.org/0000-0003-4284-8619>), Simone Kelly [aut] (<https://orcid.org/0000-0002-6528-8557>), Colette Southam [aut] (<https://orcid.org/0000-0001-7263-2347>), Bruce Vanstone [aut] (<https://orcid.org/0000-0002-3977-2468>)
Maintainer: Thomas Aspinall <tomaspinall2512@gmail.com>
Repository: CRAN
Date/Publication: 2021-01-13 12:00:06 UTC

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New package mediateP with initial version 0.1.0
Package: mediateP
Type: Package
Title: Mediation Analysis Based on the Product Method
Version: 0.1.0
Author: Chao Cheng
Maintainer: Chao Cheng <c.cheng@yale.edu>
Depends: R (>= 3.6.0)
Imports: boot
Description: Functions for calculating the point and interval estimates of the natural indirect effect (NIE), total effect (TE), and mediation proportion (MP), based on the product approach. We perform the methods considered in Chao Cheng, Donna Spiegelman, and Fan Li. (2020+) <https://github.com/chaochengstat/chaochengstat.github.io/blob/master/manuscript_Epidemiologic_Methods.pdf>.
License: GPL
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2021-01-08 20:10:09 UTC; chaocheng
Repository: CRAN
Date/Publication: 2021-01-13 11:30:02 UTC

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New package fullROC with initial version 0.1.0
Package: fullROC
Type: Package
Title: Plot Full ROC Curves using Eyewitness Lineup Data
Version: 0.1.0
Authors@R: person("Yueran", "Yang", email = "yuerany@unr.edu", role = c("aut", "cre"))
Description: Enable researchers to adjust identification rates using the 1/(lineup size) method, generate the full receiver operating characteristic (ROC) curves, and statistically compare the area under the curves (AUC). References: Yueran Yang & Andrew Smith. (2020). "fullROC: An R package for generating and analyzing eyewitness-lineup ROC curves". <doi:10.13140/RG.2.2.20415.94885/1> , Andrew Smith, Yueran Yang, & Gary Wells. (2020). "Distinguishing between investigator discriminability and eyewitness discriminability: A method for creating full receiver operating characteristic curves of lineup identification performance". Perspectives on Psychological Science, 15(3), 589-607. <doi:10.1177/1745691620902426>.
BugReports: https://github.com/yuerany/fullROC/issues
Language: en-US
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Imports: stats, graphics
NeedsCompilation: no
Packaged: 2021-01-09 00:56:52 UTC; yueran
Author: Yueran Yang [aut, cre]
Maintainer: Yueran Yang <yuerany@unr.edu>
Repository: CRAN
Date/Publication: 2021-01-13 11:50:10 UTC

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New package fdaPOIFD with initial version 1.0.0
Package: fdaPOIFD
Type: Package
Title: Partially Observed Integrated Functional Depth
Version: 1.0.0
Authors@R: c(person("Antonio", "Elías", email = "antonioefz91@gmail.com", role = c("aut", "cre")), person("Raúl", "Jiménez", email = "", role = c("ctb")), person("Anna M.", "Paganoni", email = "", role = c("ctb")), person("Laura M.", "Sangalli", email = "", role = c("ctb")))
Maintainer: Antonio Elías <antonioefz91@gmail.com>
Description: Integrated Depths for Partially Observed Functional Data (PoFD). Applications to visualization, outlier detection and classification. Software companion for Elías, Antonio, Jiménez, Raúl, Paganoni, Anna M. and Sangalli, Laura M., (2020), "Integrated Depth for Partially Observed Functional Data".
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Depends: R (>= 3.5.0)
Imports: ggplot2, tibble, magrittr, reshape2, patchwork, MASS, fdapace, FastGP, stats
URL: https://github.com/aefdz/fdaPOIFD
BugReports: https://github.com/aefdz/fdaPOIFD
NeedsCompilation: no
Packaged: 2021-01-08 16:56:50 UTC; anton
Author: Antonio Elías [aut, cre], Raúl Jiménez [ctb], Anna M. Paganoni [ctb], Laura M. Sangalli [ctb]
Repository: CRAN
Date/Publication: 2021-01-13 12:00:02 UTC

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New package dejaVu with initial version 0.2.1
Package: dejaVu
Type: Package
Title: Multiple Imputation for Recurrent Events
Version: 0.2.1
Authors@R: c( person("Nikolas", "Burkoff", role=c("aut")), person("Paul", "Metcalfe", email='paul.metcalfe@astrazeneca.com', role=c("aut")), person("Jonathan", "Bartlett", email='j.w.bartlett@bath.ac.uk', role=c("aut", "cre")), person("David", "Ruau", role=c("aut")) )
Maintainer: Jonathan Bartlett <j.w.bartlett@bath.ac.uk>
Description: Performs reference based multiple imputation of recurrent event data based on a negative binomial regression model, as described by Keene et al (2014) <doi:10.1002/pst.1624>.
License: GPL (>= 2)
LazyData: true
Suggests: knitr, testthat,
Depends: R (>= 3.1.0)
Imports: MASS, stats
VignetteBuilder: knitr
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2021-01-08 23:27:50 UTC; JWB-beast
Author: Nikolas Burkoff [aut], Paul Metcalfe [aut], Jonathan Bartlett [aut, cre], David Ruau [aut]
Repository: CRAN
Date/Publication: 2021-01-13 11:50:16 UTC

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New package vectorwavelet with initial version 0.1.0
Package: vectorwavelet
Type: Package
Title: Vector Wavelet Coherence for Multiple Time Series
Version: 0.1.0
Date: 2021-01-04
Author: Tunc Oygur [aut, cre], Gazanfer Unal [aut], Tarik C. Gouhier [ctb], Aslak Grinsted [ctb], Viliam Simko [ctb]
Maintainer: Tunc Oygur <info@tuncoygur.com.tr>
Description: New wavelet methodology (vector wavelet coherence) (Oygur, T., Unal, G, 2020 <doi:10.1007/s40435-020-00706-y>) to handle dynamic co-movements of multivariate time series via extending multiple and quadruple wavelet coherence methodologies. This package can be used to perform multiple wavelet coherence, quadruple wavelet coherence, and n-dimensional vector wavelet coherence analyses.
License: GPL (>= 2)
URL: https://github.com/toygur/vectorwavelet
BugReports: https://github.com/toygur/vectorwavelet/issues
Depends: biwavelet (>= 0.20.19)
Imports: iterators, spam, maps, fields, foreach, Rcpp
Suggests: knitr, rmarkdown, devtools
Encoding: UTF-8
LazyData: TRUE
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2021-01-08 19:29:56 UTC; toygur
Repository: CRAN
Date/Publication: 2021-01-13 10:50:02 UTC

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New package marginalRisk with initial version 2021.1-7
Package: marginalRisk
LazyLoad: yes
LazyData: yes
Version: 2021.1-7
Title: Estimating Marginal Risk
Authors@R: c(person("Youyi", "Fong", role = "cre", email = "youyifong@gmail.com"), person("Peter", "Gilbert", role = "aut", email = "pgilbert@scharp.org") )
Depends: R (>= 3.6)
Imports:
Suggests: RUnit, R.rsp, survival
Description: Estimates risk as a function of a marker by integrating over other covariates in a conditional risk model.
VignetteBuilder: R.rsp
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2021-01-08 17:32:41 UTC; Youyi
Author: Youyi Fong [cre], Peter Gilbert [aut]
Maintainer: Youyi Fong <youyifong@gmail.com>
Repository: CRAN
Date/Publication: 2021-01-13 10:50:18 UTC

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Mon, 11 Jan 2021

New package lfe with initial version 2.8-6
Package: lfe
Version: 2.8-6
Date: 2021-01-04
Title: Linear Group Fixed Effects
Authors@R: c(person("Simen", "Gaure", email="Simen.Gaure@frisch.uio.no", role=c("aut"), comment=c(ORCID="https://orcid.org/0000-0001-7251-8747")), person("Grant","McDermott", email="grantmcd@uoregon.edu", role="ctb"), person("Karl", "Dunkle Werner", role="ctb"), person("Matthieu","Stigler", email = "Matthieu.Stigler@gmail.com", role= c("ctb", "cre"), comment =c(ORCID="0000-0002-6802-4290")), person("Daniel","Lüdecke",email="mail@danielluedecke.de",role="ctb"))
Copyright: 2011-2019, Simen Gaure
Depends: R (>= 2.15.2), Matrix (>= 1.1-2)
Imports: Formula, xtable, compiler, utils, methods, sandwich, parallel
Suggests: knitr, digest, igraph, plm, cubature (>= 2.0.3), numDeriv, data.table, alpaca, testthat
VignetteBuilder: knitr
ByteCompile: yes
Description: Transforms away factors with many levels prior to doing an OLS. Useful for estimating linear models with multiple group fixed effects, and for estimating linear models which uses factors with many levels as pure control variables. See Gaure (2013) <doi:10.1016/j.csda.2013.03.024> Includes support for instrumental variables, conditional F statistics for weak instruments, robust and multi-way clustered standard errors, as well as limited mobility bias correction (Gaure 2014 <doi:10.1002/sta4.68>). WARNING: This package is NOT under active development anymore, no further improvements are to be expected, and the package is at risk of being removed from CRAN.
License: Artistic-2.0
Classification/JEL: C13, C23, C60
Classification/MSC: 62J05, 65F10, 65F50
URL: https://github.com/sgaure/lfe
BugReports: https://github.com/sgaure/lfe/issues
Encoding: UTF-8
RoxygenNote: 7.1.1
NeedsCompilation: yes
Packaged: 2021-01-04 17:50:26 UTC; matifou
Author: Simen Gaure [aut] (<https://orcid.org/0000-0001-7251-8747>), Grant McDermott [ctb], Karl Dunkle Werner [ctb], Matthieu Stigler [ctb, cre] (<https://orcid.org/0000-0002-6802-4290>), Daniel Lüdecke [ctb]
Maintainer: Matthieu Stigler <Matthieu.Stigler@gmail.com>
Repository: CRAN
Date/Publication: 2021-01-11 15:50:02 UTC

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New package arcos with initial version 1.25
Package: arcos
Type: Package
Title: Load ARCOS Prescription Data Prepared by the Washington Post
Version: 1.25
Date: 2020-12-30
Authors@R: c( person(given="Steven", family="Rich", email="steven.rich@washpost.com",role=c("aut", "ctb")), person(given="Andrew", family="Ba Tran", email="andrew.tran@washpost.com", role=c("aut", "cre")), person(given="Aaron", family="Williams", email="aaron.williams@washpost.com", role=c("aut", "ctb")), person(given="Jason", family="Holt", email="jason.holt@washpost.com", role=c("ctb")), person(given="The Washington Post", role=c("cph")), person(given="The Charleston Gazette-Mail", role=c("cph")) )
URL: https://github.com/wpinvestigative/arcos
BugReports: https://github.com/wpinvestigative/arcos/issues
Description: A wrapper for the 'ARCOS API' <https://arcos-api.ext.nile.works/__swagger__/> that returns raw and summarized data frames from the Drug Enforcement Administration’s Automation of Reports and Consolidated Orders System, a database that monitors controlled substances transactions between manufacturers and distributors which was made public by The Washington Post and The Charleston Gazette-Mail.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.3.0)
Suggests: ggplot2, forcats, leaflet, knitr, sf, tigris, testthat (>= 2.1.0), rmarkdown, data.table, formattable, geofacet, lubridate, scales, viridis, zoo
Imports: stringr, magrittr, jsonlite, dplyr, tidyr, urltools, httr, curl, vroom
RoxygenNote: 7.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-01-11 03:34:32 UTC; trana
Author: Steven Rich [aut, ctb], Andrew Ba Tran [aut, cre], Aaron Williams [aut, ctb], Jason Holt [ctb], The Washington Post [cph], The Charleston Gazette-Mail [cph]
Maintainer: Andrew Ba Tran <andrew.tran@washpost.com>
Repository: CRAN
Date/Publication: 2021-01-11 15:40:02 UTC

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New package DSWE with initial version 1.5.1
Package: DSWE
Title: Data Science for Wind Energy
Version: 1.5.1
Authors@R: c( person(given = "Nitesh", family = "Kumar", role = c("aut"), email = "nitesh.kumar@tamu.edu"), person(given = "Abhinav", family = "Prakash", role = c("aut"), email = "abhinavp@tamu.edu"), person(given = "Yu", family = "Ding", role = c("aut","cre"), email = "yuding@tamu.edu"), person(given = "Rui", family = "Tuo", role = c("ctb","cph"), email = "ruituo@tamu.edu"))
Description: Data science methods used in wind energy applications. Current functionalities include creating a multi-dimensional power curve model, performing power curve function comparison, and covariate matching. Relevant works for the developed functions are: funGP() - Prakash et al. (2020) <arxiv:2003.07899>, AMK() - Lee et al. (2015) <doi:10.1080/01621459.2014.977385>, tempGP() - Prakash et al. (2020) <arxiv:2012.01349>, ComparePCurve() - Ding et al. (2020) <arxiv:2005.08652>, All other functions - Ding (2019, ISBN:9780429956508).
Depends: R (>= 3.5.0)
License: MIT + file LICENSE
URL: https://github.com/TAMU-AML/DSWE-Package, https://aml.engr.tamu.edu/book-dswe/
BugReports: https://github.com/TAMU-AML/DSWE-Package/issues
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
LinkingTo: Rcpp (>= 1.0.4.6) , RcppArmadillo (>= 0.9.870.2.0)
Imports: Rcpp (>= 1.0.4.6) , matrixStats (>= 0.55.0) , FNN (>= 1.1.3) , KernSmooth (>= 2.23-16) , mixtools (>= 1.1.0), BayesTree (>= 0.3-1.4), gss (>= 2.2-2), e1071 (>= 1.7-3), stats (>= 3.5.0)
NeedsCompilation: yes
Packaged: 2021-01-08 16:45:32 UTC; abhinavprakash
Author: Nitesh Kumar [aut], Abhinav Prakash [aut], Yu Ding [aut, cre], Rui Tuo [ctb, cph]
Maintainer: Yu Ding <yuding@tamu.edu>
Repository: CRAN
Date/Publication: 2021-01-11 10:30:07 UTC

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New package shinydrive with initial version 0.1.1
Package: shinydrive
Type: Package
Title: File Sharing Shiny Module
Version: 0.1.1
Authors@R: c( person("Benoit", "Thieurmel", email = "benoit.thieurmel@datastorm.fr", role = c("aut", "cre")), person("Titouan", "Robert", email = "titouan.robert@datastorm.fr", role = c("aut")), person("Thibaut", "Dubois", email = "thibaut.dubois@datastorm.fr", role = c("aut")) )
Description: Shiny module for easily sharing files between users. Admin can add, remove, edit and download file. User can only download file. It's also possible to manage files using R functions directly.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Imports: htmltools, shiny, tools, yaml, DT, R.utils, knitr
Suggests: testthat
NeedsCompilation: no
Packaged: 2021-01-08 08:41:21 UTC; BenoitThieurmel
Author: Benoit Thieurmel [aut, cre], Titouan Robert [aut], Thibaut Dubois [aut]
Maintainer: Benoit Thieurmel <benoit.thieurmel@datastorm.fr>
Repository: CRAN
Date/Publication: 2021-01-11 09:30:02 UTC

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New package rticulate with initial version 1.7.2
Package: rticulate
Type: Package
Title: Ultrasound Tongue Imaging in R
Version: 1.7.2
Date: 2021-01-08
Authors@R: c(person(given = "Stefano", family = "Coretta", email = paste0("stefano.coretta", "@", "gmail.com"), role = c("aut", "cre")))
Maintainer: Stefano Coretta <stefano.coretta@gmail.com>
Description: It provides functions for processing Articulate Assistant Advanced™ (AAA) export files and plot tongue contour data from any system.
URL: https://github.com/stefanocoretta/rticulate
BugReports: https://github.com/stefanocoretta/rticulate/issues
Depends: R (>= 3.0.0)
Encoding: UTF-8
LazyData: true
Imports: dplyr, ggplot2, glue, magrittr, mgcv, purrr, readr, rlang, stats, stringr, tibble, tidymv, tidyr, tidyverse, tidyselect
RoxygenNote: 7.1.1
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
Language: en_GB
License: MIT + file LICENSE
NeedsCompilation: no
Packaged: 2021-01-08 11:57:57 UTC; stefano
Author: Stefano Coretta [aut, cre]
Repository: CRAN
Date/Publication: 2021-01-11 09:50:02 UTC

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New package onlineBcp with initial version 0.1.0
Package: onlineBcp
Type: Package
Title: Online Bayesian Methods for Change Point Analysis
Version: 0.1.0
Authors@R: c( person("Hongyan", "Xu", email = "hxu@augusta.edu", role = c("cre", "aut")), person("Ayten", "Yigiter", email = "yigiter@hacettepe.edu.tr", role = "aut"), person("Jie", "Chen", email = "jchen@augusta.edu", role = "aut"))
Description: It implements the online Bayesian methods for change point analysis. It can also perform missing data imputation with methods from 'VIM'. The reference is Yigiter A, Chen J, An L, Danacioglu N (2015) <doi:10.1080/02664763.2014.1001330>.
License: GPL
Depends: R (>= 3.1.0)
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
Imports: VIM
Suggests: testthat
NeedsCompilation: no
Packaged: 2021-01-07 21:45:27 UTC; hxu
Author: Hongyan Xu [cre, aut], Ayten Yigiter [aut], Jie Chen [aut]
Maintainer: Hongyan Xu <hxu@augusta.edu>
Repository: CRAN
Date/Publication: 2021-01-11 09:20:02 UTC

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New package JMbayes2 with initial version 0.1-1
Package: JMbayes2
Type: Package
Title: Extended Joint Models for Longitudinal and Time-to-Event Data
Version: 0.1-1
Authors@R: c(person("Dimitris", "Rizopoulos", email = "d.rizopoulos@erasmusmc.nl", role = c("aut", "cre"), comment = c(ORCID = '0000-0001-9397-0900')), person("Grigorios", "Papageorgiou", email = "g.papageorgiou@erasmusmc.nl", role = "aut"), person("Pedro", "Miranda Afonso", email = "p.mirandaafonso@erasmusmc.nl", role = "aut"))
Maintainer: Dimitris Rizopoulos <d.rizopoulos@erasmusmc.nl>
Date: 2021-01-08
BugReports: https://github.com/drizopoulos/JMbayes2/issues
Description: Fit joint models for longitudinal and time-to-event data under the Bayesian approach. Multiple longitudinal outcomes of mixed type (continuous/categorical) and multiple event times (competing risks and multi-state processes) are accommodated. Rizopoulos (2012, ISBN:9781439872864).
Suggests: lattice, knitr, rmarkdown, pkgdown
Encoding: UTF-8
Depends: survival, nlme, GLMMadaptive, splines
Imports: coda, Rcpp, parallel, matrixStats, ggplot2, gridExtra
LinkingTo: Rcpp, RcppArmadillo
LazyLoad: yes
LazyData: yes
License: GPL (>= 3)
URL: https://drizopoulos.github.io/JMbayes2/, https://github.com/drizopoulos/JMbayes2
NeedsCompilation: yes
Packaged: 2021-01-07 18:07:39 UTC; drizo
Author: Dimitris Rizopoulos [aut, cre] (<https://orcid.org/0000-0001-9397-0900>), Grigorios Papageorgiou [aut], Pedro Miranda Afonso [aut]
Repository: CRAN
Date/Publication: 2021-01-11 09:30:05 UTC

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New package fritools with initial version 1.0.0
Package: fritools
Title: Utilities for the Forest Research Institute of the State Baden-Wuerttemberg
Version: 1.0.0
Authors@R: person(given = "Andreas Dominik", family = "Cullmann", role = c("aut", "cre"), email = "fvafrcu@mailbox.org")
Description: Miscellaneous utilities, tools and helper functions for finding and searching files on disk, searching for and removing R objects from the workspace. These are utilities for packages <https://CRAN.R-project.org/package=cleanr>, <https://CRAN.R-project.org/package=document>, <https://CRAN.R-project.org/package=fakemake>, <https://CRAN.R-project.org/package=packager> and <https://CRAN.R-project.org/package=rasciidoc>. Does not import or depend on any third party party package, but on core R only.
License: BSD_2_clause + file LICENSE
URL: https://gitlab.com/fvafrcu/fritools
Depends: R (>= 3.5.2)
Imports:
Suggests: checkmate, desc, packager, pkgload, rasciidoc, RUnit, testthat (>= 3.0.0)
VignetteBuilder: rasciidoc
Encoding: UTF-8
LazyData: true
Language: en-US
RoxygenNote: 7.1.1
Config/testthat/edition: 3
NeedsCompilation: no
Packaged: 2021-01-08 11:33:59 UTC; qwer
Author: Andreas Dominik Cullmann [aut, cre]
Maintainer: Andreas Dominik Cullmann <fvafrcu@mailbox.org>
Repository: CRAN
Date/Publication: 2021-01-11 09:50:05 UTC

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New package ensembleTax with initial version 1.0.2
Package: ensembleTax
Title: Ensemble Taxonomic Assignments of Amplicon Sequencing Data
Version: 1.0.2
Author: Dylan Catlett [aut, cre], Kevin Son [ctb], Connie Liang [ctb]
Maintainer: Dylan Catlett <dcat4444@gmail.com>
Description: Creates ensemble taxonomic assignments of amplicon sequencing data in R using outputs of multiple taxonomic assignment algorithms and/or reference databases. Includes flexible algorithms for mapping taxonomic nomenclatures onto one another and for computing ensemble taxonomic assignments.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Imports: dplyr, Biostrings, DECIPHER, stringr, usethis
Depends: R (>= 2.10)
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-01-07 15:36:41 UTC; dylancatlett
Repository: CRAN
Date/Publication: 2021-01-11 09:20:05 UTC

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New package DOPE with initial version 1.0.4
Package: DOPE
Title: Drug Ontology Parsing Engine
Version: 1.0.4
Authors@R: c( person(given = "Raymond", family = "Balise", role = c("aut", "cre"), email = "balise@miami.edu", comment = c(ORCID = "0000-0002-9856-5901")), person(given = "Layla", family = "Bouzoubaa", role = c("aut"), email = "lab218@miami.edu", comment = c(ORCID = "https://orcid.org/0000-0002-6616-0950")), person(given = "Gabriel", family = "Odom", role = c("aut"), email = "gabriel.odom@fiu.edu", comment = c(ORCID = "0000-0003-1341-4555")))
Description: Provides information on drug names (brand, generic and street) for drugs tracked by the DEA. There are functions that will search synonyms and return the drug names and types. The vignettes have extensive information on the work done to create the data for the package.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Depends: R (>= 2.10)
Imports: dplyr
Suggests: dm, knitr, rmarkdown, conflicted, purrr, readr, readxl, rvest, sqldf, stringr, tidyr, tibble, testthat, usethis, xml2
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-01-07 15:52:57 UTC; laylabouzoubaa
Author: Raymond Balise [aut, cre] (<https://orcid.org/0000-0002-9856-5901>), Layla Bouzoubaa [aut] (<https://orcid.org/0000-0002-6616-0950>), Gabriel Odom [aut] (<https://orcid.org/0000-0003-1341-4555>)
Maintainer: Raymond Balise <balise@miami.edu>
Repository: CRAN
Date/Publication: 2021-01-11 09:10:02 UTC

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New package dataprep with initial version 0.1.0
Package: dataprep
Type: Package
Title: Efficient and Flexible Data Preprocessing Tools
Version: 0.1.0
Author: Chun-Sheng Liang <lcs14@mails.tsinghua.edu.cn; liangchunsheng@lzu.edu.cn>, Hao Wu, Hai-Yan Li, Qiang Zhang, Zhanqing Li, Ke-Bin He, Tsinghua University, Lanzhou University
Maintainer: Chun-Sheng Liang <liangchunsheng@lzu.edu.cn>
Description: Efficiently and flexibly preprocess data using a set of data filtering, deletion, and interpolation tools. These data preprocessing methods are developed based on the principles of completeness, accuracy, threshold method, and linear interpolation and through the setting of constraint conditions, time completion & recovery, and fast & efficient calculation of moving averages. Key preprocessing steps include deletions of variables and observations, outlier removal, and missing values (NA) interpolation, which are dependent on the incomplete and dispersed degrees of raw data. They clean data more accurately, keep more samples, and add no outliers after interpolation, compared with ordinary methods. Auto-identification of consecutive NA via moving averages is used in observation deletion, outlier removal, and NA interpolation; thus, new outliers are not generated in interpolation. Conditional extremum is proposed to realize point-by-point weighed outlier removal that saves non-outliers from being removed. Plus, time series interpolation with values to refer to within short periods further ensures reliable interpolation. These methods are based on and improved from the reference: Liang, C.-S., Wu, H., Li, H.-Y., Zhang, Q., Li, Z. & He, K.-B. (2020) <doi:10.1016/j.scitotenv.2020.140923>.
Depends: R (>= 3.5.0)
Imports: RcppRoll, ggplot2, scales, foreach, doParallel, dplyr, reshape2, tidyr, zoo
License: GPL (>= 2)
Suggests: knitr, rmarkdown
VignetteBuilder: knitr, rmarkdown
Encoding: UTF-8
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2021-01-08 15:04:51 UTC; 92576
Repository: CRAN
Date/Publication: 2021-01-11 10:00:02 UTC

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New package SAMTx with initial version 0.1.0
Package: SAMTx
Type: Package
Title: Sensitivity Assessment to Unmeasured Confounding with Multiple Treatments
Version: 0.1.0
Authors@R: c( person("Liangyuan", "Hu", role = "aut", email = "Liangyuan.Hu@mountsinai.org"), person("Jungang", "Zou", role = "aut", email = "jz3183@cumc.columbia.edu"), person("Jiayi", "Ji", role = c("aut", "cre"), email = "Jiayi.Ji@mountsinai.org"))
Description: A sensitivity analysis approach for unmeasured confounding in observational data with multiple treatments and a binary outcome. This approach derives the general bias formula and provides adjusted causal effect estimates in response to various assumptions about the degree of unmeasured confounding. Nested multiple imputation is embedded within the Bayesian framework to integrate uncertainty about the sensitivity parameters and sampling variability. Bayesian Additive Regression Model (BART) is used for outcome modeling. The causal estimands are the average treatment effects (ATE) based on the risk difference. For more details, see paper: Hu L et al. (2020) A flexible sensitivity analysis approach for unmeasured confounding with a multiple treatments and a binary outcome <arXiv:2012.06093>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Imports: BART
NeedsCompilation: no
Packaged: 2021-01-07 13:58:13 UTC; jiayi
Author: Liangyuan Hu [aut], Jungang Zou [aut], Jiayi Ji [aut, cre]
Maintainer: Jiayi Ji <Jiayi.Ji@mountsinai.org>
Repository: CRAN
Date/Publication: 2021-01-11 08:50:14 UTC

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New package prompter with initial version 1.0.0
Package: prompter
Type: Package
Title: Add Tooltips in 'Shiny' Apps with 'Hint.css'
Version: 1.0.0
Authors@R: person(given = "Etienne", family = "Bacher", role = c("aut", "cre", "cph"), email = "etienne.bacher@protonmail.com")
Description: In 'Shiny' apps, it is sometimes useful to store information on a particular item in a tooltip. 'Prompter' allows you to easily create such tooltips, using 'Hint.css'.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: shiny
RoxygenNote: 7.1.1
URL: https://github.com/etiennebacher/prompter
BugReports: https://github.com/etiennebacher/prompter/issues
Suggests: testthat, spelling
Language: en-US
NeedsCompilation: no
Packaged: 2021-01-07 16:27:04 UTC; etienne
Author: Etienne Bacher [aut, cre, cph]
Maintainer: Etienne Bacher <etienne.bacher@protonmail.com>
Repository: CRAN
Date/Publication: 2021-01-11 08:40:02 UTC

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New package eList with initial version 0.0.1.0
Package: eList
Title: List Comprehension and Tools
Version: 0.0.1.0
Author: Chris Mann <cmann3@unl.edu>
Maintainer: Chris Mann <cmann3@unl.edu>
Description: Create list comprehensions (and other types of comprehension) similar to those in 'python', 'haskell', and other languages. List comprehension in 'R' converts a regular for() loop into a vectorized lapply() function. Support for looping with multiple variables, parallelization, and across non-standard objects included. Package also contains a variety of functions to help with list comprehension and higher order functions for manipulating lists.
License: MIT + file LICENSE
Encoding: UTF-8
Suggests: knitr, rmarkdown, stats, parallel
VignetteBuilder: knitr
LazyData: true
RoxygenNote: 7.0.2
NeedsCompilation: no
Packaged: 2021-01-07 16:32:42 UTC; chris
Repository: CRAN
Date/Publication: 2021-01-11 08:50:06 UTC

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New package cursr with initial version 0.1.0
Package: cursr
Type: Package
Title: Cursor and Terminal Manipulation
Version: 0.1.0
Author: Chris Mann
Maintainer: Chris Mann <cmann3@unl.edu>
Description: A toolbox for developing applications, games, simulations, or agent-based models in the R terminal. Included functions allow users to move the cursor around the terminal screen, change text colors and attributes, clear the screen, hide and show the cursor, map key presses to functions, draw shapes and curves, among others. Most functionalities require users to be in a terminal (not the R GUI).
Imports: keypress
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
NeedsCompilation: no
Packaged: 2021-01-07 16:52:37 UTC; chris
Repository: CRAN
Date/Publication: 2021-01-11 08:50:09 UTC

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New package mvProbit with initial version 0.1-10
Package: mvProbit
Version: 0.1-10
Date: 2021-01-07
Title: Multivariate Probit Models
Author: Arne Henningsen <arne.henningsen@gmail.com>
Maintainer: Arne Henningsen <arne.henningsen@gmail.com>
Depends: R (>= 2.4.0), mvtnorm (>= 0.9-9994), maxLik (>= 1.0-0), abind (>= 1.3-0)
Imports: bayesm (>= 2.2-4), miscTools (>= 0.6-11)
Description: Tools for estimating multivariate probit models, calculating conditional and unconditional expectations, and calculating marginal effects on conditional and unconditional expectations.
License: GPL (>= 2)
URL: http://www.sampleSelection.org
NeedsCompilation: no
Packaged: 2021-01-07 15:58:00 UTC; gsl324
Repository: CRAN
Date/Publication: 2021-01-11 06:50:02 UTC

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New package eBsc with initial version 4.13
Package: eBsc
Type: Package
Title: "Empirical Bayes Smoothing Splines with Correlated Errors"
Version: 4.13
Date: 2021-01-06
Author: Francisco Rosales, Tatyana Krivobokova, Paulo Serra.
Description: Presents a statistical method that uses a recursive algorithm for signal extraction. The method handles a non-parametric estimation for the correlation of the errors. See "Serra", "Krivobokova" and "Rosales" (2018) <arXiv:1812.06948> for details.
License: GPL-2
Imports: Brobdingnag, parallel, nlme, Matrix, MASS, splines, Rcpp
LinkingTo: Rcpp, RcppArmadillo
NeedsCompilation: yes
Maintainer: John Barrera <johnkevinbarrera@gmail.com>
Packaged: 2021-01-07 01:48:20 UTC; john
Repository: CRAN
Date/Publication: 2021-01-11 06:50:09 UTC

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New package briskaR with initial version 1.0.2
Package: briskaR
Type: Package
Encoding: UTF-8
Title: Biological Risk Assessment
Version: 1.0.2
Date: 2021-01-04
Authors@R: c(person("Virgile", "Baudrot", role = "aut", email = "virgile.baudrot@posteo.net"), person("Emily", "Walker", role = "aut", email = "emily.walker@inrae.fr"), person("Jean-Francois", "Rey", role = c("aut","cre"), email = "jean-francois.rey@inrae.fr"), person("Melen", "Leclerc", role = "aut", email = "melen.leclerc@inrae.fr"), person("Samuel", "Soubeyrand", role = "ctb", email = "samuel.soubeyrand@inrae.fr"), person("Marc", "Bourotte", role = "ctb", email = "marc.bourotte@inrae.fr"))
Author: Virgile Baudrot [aut], Emily Walker [aut], Jean-Francois Rey [aut, cre], Melen Leclerc [aut], Samuel Soubeyrand [ctb], Marc Bourotte [ctb]
Maintainer: Jean-Francois Rey <jean-francois.rey@inrae.fr>
Description: A spatio-temporal exposure-hazard model for assessing biological risk and impact. The model is based on stochastic geometry for describing the landscape and the exposed individuals, a dispersal kernel for the dissemination of contaminants, a set of tools to handle spatio-temporal dataframe and ecotoxicological equations. Walker E, Leclerc M, Rey JF, Beaudouin R, Soubeyrand S, and Messean A, (2017), A Spatio-Temporal Exposure-Hazard Model for Assessing Biological Risk and Impact, Risk Analysis, <doi:10.1111/risa.12941>. Leclerc M, Walker E, Messean A, Soubeyrand S (2018), Spatial exposure-hazard and landscape models for assessing the impact of GM crops on non-target organisms, Science of the Total Environment, 624, 470-479.
URL: https://gitlab.paca.inrae.fr/biosp/briskaR
BugReports: https://gitlab.paca.inrae.fr/biosp/briskaR/-/issues
License: GPL (>= 2) | file LICENSE
LazyData: True
BuildVignettes: True
NeedsCompilation: yes
VignetteBuilder: knitr
Depends: methods, grDevices (>= 3.0.0), graphics (>= 3.0.0), stats (>= 3.0.2), R (>= 3.0.2)
Imports: deldir(>= 0.1), deSolve, fasterize, fftwtools(>= 0.9.6), MASS(>= 7.3.29), mvtnorm(>= 1.0.2), raster(>= 2.3.0), Rcpp (>= 1.0.0), rgdal (>= 0.9), rgeos(>= 0.3), sf (>= 0.7-1), sp (>= 1.0-17)
LinkingTo: testthat (>= 3.0.0), Rcpp, RcppArmadillo
Suggests: ggplot2, knitr, rmarkdown, dplyr, testthat (>= 3.0.1), xml2
RoxygenNote: 7.1.1
Packaged: 2021-01-04 15:32:55 UTC; root
Repository: CRAN
Date/Publication: 2021-01-11 06:50:16 UTC

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New package ActivityIndex with initial version 0.3.7
Package: ActivityIndex
Type: Package
Title: Activity Index Calculation using Raw 'Accelerometry' Data
Version: 0.3.7
Authors@R: c( person(given = "Jiawei", family = "Bai", role = c("cre", "aut"), email = "jbai@jhsph.edu", comment = c(ORCID = "0000-0003-4021-0101") ), person(given = "John", family = "Muschelli", email = "muschellij2@gmail.com", role = c("ctb"), comment = c(ORCID = "0000-0001-6469-1750")) )
Description: Reads raw 'accelerometry' from 'GT3X+' data and plain table data to calculate Activity Index from 'Bai et al.' (2016) <doi:10.1371/journal.pone.0160644>. The Activity Index refers to the square root of the second-level average variance of the three 'accelerometry' axes.
License: GPL-3
Depends: R (>= 2.10)
Imports: matrixStats, data.table, utils, R.utils
Suggests: knitr, testthat, graphics, rmarkdown
LazyData: true
LazyLoad: true
VignetteBuilder: knitr
RoxygenNote: 7.1.1
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2021-01-07 22:20:06 UTC; terry
Author: Jiawei Bai [cre, aut] (<https://orcid.org/0000-0003-4021-0101>), John Muschelli [ctb] (<https://orcid.org/0000-0001-6469-1750>)
Maintainer: Jiawei Bai <jbai@jhsph.edu>
Repository: CRAN
Date/Publication: 2021-01-11 06:50:23 UTC

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Sun, 10 Jan 2021

New package ungroup with initial version 1.3.0
Package: ungroup
Type: Package
Title: Penalized Composite Link Model for Efficient Estimation of Smooth Distributions from Coarsely Binned Data
Version: 1.3.0
Authors@R: c( person("Marius D.", "Pascariu", role = c("aut", "cre"), email = "rpascariu@outlook.com", comment = c(ORCID = "0000-0002-2568-6489")), person("Silvia", "Rizzi", role = "aut", email = "srizzi@health.sdu.dk"), person("Jonas", "Schoeley", role = "aut", comment = c(ORCID = "0000-0002-3340-8518")), person("Maciej J.", "Danko", role = "aut", email = "Danko@demogr.mpg.de", comment = c(ORCID = "0000-0002-7924-9022")) )
Description: Versatile method for ungrouping histograms (binned count data) assuming that counts are Poisson distributed and that the underlying sequence on a fine grid to be estimated is smooth. The method is based on the composite link model and estimation is achieved by maximizing a penalized likelihood. Smooth detailed sequences of counts and rates are so estimated from the binned counts. Ungrouping binned data can be desirable for many reasons: Bins can be too coarse to allow for accurate analysis; comparisons can be hindered when different grouping approaches are used in different histograms; and the last interval is often wide and open-ended and, thus, covers a lot of information in the tail area. Age-at-death distributions grouped in age classes and abridged life tables are examples of binned data. Because of modest assumptions, the approach is suitable for many demographic and epidemiological applications. For a detailed description of the method and applications see Rizzi et al. (2015) <doi:10.1093/aje/kwv020>.
License: MIT + file LICENSE
LazyData: TRUE
Depends: R (>= 3.4.0)
Imports: pbapply (>= 1.3), Rcpp (>= 0.12.0), rgl (>= 0.99.0), Rdpack (>= 0.8), Matrix
LinkingTo: Rcpp, RcppEigen
Suggests: MortalityLaws (>= 1.5.0), knitr (>= 1.20), rmarkdown (>= 1.10), testthat (>= 2.0.0)
RdMacros: Rdpack
URL: https://github.com/mpascariu/ungroup
BugReports: https://github.com/mpascariu/ungroup/issues
VignetteBuilder: knitr
RoxygenNote: 7.1.1
NeedsCompilation: yes
Packaged: 2021-01-08 09:11:31 UTC; mpascariu
Author: Marius D. Pascariu [aut, cre] (<https://orcid.org/0000-0002-2568-6489>), Silvia Rizzi [aut], Jonas Schoeley [aut] (<https://orcid.org/0000-0002-3340-8518>), Maciej J. Danko [aut] (<https://orcid.org/0000-0002-7924-9022>)
Maintainer: Marius D. Pascariu <rpascariu@outlook.com>
Repository: CRAN
Date/Publication: 2021-01-10 15:40:02 UTC

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New package resumer with initial version 0.0.4
Package: resumer
Title: Build Resumes with R
Version: 0.0.4
Authors@R: person("Jared", "Lander", email = "packages@jaredlander.com", role = c("aut", "cre"))
Description: Using a CSV, LaTeX and R to easily build attractive resumes.
Depends: R (>= 3.2.1)
License: BSD_3_clause + file LICENSE
LazyData: true
ByteCompile: true
URL: https://github.com/jaredlander/resumer
BugReports: https://github.com/jaredlander/resumer/issues
Suggests: testthat
Imports: useful, dplyr, rmarkdown
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2021-01-08 03:08:31 UTC; jared
Author: Jared Lander [aut, cre]
Maintainer: Jared Lander <packages@jaredlander.com>
Repository: CRAN
Date/Publication: 2021-01-10 15:40:06 UTC

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New package REEMtree with initial version 0.90.4
Package: REEMtree
Type: Package
Title: Regression Trees with Random Effects for Longitudinal (Panel) Data
Version: 0.90.4
Date: 2021-01-08
Author: Rebecca Sela, Jeffrey Simonoff and Wenbo Jing
Maintainer: Wenbo Jing <wj2093@stern.nyu.edu>
Depends: nlme, rpart, methods, graphics, stats
Suggests: AER
Description: A data mining approach for longitudinal and clustered data, which combines the structure of mixed effects model with tree-based estimation methods. See Sela, R.J. and Simonoff, J.S. (2012) RE-EM trees: a data mining approach for longitudinal and clustered data <doi:10.1007/s10994-011-5258-3>.
License: GPL
URL: http://pages.stern.nyu.edu/~jsimonof/REEMtree/
NeedsCompilation: no
Packaged: 2021-01-08 01:22:24 UTC; WENBO JING
Repository: CRAN
Date/Publication: 2021-01-10 15:40:15 UTC

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New package knitcitations with initial version 1.0.12
Package: knitcitations
Type: Package
Title: Citations for 'Knitr' Markdown Files
Authors@R: person("Carl", "Boettiger", role=c("aut", "cre"), email="cboettig@gmail.com", comment = "https://orcid.org/0000-0002-1642-628X")
Version: 1.0.12
Description: Provides the ability to create dynamic citations in which the bibliographic information is pulled from the web rather than having to be entered into a local database such as 'bibtex' ahead of time. The package is primarily aimed at authoring in the R 'markdown' format, and can provide outputs for web-based authoring such as linked text for inline citations. Cite using a 'DOI', URL, or 'bibtex' file key. See the package URL for details.
URL: https://github.com/cboettig/knitcitations
BugReports: https://github.com/cboettig/knitcitations/issues
License: MIT + file LICENSE
VignetteBuilder: knitr
Depends: R (>= 3.0)
Imports: RefManageR (>= 0.8.2), digest, httr (>= 0.3), methods, utils
Suggests: testthat, knitr (>= 1.6), rmarkdown
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2021-01-08 17:07:39 UTC; cboettig
Author: Carl Boettiger [aut, cre] (<https://orcid.org/0000-0002-1642-628X>)
Maintainer: Carl Boettiger <cboettig@gmail.com>
Repository: CRAN
Date/Publication: 2021-01-10 15:40:09 UTC

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New package HydroMe with initial version 2.0-1
Package: HydroMe
Type: Package
Title: Estimating Water Retention and Infiltration Model Parameters using Experimental Data
Version: 2.0-1
Date: 2021-01-07
Imports: stats
Suggests: minpack.lm, nlme
Author: Christian Thine Omuto [aut, cre], Martin Maechler [ctb], Vitalis Too [ctb]
Maintainer: Christian Thine Omuto <thineomuto@yahoo.com>
Description: This version 2 of the HydroMe v.1 package estimates the parameters in infiltration and water retention models by curve-fitting methods <doi:10.1016/j.cageo.2008.08.011>. The models considered are those commonly used in soil science. It has new models for water retention and characteristic curves.
License: GPL (>= 2)
URL: https://CRAN.r-project.org/package=HydroMe
NeedsCompilation: no
Packaged: 2021-01-08 07:54:40 UTC; Cthin
Repository: CRAN
Date/Publication: 2021-01-10 15:40:18 UTC

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New package bdlp with initial version 0.9-2
Package: bdlp
Version: 0.9-2
Date: 2021-01-03
Authors@R: c(person(given="Rainer", family="Dangl", email="rainer.dangl@bildung.gv.at", role=c("aut", "cre")))
Title: Transparent and Reproducible Artificial Data Generation
Depends: R (>= 3.0.0), graphics
Imports: GenOrd, MultiOrd, stringdist, rgl, RSQLite, MASS, DBI, methods, grDevices, stats, utils
Description: The main function generateDataset() processes a user-supplied .R file that contains metadata parameters in order to generate actual data. The metadata parameters have to be structured in the form of metadata objects, the format of which is outlined in the package vignette. This approach allows to generate artificial data in a transparent and reproducible manner.
License: GPL-2
LazyLoad: yes
Author: Rainer Dangl [aut, cre]
Maintainer: Rainer Dangl <rainer.dangl@bildung.gv.at>
RoxygenNote: 7.1.1
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-01-05 18:39:48 UTC; raine
Repository: CRAN
Date/Publication: 2021-01-10 15:10:05 UTC

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New package aptg with initial version 0.1.1
Package: aptg
Type: Package
Title: Automatic Phylogenetic Tree Generator
Version: 0.1.1
Author: Christophe Benjamin
Maintainer: Christophe Benjamin <christophe.benjamin@protonmail.com>
Description: Generates phylogenetic trees and distance matrices ('brranching', <https://CRAN.R-project.org/package=brranching>) from a list of species name or from a taxon down to whatever lower taxon ('taxize', <https://github.com/ropensci/taxize>). It can do so based on two reference super trees: mammals (Bininda-Emonds et al., 2007; <doi:10.1038/nature05634>) and angiosperms (Zanne et al., 2014; <doi:10.1038/nature12872>).
Depends: ape,brranching, phytools, taxize, xml2
Suggests: paco, vegan, knitr, rmarkdown, qpdf
VignetteBuilder: knitr
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2021-01-07 14:54:10 UTC; Chris
Repository: CRAN
Date/Publication: 2021-01-10 15:20:19 UTC

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New package TukeyRegion with initial version 0.1.4
Package: TukeyRegion
Type: Package
Title: Tukey Region and Median
Version: 0.1.4
Date: 2021-01-09
Authors@R: c(person("C.B.", "Barber", role = c("aut", "cph"), comment = "Qhull library"), person("The Geometry Center", "University of Minnesota", role = c("cph"), comment = "Qhull library"), person("Pavlo", "Mozharovskyi", role = c("aut", "cre"), email = "pavlo.mozharovskyi@telecom-paris.fr"))
Description: Tukey regions are polytopes in the Euclidean space, viz. upper-level sets of the Tukey depth function on given data. The bordering hyperplanes of a Tukey region are computed as well as its vertices, facets, centroid, and volume. In addition, the Tukey median set, which is the non-empty Tukey region having highest depth level, and its barycenter (= Tukey median) are calculated. Tukey regions are visualized in dimension two and three. For details see Liu, Mosler, and Mozharovskyi (2019, <doi:10.1080/10618600.2018.1546595>). See file LICENSE.note for additional license information.
License: GPL (>= 3)
SystemRequirements: C++11
Depends: rgl,ddalpha,MASS,bfp,Rglpk
Imports: Rcpp (>= 0.11.0)
LinkingTo: Rcpp,BH
NeedsCompilation: yes
Packaged: 2021-01-09 11:22:34 UTC; pavlo.mozharovskyi
Author: C.B. Barber [aut, cph] (Qhull library), The Geometry Center University of Minnesota [cph] (Qhull library), Pavlo Mozharovskyi [aut, cre]
Maintainer: Pavlo Mozharovskyi <pavlo.mozharovskyi@telecom-paris.fr>
Repository: CRAN
Date/Publication: 2021-01-10 14:30:11 UTC

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New package simPH with initial version 1.3.13
Package: simPH
Title: Simulate and Plot Estimates from Cox Proportional Hazards Models
Description: Simulates and plots quantities of interest (relative hazards, first differences, and hazard ratios) for linear coefficients, multiplicative interactions, polynomials, penalised splines, and non-proportional hazards, as well as stratified survival curves from Cox Proportional Hazard models. It also simulates and plots marginal effects for multiplicative interactions. Methods described in Gandrud (2015) <doi:10.18637/jss.v065.i03>.
Version: 1.3.13
Date: 2021-01-09
Authors@R: c( person("Christopher", "Gandrud", email = "christopher.gandrud@gmail.com", role = c("aut", "cre")) )
URL: https://CRAN.R-project.org/package=simPH
BugReports: https://github.com/christophergandrud/simPH/issues
Depends: R (>= 3.0.2)
License: GPL-3
Imports: data.table (>= 1.9.6), dplyr (>= 0.4), ggplot2, gridExtra, lazyeval, MASS, mgcv, stringr, survival, quadprog
Suggests: knitr, stats, testthat, covr
VignetteBuilder: knitr
BuildVignettes: true
LazyData: true
Encoding: UTF-8
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2021-01-09 06:48:22 UTC; cgandrud
Author: Christopher Gandrud [aut, cre]
Maintainer: Christopher Gandrud <christopher.gandrud@gmail.com>
Repository: CRAN
Date/Publication: 2021-01-10 14:50:05 UTC

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New package mortyr with initial version 0.0.2
Package: mortyr
Title: Wrapper to 'The Rick and Morty' API
Version: 0.0.2
Authors@R: person("Michael", "Page", email = "hello@mikejohnpage.com", role = c("aut", "cre"))
Description: Returns information about characters, locations, and episodes from 'The Rick and Morty' API: <https://rickandmortyapi.com>.
License: MIT + file LICENSE
URL: https://github.com/mikejohnpage/mortyr
BugReports: https://github.com/mikejohnpage/mortyr/issues
Encoding: UTF-8
LazyData: true
Imports: httr, jsonlite, tibble
Suggests: testthat
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2021-01-09 20:57:13 UTC; mike
Author: Michael Page [aut, cre]
Maintainer: Michael Page <hello@mikejohnpage.com>
Repository: CRAN
Date/Publication: 2021-01-10 14:30:08 UTC

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Sat, 09 Jan 2021

New package scrappy with initial version 0.0.1
Package: scrappy
Title: A Simple Web Scraper
Version: 0.0.1
Authors@R: c( person(given = "Roberto", family = "Villegas-Diaz", role = c("aut", "cre"), email = "villegas.roberto@hotmail.com", comment = c(ORCID = "0000-0001-5036-8661")))
Description: A group of functions to scrape data from different websites, for academic purposes.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
URL: https://github.com/villegar/scrappy/, https://villegar.github.io/scrappy/
BugReports: https://github.com/villegar/scrappy/issues/
Language: en-GB
Imports: magrittr, rvest, xml2
NeedsCompilation: no
Packaged: 2021-01-07 12:14:03 UTC; roberto.villegas-diaz
Author: Roberto Villegas-Diaz [aut, cre] (<https://orcid.org/0000-0001-5036-8661>)
Maintainer: Roberto Villegas-Diaz <villegas.roberto@hotmail.com>
Repository: CRAN
Date/Publication: 2021-01-09 14:20:02 UTC

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New package msaeDB with initial version 0.1.0
Package: msaeDB
Type: Package
Title: Difference Benchmarking for Multivariate Small Area Estimation
Version: 0.1.0
Author: Zaza Yuda Perwira, Azka Ubaidillah
Maintainer: Zaza Yuda Perwira <221710086@stis.ac.id>
Description: Implements Benchmarking Method for Multivariate Small Area Estimation under Fay Herriot Model. Multivariate Small Area Estimation (MSAE) is a development of Univariate Small Area Estimation that considering the correlation among response variables and borrowing the strength from auxiliary variables effectiveness of a domain sample size, the multivariate model in this package is based on multivariate model 1 proposed by Roberto Benavent and Domingo Morales (2015) <doi:10.1016/j.csda.2015.07.013>. Benchmarking in Small Area Estimation is a modification of Small Area Estimation model to guarantees that the aggregate weighted mean of the county predictors equals the corresponding weighted mean of survey estimates. Difference Benchmarking is the simplest benchmarking method but widely used by multiplying empirical best linear unbiased prediction (EBLUP) estimator by the common adjustment factors (J.N.K Rao and Isabel Molina, 2013).
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
URL: https://github.com/zazaperwira/msaeDB
BugReports: https://github.com/zazaperwira/msaeDB/issues
Suggests: knitr, rmarkdown, covr
VignetteBuilder: knitr
Imports: MASS, magic, stats
Depends: R (>= 2.10)
NeedsCompilation: no
Packaged: 2021-01-07 09:56:44 UTC; Windows 10
Repository: CRAN
Date/Publication: 2021-01-09 14:10:02 UTC

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New package metaggR with initial version 0.1.0
Package: metaggR
Type: Package
Title: Calculate the Knowledge-Weighted Estimate
Version: 0.1.0
Authors@R: c(person(given = "Ville", family = "Satopää", email = "ville.satopaa@gmail.com", role = c("aut", "cre", "cph")), person(given = "Asa", family = "Palley", role = "aut"))
Description: According to a phenomenon known as "the wisdom of the crowds," combining point estimates from multiple judges often provides a more accurate aggregate estimate than using a point estimate from a single judge. However, if the judges use shared information in their estimates, the simple average will over-emphasize this common component at the expense of the judges’ private information. Asa Palley & Ville Satopää (2021) "Boosting the Wisdom of Crowds Within a Single Judgment Problem: Selective Averaging Based on Peer Predictions" <https://papers.ssrn.com/sol3/Papers.cfm?abstract_id=3504286> proposes a procedure for calculating a weighted average of the judges’ individual estimates such that resulting aggregate estimate appropriately combines the judges' collective information within a single estimation problem. The authors use both simulation and data from six experimental studies to illustrate that the weighting procedure outperforms existing averaging-like methods, such as the equally weighted average, trimmed average, and median. This aggregate estimate -- know as "the knowledge-weighted estimate" -- inputs a) judges' estimates of a continuous outcome (E) and b) predictions of others' average estimate of this outcome (P). In this R-package, the function knowledge_weighted_estimate(E,P) implements the knowledge-weighted estimate. Its use is illustrated with a simple stylized example and on real-world experimental data.
License: GPL-2
Copyright: (c) Ville Satopaa
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Imports: MASS, stats
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
Config/testthat/edition: 3
Depends: R (>= 2.10)
NeedsCompilation: no
Packaged: 2021-01-07 11:39:12 UTC; ville.satopaa
Author: Ville Satopää [aut, cre, cph], Asa Palley [aut]
Maintainer: Ville Satopää <ville.satopaa@gmail.com>
Repository: CRAN
Date/Publication: 2021-01-09 14:20:05 UTC

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New package MARSSVRhybrid with initial version 0.1.0
Package: MARSSVRhybrid
Type: Package
Title: MARS SVR Hybrid
Version: 0.1.0
Authors@R: c(person("Pankaj", "Das", role = c("aut","cre"),email="pankaj.das2@icar.gov.in"),person("Achal", "Lama", role = "aut",email="achal.lama@icar.gov.in"), person("Girish", "Jha", role = "ths",email="grish.stat@gmail.com"))
Author: Pankaj Das [aut, cre], Achal Lama [aut], Girish Jha [ths]
Maintainer: Pankaj Das <pankaj.das2@icar.gov.in>
Depends: R (>= 3.3.0),e1071,earth,stats
Description: Multivariate Adaptive Regression Spline (MARS) based Support Vector Regression (SVR) hybrid model is combined Machine learning hybrid approach which selects important variables using MARS and then fits SVR on the extracted important variables.
Encoding: UTF-8
LazyData: true
License: GPL-3
NeedsCompilation: no
Packaged: 2021-01-07 12:39:02 UTC; USER
Repository: CRAN
Date/Publication: 2021-01-09 14:30:05 UTC

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New package geostats with initial version 1.0
Package: geostats
Title: An Introduction to Statistics for Geoscientists
Version: 1.0
Date: 2021-01-05
Authors@R: person("Pieter", "Vermeesch", , "p.vermeesch@ucl.ac.uk", role = c("aut", "cre"))
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>
Depends: R (>= 3.5.0)
Imports: MASS
License: GPL-3
URL: https://github.com/pvermees/geostats/
LazyData: true
RoxygenNote: 7.1.1
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2021-01-07 09:24:54 UTC; pvermees
Repository: CRAN
Date/Publication: 2021-01-09 14:10:05 UTC

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New package ctsemOMX with initial version 1.0.3
Package: ctsemOMX
Type: Package
Title: Continuous Time SEM - 'OpenMx' Based Functions
Version: 1.0.3
Date: 2020-12-17
Authors@R: c(person("Charles", "Driver", role = c("aut","cre","cph"),email="driver@mpib-berlin.mpg.de"), person("Manuel", "Voelkle", role = c("aut","cph")), person("Han", "Oud", role = c("aut","cph") ))
Description: Original 'ctsem' (continuous time structural equation modelling) functionality, based on the 'OpenMx' software, as described in Driver, Oud, Voelkle (2017) <doi:10.18637/jss.v077.i05>, with updated details in vignette. Combines stochastic differential equations representing latent processes with structural equation measurement models. These functions were split off from the main package of 'ctsem', as the main package uses the 'rstan' package as a backend now -- offering estimation options from max likelihood to Bayesian. There are nevertheless use cases for the wide format SEM style approach as offered here, particularly when there are no individual differences in observation timing and the number of individuals is large. For the main 'ctsem' package, see <https://cran.r-project.org/package=ctsem>.
License: GPL-3
Depends: R (>= 3.5.0), ctsem (>= 3.3.2), OpenMx (>= 2.9.0)
URL: https://github.com/cdriveraus/ctsemOMX
Imports: graphics, grDevices, Matrix, methods, plyr, stats, utils
Encoding: UTF-8
LazyData: true
ByteCompile: true
Suggests: knitr, testthat
VignetteBuilder: knitr
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2021-01-08 12:52:37 UTC; Driver
Author: Charles Driver [aut, cre, cph], Manuel Voelkle [aut, cph], Han Oud [aut, cph]
Maintainer: Charles Driver <driver@mpib-berlin.mpg.de>
Repository: CRAN
Date/Publication: 2021-01-09 14:10:08 UTC

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New package covid19jp with initial version 0.1.0
Package: covid19jp
Title: Japanese Covid-19 Datasets
Version: 0.1.0
Authors@R: person(given = "Koji", family = "Higuchi", role = c("aut", "cre"), email = "kojih9@gmail.com")
Description: Ready to use Japanese covid-19 datasets.
License: MIT + file LICENSE
URL: https://github.com/kj-9/covid19jp
BugReports: https://github.com/kj-9/covid19jp/issues
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Language: en, ja
Suggests: testthat, purrr, dplyr, readr, jsonlite, log4r, rJava, tabulizer, modules, stringr, rvest, xml2, pointblank
Depends: R (>= 2.10)
Imports: devtools
NeedsCompilation: no
Packaged: 2021-01-07 13:30:12 UTC; rstudio
Author: Koji Higuchi [aut, cre]
Maintainer: Koji Higuchi <kojih9@gmail.com>
Repository: CRAN
Date/Publication: 2021-01-09 14:30:02 UTC

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New package QuadRoot with initial version 0.1.0
Package: QuadRoot
Type: Package
Title: Quadratic Root for any Quadratic Equation
Version: 0.1.0
Author: Pankaj Das
Maintainer: Pankaj Das <pankaj.das2@icar.gov.in>
Description: It will assist the user to find simple quadratic roots from any quadratic equation.
License: GPL-3
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2021-01-07 05:04:45 UTC; USER
Repository: CRAN
Date/Publication: 2021-01-09 13:50:10 UTC

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New package EMDSVRhybrid with initial version 0.1.0
Package: EMDSVRhybrid
Type: Package
Title: Hybrid Machine Learning Model
Version: 0.1.0
Authors@R: c(person("Pankaj", "Das", role = c("aut","cre"),email="pankaj.das2@icar.gov.in"),person("Achal", "Lama", role = "aut",email="achal.lama@icar.gov.in"), person("Girish", "Jha", role = "aut",email="grish.stat@gmail.com"))
Author: Pankaj Das [aut, cre], Achal Lama [aut], Girish Jha [aut]
Maintainer: Pankaj Das <pankaj.das2@icar.gov.in>
Depends: R (>= 3.3.0),EMD,e1071
Description: Researchers can fit Empirical Mode Decomposition and Support Vector Regression based hybrid model for nonlinear and non stationary time series data using this package.
Encoding: UTF-8
LazyData: true
License: GPL-3
NeedsCompilation: no
Packaged: 2021-01-07 04:35:04 UTC; USER
Repository: CRAN
Date/Publication: 2021-01-09 13:50:13 UTC

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New package convergEU with initial version 0.5.1
Package: convergEU
Type: Package
Title: Monitoring Convergence of EU Countries
Version: 0.5.1
Depends: R (>= 3.6.0)
Authors@R: c(person(given = "Federico M.", family = "Stefanini", role = c("arc", "aut", "cre"), email = "federico.stefanini@unifi.it"), person(given = "Massimiliano", family = "Mascherini", role = "arc", email = "massimiliano.mascherini@eurofound.europa.eu"), person(given = "Eleonora Peruffo", role = "ctb"), person(given = "Nedka Nikiforova", role = "ctb"), person(given = "Chiara Litardi", role = "ctb"))
Maintainer: Federico M. Stefanini <federico.stefanini@unifi.it>
URL: https://local.disia.unifi.it/stefanini/RESEARCH/coneu/tutorial-conv.html, https://www.eurofound.europa.eu/sites/default/files/wpef20008.pdf, https://www.eurofound.europa.eu/sites/default/files/ef_publication/field_ef_document/ef18003en.pdf
Description: Indicators and measures by country and time describe what happens at economic and social levels. This package provides functions to calculate several measures of convergence after imputing missing values. The automated downloading of Eurostat data, followed by the production of country fiches and indicator fiches, makes possible to produce automated reports. The Eurofound report (<doi:10.2806/68012>) "Upward convergence in the EU: Concepts, measurements and indicators", 2018, is a detailed presentation of convergence.
Imports: dplyr, tibble, ggplot2, eurostat, tidyr, rlang, utils, purrr, caTools, broom, stringr, rmarkdown, ggpubr
Suggests: devtools, formattable, gridExtra, knitr, kableExtra, magrittr, readr, readxl, tidyverse, rvest, testthat, utf8
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-01-08 19:14:06 UTC; fred
Author: Federico M. Stefanini [arc, aut, cre], Massimiliano Mascherini [arc], Eleonora Peruffo [ctb], Nedka Nikiforova [ctb], Chiara Litardi [ctb]
Repository: CRAN
Date/Publication: 2021-01-09 13:50:06 UTC

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New package APCI with initial version 0.1.0
Package: APCI
Type: Package
Title: A New Age-Period-Cohort Model for Describing and Investigating Inter-Cohort Differences and Life Course Dynamics
Version: 0.1.0
Author: Liying Luo, Jiahui Xu
Maintainer: Jiahui Xu <jpx5053@psu.edu>
Depends: R (>= 3.6.0)
Description: It implemented APC-I Model proposed in the paper of Luo and Hodges (2019). A new age-period-cohort model for describing and investigating inter-cohort differences and life course dynamics.
Imports: haven, survey, magrittr, tidyverse, dplyr, ggplot2, data.table, ggpubr, stringr
License: GPL-2
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2021-01-08 17:37:53 UTC; xujiahui
Repository: CRAN
Date/Publication: 2021-01-09 06:30:35 UTC

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Fri, 08 Jan 2021

New package tabulator with initial version 1.0.0
Package: tabulator
Title: Efficient Tabulation with Stata-Like Output
Version: 1.0.0
Authors@R: person("Sean", "Higgins", email = "sean.higgins@kellogg.northwestern.edu", role = c("aut", "cre"))
Description: Efficient tabulation with Stata-like output. For each unique value of the variable, it shows the number of observations with that value, proportion of observations with that value, and cumulative proportion, in descending order of frequency. Accepts data.table, tibble, or data.frame as input. Efficient with big data: if you give it a data.table, tab() uses data.table syntax.
Imports: assertthat, dplyr, data.table, magrittr, purrr, rlang, stats, stringr, tibble, tidyr
Depends: R (>= 3.4.0)
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2021-01-06 22:03:57 UTC; cesarlandin
Author: Sean Higgins [aut, cre]
Maintainer: Sean Higgins <sean.higgins@kellogg.northwestern.edu>
Repository: CRAN
Date/Publication: 2021-01-08 13:20:02 UTC

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New package tablet with initial version 0.2.0
Package: tablet
Type: Package
Title: Tabulate Descriptive Statistics in Multiple Formats
Version: 0.2.0
Author: Tim Bergsma
Maintainer: Tim Bergsma <bergsmat@gmail.com>
Description: Creates a table of descriptive statistics for factor and numeric columns in a data frame. Displays these by groups, if any. Highly customizable, with support for 'html' and 'pdf' provided by 'kableExtra'. Respects original column order, column labels, and factor level order. See ?tablet.data.frame and vignettes.
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: dplyr (>= 1.0.2), rlang, tidyr, kableExtra (>= 0.9.0), tidyselect
RoxygenNote: 7.1.1
VignetteBuilder: knitr
Suggests: knitr, magrittr, rmarkdown, yamlet, boot, testthat
NeedsCompilation: no
Packaged: 2021-01-06 23:10:06 UTC; tim.bergsma
Repository: CRAN
Date/Publication: 2021-01-08 13:30:03 UTC

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New package read.gt3x with initial version 1.0.1
Package: read.gt3x
Type: Package
Title: Parse 'Actigraph' 'GT3X'/'GT3X+' 'Accelerometer' Data
Version: 1.0.1
Authors@R: c(person(given = "Tuomo", family = "Nieminen", role = c("aut", "cre"), email = "tuomo.a.nieminen@gmail.com"), person(given = "John", family = "Muschelli", role = "aut", email = "muschellij2@gmail.com", comment = c(ORCID = "0000-0001-6469-1750")))
Description: Implements a high performance C++ parser for 'ActiGraph' 'GT3X'/'GT3X+' data format (with extension '.gt3x') for 'accelerometer' samples. Activity samples can be easily read into a matrix or data.frame. This allows for storing the raw 'accelerometer' samples in the original binary format to reserve space.
License: EUPL
Encoding: UTF-8
LazyData: true
LinkingTo: Rcpp
Imports: Rcpp, utils, R.utils, tools
RoxygenNote: 7.1.1
Suggests: knitr, rmarkdown, testthat (>= 2.1.0), data.table, zoo, readr, lubridate, zip
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2021-01-06 22:23:54 UTC; tuomo
Author: Tuomo Nieminen [aut, cre], John Muschelli [aut] (<https://orcid.org/0000-0001-6469-1750>)
Maintainer: Tuomo Nieminen <tuomo.a.nieminen@gmail.com>
Repository: CRAN
Date/Publication: 2021-01-08 13:20:05 UTC

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New package matrixdist with initial version 1.0
Package: matrixdist
Type: Package
Title: Statistics for Matrix Distributions
Version: 1.0
Date: 2020-12-12
Authors@R: c(person("Martin", "Bladt", email = "martinbladt@gmail.com", role = c("aut", "cre")), person("Jorge", "Yslas", email = "jorge.yslas1@gmail.com", role = "aut") )
Maintainer: Martin Bladt <martinbladt@gmail.com>
Description: Tools for homogeneous and in-homogeneous phase-type distributions. Methods for functional evaluation, simulation and estimation using the expectation-maximization (EM) algorithm are provided. The methods of this package are based on the following references. Asmussen, S., Nerman, O., & Olsson, M. (1996) <https://www.jstor.org/stable/4616418>, Olsson, M. (1996) <https://www.jstor.org/stable/4616419>. Albrecher, H., & Bladt, M. (2019) <doi:10.1017/jpr.2019.60> Albrecher, H., Bladt, M., & Yslas, J. (2020) <doi:10.1111/sjos.12505> Bladt, M., & Yslas, J. (2020) <arXiv:abs/2011.03219>.
Depends: R (>= 3.1.0)
License: GPL-3
Imports: Rcpp, methods
LinkingTo: Rcpp
SystemRequirements: C++11
Encoding: UTF-8
RoxygenNote: 7.1.1
NeedsCompilation: yes
Packaged: 2021-01-07 01:26:20 UTC; martinbladt
Author: Martin Bladt [aut, cre], Jorge Yslas [aut]
Repository: CRAN
Date/Publication: 2021-01-08 13:40:02 UTC

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New package mactivate with initial version 0.6.4
Package: mactivate
Type: Package
Title: Multiplicative Activation
Version: 0.6.4
Date: 2021-01-06
Author: Dave Zes
Maintainer: Dave Zes <zesdave@gmail.com>
Description: Provides methods and classes for adding m-activation ("multiplicative activation") layers to MLR or multivariate logistic regression models. M-activation layers created in this library detect and add input interaction (polynomial) effects into a predictive model. M-activation can detect high-order interactions -- a traditionally non-trivial challenge. Details concerning application, methodology, and relevant survey literature can be found in this library's vignette, "About."
License: GPL (>= 3)
Depends: R (>= 3.5.0)
NeedsCompilation: yes
Packaged: 2021-01-06 20:31:31 UTC; davezes
Repository: CRAN
Date/Publication: 2021-01-08 12:50:02 UTC

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New package RandomForestsGLS with initial version 0.1.0
Package: RandomForestsGLS
Type: Package
Title: Random Forests for Dependent Data
Version: 0.1.0
Authors@R: c(person("Arkajyoti", "Saha", role=c("aut", "cre"), email="arkajyotisaha93@gmail.com"), person("Sumanta", "Basu", role="aut", email="sumbose@cornell.edu"), person("Abhirup", "Datta", role="aut", email="abhidatta@jhu.edu"))
Maintainer: Arkajyoti Saha <arkajyotisaha93@gmail.com>
Author: Arkajyoti Saha [aut, cre], Sumanta Basu [aut], Abhirup Datta [aut]
Depends: R (>= 3.3.0)
Imports: BRISC, parallel, stats, matrixStats, randomForest, pbapply
Suggests: knitr, rmarkdown, ggplot2, testthat (>= 2.1.0)
Description: Fits non-linear regression models on dependant data with Generalised Least Square (GLS) based Random Forest (RF-GLS) detailed in Saha, Basu and Datta (2020) <arXiv:2007.15421>.
License: GPL (>= 2)
URL: https://github.com/ArkajyotiSaha/RandomForestsGLS
BugReports: https://github.com/ArkajyotiSaha/RandomForestsGLS/issues
Encoding: UTF-8
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2021-01-06 18:00:38 UTC; arkajyotisaha
Repository: CRAN
Date/Publication: 2021-01-08 10:50:02 UTC

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New package KPC with initial version 0.1.0
Package: KPC
Type: Package
Title: Kernel Partial Correlation Coefficient
Version: 0.1.0
Authors@R: c(person("Zhen", "Huang", email = "zh2395@columbia.edu", role = c("aut", "cre")), person("Nabarun", "Deb", email = "nd2560@columbia.edu", role = "ctb"), person("Bodhisattva", "Sen", email = "bodhi@stat.columbia.edu", role = "ctb"))
Maintainer: Zhen Huang <zh2395@columbia.edu>
Description: Implementations of two empirical versions the kernel partial correlation (KPC) coefficient and the associated variable selection algorithms. KPC is a measure of the strength of conditional association between Y and Z given X, with X, Y, Z being random variables taking values in general topological spaces. As the name suggests, KPC is defined in terms of kernels on reproducing kernel Hilbert spaces (RKHSs). The population KPC is a deterministic number between 0 and 1; it is 0 if and only if Y is conditionally independent of Z given X, and it is 1 if and only if Y is a measurable function of Z and X. One empirical KPC estimator is based on geometric graphs, such as K-nearest neighbor graphs and minimum spanning trees, and is consistent under very weak conditions. The other empirical estimator, defined using conditional mean embeddings (CMEs) as used in the RKHS literature, is also consistent under suitable conditions. Using KPC, a stepwise forward variable selection algorithm KFOCI (using the graph based estimator of KPC) is provided, as well as a similar stepwise forward selection algorithm based on the RKHS based estimator. For more details on KPC, its empirical estimators and its application on variable selection, see Huang, Z., N. Deb, and B. Sen (2020). “Kernel partial correlation coefficient – a measure of conditional dependence” <arXiv:2012.14804>. When X is empty, KPC measures the unconditional dependence between Y and Z, which has been described in Deb, N., P. Ghosal, and B. Sen (2020), “Measuring association on topological spaces using kernels and geometric graphs” <arXiv:2010.01768>, and it is implemented in the functions KMAc() and Klin() in this package. The latter can be computed in near linear time.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Depends: R (>= 3.6.0), data.table, kernlab
Imports: RANN, proxy, parallel, gmp, emstreeR
NeedsCompilation: no
Packaged: 2021-01-06 18:49:32 UTC; huangzhen
Author: Zhen Huang [aut, cre], Nabarun Deb [ctb], Bodhisattva Sen [ctb]
Repository: CRAN
Date/Publication: 2021-01-08 10:50:05 UTC

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