Tue, 02 Jun 2020

New package tidycat with initial version 0.1.0
Package: tidycat
Type: Package
Title: Expand broom::tidy() Output for Categorical Parameter Estimates
Version: 0.1.0
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>
URL: https://github.com/guyabel/tidycat
BugReports: https://github.com/guyabel/tidycat/issues
Description: Create additional rows and columns on broom::tidy() output to allow for easier control of plotting categorical parameter estimates.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
Imports: magrittr, utils, tidyr, tibble, dplyr, stringr, stats, forcats
Suggests: broom, ggplot2, ggforce, knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-05-26 08:33:13 UTC; Guy
Author: Guy J. Abel [aut, cre] (<https://orcid.org/0000-0002-4893-5687>)
Repository: CRAN
Date/Publication: 2020-06-02 09:20:02 UTC

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New package shinySearchbar with initial version 1.0.0
Package: shinySearchbar
Title: Shiny Searchbar - An Input Widget for Highlighting Text and More
Version: 1.0.0
Authors@R: c( person("Jesse", "Norris", email = "affeinated@gmail.com", role = c("aut", "cre")), person("Julian", "Kühnel", role = "ctb", comment = "mark.js") )
Description: Add a searchbar widget to your 'Shiny' application. The widget quickly integrates with any existing element containing text to highlight matches. Highlighting is done with the 'JavaScript' library 'mark.js'. The widget includes buttons to cycle through multiple instances of the match and automatically scroll to the matches in an overflow element (or window). The widget also displays the total number of matches and which match is currently being cycled through. The widget is structured as a 'Bootstrap 3' input group.
URL: https://github.com/jes-n/shiny-searchbar
BugReports: https://github.com/jes-n/shiny-searchbar/issues
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
Collate: 'demo.R' 'utils.R' 'input-searchbar.R'
Imports: shiny, jsonlite
Suggests: testthat
Depends: R (>= 2.10)
NeedsCompilation: no
Packaged: 2020-05-26 02:49:25 UTC; jesse
Author: Jesse Norris [aut, cre], Julian Kühnel [ctb] (mark.js)
Maintainer: Jesse Norris <affeinated@gmail.com>
Repository: CRAN
Date/Publication: 2020-06-02 09:50:02 UTC

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New package rsyntax with initial version 0.1.0
Package: rsyntax
Type: Package
Title: Extract Semantic Relations from Text by Querying and Reshaping Syntax
Version: 0.1.0
Date: 2020-05-13
Author: Kasper Welbers and Wouter van Atteveldt
Maintainer: Kasper Welbers <kasperwelbers@gmail.com>
Depends: R (>= 3.2.0)
Imports: igraph, tidyselect, methods, stringi, digest, rlang, magrittr, tokenbrowser, base64enc, png, data.table (>= 1.11.8)
LazyData: true
Encoding: UTF-8
Description: Various functions for querying and reshaping dependency trees, as for instance created with the 'spacyr' or 'udpipe' packages. This enables the automatic extraction of useful semantic relations from texts, such as quotes (who said what) and clauses (who did what). Method proposed in Van Atteveldt et al. (2017) <doi:10.1017/pan.2016.12>.
License: GPL-3
RoxygenNote: 7.1.0
Suggests: testthat
NeedsCompilation: no
Packaged: 2020-05-26 08:16:57 UTC; kasper
Repository: CRAN
Date/Publication: 2020-06-02 09:20:05 UTC

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New package MSRDT with initial version 0.1.0
Package: MSRDT
Type: Package
Title: Multi-State Reliability Demonstration Tests (MSRDT)
Version: 0.1.0
Authors@R: c(person("Suiyao", "Chen", role = c("aut", "cre"), email = "csycsy12377@gmail.com"))
Maintainer: Suiyao Chen <csycsy12377@gmail.com>
Description: This is a implementation of design methods for multi-state reliability demonstration tests (MSRDT) with failure count data, which is associated with the work from the published paper "Multi-state Reliability Demonstration Tests" by Suiyao Chen et al. (2017) <doi:10.1080/08982112.2017.1314493>. It implements two types of MSRDT, multiple periods (MP) and multiple failure modes (MFM). For MP, two different scenarios with criteria on cumulative periods (Cum) or separate periods (Sep) are implemented respectively. It also provides the implementation of conventional design method, namely binomial tests for failure count data.
Depends: R (>= 3.3.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
Imports: gtools, stats, reshape2, dplyr, utils
Suggests: tidyverse, knitr, rmarkdown
URL: https://github.com/ericchen12377/MSRDT
BugReports: https://github.com/ericchen12377/MSRDT/issues
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-05-26 13:46:06 UTC; chens
Author: Suiyao Chen [aut, cre]
Repository: CRAN
Date/Publication: 2020-06-02 10:00:02 UTC

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New package mindicador with initial version 0.1.5
Package: mindicador
Title: Indicadores Economicos de Chile (Economic Outlook for Chile)
Version: 0.1.5
Authors@R: person(given = "Mauricio", family = "Vargas", role = c("aut", "cre", "cph"), email = "mvargas@dcc.uchile.cl", comment = c(ORCID = "0000-0003-1017-7574"))
Description: Importa datos de la API de <https://mindicador.cl> en formato de cuadro de datos o serie de tiempo. El objetivo es facilitar el uso de algunos datos economicos a periodistas y profesionales que requieren informacion desplegada de forma clara y concisa. (Imports data from <https://mindicador.cl> API in data frame or time series format. The goal is to ease using certain economic data with different R packages, having in mind journalists and professionals that require information displayed in a clear and concise way.)
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
Imports: crul, data.table, digest, jsonlite, memoise, xts
Suggests: knitr, rmarkdown, vcr, covr, testthat, ggplot2, readxl
VignetteBuilder: knitr
Depends: R (>= 2.10)
URL: https://github.com/pachamaltese/mindicador
BugReports: https://github.com/pachamaltese/mindicador/issues
NeedsCompilation: no
Packaged: 2020-05-25 22:41:01 UTC; pacha
Author: Mauricio Vargas [aut, cre, cph] (<https://orcid.org/0000-0003-1017-7574>)
Maintainer: Mauricio Vargas <mvargas@dcc.uchile.cl>
Repository: CRAN
Date/Publication: 2020-06-02 09:30:02 UTC

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New package ICSS with initial version 1.0
Package: ICSS
Type: Package
Title: ICSS Algorithm by Inclan/Tiao (1994)
Version: 1.0
Date: 2020-05-26
Authors@R: person(given = "Siegfried", family = "Köstlmeier", role = c("aut", "cre", "cph"), email = "siegfried.koestlmeier@gmail.com", comment = c(ORCID = "0000-0002-7221-6981"))
Maintainer: Siegfried Köstlmeier <siegfried.koestlmeier@gmail.com>
Description: The Iterative Cumulative Sum of Squares (ICSS) algorithm by Inclan/Tiao (1994) <https://www.jstor.org/stable/2290916> detects multiple change points, i.e. structural break points, in the variance of a sequence of independent observations. For series of moderate size (i.e. 200 observations and beyond), the ICSS algorithm offers results comparable to those obtained by a Bayesian approach or by likelihood ration tests, without the heavy computational burden required by these approaches.
License: GPL-2
Depends: R (>= 3.5.0)
Imports: rstack
Suggests: testthat
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2020-05-26 11:52:46 UTC; LocalAdmin
Author: Siegfried Köstlmeier [aut, cre, cph] (<https://orcid.org/0000-0002-7221-6981>)
Repository: CRAN
Date/Publication: 2020-06-02 09:40:09 UTC

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New package farrell with initial version 0.1.0
Package: farrell
Type: Package
Title: Interactive Interface to Data Envelopment Analysis Modeling
Version: 0.1.0
Author: Mohamed El Fodil Ihaddaden
Maintainer: Mohamed El Fodil Ihaddaden <ihaddaden.fodeil@gmail.com>
Description: Allows the user to execute interactively radial data envelopment analysis models. The user has the ability to upload a data frame, select the input/output variables, choose the technology assumption to adopt and decide whether to run an input or an output oriented model. When the model is executed a set of results are displayed which include efficiency scores, peers' determination, scale efficiencies' evaluation and slacks' calculation. Fore more information about the theoretical background of the package, please refer to Bogetoft & Otto (2011) <doi:10.1007/978-1-4419-7961-2>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: shiny, miniUI, data.table, magrittr, shinyWidgets, Benchmarking, shinycssloaders, readr, rlang, tibble, utils, dplyr, DT
RoxygenNote: 7.1.0
URL: https://github.com/feddelegrand7/farrell
BugReports: https://github.com/feddelegrand7/farrell/issues
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-05-26 11:06:17 UTC; THINKPAD L390
Repository: CRAN
Date/Publication: 2020-06-02 09:40:06 UTC

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New package tfaddons with initial version 0.10.0
Package: tfaddons
Type: Package
Title: Interface to 'TensorFlow SIG Addons'
Version: 0.10.0
Authors@R: c( person("Turgut", "Abdullayev", role = c("aut", "cre"), email = "turqut.a.314@gmail.com") )
Maintainer: Turgut Abdullayev <turqut.a.314@gmail.com>
Description: 'TensorFlow SIG Addons' <https://www.tensorflow.org/addons> is a repository of community contributions that conform to well-established API patterns, but implement new functionality not available in core 'TensorFlow'. 'TensorFlow' natively supports a large number of operators, layers, metrics, losses, optimizers, and more. However, in a fast moving field like Machine Learning, there are many interesting new developments that cannot be integrated into core 'TensorFlow' (because their broad applicability is not yet clear, or it is mostly used by a smaller subset of the community).
License: Apache License 2.0
URL: https://github.com/henry090/tfaddons
BugReports: https://github.com/henry090/tfaddons/issues
SystemRequirements: TensorFlow >= 2.0 (https://www.tensorflow.org/)
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
Imports: reticulate, tensorflow, rstudioapi, keras, purrr
Suggests: knitr, rmarkdown, testthat, dplyr
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-05-25 15:30:15 UTC; turgutabdullayev
Author: Turgut Abdullayev [aut, cre]
Repository: CRAN
Date/Publication: 2020-06-02 08:50:04 UTC

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New package Rdca with initial version 0.1.0
Package: Rdca
Title: DCA Tools for Decline Rate Analysis and EUR Forecast
Version: 0.1.0
Date: 2020-05-25
Authors@R: person(given = "Farshad", family = "Tabasinejad", role = c("aut", "cre"), email = "farshad.tabasinejad@susaenergy.com")
Description: Arps Decline Curve Analysis (DCA) models for production rate, cumulative production, nominal decline rate, the derivative of loss-ratio, and estimated ultimate recovery (EUR) predictions for oil and gas wells. Arps, J. J. (1945) <doi:10.2118/945228-G>. Robertson, S. (1988) <https://www.onepetro.org/general/SPE-18731-MS>.
License: GPL-3
URL: https://susaenergy.github.io/Rdca_ws/
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
LinkingTo: Rcpp, RcppArmadillo
Imports: Rcpp, minpack.lm, Rdpack, dplyr, magrittr
RdMacros: Rdpack
Suggests: knitr, rmarkdown, testthat, tibble, ggplot2, ggpubr
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2020-05-26 02:56:52 UTC; ftn60
Author: Farshad Tabasinejad [aut, cre]
Maintainer: Farshad Tabasinejad <farshad.tabasinejad@susaenergy.com>
Repository: CRAN
Date/Publication: 2020-06-02 08:50:29 UTC

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New package precisely with initial version 0.1.0
Type: Package
Package: precisely
Title: Estimate Sample Size Based on Precision Rather than Power
Version: 0.1.0
Authors@R: person("Malcolm", "Barrett", email = "malcolmbarrett@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0003-0299-5825"))
Maintainer: Malcolm Barrett <malcolmbarrett@gmail.com>
Description: Estimate sample size based on precision rather than power. 'precisely' is a study planning tool to calculate sample size based on precision. Power calculations are focused on whether or not an estimate will be statistically significant; calculations of precision are based on the same principles as power calculation but turn the focus to the width of the confidence interval. 'precisely' is based on the work of Rothman and Greenland (2018) <doi: 10.1097/EDE.0000000000000876>.
License: MIT + file LICENSE
URL: https://github.com/malcolmbarrett/precisely
BugReports: https://github.com/malcolmbarrett/precisely/issues
Depends: R (>= 3.2.0)
Imports: dplyr, ggplot2, magrittr, purrr, rlang, shiny, shinycssloaders, shinythemes, tidyr
Suggests: ggrepel, knitr, rmarkdown, spelling, testthat, vdiffr, covr
VignetteBuilder: knitr
Encoding: UTF-8
Language: en-US
LazyData: true
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-05-26 03:56:01 UTC; malcolmbarrett
Author: Malcolm Barrett [aut, cre] (<https://orcid.org/0000-0003-0299-5825>)
Repository: CRAN
Date/Publication: 2020-06-02 08:50:09 UTC

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Sun, 31 May 2020

New package glmm with initial version 1.4
Package: glmm
Type: Package
Title: Generalized Linear Mixed Models via Monte Carlo Likelihood Approximation
Version: 1.4
Date: 2020-5-24
Authors@R: c(person("Christina", "Knudson", role = c("aut", "cre"), email = "knud8583@stthomas.edu"), person("Charles J.", "Geyer", role = "ctb", email = "geyer@umn.edu"), person("Sydney", "Benson", role = "ctb", email = "bens0643@umn.edu"))
Maintainer: Christina Knudson <knud8583@stthomas.edu>
Description: Approximates the likelihood of a generalized linear mixed model using Monte Carlo likelihood approximation. Then maximizes the likelihood approximation to return maximum likelihood estimates, observed Fisher information, and other model information.
License: GPL-2
Depends: R (>= 3.5), trust, mvtnorm, Matrix, parallel, doParallel
Imports: stats, foreach, itertools, utils
ByteCompile: TRUE
NeedsCompilation: yes
Suggests: knitr
RoxygenNote: 7.0.2
Packaged: 2020-05-24 20:40:44 UTC; admin
Author: Christina Knudson [aut, cre], Charles J. Geyer [ctb], Sydney Benson [ctb]
Repository: CRAN
Date/Publication: 2020-05-31 10:30:02 UTC

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New package AmpGram with initial version 1.0
Package: AmpGram
Type: Package
Title: Prediction of Antimicrobial Peptides
Version: 1.0
LazyData: TRUE
Date: 2020-05-19
Authors@R: c(person("Michal", "Burdukiewicz", email = "michalburdukiewicz@gmail.com", comment = c(ORCID = "0000-0001-8926-582X"), role = c("cre", "aut")), person("Katarzyna", "Sidorczuk", email = "sidorczuk.katarzyna17@gmail.com", role = c("ctb")), person("Filip", "Pietluch", email = "fpietluch@gmail.com", role = c("ctb")), person("Dominik", "Rafacz", email = "dominikrafacz@gmail.com", role = c("aut")), person("Stefan", "Roediger", email = "stefan.roediger@b-tu.de", comment = c(ORCID = "0000-0002-1441-6512"), role = c("ctb")), person("Jaroslaw", "Chilimoniuk", email = "jaroslaw.chilimoniuk@gmail.com", comment = c(ORCID = "0000-0001-5467-018X"), role = c("ctb")))
Description: Predicts antimicrobial peptides using random forests trained on the n-gram encoded peptides. The implemented algorithm can be accessed from both the command line and shiny-based GUI. The AmpGram model is too large for CRAN and it has to be downloaded separately from the repository: <https://github.com/michbur/AmpGramModel>.
License: GPL-3
URL: https://github.com/michbur/AmpGram
BugReports: https://github.com/michbur/AmpGram/issues
Encoding: UTF-8
Depends: R (>= 3.5.0)
Imports: biogram, devtools, pbapply, ranger, shiny, stringi
Suggests: DT, ggplot2, pander, rmarkdown, shinythemes, spelling
Repository: CRAN
RoxygenNote: 7.1.0
Language: en-US
NeedsCompilation: no
Packaged: 2020-05-22 11:38:49 UTC; michal
Author: Michal Burdukiewicz [cre, aut] (<https://orcid.org/0000-0001-8926-582X>), Katarzyna Sidorczuk [ctb], Filip Pietluch [ctb], Dominik Rafacz [aut], Stefan Roediger [ctb] (<https://orcid.org/0000-0002-1441-6512>), Jaroslaw Chilimoniuk [ctb] (<https://orcid.org/0000-0001-5467-018X>)
Maintainer: Michal Burdukiewicz <michalburdukiewicz@gmail.com>
Date/Publication: 2020-05-31 10:10:03 UTC

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New package universals with initial version 0.0.1
Package: universals
Title: S3 Generics for Bayesian Analyses
Version: 0.0.1
Authors@R: c(person(given = "Joe", family = "Thorley", role = c("aut", "cre"), email = "joe@poissonconsulting.ca", comment = c(ORCID = "0000-0002-7683-4592")), person(given = "Poisson Consulting", role = c("cph", "fnd")))
Description: Provides S3 generic methods and some default implementations for Bayesian analyses that generate Markov Chain Monte Carlo (MCMC) samples. The purpose of 'universals' is to reduce package dependencies and conflicts. The 'nlist' package implements all the methods for its 'nlists' class.
License: MIT + file LICENSE
URL: https://github.com/poissonconsulting/universals
BugReports: https://github.com/poissonconsulting/universals/issues
Depends: R (>= 3.3)
Suggests: covr, testthat
Encoding: UTF-8
Language: en-US
LazyData: true
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-05-19 22:07:23 UTC; joe
Author: Joe Thorley [aut, cre] (<https://orcid.org/0000-0002-7683-4592>), Poisson Consulting [cph, fnd]
Maintainer: Joe Thorley <joe@poissonconsulting.ca>
Repository: CRAN
Date/Publication: 2020-05-31 09:50:02 UTC

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New package TwitterAutomatedTrading with initial version 0.1.0
Package: TwitterAutomatedTrading
Type: Package
Title: Automated Trading Using Tweets
Version: 0.1.0
Author: Lucas Godeiro
Maintainer: Lucas Godeiro <lucas.godeiro@hotmail.com>
Description: Provides an integration to the 'metatrader 5'. The functionalities carry out automated trading using sentiment indexes computed from 'twitter' and/or 'stockwits'. The sentiment indexes are based on the ph.d. dissertation "Essays on Economic Forecasting Models" (Godeiro,2018) <https://repositorio.ufpb.br/jspui/handle/123456789/15198> The integration between the 'R' and the 'metatrader 5' allows sending buy/sell orders to the brokerage.
License: GPL-3
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.1.0)
RoxygenNote: 7.1.0
URL: https://github.com/lucasgodeiro/TwitterAutomatedTrading
BugReports: https://github.com/lucasgodeiro/TwitterAutomatedTrading/issues
Suggests: knitr, rmarkdown, covr
VignetteBuilder: knitr
Imports: curl, dplyr, jsonlite, lubridate, plyr, purrr, tibble, twitteR, naptime, utils, tidytext, magrittr
NeedsCompilation: no
Packaged: 2020-05-13 15:52:02 UTC; Cliente
Repository: CRAN
Date/Publication: 2020-05-31 09:50:13 UTC

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New package stringfish with initial version 0.11
Package: stringfish
Title: Alt String Implementation
Version: 0.11
Authors@R: c( person("Travers", "Ching", email = "traversc@gmail.com", role = c("aut", "cre", "cph")), person("Phillip", "Hazel", role = c("ctb"), comment = "Bundled PCRE2 code"), person("Zoltan", "Herczeg", role = c("ctb", "cph"), comment = "Bundled PCRE2 code"), person("University of Cambridge", role = c("cph"), comment = "Bundled PCRE2 code"), person("Tilera Corporation", role = c("cph"), comment = "Stack-less Just-In-Time compiler bundled with PCRE2"))
Maintainer: Travers Ching <traversc@gmail.com>
Description: Provides an extendable and performant 'alt-string' implementation backed by 'C++' vectors and strings.
License: GPL-3
Biarch: true
Encoding: UTF-8
Depends: R (>= 3.5.0)
SystemRequirements: C++11
LinkingTo: Rcpp (>= 0.12.18.3)
Imports: Rcpp
Suggests: qs, knitr, rmarkdown
VignetteBuilder: knitr
RoxygenNote: 7.1.0
Copyright: Copyright for the bundled 'PCRE2' library is held by University of Cambridge, Zoltan Herczeg and Tilera Coporation (Stack-less Just-In-Time compiler).
URL: https://github.com/traversc/stringfish
BugReports: https://github.com/traversc/stringfish/issues
NeedsCompilation: yes
Packaged: 2020-05-14 08:19:19 UTC; tching
Author: Travers Ching [aut, cre, cph], Phillip Hazel [ctb] (Bundled PCRE2 code), Zoltan Herczeg [ctb, cph] (Bundled PCRE2 code), University of Cambridge [cph] (Bundled PCRE2 code), Tilera Corporation [cph] (Stack-less Just-In-Time compiler bundled with PCRE2)
Repository: CRAN
Date/Publication: 2020-05-31 09:50:07 UTC

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New package quantilogram with initial version 2.0.1
Package: quantilogram
Title: Cross-Quantilogram
Version: 2.0.1
Authors@R: c(person(given = "Tatsushi", family = "Oka", role = c("aut", "cre"), email = "oka.econ@gmail.com"), person(given = "Heejon", family = "Han", role = "ctb"), person(given = "Oliver", family = "Linton", role = "ctb"), person(given = "Yoon-Jae", family = "Whang", role = "ctb"))
Maintainer: Tatsushi Oka <oka.econ@gmail.com>
Description: Estimation and inference methods for the cross-quantilogram. The cross-quantilogram is a measure of nonlinear dependence between two variables, based on either unconditional or conditional quantile functions. The cross-quantilogram can be considered as an extension of the correlogram, which is a correlation function over multiple lag periods and mainly focuses on linear dependency. One can use the cross-quantilogram to detect the presence of directional predictability from one time series to another. This package provides a statistical inference method based on the stationary bootstrap. See Linton and Whang (2007) <doi:10.1016/j.jeconom.2007.01.004> for univariate time series analysis and Han, Linton, Oka and Whang (2016) <doi:10.1016/j.jeconom.2016.03.001> for multivariate time series analysis.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
Imports: quantreg, SparseM, stats, np
Depends: R (>= 2.10)
NeedsCompilation: no
Packaged: 2020-05-13 08:29:15 UTC; student-t
Author: Tatsushi Oka [aut, cre], Heejon Han [ctb], Oliver Linton [ctb], Yoon-Jae Whang [ctb]
Repository: CRAN
Date/Publication: 2020-05-31 10:00:03 UTC

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New package pbixr with initial version 0.1.3
Package: pbixr
Type: Package
Title: Access Data and Metadata from 'Microsoft' 'Power BI' Documents
Version: 0.1.3
Author: Don Diproto [aut, cre]
Maintainer: Don Diproto <package.pbixr@gmail.com>
Description: Access data and metadata from 'Microsoft' 'Power BI' ('.pbix', <https://powerbi.microsoft.com>) documents with R. The 'pbixr' package enables one to extract 'Power Query M' formulas (<https://docs.microsoft.com/en-us/power-query/>) and 'Data Analysis Expressions' ('DAX', <https://docs.microsoft.com/en-us/dax/>) queries and their properties, report layout and style, and data and data models.
URL: https://github.com/pbixr/pbixr
BugReports: https://github.com/pbixr/pbixr/issues
Depends: R (>= 3.2.0), dplyr
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: formatR, xml2, jsonlite, zip, utils, textclean, stringr
Suggests: knitr, rmarkdown, testthat (>= 2.1.0), RCurl, ggplot2, ggraph, igraph, imager, tidyr
VignetteBuilder: knitr
RoxygenNote: 7.0.0
SystemRequirements: 'Microsoft' 'PowerShell' (<https://docs.microsoft.com/en-us/powershell/>), 'Microsoft' 'Power BI' (<https://powerbi.microsoft.com>)
NeedsCompilation: no
Packaged: 2020-05-16 21:13:15 UTC; VIP
Repository: CRAN
Date/Publication: 2020-05-31 09:50:10 UTC

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New package knockoff with initial version 0.3.2
Package: knockoff
Type: Package
Title: The Knockoff Filter for Controlled Variable Selection
Version: 0.3.2
Date: 2018-09-15
Authors@R: c(person("Rina", "Foygel Barber", role = c("ctb"), comment="Development of the original Fixed-X Knockoffs"), person("Emmanuel", "Candes", role = c("ctb"), comment="Development of Model-X Knockoffs and original Fixed-X Knockoffs"), person("Lucas", "Janson", role = c("ctb"), comment="Development of Model-X Knockoffs"), person("Evan", "Patterson", role = c("aut"), comment="Original R package for the original Fixed-X Knockoffs"), person("Matteo", "Sesia", role = c("aut","cre"), comment="R package for Model-X Knockoffs", email="msesia@stanford.edu"))
Description: The knockoff filter is a general procedure for controlling the false discovery rate (FDR) when performing variable selection. For more information, see the website below and the accompanying paper: Candes et al., "Panning for Gold: Model-X Knockoffs for High-dimensional Controlled Variable Selection", 2016, <arXiv:1610.02351>.
License: GPL-3
URL: https://web.stanford.edu/group/candes/knockoffs/index.html
Depends: methods, stats
Imports: Rdsdp, Matrix, corpcor, glmnet, RSpectra, gtools, utils
Suggests: knitr, testthat, rmarkdown, lars, ranger, stabs, flare, doMC, parallel
RoxygenNote: 6.0.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-09-15 21:03:11 UTC; msesia
Author: Rina Foygel Barber [ctb] (Development of the original Fixed-X Knockoffs), Emmanuel Candes [ctb] (Development of Model-X Knockoffs and original Fixed-X Knockoffs), Lucas Janson [ctb] (Development of Model-X Knockoffs), Evan Patterson [aut] (Original R package for the original Fixed-X Knockoffs), Matteo Sesia [aut, cre] (R package for Model-X Knockoffs)
Maintainer: Matteo Sesia <msesia@stanford.edu>
Repository: CRAN
Date/Publication: 2018-09-16 16:30:08 UTC

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Sat, 30 May 2020

New package icd with initial version 4.0.9
Package: icd
Title: Comorbidity Calculations and Tools for ICD-9 and ICD-10 Codes
Version: 4.0.9
Authors@R: c(person(given = "Jack O.", family = "Wasey", role = c("aut", "cre", "cph"), email = "jack@jackwasey.com", comment = c(ORCID = "0000-0003-3738-4637")), person(given = "William", family = "Murphy", role = "ctb", email = "WMurphy@eatright.org", comment = "Van Walraven scores"), person(given = "Anobel", family = "Odisho", role = "ctb", email = "anobel.odisho@ucsf.edu", comment = "CMS Hierarchical Condition Codes"), person(given = "Vitaly", family = "Druker", role = "ctb", email = "vdruker@gmail.com", comment = "AHRQ CCS"), person(given = "Ed", family = "Lee", role = "ctb", comment = "explain codes in table format"), person(given = "Patrick", family = "McCormick", role = "ctb", email = "patrick@patrickmd.net", comment = "Multiple great pull requests"), person(given = "Alessandro", family = "Gasparini", role = "ctb"), person(given = "Michel", family = "Lang", role = "aut", email = "michellang@gmail.com", comment = "backport of R_user-dir for R version >4. ORCID = 0000-0001-9754-0393"), person(given = "R Core Team", role = c("aut", "cph"), comment = "utils::askYesNo backport and m4 script for OpenMP detection."))
Maintainer: Jack O. Wasey <jack@jackwasey.com>
Description: Calculate comorbidities, medical risk scores, and work very quickly and precisely with ICD-9 and ICD-10 codes. This package enables a work flow from raw tables of ICD codes in hospital databases to comorbidities. ICD-9 and ICD-10 comorbidity mappings from Quan (Deyo and Elixhauser versions), Elixhauser and AHRQ included. Common ambiguities and code formats are handled. Comorbidity computation includes Hierarchical Condition Codes, and an implementation of AHRQ Clinical Classifications. Risk scores include those of Charlson and van Walraven. US Clinical Modification, Word Health Organization, Belgian and French ICD-10 codes are supported, most of which are downloaded on demand.
License: GPL-3
URL: https://jackwasey.github.io/icd/
BugReports: https://github.com/jackwasey/icd/issues
Depends: R (>= 3.4)
Imports: methods, Rcpp (>= 0.12.3)
Suggests: graphics, httr, jsonlite, knitr, magrittr, nhds, readxl, rmarkdown (>= 1.11), RODBC, roxygen2 (>= 5.0.0), stats, testthat (>= 0.11.1), utils, xml2
LinkingTo: Rcpp (>= 0.12.3), RcppEigen
VignetteBuilder: knitr
Biarch: true
Classification/ACM-2012: Social and professional topics~Medical records, Applied computing~Health care information systems, Applied computing~Health informatics, Applied computing~Bioinformatics
Copyright: See file (inst/)COPYRIGHTS
Encoding: UTF-8
Language: en-US
LazyData: true
LazyDataCompression: xz
RoxygenNote: 7.1.0
NeedsCompilation: yes
Packaged: 2020-05-30 18:42:42 UTC; jack
Author: Jack O. Wasey [aut, cre, cph] (<https://orcid.org/0000-0003-3738-4637>), William Murphy [ctb] (Van Walraven scores), Anobel Odisho [ctb] (CMS Hierarchical Condition Codes), Vitaly Druker [ctb] (AHRQ CCS), Ed Lee [ctb] (explain codes in table format), Patrick McCormick [ctb] (Multiple great pull requests), Alessandro Gasparini [ctb], Michel Lang [aut] (backport of R_user-dir for R version >4. ORCID = 0000-0001-9754-0393), R Core Team [aut, cph] (utils::askYesNo backport and m4 script for OpenMP detection.)
Repository: CRAN
Date/Publication: 2020-05-31 02:00:07 UTC

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Fri, 29 May 2020

New package bioassays with initial version 0.1.0
Package: bioassays
Type: Package
Title: Summarising Multi Well Plate Cellular Assay
Version: 0.1.0
Authors@R: c(person("Anwar Azad", "Palakkan", role = c("aut", "cre"), email = "bioanwar@gmail.com"), person("Jamie", "Davies", role = "aut", email = "jamie.davies@ed.ac.uk"))
Description: The goal is to help users to analyse data from multi wells with minimum effort. Using these functions several plates can be analyzed automatically.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Imports: dplyr, ggplot2, stats, magrittr, nplr, reshape2, rlang
RoxygenNote: 7.1.0
Depends: R (>= 4.00)
Suggests: knitr, rmarkdown, testthat
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-05-22 15:18:12 UTC; Anwar
Author: Anwar Azad Palakkan [aut, cre], Jamie Davies [aut]
Maintainer: Anwar Azad Palakkan <bioanwar@gmail.com>
Repository: CRAN
Date/Publication: 2020-05-29 13:20:06 UTC

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New package projects with initial version 2.1.1
Package: projects
Title: A Project Infrastructure for Researchers
Version: 2.1.1
Authors@R: c(person(given = "Nik", family = "Krieger", role = c("aut", "cre"), email = "nk@case.edu"), person(given = "Adam", family = "Perzynski", role = "aut"), person(given = "Jarrod", family = "Dalton", role = "aut"))
Description: Provides a project infrastructure with a focus on manuscript creation. Creates a project folder with a single command, containing subdirectories for specific components, templates for manuscripts, and so on.
License: MIT + file LICENSE
URL: https://cran.r-project.org/package=projects
Depends: R (>= 3.4.0)
Imports: dplyr (>= 0.8.5), fs (>= 1.4.1), lubridate (>= 1.7.8), magrittr (>= 1.5), methods, purrr (>= 0.3.4), readr (>= 1.3.1), rlang (>= 0.4.6), rstudioapi (>= 0.11), sessioninfo (>= 1.1.1), stringr (>= 1.4.0), tibble (>= 3.0.1), vctrs (>= 0.2.4), zip (>= 2.0.4)
Suggests: forcats, here (>= 0.1), testthat (>= 2.3.2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
Collate: 'set_generics.R' 'class-projects_author.R' 'class-projects_stage.R' 'new.R' 'edit.R' 'email_authors.R' 'file_management.R' 'getters.R' 'header.R' 'metadata_manipulation.R' 'projects.R' 'reproducibility.R' 'setup.R' 'update.R' 'utilities.R' 'utils-pipe.R' 'validation.R' 'zzz.R'
NeedsCompilation: no
Packaged: 2020-05-28 15:06:36 UTC; kriegen
Author: Nik Krieger [aut, cre], Adam Perzynski [aut], Jarrod Dalton [aut]
Maintainer: Nik Krieger <nk@case.edu>
Repository: CRAN
Date/Publication: 2020-05-29 12:40:02 UTC

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New package DirichletReg with initial version 0.7-0
Package: DirichletReg
Type: Package
Version: 0.7-0
Date: 2020-05-28
Title: Dirichlet Regression in R
Description: Implements Dirichlet regression models in R.
Authors@R: person(given = c("Marco", "Johannes"), family = "Maier", email = "marco_maier@posteo.de", role = c("cre", "aut"), comment = c(ORCID = "0000-0002-1715-7456"))
Encoding: UTF-8
Depends: R (>= 3.0.0), Formula
Imports: stats, graphics, methods, maxLik
Suggests: rgl, knitr, formatR, testthat
License: GPL (>= 2)
URL: https://github.com/maiermarco/DirichletReg https://CRAN.R-project.org/package=DirichletReg
ByteCompile: yes
LazyLoad: yes
LazyData: yes
ZipData: yes
VignetteBuilder: knitr
Author: Marco Johannes Maier [cre, aut] (<https://orcid.org/0000-0002-1715-7456>)
Maintainer: Marco Johannes Maier <marco_maier@posteo.de>
Repository: CRAN
Repository/R-Forge/Project: dirichletreg
Repository/R-Forge/Revision: 32
Repository/R-Forge/DateTimeStamp: 2020-05-28 18:49:22
Date/Publication: 2020-05-29 12:30:14 UTC
NeedsCompilation: yes
Packaged: 2020-05-28 19:13:07 UTC; rforge

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New package DCPO with initial version 0.5.3
Package: DCPO
Version: 0.5.3
Title: Dynamic Comparative Public Opinion
Description: Estimates latent variables of public opinion cross-nationally and over time from sparse and incomparable survey data. 'DCPO' uses a population-level graded response model with country-specific item bias terms. Sampling is conducted with 'Stan'. References: Solt (2020) <doi:10.31235/osf.io/d5n9p>.
Authors@R: c( person("Frederick", "Solt", email = "frederick-solt@uiowa.edu", role = c("aut", "cre")), person("Trustees of", "Columbia University", role = "cph"))
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
ByteCompile: true
Depends: R (>= 3.4.0), Rcpp (>= 0.12.17), methods
Imports: rstan (>= 2.18.1), rstantools (>= 2.0.0), beepr, dplyr, forcats, janitor, purrr, tibble, tidyr
LinkingTo: StanHeaders (>= 2.18.0), rstan (>= 2.18.1), BH (>= 1.66.0-1), Rcpp (>= 0.12.0), RcppEigen (>= 0.3.3.4.0)
Suggests: knitr
SystemRequirements: GNU make
NeedsCompilation: yes
RoxygenNote: 7.0.0
Biarch: true
Packaged: 2020-05-28 13:23:22 UTC; fredsolt
Author: Frederick Solt [aut, cre], Trustees of Columbia University [cph]
Maintainer: Frederick Solt <frederick-solt@uiowa.edu>
Repository: CRAN
Date/Publication: 2020-05-29 12:50:02 UTC

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New package newscatcheR with initial version 0.0.1
Package: newscatcheR
Title: Programmatically Collect Normalized News from (Almost) Any Website
Version: 0.0.1
Authors@R: c(person(given = "Novica", family = "Nakov", role = c("aut", "cre"), email = "nnovica@gmail.com"), person(given = "Teofil", family = "Nakov", role = "ctb", email = "teofiln@gmail.com"), person(given = "Discindo", role = "cph"))
Description: Programmatically collect normalized news from (almost) any website. An 'R' clone of the <https://github.com/kotartemiy/newscatcher> 'Python' module.
License: MIT + file LICENSE
Depends: R (>= 2.10)
Imports: tidyRSS, utils
Suggests: knitr, rmarkdown, testthat
VignetteBuilder: knitr
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
Language: en-US
NeedsCompilation: no
Packaged: 2020-05-06 14:14:13 UTC; novica
Author: Novica Nakov [aut, cre], Teofil Nakov [ctb], Discindo [cph]
Maintainer: Novica Nakov <nnovica@gmail.com>
Repository: CRAN
Date/Publication: 2020-05-29 10:50:02 UTC

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New package glca with initial version 0.1.0
Package: glca
Type: Package
Title: Latent Class Analysis with Grouped Data
Date: 2020-05-22
Version: 0.1.0
Author: Youngsun Kim, Hwan Chung
Maintainer: Youngsun Kim <kim0sun@korea.ac.kr>
Description: Fits latent class analysis (LCA) including group variable and covariates. The group variable can be handled either by multilevel LCA described in Vermunt (2003) <DOI:10.1111/j.0081-1750.2003.t01-1-00131.x> or standard LCA at each level of group variable. The covariates can be incorporated in the form of logistic regression (Bandeen-Roche et al. (1997) <DOI:10.1080/01621459.1997.10473658>).
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.5.0)
Imports: Rcpp (>= 1.0.3), MASS
LinkingTo: Rcpp
RoxygenNote: 6.1.1
NeedsCompilation: yes
Packaged: 2020-05-22 01:38:48 UTC; kim0sun
Repository: CRAN
Date/Publication: 2020-05-29 10:50:06 UTC

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New package EMSS with initial version 1.0.0
Package: EMSS
Type: Package
Title: Some EM-Type Estimation Methods for the Heckman Selection Model
Version: 1.0.0
Author: Kexuan Yang <717260446@qq.com>, Sang Kyu Lee <leesa111@msu.edu>, Zhao Jun <zhaojun2021@hotmail.com>, and Hyoung-Moon Kim <hmk966a@gmail.com >
Maintainer: Sang Kyu Lee <leesa111@msu.edu>
Description: Some EM-type algorithms to estimate parameters for the well-known Heckman selection model are provided in the package. Such algorithms are as follow: ECM(Expectation/Conditional Maximization), ECM(NR)(the Newton-Raphson method is adapted to the ECM) and ECME(Expectation/Conditional Maximization Either). Since the algorithms are based on the EM algorithm, they also have EM’s main advantages, namely, stability and ease of implementation. Further details and explanations of the algorithms can be found in Zhao et al. (2020) <doi: 10.1016/j.csda.2020.106930>.
Depends: R (>= 2.10)
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Imports: sampleSelection, mvtnorm
NeedsCompilation: no
Packaged: 2020-05-21 20:16:00 UTC; sangkyu
Repository: CRAN
Date/Publication: 2020-05-29 10:30:06 UTC

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New package MrSGUIDE with initial version 0.1.0
Package: MrSGUIDE
Type: Package
Title: Multiple Responses Subgroup Identification using 'GUIDE' Algorithm
Version: 0.1.0
Date: 2020-05-04
Authors@R: c(person(given ="Peigen", family = "Zhou", role = c("aut", "cre"), email = "pzhou9@wisc.edu", comment = c(ORCID = "0000-0003-4609-0374")), person(given = "Wei-Yin", family = "Loh", role = c("aut"), email= "loh@stat.wisc.edu", comment = c(ORCID = "0000-0001-6983-2495")))
Maintainer: Peigen Zhou <pzhou9@wisc.edu>
Description: An R implementation of 'GUIDE' style algorithm focusing on subgroup identification problem under multiple responses of Loh et al. (2019) <doi:10.1002/widm.1326>. This package is intended for use for randomized trials and observational studies.
License: GPL-3
URL: http://www.stat.wisc.edu/~loh/guide.html, https://baconzhou.github.io/MrSGUIDE/, http://pages.stat.wisc.edu/~loh/treeprogs/guide/LZ19.pdf, http://pages.stat.wisc.edu/~loh/treeprogs/guide/sm19.pdf
BugReports: https://github.com/baconzhou/mrsguide/issues
LinkingTo: Rcpp, RcppArmadillo, BH
SystemRequirements: GNU make, C++11
Depends: R (>= 3.1.0)
Imports: Rcpp, yaml, magrittr
RoxygenNote: 7.1.0
Suggests: knitr, rmarkdown, visNetwork, ggplot2
VignetteBuilder: knitr
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2020-05-21 17:12:20 UTC; peigen
Author: Peigen Zhou [aut, cre] (<https://orcid.org/0000-0003-4609-0374>), Wei-Yin Loh [aut] (<https://orcid.org/0000-0001-6983-2495>)
Repository: CRAN
Date/Publication: 2020-05-29 10:00:02 UTC

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Thu, 28 May 2020

New package BayesPostEst with initial version 0.2.1
Package: BayesPostEst
Type: Package
Title: Generate Postestimation Quantities for Bayesian MCMC Estimation
Version: 0.2.1
Date: 2020-05-27
Authors@R: c(person("Johannes", "Karreth", email = "jkarreth@ursinus.edu", role = c("aut"), comment = c(ORCID = "0000-0003-4586-7153")), person("Shana", "Scogin", email = "shanarscogin@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-7801-853X")), person("Rob", "Williams", email = "jayrobwilliams@gmail.com", role = c("aut"), comment = c(ORCID = "0000-0001-9259-3883")), person("Andreas", "Beger", email = "adbeger@gmail.com", role = c("aut"), comment = c(ORCID = "0000-0003-1883-3169")), person("Myunghee", "Lee", email = "mlq38@mail.missouri.edu", role = c("ctb")), person("Neil", "Williams", email = "snpwill@uga.edu", role = c("ctb")))
Description: An implementation of functions to generate and plot postestimation quantities after estimating Bayesian regression models using Markov chain Monte Carlo (MCMC). Functionality includes the estimation of the Precision-Recall curves (see Beger, 2016 <doi:10.2139/ssrn.2765419>), the implementation of the observed values method of calculating predicted probabilities by Hanmer and Kalkan (2013) <doi:10.1111/j.1540-5907.2012.00602.x>, the implementation of the average value method of calculating predicted probabilities (see King, Tomz, and Wittenberg, 2000 <doi:10.2307/2669316>), and the generation and plotting of first differences to summarize typical effects across covariates (see Long 1997, ISBN:9780803973749; King, Tomz, and Wittenberg, 2000 <doi:10.2307/2669316>). This package can be used with MCMC output generated by any Bayesian estimation tool including 'JAGS', 'BUGS', 'MCMCpack', and 'Stan'.
URL: https://github.com/ShanaScogin/BayesPostEst
BugReports: https://github.com/ShanaScogin/BayesPostEst/issues
License: GPL-3
Imports: carData, caTools, coda (>= 0.13), dplyr (>= 0.5.0), ggmcmc, ggplot2, ggridges, R2jags, reshape2, rlang, stats, texreg, runjags, tidyr (>= 0.5.1), HDInterval, ROCR
Depends: R (>= 3.5.0)
Encoding: UTF-8
LazyData: TRUE
LazyLoad: TRUE
Suggests: datasets, knitr, MCMCpack, rjags, rmarkdown, rstan (>= 2.10.1), rstanarm, testthat, covr
VignetteBuilder: knitr
RoxygenNote: 6.1.1
SystemRequirements: JAGS (http://mcmc-jags.sourceforge.net)
NeedsCompilation: no
Packaged: 2020-05-27 19:56:24 UTC; shanascogin
Author: Johannes Karreth [aut] (<https://orcid.org/0000-0003-4586-7153>), Shana Scogin [aut, cre] (<https://orcid.org/0000-0002-7801-853X>), Rob Williams [aut] (<https://orcid.org/0000-0001-9259-3883>), Andreas Beger [aut] (<https://orcid.org/0000-0003-1883-3169>), Myunghee Lee [ctb], Neil Williams [ctb]
Maintainer: Shana Scogin <shanarscogin@gmail.com>
Repository: CRAN
Date/Publication: 2020-05-28 23:50:02 UTC

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New package genius with initial version 2.2.2
Package: genius
Title: Easily Access Song Lyrics from Genius.com
Version: 2.2.2
Authors@R: c( person("Josiah", "Parry", email = "josiah.parry@gmail.com", role = c("aut", "cre")), person("Nathan", "Barr", email = "nab222@cornell.edu", role = c("aut", "ctb")), person("Chris", "Billingham", email = "chris.billingham@gmail.com", role = "ctb"), person("Evan", "Oppenheimer", email = "eoppe1022@gmail.com", role = "ctb") )
Description: Easily access song lyrics in a tidy way.
URL: https://github.com/josiahparry/genius
BugReports: https://github.com/josiahparry/genius/issues
Depends: R (>= 3.1.2)
Imports: dplyr (>= 0.7.0), rvest, stringr, tidyr, purrr, readr, tibble, tidytext, reshape2, rlang
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
Suggests: knitr, rmarkdown, testthat
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-05-26 19:17:53 UTC; josiah
Author: Josiah Parry [aut, cre], Nathan Barr [aut, ctb], Chris Billingham [ctb], Evan Oppenheimer [ctb]
Maintainer: Josiah Parry <josiah.parry@gmail.com>
Repository: CRAN
Date/Publication: 2020-05-28 16:10:02 UTC

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New package NBLDA with initial version 1.0.0
Package: NBLDA
Type: Package
Title: Negative Binomial Linear Discriminant Analysis
Version: 1.0.0
Date: 2020-05-28
Authors@R: c(person("Dincer", "Goksuluk", role = c("aut", "cre"), email = "dincergoksuluk@erciyes.edu.tr"), person("Gokmen", "Zararsiz", role = c("aut")), person("Selcuk", "Korkmaz", role = c("aut")), person(c("Ahmet", "Ergun"), "Karaagaoglu", role = c("ths", "aut")))
Description: We proposed a package for classification task which uses Negative Binomial distribution within Linear Discriminant Analysis (NBLDA). It is basically an extension of 'PoiClaClu' package to Negative Binomial distribution. The classification algorithms are based on the papers Dong et al. (2016, ISSN: 1471-2105) and Witten, DM (2011, ISSN: 1932-6157) for NBLDA and PLDA respectively. Although PLDA is a sparse algorithm and can be used for variable selection, the algorithm proposed by Dong et. al. is not sparse, hence, it uses all variables in the classifier. Here, we extent Dong et. al.'s algorithm to sparse case by shrinking overdispersion towards 0 (Yu et. al., 2013, ISSN: 1367-4803) and offset parameter towards 1 (as proposed by Witten DM, 2011). We support only the classification task with this version. However, the clustering task will be included with the following versions.
Imports: methods, stats, graphics
Suggests: knitr
Depends: ggplot2
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
Collate: 'FindBestTransform.R' 'all_classes.R' 'all_generics.R' 'control.R' 'copiedFromOtherPackages.R' 'generateCountData.R' 'getShrinkedDispersions.R' 'helper_functions.R' 'normalize_counts.R' 'package_and_supplementary.R' 'plot.nblda.R' 'predict.nblda.R' 'trainNBLDA.R' 'zzz_methods.R'
NeedsCompilation: no
Packaged: 2020-05-28 09:29:32 UTC; dncr
Author: Dincer Goksuluk [aut, cre], Gokmen Zararsiz [aut], Selcuk Korkmaz [aut], Ahmet Ergun Karaagaoglu [ths, aut]
Maintainer: Dincer Goksuluk <dincergoksuluk@erciyes.edu.tr>
Repository: CRAN
Date/Publication: 2020-05-28 10:50:13 UTC

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New package maptpx with initial version 1.9-7
Package: maptpx
Title: MAP Estimation of Topic Models
Version: 1.9-7
Author: Matt Taddy <mataddy@gmail.com>
Depends: R (>= 2.10), slam
Suggests: MASS
Description: Maximum a posteriori (MAP) estimation for topic models (i.e., Latent Dirichlet Allocation) in text analysis, as described in Taddy (2012) 'On estimation and selection for topic models'. Previous versions of this code were included as part of the 'textir' package. If you want to take advantage of openmp parallelization, uncomment the relevant flags in src/MAKEVARS before compiling.
Maintainer: Matt Taddy <mataddy@gmail.com>
License: GPL-3
URL: http://taddylab.com
NeedsCompilation: yes
Packaged: 2020-05-27 23:43:34 UTC; mataddy
Repository: CRAN
Date/Publication: 2020-05-28 10:50:06 UTC

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Wed, 27 May 2020

New package Rchoice with initial version 0.3-2
Package: Rchoice
Title: Discrete Choice (Binary, Poisson and Ordered) Models with Random Parameters
Version: 0.3-2
Author: Mauricio Sarrias <msarrias86@gmail.com>
Maintainer: Mauricio Sarrias <msarrias86@gmail.com>
Description: An implementation of simulated maximum likelihood method for the estimation of Binary (Probit and Logit), Ordered (Probit and Logit) and Poisson models with random parameters for cross-sectional and longitudinal data.
Depends: R (>= 3.1.0), Formula, maxLik
Imports: msm, plm, plotrix, stats, graphics
Suggests: car, lmtest, memisc, pglm, sandwich
License: GPL (>= 2)
URL: http://msarrias.com/rchoice-package-in-r.html
LazyData: no
RoxygenNote: 7.1.0
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2020-05-27 12:42:31 UTC; mauriciosarrias
Repository: CRAN
Date/Publication: 2020-05-27 15:30:07 UTC

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New package sanon with initial version 1.6
Package: sanon
Type: Package
Title: Stratified Analysis with Nonparametric Covariable Adjustment
Version: 1.6
Date: 2020-05-27
Author: Atsushi Kawaguchi
Maintainer: Atsushi Kawaguchi <kawa_a24@yahoo.co.jp>
Depends: R (>= 3.5)
Description: There are several functions to implement the method for analysis in a randomized clinical trial with strata with following key features. A stratified Mann-Whitney estimator addresses the comparison between two randomized groups for a strictly ordinal response variable. The multivariate vector of such stratified Mann-Whitney estimators for multivariate response variables can be considered for one or more response variables such as in repeated measurements and these can have missing completely at random (MCAR) data. Non-parametric covariance adjustment is also considered with the minimal assumption of randomization. The p-value for hypothesis test and confidence interval are provided.
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2020-05-27 12:50:45 UTC; kawaguchi
Repository: CRAN
Date/Publication: 2020-05-27 14:20:03 UTC

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New package OasisR with initial version 3.0.2
Package: OasisR
Type: Package
Version: 3.0.2
Date: 2020-05-27
Title: Outright Tool for the Analysis of Spatial Inequalities and Segregation
Author: Mihai Tivadar <mihai.tivadar@inrae.fr>
Maintainer: Mihai Tivadar <mihai.tivadar@inrae.fr>
Description: A set of indexes and tests for the analysis of social segregation.
Depends: R (>= 4.0.0)
Imports: rgdal (>= 1.4-8), rgeos (>= 0.5-3), spdep (>= 1.1-3), measurements (>= 1.4.0), methods (>= 4.0.0), seg (>= 0.5-7), outliers (>= 0.14)
License: GPL-2 | GPL-3
LazyData: true
Suggests: testthat, knitr
RoxygenNote: 7.1.0
NeedsCompilation: no
Encoding: UTF-8
Packaged: 2020-05-27 10:33:58 UTC; mihai.tivadar
Repository: CRAN
Date/Publication: 2020-05-27 13:10:09 UTC

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New package Rarefy with initial version 1.0
Package: Rarefy
Type: Package
Title: Rarefaction Methods
Version: 1.0
Date: 2020-04-20
Authors@R: c(person("Elisa","Thouverai",email="elisa.th95@gmail.com",role=c("aut","cre")),person("Sandrine","Pavoine",role="aut"),person("Enrico","Tordoni",role="aut"),person("Duccio","Rocchini",role='aut'),person("Carlo","Ricotta",role='aut'),person("Alessandro","Chiarucci",role='aut'),person("Giovanni","Bacaro",role="aut"))
Description: Includes functions for the calculation of spatially and non-spatially explicit rarefaction curves using different indices of taxonomic, functional and phylogenetic diversity. The user can also rarefy any biodiversity metric as provided by a self-written function (or an already existent one) that gives as output a vector with the values of a certain index of biodiversity calculated per plot (Ricotta, C., Acosta, A., Bacaro, G., Carboni, M., Chiarucci, A., Rocchini, D., Pavoine, S. (2019) <doi:10.1016/j.ecolind.2019.105606>; Bacaro, G., Altobelli, A., Cameletti, M., Ciccarelli, D., Martellos, S., Palmer, M. W., … Chiarucci, A. (2016) <doi:10.1016/j.ecolind.2016.04.026>; Bacaro, G., Rocchini, D., Ghisla, A., Marcantonio, M., Neteler, M., & Chiarucci, A. (2012) <doi:10.1016/j.ecocom.2012.05.007>).
Depends: R (>= 3.5.0)
Imports: ade4,adiv,dplyr,geiger,methods,stats,vegan
Suggests: picante
License: GPL (>= 2)
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2020-05-21 16:20:53 UTC; elisathouverai
Author: Elisa Thouverai [aut, cre], Sandrine Pavoine [aut], Enrico Tordoni [aut], Duccio Rocchini [aut], Carlo Ricotta [aut], Alessandro Chiarucci [aut], Giovanni Bacaro [aut]
Maintainer: Elisa Thouverai <elisa.th95@gmail.com>
Repository: CRAN
Date/Publication: 2020-05-27 10:30:10 UTC

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New package featureCorMatrix with initial version 0.4.0
Package: featureCorMatrix
Type: Package
Title: Measurement Level Independent Feature Correlation Matrix
Version: 0.4.0
Authors@R: c(person("Guido", "Moeser", role = c("aut", "cre"), email = "guido.moeser@masem.de"), person("Ilja", "Muhl", role = "aut"))
Maintainer: Guido Moeser <guido.moeser@masem.de>
Description: Uses three different correlation coefficients to calculate measurement-level adequate correlations in a feature matrix: Pearson product-moment correlation coefficient, Intraclass correlation and Cramer's V.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Imports: stats
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-05-18 13:57:00 UTC; Dr. Guido Möser
Author: Guido Moeser [aut, cre], Ilja Muhl [aut]
Repository: CRAN
Date/Publication: 2020-05-27 10:30:02 UTC

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New package bbsBayes with initial version 2.2.1
Package: bbsBayes
Type: Package
Title: Hierarchical Bayesian Analysis of North American BBS Data
Version: 2.2.1
Date: 2020-05-13
Authors@R: c(person("Brandon P.M.", "Edwards", role = c("aut", "cre"), email = "edwardsb@uoguelph.ca"), person("Adam C.", "Smith", role = "aut", email = "adam.smith2@canada.ca"))
Imports: progress, jagsUI, ggrepel, geofacet, ggplot2, stringr, grDevices, rgdal, dplyr, sf, tools, latticeExtra, rappdirs
Depends: R (>= 3.5)
SystemRequirements: JAGS 4.3.0 (https://sourceforge.net/projects/mcmc-jags/)
URL: https://github.com/BrandonEdwards/bbsBayes
NeedsCompilation: no
Description: The North American Breeding Bird Survey (BBS) is a long-running program that seeks to monitor the status and trends of the breeding birds in North America. Since its start in 1966, the BBS has accumulated over 50 years of data for over 300 species of North American Birds. Given the temporal and spatial structure of the data, hierarchical Bayesian models are used to assess the status and trends of these 300+ species of birds. 'bbsBayes' allows you to perform hierarchical Bayesian analysis of BBS data. You can run a full model analysis for one or more species that you choose, or you can take more control and specify how the data should be stratified, prepared for 'JAGS', or modelled. The functions provided here allow you to replicate analyses performed by the United State Geological Survey (USGS, see Link and Sauer (2011) <doi:10.1525/auk.2010.09220>) and Canadian Wildlife Service (CWS, see Smith and Edwards (2020) <doi:10.1101/2020.03.26.010215>).
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Packaged: 2020-05-21 14:01:22 UTC; brand
Author: Brandon P.M. Edwards [aut, cre], Adam C. Smith [aut]
Maintainer: Brandon P.M. Edwards <edwardsb@uoguelph.ca>
Repository: CRAN
Date/Publication: 2020-05-27 10:30:06 UTC

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New package almanac with initial version 0.1.0
Package: almanac
Title: Tools for Working with Recurrence Rules
Version: 0.1.0
Authors@R: c(person(given = "Davis", family = "Vaughan", role = c("aut", "cre"), email = "davis@rstudio.com"), person(given = "RStudio", role = "cph"))
Description: Provides tools for defining recurrence rules and recurrence bundles. Recurrence rules are a programmatic way to define a recurring event, like the first Monday of December. Multiple recurrence rules can be combined into larger recurrence bundles. Together, these provide a system for adjusting and generating sequences of dates while simultaneously skipping over dates in a recurrence bundle's event set.
License: MIT + file LICENSE
URL: https://github.com/DavisVaughan/almanac
BugReports: https://github.com/DavisVaughan/almanac/issues
Depends: R (>= 3.2)
Imports: glue, lubridate, magrittr, R6, rlang, V8 (>= 3.0.1), vctrs (>= 0.3.0)
Suggests: covr, knitr, rmarkdown, testthat (>= 2.1.0)
VignetteBuilder: knitr
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
NeedsCompilation: yes
Packaged: 2020-05-21 10:33:31 UTC; davis
Author: Davis Vaughan [aut, cre], RStudio [cph]
Maintainer: Davis Vaughan <davis@rstudio.com>
Repository: CRAN
Date/Publication: 2020-05-27 10:10:03 UTC

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New package geodaData with initial version 0.1.0
Package: geodaData
Title: Spatial Analysis Datasets for Teaching
Version: 0.1.0
Authors@R: c(person(given = "Angela", family = "Li", role = c("aut", "cre"), email = "ali6@uchicago.edu", comment = c(ORCID = "0000-0002-8956-419X")), person(given = "Luc", family = "Anselin", role = c("ctb"), comment = "Creator of original spatial datasets") )
Description: Stores small spatial datasets used to teach basic spatial analysis concepts. Datasets are based off of the 'GeoDa' software workbook and data site <https://geodacenter.github.io/data-and-lab/> developed by Luc Anselin and team at the University of Chicago. Datasets are stored as 'sf' objects.
Depends: R (>= 3.3.0)
License: CC0
URL: https://github.com/spatialanalysis/geodaData
BugReports: https://github.com/spatialanalysis/geodaData/issues
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
Suggests: sf
NeedsCompilation: no
Packaged: 2020-05-20 01:07:05 UTC; angela
Author: Angela Li [aut, cre] (<https://orcid.org/0000-0002-8956-419X>), Luc Anselin [ctb] (Creator of original spatial datasets)
Maintainer: Angela Li <ali6@uchicago.edu>
Repository: CRAN
Date/Publication: 2020-05-27 09:20:02 UTC

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New package cprobit with initial version 1.0.2
Package: cprobit
Type: Package
Title: Conditional Probit Model for Analysing Continuous Outcomes
Version: 1.0.2
Author: Ning Yilin, Tan Chuen Seng
Maintainer: Ning Yilin <ningyilinnyl@gmail.com>
Depends: R (>= 3.5.0)
Imports: car, nortest, ggplot2, gridExtra
Description: Implements the three-step workflow for robust analysis of change in two repeated measurements of continuous outcomes, described in Ning et al. (in press), "Robust estimation of the effect of an exposure on the change in a continuous outcome", BMC Medical Research Methodology.
License: LGPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-05-21 06:13:47 UTC; yilinning
Repository: CRAN
Date/Publication: 2020-05-27 10:00:08 UTC

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Tue, 26 May 2020

New package UniprotR with initial version 1.3.0
Package: UniprotR
Title: Retrieving Information of Proteins from Uniprot
Version: 1.3.0
Authors@R: c(person("Mohamed", "Soudy", email = "MohmedSoudy2009@gmail.com", role=c("aut", "cre")), person("Ali", "Mostafa", email = "ali.mo.anwar@std.agr.cu.edu.eg", role = "aut"))
Author: Mohamed Soudy [aut, cre], Ali Mostafa [aut]
Maintainer: Mohamed Soudy <MohmedSoudy2009@gmail.com>
Description: Connect to Uniprot <https://www.uniprot.org/> to retrieve information about proteins using their accession number such information could be name or taxonomy information, For detailed information kindly read the publication <https://www.sciencedirect.com/science/article/pii/S1874391919303859>.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Imports: utils , grDevices , graphics, httr , plyr , dplyr , scales , stats , magrittr , magick , data.tree , ggplot2 , tidyverse , grid , gridExtra , ggpubr , alakazam, curl
URL: https://github.com/Proteomicslab57357/UniprotR
BugReports: https://github.com/Proteomicslab57357/UniprotR/issues
NeedsCompilation: no
Packaged: 2020-05-26 16:51:55 UTC; RSH
Repository: CRAN
Date/Publication: 2020-05-26 22:40:08 UTC

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New package treeman with initial version 1.1.4
Package: treeman
Type: Package
Title: Phylogenetic Tree Manipulation Class and Methods
Version: 1.1.4
Author: D.J. Bennett
Maintainer: D.J. Bennett <dominic.john.bennett@gmail.com>
Description: S4 class and methods for intuitive and efficient phylogenetic tree manipulation.
License: GPL-2
Depends: R (>= 3.2.4), methods
Imports: plyr, ape, RJSONIO, stringr, bigmemory
Suggests: testthat
RoxygenNote: 7.0.2
Collate: 'calc-methods.R' 'check_methods.R' 'cnvrt-methods.R' 'gen-methods.R' 'get-nd-methods.R' 'get-nds-methods.R' 'get-spcl-methods.R' 'manip-methods.R' 'ndlst-methods.R' 'ndmtrx-methods.R' 'node-declaration.R' 'read-write-methods.R' 'server-methods.R' 'set-methods.R' 'treeman-declaration.R' 'treemen-declaration.R' 'update-methods.R' 'viz-methods.R' 'zzz.R'
NeedsCompilation: yes
Packaged: 2020-05-26 17:31:36 UTC; domben
Repository: CRAN
Date/Publication: 2020-05-26 22:40:02 UTC

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New package mediationsens with initial version 0.0.1
Package: mediationsens
Version: 0.0.1
Date: 2020-05-18
Title: Simulation-Based Sensitivity Analysis for Causal Mediation Studies
Author: Xu Qin and Fan Yang
Maintainer: Xu Qin <xuqin@pitt.edu>
Depends: mediation, distr
Description: We implement the simulation-based sensitivity analysis for causal mediation studies using the methods proposed by Qin and Yang (2020). It numerically and graphically evaluates the sensitivity of causal mediation analysis results to the presence of unmeasured pretreatment confounding. The proposed method has primary advantages over existing methods. First, using an unmeasured pretreatment confounder conditional associations with the treatment, mediator, and outcome as sensitivity parameters, the method enables users to intuitively assess sensitivity in reference to prior knowledge about the strength of a potential unmeasured pretreatment confounder. Second, the method accurately reflects the influence of unmeasured pretreatment confounding on the efficiency of estimation of the causal effects. Third, the method can be implemented in different causal mediation analysis approaches, including regression-based, simulation-based, and propensity score-based methods. It is applicable to both randomized experiments and observational studies.
License: GPL-2
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-05-19 01:06:45 UTC; Xu Qin
Repository: CRAN
Date/Publication: 2020-05-26 22:20:10 UTC

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New package bvpSolve with initial version 1.4
Package: bvpSolve
Version: 1.4
Title: Solvers for Boundary Value Problems of Differential Equations
Authors@R: c(person("Karline","Soetaert", role = c("aut","cre"), email = "karline.soetaert@nioz.nl"), person("Jeff","Cash", role = "aut", email = "j.cash@imperial.ac.uk"), person("Francesca","Mazzia", role = "aut", email = "mazzia@dm.uniba.it"), person("Uri M.","Ascher", role = "ctb", comment = "files colsysR.f, colnewR.f, coldaeR.f"), person("G.","Bader", role = "ctb", comment = "file colnewR.f"), person("J.","Christiansen", role = "ctb", comment = "file colsysR.f"), person("Robert R.","Russell", role = "ctb", comment = "file colsysR.f"))
Author: Karline Soetaert [aut, cre], Jeff Cash [aut], Francesca Mazzia [aut], Uri M. Ascher [ctb] (files colsysR.f, colnewR.f, coldaeR.f), G. Bader [ctb] (file colnewR.f), J. Christiansen [ctb] (file colsysR.f), Robert R. Russell [ctb] (file colsysR.f)
Maintainer: Karline Soetaert <karline.soetaert@nioz.nl>
Depends: R (>= 2.01), deSolve
Imports: rootSolve, stats, graphics, grDevices
Description: Functions that solve boundary value problems ('BVP') of systems of ordinary differential equations ('ODE') and differential algebraic equations ('DAE'). The functions provide an interface to the FORTRAN functions 'twpbvpC', 'colnew/colsys', and an R-implementation of the shooting method. 'Mazzia, F., J.R. Cash and K. Soetaert, 2014. <DOI:10.7494/OpMath.2014.34.2.387>.
License: GPL (>= 2)
LazyData: yes
NeedsCompilation: yes
Packaged: 2020-05-26 06:37:30 UTC; karlines
Repository: CRAN
Date/Publication: 2020-05-26 22:10:18 UTC

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New package BMTME with initial version 1.0.15
Package: BMTME
Title: Bayesian Multi-Trait Multi-Environment for Genomic Selection Analysis
Version: 1.0.15
Date: 2020-5-23
Language: en-US
Authors@R: c(person("Francisco Javier", "Luna-Vazquez", email = "frahik@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-5370-7152")), person("Fernando H.", "Toledo", role = "aut"), person("Osval Antonio", "Montesinos-Lopez", email= "oamontes1@ucol.mx", role = "aut", comment = c(ORCID = "0000-0002-3973-6547")), person("Abelardo", "Montesinos-Lopez", role = "aut"), person("Jose", "Crossa", role = "aut", comment = c(ORCID = "0000-0001-9429-5855")))
Maintainer: Francisco Javier Luna-Vazquez <frahik@gmail.com>
Description: Genomic selection and prediction models with the capacity to use multiple traits and environments, through ready-to-use Bayesian models. It consists a group of functions that help to create regression models for some genomic models proposed by Montesinos-López, et al. (2016) <doi:10.1534/g3.116.032359> also in Montesinos-López et al. (2018) <doi:10.1534/g3.118.200728> and Montesinos-López et al. (2018) <doi:10.2134/agronj2018.06.0362>.
Depends: R (>= 3.5)
License: LGPL-3
Encoding: UTF-8
LazyData: true
Type: Package
RoxygenNote: 7.1.0
URL: https://github.com/frahik/BMTME
BugReports: https://github.com/frahik/BMTME/issues/new
NeedsCompilation: yes
Collate: BME.R BMTME.R BMTME_Package.R BMORS.R BMORSEnv.R cholesky.R datasets.R detectCore.R RandomPartition.R RcppExports.R utils.R
Imports: BGLR, doSNOW, dplyr, foreach, matrixcalc, mvtnorm, progress, snow, tidyr
LinkingTo: Rcpp, RcppArmadillo
SystemRequirements: C++11, GNU
Suggests: covr, testthat,
Packaged: 2020-05-26 21:39:45 UTC; frahik
Author: Francisco Javier Luna-Vazquez [aut, cre] (<https://orcid.org/0000-0002-5370-7152>), Fernando H. Toledo [aut], Osval Antonio Montesinos-Lopez [aut] (<https://orcid.org/0000-0002-3973-6547>), Abelardo Montesinos-Lopez [aut], Jose Crossa [aut] (<https://orcid.org/0000-0001-9429-5855>)
Repository: CRAN
Date/Publication: 2020-05-26 22:40:12 UTC

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New package ot with initial version 0.2.0
Package: ot
Type: Package
Title: 'Open Tracing'
Version: 0.2.0
Author: Neal Fultz <nfultz@gmail.com>
Maintainer: Neal Fultz <nfultz@gmail.com>
Description: 'Open Tracing' <https://opentracing.io> allows developers to add instrumentation to their application code using interfaces that are vendor-agnostic. This is used to monitor services, triage failures and find performance bottlenecks, among other things. The 'ot' package has generic methods to be extended when implementing the specification for a specific vendor.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-05-18 16:15:43.31 UTC; nfultz
Repository: CRAN
Date/Publication: 2020-05-26 16:10:02 UTC

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New package SocEpi with initial version 1.0.0
Package: SocEpi
Type: Package
Title: Health Inequality Analysis
Version: 1.0.0
Authors@R: person("Mirjam", "Allik", email="mirjam.allik@gmail.com", role=c("aut", "cre"))
Description: Tools for calculating deprivation measures and analysing health outcomes and mortality by deprivation. Included are the functions: zscore() and w_pcntile() for developing deprivation measures and the functions smr(), st_rate() and rii() for calculating standardized mortality ratios, direct standardized rates and Slope and Relative indices of Inequality (SII and RII). Test data is included (dep_data and health_data). The RII/SII are calculated following Pamuk ER (1985) <doi:10.1080/0032472031000141256>. The confidence intervals for SII/RII are calculated using a multinomial distribution as described in Lumme et al (2015) <doi:10.1007/s10742-015-0137-1>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
Depends: R (>= 3.2.0)
Imports: tidyr, dplyr, Rcpp
LinkingTo: Rcpp
Suggests: knitr, rmarkdown, testthat
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2020-05-18 08:15:04 UTC; ma166k
Author: Mirjam Allik [aut, cre]
Maintainer: Mirjam Allik <mirjam.allik@gmail.com>
Repository: CRAN
Date/Publication: 2020-05-26 14:20:06 UTC

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New package rbiom with initial version 1.0.0
Package: rbiom
Type: Package
Title: Read/Write, Transform, and Summarize 'BIOM' Data
Version: 1.0.0
Authors@R: person("Daniel P.", "Smith", email = "dansmith@orst.edu", role = c("aut", "cre", "cph"), comment = c(ORCID = "0000-0002-2479-2044"))
Description: A toolkit for working with Biological Observation Matrix ('BIOM') files. Features include reading/writing all 'BIOM' formats, rarefaction, alpha diversity, beta diversity (including 'UniFrac'), summarizing counts by taxonomic level, and sample subsetting. Standalone functions for reading, writing, and subsetting phylogenetic trees are also provided. All CPU intensive operations are encoded in C with multi-thread support.
URL: https://cmmr.github.io/rbiom/index.html
BugReports: https://github.com/cmmr/rbiom/issues
License: AGPL-3
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.6.0)
LinkingTo: Rcpp, RcppParallel
Imports: magrittr, methods, plyr, Rcpp, RcppParallel, R.utils, rhdf5, rjson, slam, openxlsx
Suggests: ape, reshape2, testthat
RoxygenNote: 7.1.0
NeedsCompilation: yes
Packaged: 2020-05-18 06:12:09 UTC; Daniel
Author: Daniel P. Smith [aut, cre, cph] (<https://orcid.org/0000-0002-2479-2044>)
Maintainer: Daniel P. Smith <dansmith@orst.edu>
Repository: CRAN
Date/Publication: 2020-05-26 14:20:02 UTC

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New package eventr with initial version 1.0.0
Package: eventr
Title: Create Event Based Data Architectures
Version: 1.0.0
Authors@R: c( person(given = "Alvaro", family = "Franquet", role = c("aut", "cre"), email = "afranquet@salutemporda.cat"), person(given = "Maria Antonia", family = "Barceló", role = c("aut"), email = "antonia.barcelo@udg.edu", comment = c(ORCID = "0000-0001-9720-690X")), person(given = "Marc", family = "Saez", role = c("aut"), email = "marc.saez@udg.edu", comment = c(ORCID = "0000-0003-1882-0157")), person(given = "Pere", family = "Plaja", role = c("aut"), email = "pplaja@salutemporda.cat") )
Description: Event-driven programming is a programming paradigm where the flow of execution is defined by event. In this paradigm an event can be defined as "a change in the state" of an object. This package offers a set of functions for creating event-based architectures using three basic functions: events, dispatchers, and handlers. The handlers manage the events, the dispatchers are in charge of redirecting the events to each of the handlers, finally the events are the objects that carry the information about the change of state.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
Imports: purrr, dplyr, magrittr
Suggests: knitr, rmarkdown
NeedsCompilation: no
Packaged: 2020-05-18 14:12:01 UTC; afranquet
Author: Alvaro Franquet [aut, cre], Maria Antonia Barceló [aut] (<https://orcid.org/0000-0001-9720-690X>), Marc Saez [aut] (<https://orcid.org/0000-0003-1882-0157>), Pere Plaja [aut]
Maintainer: Alvaro Franquet <afranquet@salutemporda.cat>
Repository: CRAN
Date/Publication: 2020-05-26 14:40:02 UTC

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New package nodiv with initial version 1.4.0
Package: nodiv
Type: Package
Title: Compares the Distribution of Sister Clades Through a Phylogeny
Version: 1.4.0
Date: 2020-05-26
Author: Michael Krabbe Borregaard
Maintainer: Michael Krabbe Borregaard <mkborregaard@sund.ku.dk>
Description: An implementation of the nodiv algorithm, see Borregaard, M.K., Rahbek, C., Fjeldsaa, J., Parra, J.L., Whittaker, R.J. & Graham, C.H. 2014. Node-based analysis of species distributions. Methods in Ecology and Evolution 5(11): 1225-1235. <DOI:10.1111/2041-210X.12283>. Package for phylogenetic analysis of species distributions. The main function goes through each node in the phylogeny, compares the distributions of the two descendant nodes, and compares the result to a null model. This highlights nodes where major distributional divergence have occurred. The distributional divergence for these nodes is mapped using the SOS statistic.
Depends: R (>= 3.0)
Imports: picante, raster, ape, sp, vegan, utils
Suggests: RColorBrewer, parallel, testthat, colorspace
License: MIT + file LICENSE
URL: https://github.com/mkborregaard/nodiv
NeedsCompilation: no
Packaged: 2020-05-26 11:11:33 UTC; michael
Repository: CRAN
Date/Publication: 2020-05-26 11:30:09 UTC

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New package SoupX with initial version 1.4.5
Package: SoupX
Title: Single Cell mRNA Soup eXterminator
Version: 1.4.5
Date: 2020-05-15
Author: Matthew Daniel Young
Maintainer: Matthew Daniel Young <my4@sanger.ac.uk>
Description: Quantify, profile and remove ambient mRNA contamination (the "soup") from droplet based single cell RNA-seq experiments. Implements the method described in Young et al. (2018) <doi:10.1101/303727>.
URL: https://github.com/constantAmateur/SoupX
Suggests: knitr, rstan, DropletUtils, rmarkdown
VignetteBuilder: knitr
Imports: ggplot2, Matrix, methods, Seurat
Depends: R (>= 3.5.0)
LazyData: true
License: GPL-2
Encoding: UTF-8
RoxygenNote: 7.0.2
NeedsCompilation: no
Packaged: 2020-05-15 16:36:15 UTC; my4
Repository: CRAN
Date/Publication: 2020-05-26 10:00:06 UTC

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New package crispRdesignR with initial version 1.1.5
Package: crispRdesignR
Type: Package
Title: Guide Sequence Design for CRISPR/Cas9
Version: 1.1.5
Encoding: UTF-8
Authors@R: c( person("Dylan", "Beeber", email = "dylan.beeber@gmail.com", role = c("aut", "cre")), person("Frederic", "Chain", role = "aut"))
Description: Designs guide sequences for CRISPR/Cas9 genome editing and provides information on sequence features pertinent to guide efficiency. Sequence features include annotated off-target predictions in a user-selected genome and a predicted efficiency score based on the model described in Doench et al. (2016) <doi:10.1038/nbt.3437>. Users are able to import additional genomes and genome annotation files to use when searching and annotating off-target hits. All guide sequences and off-target data can be generated through the 'R' console with sgRNA_Design() or through 'crispRdesignR's' user interface with crispRdesignRUI(). CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) and the associated protein Cas9 refer to a technique used in genome editing.
URL: <https://github.com/dylanbeeber/crispRdesignR>
License: GPL-3
Depends: R (>= 2.10)
Imports: Biostrings, gbm, GenomicRanges, BiocGenerics, IRanges, GenomeInfoDb, S4Vectors, rtracklayer, stringr, vtreat, shiny, DT
Suggests: BSgenome.Scerevisiae.UCSC.sacCer2
LazyData: true
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-05-16 22:56:21 UTC; Dylan
Author: Dylan Beeber [aut, cre], Frederic Chain [aut]
Maintainer: Dylan Beeber <dylan.beeber@gmail.com>
Repository: CRAN
Date/Publication: 2020-05-26 10:00:03 UTC

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New package climwin with initial version 1.2.3
Package: climwin
Type: Package
Title: Climate Window Analysis
Version: 1.2.3
Author: Liam D. Bailey and Martijn van de Pol
Maintainer: Liam D. Bailey <liam.bailey@liamdbailey.com>
URL: https://github.com/LiamDBailey/climwin
BugReports: https://github.com/LiamDBailey/climwin/issues
Description: Contains functions to detect and visualise periods of climate sensitivity (climate windows) for a given biological response. Please see van de Pol et al. (2016) <doi:10.1111/2041-210X.12590> and Bailey and van de Pol (2016) <doi:10.1371/journal.pone.0167980> for details.
Depends: R (>= 2.10), ggplot2, gridExtra, Matrix
Imports: evd, lubridate, lme4, MuMIn, reshape, numDeriv, RcppRoll, nlme
Suggests: testthat, knitr, rmarkdown
License: GPL-2
Repository: CRAN
LazyData: True
VignetteBuilder: knitr
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-05-26 07:54:24 UTC; Liam
Date/Publication: 2020-05-26 09:50:06 UTC

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New package BayesSenMC with initial version 0.1.2
Package: BayesSenMC
Title: Different Models of Posterior Distributions of Adjusted Odds Ratio
Version: 0.1.2
Author: Jinhui Yang, Haitao Chu, and Lifeng Lin
Maintainer: Jinhui Yang <james.yangjinhui@gmail.com>
Description: Generates different posterior distributions of adjusted odds ratio under different priors of sensitivity and specificity, and plots the models for comparison. It also provides estimations for the specifications of the models using diagnostics of exposure status with a non-linear mixed effects model. It implements the methods that are first proposed in <doi:10.1016/j.annepidem.2006.04.001> and <doi:10.1177/0272989X09353452>.
License: GPL-2
Encoding: UTF-8
LazyData: true
Imports: dplyr, ggplot2, rstan (>= 2.16.2), lme4,
Depends: Rcpp (>= 0.12.19)
Suggests: gridExtra
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2020-05-26 04:38:18 UTC; james
Repository: CRAN
Date/Publication: 2020-05-26 09:50:11 UTC

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Mon, 25 May 2020

New package rkeops with initial version 1.4.1
Package: rkeops
Type: Package
Title: Kernel Operations on the GPU, with Autodiff, without Memory Overflows
Version: 1.4.1
Date: 2020-05-14
Authors@R: c( person(given="Benjamin", family="Charlier", comment="<http://imag.umontpellier.fr/~charlier/>", role="aut"), person(given="Jean", family="Feydy", comment="<https://www.math.ens.fr/~feydy/>", role="aut"), person(given="Joan A.", family="Glaunès", comment="<https://www.mi.parisdescartes.fr/~glaunes/>", role="aut"), person(given="Ghislain", family="Durif", comment="<https://gdurif.perso.math.cnrs.fr/>", email="gd.dev@libertymail.net", role=c("aut", "cre")), person(given="François-David", family="Collin", comment="Development-related consulting and support", role="ctb"), person(given="Daniel", family="Frey", comment="Author of the included C++ library 'sequences'", role="ctb"))
Description: The 'KeOps' library lets you compute generic reductions of very large arrays whose entries are given by a mathematical formula. It combines a tiled reduction scheme with an automatic differentiation engine, and can be used through 'R', 'Matlab', 'NumPy' or 'PyTorch' backends. It is perfectly suited to the computation of Kernel dot products and the associated gradients, even when the full kernel matrix does not fit into the GPU memory.
License: MIT + file LICENSE
Depends: R (>= 3.1.0)
LinkingTo: Rcpp (>= 1.0.1), RcppEigen (>= 0.3.3.5)
Imports: Rcpp (>= 1.0.1), openssl (>= 1.3), stringr (>= 1.4.0)
Suggests: testthat (>= 2.1.0), knitr, rmarkdown
OS_type: unix
SystemRequirements: C++11, cmake (>= 3.10), clang (optional), CUDA (optional but recommended)
URL: https://www.kernel-operations.io/, https://github.com/getkeops/keops/
BugReports: https://github.com/getkeops/keops/issues
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2020-05-25 08:17:50 UTC; drg
Author: Benjamin Charlier [aut] (<http://imag.umontpellier.fr/~charlier/>), Jean Feydy [aut] (<https://www.math.ens.fr/~feydy/>), Joan A. Glaunès [aut] (<https://www.mi.parisdescartes.fr/~glaunes/>), Ghislain Durif [aut, cre] (<https://gdurif.perso.math.cnrs.fr/>), François-David Collin [ctb] (Development-related consulting and support), Daniel Frey [ctb] (Author of the included C++ library 'sequences')
Maintainer: Ghislain Durif <gd.dev@libertymail.net>
Repository: CRAN
Date/Publication: 2020-05-25 22:10:02 UTC

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New package AmpliconDuo with initial version 1.1.1
Package: AmpliconDuo
Type: Package
Title: Statistical Analysis of Amplicon Data of the Same Sample to Identify Artefacts
Authors@R: c(person(given = "Anja", family = "Lange", role = c("aut", "cre"), email = "anja.lange@uni-due.de"), person(given = "Daniel", family = "Hoffmann", role = "aut", email = "daniel.hoffmann@uni-due.de"))
Version: 1.1.1
Date: 2020-05-22
Author: Anja Lange [aut, cre], Daniel Hoffmann [aut]
Maintainer: Anja Lange <anja.lange@uni-due.de>
Depends: R (>= 2.10), stats, ggplot2, xtable
Description: Increasingly powerful techniques for high-throughput sequencing open the possibility to comprehensively characterize microbial communities, including rare species. However, a still unresolved issue are the substantial error rates in the experimental process generating these sequences. To overcome these limitations we propose an approach, where each sample is split and the same amplification and sequencing protocol is applied to both halves. This procedure should allow to detect likely PCR and sequencing artifacts, and true rare species by comparison of the results of both parts. The AmpliconDuo package, whereas amplicon duo from here on refers to the two amplicon data sets of a split sample, is intended to help interpret the obtained read frequency distribution across split samples, and to filter the false positive reads.
License: GPL (>= 3)
NeedsCompilation: no
Packaged: 2020-05-25 10:31:28 UTC; anja
Repository: CRAN
Date/Publication: 2020-05-25 22:20:02 UTC

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New package tidylo with initial version 0.1.0
Type: Package
Package: tidylo
Title: Weighted Tidy Log Odds Ratio
Version: 0.1.0
Authors@R: c(person(given = "Tyler", family = "Schnoebelen", role = "aut", email = "tjs1976@gmail.com"), person(given = "Julia", family = "Silge", role = c("aut", "cre", "cph"), email = "julia.silge@gmail.com", comment = c(ORCID = "0000-0002-3671-836X")), person(given = "Alex", family = "Hayes", role = "aut", email = "alexpghayes@gmail.com", comment = c(ORCID = "0000-0002-4985-5160")))
Description: How can we measure how the usage or frequency of some feature, such as words, differs across some group or set, such as documents? One option is to use the log odds ratio, but the log odds ratio alone does not account for sampling variability; we haven't counted every feature the same number of times so how do we know which differences are meaningful? Enter the weighted log odds, which 'tidylo' provides an implementation for, using tidy data principles. In particular, here we use the method outlined in Monroe, Colaresi, and Quinn (2008) <doi:10.1093/pan/mpn018> to weight the log odds ratio by a prior. By default, the prior is estimated from the data itself, an empirical Bayes approach, but an uninformative prior is also available.
License: MIT + file LICENSE
URL: http://github.com/juliasilge/tidylo
BugReports: http://github.com/juliasilge/tidylo/issues
Imports: dplyr, rlang
Suggests: covr, ggplot2, janeaustenr, knitr, rmarkdown, stringr, testthat (>= 2.1.0), tidytext
VignetteBuilder: knitr
Encoding: UTF-8
LazyData: TRUE
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-05-16 16:40:27 UTC; juliasilge
Author: Tyler Schnoebelen [aut], Julia Silge [aut, cre, cph] (<https://orcid.org/0000-0002-3671-836X>), Alex Hayes [aut] (<https://orcid.org/0000-0002-4985-5160>)
Maintainer: Julia Silge <julia.silge@gmail.com>
Repository: CRAN
Date/Publication: 2020-05-25 19:10:03 UTC

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New package stratallo with initial version 0.1.0
Package: stratallo
Title: Optimum Sample Allocation in Stratified Random Sampling Scheme
Version: 0.1.0
Authors@R: c( person("Wojciech", "Wojciak", email = "wojciech.wojciak@gmail.com", role = c("aut", "cre")), person("Jacek", "Wesolowski", email = "j.wesolowski@mini.pw.edu.pl", role = "sad"), person("Robert", "Wieczorkowski", email = "R.Wieczorkowski@stat.gov.pl", role = "ctb"))
Description: Functions in this package provide solution to classical problem in survey methodology - an optimum sample allocation in stratified sampling scheme with simple random sampling without replacement design in each stratum. In this context, the optimal allocation is in the classical Tschuprow-Neyman's sense, and it satisfies additional upper bounds restrictions imposed on sample sizes in strata. There are four different algorithms available to use, and one of them is Neyman optimal allocation applied in a recursive way. All the algorithms are described in detail in "Wojciak W. Optimal allocation in stratified sampling schemes. Master's diploma thesis, Warsaw University of Technology. 2019", available on-line at <http://home.elka.pw.edu.pl/~wwojciak/msc_optimal_allocation.pdf>.
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-05-16 18:22:10 UTC; user1
Author: Wojciech Wojciak [aut, cre], Jacek Wesolowski [sad], Robert Wieczorkowski [ctb]
Maintainer: Wojciech Wojciak <wojciech.wojciak@gmail.com>
Repository: CRAN
Date/Publication: 2020-05-25 19:10:06 UTC

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New package i2dash with initial version 0.2
Package: i2dash
Type: Package
Title: Iterative and Interactive Dashboards
Version: 0.2
Authors@R: c( person(given = "Arsenij", family = "Ustjanzew", email = "arsenij.ustjanzew@mpi-bn.mpg.de", role = c("aut", "cre", "cph")), person(given = "Jens", family = "Preussner", email = "jens.preussner@mpi-bn.mpg.de", role = c("aut", "cph"), comment = c(ORCID = "0000-0003-1927-3458")), person(given = "Mario", family = "Looso", email = "mario.looso@mpi-bn.mpg.de", role = c("aut", "cph"), comment = c(ORCID = "0000-0003-1495-9530")))
Description: Create customized, web-based dashboards for data presentation, exploration and sharing. 'i2dash' integrates easily into existing data analysis pipelines and can organize scientific findings thematically across different pages and layouts.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
VignetteBuilder: knitr
Imports: magrittr, knitr, flexdashboard, yaml, assertive.sets, assertive.types, rmarkdown, stringr, stringi, glue, ymlthis, methods, stats, utils
Suggests: switchr, plotly, BiocStyle, xfun, htmltools, testthat, ComplexHeatmap, digest, ggplot2, gt, kableExtra, forcats, leaflet
Collate: 'i2dashboard.R' 'AllGenerics.R' 'assemble.R' 'components.R' 'colormap.R' 'get_set.R' 'pages.R' 'reexports.R' 'sidebar.R' 'vis_objects.R'
NeedsCompilation: no
Packaged: 2020-05-15 13:28:20 UTC; austjan
Author: Arsenij Ustjanzew [aut, cre, cph], Jens Preussner [aut, cph] (<https://orcid.org/0000-0003-1927-3458>), Mario Looso [aut, cph] (<https://orcid.org/0000-0003-1495-9530>)
Maintainer: Arsenij Ustjanzew <arsenij.ustjanzew@mpi-bn.mpg.de>
Repository: CRAN
Date/Publication: 2020-05-25 18:30:02 UTC

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New package distributionsrd with initial version 0.0.6
Package: distributionsrd
Title: Distribution Fitting and Evaluation
Version: 0.0.6
Authors@R: person("Ruben", "Dewitte", email = "ruben0dewitte@gmail.com", role = c("aut", "cre"))
Description: A library of density, distribution function, quantile function, (bounded) raw moments and random generation for a collection of distributions relevant for the firm size literature. Additionally, the package contains tools to fit these distributions using maximum likelihood and evaluate these distributions based on (i) log-likelihood ratio and (ii) deviations between the empirical and parametrically implied moments of the distributions. We add flexibility by allowing the considered distributions to be combined into piecewise composite or finite mixture distributions, as well as to be used when truncated. See Dewitte (2020) <https://hdl.handle.net/1854/LU-8644700> for a description and application of methods available in this package.
Depends: R (>= 3.6.0)
Imports: Rdpack, stats, flexmix, modeltools, methods
RdMacros: Rdpack
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
Suggests: knitr, rmarkdown, tidyverse, testthat
NeedsCompilation: no
Packaged: 2020-05-15 16:43:21 UTC; ruben
Author: Ruben Dewitte [aut, cre]
Maintainer: Ruben Dewitte <ruben0dewitte@gmail.com>
Repository: CRAN
Date/Publication: 2020-05-25 18:50:03 UTC

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New package nombre with initial version 0.1.0
Package: nombre
Title: Number Names
Version: 0.1.0
Authors@R: person(given = "Alexander", family = "Rossell Hayes", role = c("aut", "cre"), email = "alexander@rossellhayes.com", comment = c(ORCID = "0000-0001-9412-0457"))
Description: Converts numeric vectors to character vectors of English number names. Provides conversion to cardinals, ordinals, numerators, and denominators. Supports negative and non-integer numbers.
License: MIT + file LICENSE
URL: https://github.com/rossellhayes/nombre
BugReports: https://github.com/rossellhayes/nombre/issues
Depends: R (>= 2.10)
Suggests: MASS, testthat, covr
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-05-15 03:47:59 UTC; Alex
Author: Alexander Rossell Hayes [aut, cre] (<https://orcid.org/0000-0001-9412-0457>)
Maintainer: Alexander Rossell Hayes <alexander@rossellhayes.com>
Repository: CRAN
Date/Publication: 2020-05-25 17:50:03 UTC

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New package higlasso with initial version 0.9.0
Package: higlasso
Title: Hierarchical Integrative Group LASSO
Version: 0.9.0
Authors@R: c( person(given = "Alexander", family = "Rix", role = c("aut", "cre"), email = "alexrix@umich.edu"), person(given = "Jonathan", family = "Boss", role = c("aut"), email = "bossjona@umich.edu") )
Description: Environmental health studies are increasingly measuring multiple pollutants to characterize the joint health effects attributable to exposure mixtures. However, the underlying dose-response relationship between toxicants and health outcomes of interest may be highly nonlinear, with possible nonlinear interaction effects. Hierarchical integrative group least absolute shrinkage and selection operator (HiGLASSO), developed by Boss et al (2020) <arXiv:2003.12844>, is a general framework to identify noteworthy nonlinear main and interaction effects in the presence of group structures among a set of exposures.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
Depends: R (>= 3.5.0)
Imports: gcdnet, gglasso, purrr, splines, Rcpp
LinkingTo: Rcpp, RcppArmadillo
Suggests: knitr, rmarkdown, testthat
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2020-05-15 03:12:43 UTC; alex
Author: Alexander Rix [aut, cre], Jonathan Boss [aut]
Maintainer: Alexander Rix <alexrix@umich.edu>
Repository: CRAN
Date/Publication: 2020-05-25 17:40:03 UTC

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New package GermaParl with initial version 1.4.2
Package: GermaParl
Type: Package
Title: Download and Augment the Corpus of Plenary Protocols of the German Bundestag
Version: 1.4.2
Date: 2020-05-12
Authors@R: c(person(given = "Andreas", family = "Blaette", role = c("aut", "cre"), email = "andreas.blaette@uni-due.de"))
Depends: R (>= 3.5.0)
Imports: polmineR, cwbtools (>= 0.2.0), data.table, methods, RcppCWB, jsonlite, RCurl
Suggests: topicmodels, knitr, rmarkdown, testthat
LazyData: yes
Description: Data package to disseminate the 'GermaParl' corpus of parliamentary debates of the German Bundestag prepared in the 'PolMine Project'. The package includes a small subset of the corpus for demonstration and testing purposes. The package includes functionality to load the full corpus from the open science repository 'Zenodo' and some auxiliary functions to enhance the corpus.
URL: https://github.com/polmine/GermaParl
BugReports: https://github.com/polmine/GermaParl/issues
License: GPL-3
VignetteBuilder: knitr
Encoding: UTF-8
Collate: 'GermaParl.R' 'download.R' 'lda.R' 'speeches.R'
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-05-15 07:52:27 UTC; andreasblaette
Author: Andreas Blaette [aut, cre]
Maintainer: Andreas Blaette <andreas.blaette@uni-due.de>
Repository: CRAN
Date/Publication: 2020-05-25 18:00:06 UTC

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New package TechPhD with initial version 1.0.0
Package: TechPhD
Type: Package
Title: Tests and Estimation of Covariance Change-Points for Hi-Dim Data
Version: 1.0.0
Date: 2020-05-08
Authors@R: c(person("Ping-Shou", "Zhong", role = c("aut", "cre"), email = "pszhong@uic.edu"), person("Shawn", "Santo", role = "aut"), person("Nurlan", "Abdukadyrov", role = "ctb"), person("Bo", "Liu", role="ctb"))
Depends: R (>= 3.6.0)
Description: An implementation of the procedures in Zhong et al. (2019) and Santo and Zhong (2020) for testing the homogeneity of covariance matrices, and estimating multiple change-points in high-dimensional (Hi-Dim) longitudinal/functional data with general temporospatial dependence. The null hypothesis of the homogeneity test is that all covariance matrices are equal at each time point. If the null hypothesis is rejected, the procedure further identifies the locations of the change points. Note: The package uses Open MP. Mac OS X users may need to update clang compiler so that it supports Open MP. References: Ping-Shou Zhong, Runze Li, Shawn Santo (2019) <doi:10.1093/biomet/asz011> Shawn Santo, Ping-Shou Zhong (2020) <arXiv:2005.01895>.
URL:
License: GPL (>= 2)
Imports: mvtnorm, stats
SystemRequirements: Open MP
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: yes
Packaged: 2020-05-14 17:39:36 UTC; Nurlan
Author: Ping-Shou Zhong [aut, cre], Shawn Santo [aut], Nurlan Abdukadyrov [ctb], Bo Liu [ctb]
Maintainer: Ping-Shou Zhong <pszhong@uic.edu>
Repository: CRAN
Date/Publication: 2020-05-25 13:30:07 UTC

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New package nhlapi with initial version 0.1.2
Package: nhlapi
Type: Package
Title: A Minimum-Dependency 'R' Interface to the 'NHL' API
Version: 0.1.2
Authors@R: person("Jozef", "Hajnala", email = "jozef.hajnala@gmail.com", role = c("aut", "cre"))
Maintainer: Jozef Hajnala <jozef.hajnala@gmail.com>
Description: Retrieves and processes the data exposed by the open 'NHL' API. This includes information on players, teams, games, tournaments, drafts, standings, schedules and other endpoints. A lower-level interface to access the data via URLs directly is also provided.
Depends: R (>= 2.10)
Imports: jsonlite
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
Suggests: testthat, roxygen2, knitr
License: AGPL-3
Language: en-US
URL: https://github.com/jozefhajnala/nhlapi
BugReports: https://github.com/jozefhajnala/nhlapi/issues
VignetteBuilder: knitr
SysDataCompression: xz
Copyright: NHL and the NHL Shield are registered trademarks of the National Hockey League. NHL and NHL team marks are the property of the NHL and its teams.
NeedsCompilation: no
Packaged: 2020-05-14 15:28:20 UTC; root
Author: Jozef Hajnala [aut, cre]
Repository: CRAN
Date/Publication: 2020-05-25 13:10:02 UTC

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New package applicable with initial version 0.0.1
Package: applicable
Title: A Compilation of Applicability Domain Methods
Version: 0.0.1
Authors@R: c( person(given = "Marly", family = "Gotti", email = "marlygotti@gmail.com", role = c("aut", "cre")), person(given = "Max", family = "Kuhn", email = "max@rstudio.com", role = c("aut")), person("RStudio", role = "cph"))
Description: A modeling package compiling applicability domain methods in R. It combines different methods to measure the amount of extrapolation new samples can have from the training set. See Netzeva et al (2005) <doi:10.1177/026119290503300209> for an overview of applicability domains.
URL: https://github.com/tidymodels/applicable
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.3), ggplot2
Imports: hardhat (>= 0.1.2), rlang, stats, glue, tibble, proxyC, Matrix, dplyr, utils, purrr, tidyselect, tidyr
Suggests: recipes (>= 0.1.7), testthat (>= 2.1.0), knitr, rmarkdown, covr, AmesHousing, spelling, xml2, modeldata
RoxygenNote: 7.1.0
VignetteBuilder: knitr
Language: en-US
NeedsCompilation: no
Packaged: 2020-05-15 02:48:39 UTC; marlygotti
Author: Marly Gotti [aut, cre], Max Kuhn [aut], RStudio [cph]
Maintainer: Marly Gotti <marlygotti@gmail.com>
Repository: CRAN
Date/Publication: 2020-05-25 14:00:02 UTC

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New package upsetjs with initial version 1.0.2
Package: upsetjs
Type: Package
Title: 'HTMLWidget' Wrapper of 'UpSet.s' for Exploring Large Set Intersections
Description: 'UpSet.js' is a re-implementation of 'UpSetR' to create interactive set visualizations for more than three sets. This is a 'htmlwidget' wrapper around the 'JavaScript' library 'UpSet.js'.
Version: 1.0.2
Date: 2020-05-14
Author: Samuel Gratzl [aut, cre]
Authors@R: person("Samuel", "Gratzl", email = "sam@sgratzl.com", role = c("aut", "cre"))
Maintainer: Samuel Gratzl <sam@sgratzl.com>
URL: https://github.com/upsetjs/upsetjs_r/
BugReports: https://github.com/upsetjs/upsetjs_r/issues
Depends: R (>= 3.2.0)
License: AGPL-3 | file LICENSE
Encoding: UTF-8
Imports: htmlwidgets, magrittr
Suggests: knitr, crosstalk, rmarkdown, formatR
LazyData: true
RoxygenNote: 7.0.2
VignetteBuilder: knitr
Language: en-US
NeedsCompilation: no
Packaged: 2020-05-14 11:03:15 UTC; sam
Repository: CRAN
Date/Publication: 2020-05-25 10:00:03 UTC

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New package sketcher with initial version 0.1.3
Package: sketcher
Title: Pencil Sketch Effect
Version: 0.1.3
Authors@R: person(given = "Hiroyuki", family = "Tsuda", role = c("aut", "cre"), email = "tsuda16k@gmail.com", comment = c(ORCID = "0000-0001-9396-5327"))
Description: An implementation of image processing effects that convert a photo into a line drawing image. For details, please refer to Tsuda, H. (2020). sketcher: An R package for converting a photo into a sketch style image. <doi:10.31234/osf.io/svmw5>.
URL: https://htsuda.net/sketcher/
BugReports: https://github.com/tsuda16k/sketcher/issues/
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
Imports: jpeg, png, readbitmap, downloader, imager, magrittr, methods, stringr, dplyr
Depends: R (>= 2.10)
Suggests: knitr, rmarkdown
NeedsCompilation: no
Packaged: 2020-05-14 06:19:38 UTC; tsuhir
Author: Hiroyuki Tsuda [aut, cre] (<https://orcid.org/0000-0001-9396-5327>)
Maintainer: Hiroyuki Tsuda <tsuda16k@gmail.com>
Repository: CRAN
Date/Publication: 2020-05-25 09:10:02 UTC

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New package pharmaRTF with initial version 0.1.0
Package: pharmaRTF
Type: Package
Title: Enhanced RTF Wrapper for Use with Existing Table Packages
Version: 0.1.0
Authors@R: c( person(family = "Miller", given = "Eli", email = "eli.miller@atorusresearch.com", role = "aut", comment = c(ORCID = "0000-0002-2127-9456")), person(family = "Tarasiewicz", given = "Ashley", email = "Ashley.Tarasiewicz@atorusresearch.com", role = "aut"), person(family = "Stackhouse", given = "Michael", email = "mike.stackhouse@atorusresearch.com", role = c("aut", "cre")), person(given = "Atorus Research LLC", role = "cph") )
Description: Enhanced RTF wrapper written in R for use with existing R tables packages such as 'Huxtable' or 'GT'. This package fills a gap where tables in certain packages can be written out to RTF, but cannot add certain metadata or features to the document that are required/expected in a report for a regulatory submission, such as multiple levels of titles and footnotes, making the document landscape, and controlling properties such as margins.
Depends: R (>= 3.5.0)
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: assertthat (>= 0.2.1), stringr (>= 1.4.0), purrr (>= 0.3.3)
Suggests: testthat (>= 2.1.0), huxtable (>= 4.7.1), dplyr (>= 0.8.4), readr (>= 1.3.1), gt (>= 0.2.0), magrittr (>= 1.5), knitr (>= 1.28), rmarkdown (>= 2.1), readxl (>= 1.3.1), kableExtra (>= 1.1.0), plyr (>= 1.8.5), tidyverse (>= 1.3.0)
RoxygenNote: 7.0.2
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-05-14 12:54:56 UTC; emiller
Author: Eli Miller [aut] (<https://orcid.org/0000-0002-2127-9456>), Ashley Tarasiewicz [aut], Michael Stackhouse [aut, cre], Atorus Research LLC [cph]
Maintainer: Michael Stackhouse <mike.stackhouse@atorusresearch.com>
Repository: CRAN
Date/Publication: 2020-05-25 10:00:06 UTC

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New package exams.mylearn with initial version 1.1
Package: exams.mylearn
Title: Question Generation in the 'MyLearn' XML Format
Version: 1.1
Authors@R: person(given = "Darjus", family = "Hosszejni", role = c("aut", "cre"), email = "darjus.hosszejni@wu.ac.at", comment = c(ORCID = "0000-0002-3803-691X"))
Description: Randomized multiple-select and single-select question generation for the 'MyLearn' teaching and learning platform. Question templates in the form of the R/exams package (see <http://www.r-exams.org/>) are transformed into XML format required by 'MyLearn'.
License: GPL-3
Depends: R (>= 3.3.0)
Imports: exams (>= 2.3-4), glue (>= 1.4.0), stringr (>= 1.4.0), stringi (>= 1.4.6), xml2 (>= 1.2.5)
Suggests: knitr
URL: https://github.com/hdarjus/WU-MyLearn-QGen
BugReports: https://github.com/hdarjus/WU-MyLearn-QGen/issues
Encoding: UTF-8
LazyData: true
VignetteBuilder: knitr
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-05-14 09:58:01 UTC; dhosszejni
Author: Darjus Hosszejni [aut, cre] (<https://orcid.org/0000-0002-3803-691X>)
Maintainer: Darjus Hosszejni <darjus.hosszejni@wu.ac.at>
Repository: CRAN
Date/Publication: 2020-05-25 09:50:02 UTC

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New package BOJ with initial version 0.2.2
Package: BOJ
Type: Package
Title: Interface to Bank of Japan Statistics
Version: 0.2.2
Date: 2020-05-14
Authors@R: person("Stefan", "Angrick", email = "contact@stefanangrick.net", role = c("aut", "cre", "cph"))
Description: Provides an interface to data provided by the Bank of Japan <https://www.boj.or.jp>.
License: MIT + file LICENSE
LazyData: TRUE
Suggests: knitr, rmarkdown, ggplot2, zoo
Imports: dplyr, readr, tidyr, tidyselect, rvest, xml2
VignetteBuilder: knitr
Encoding: UTF-8
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-05-14 11:43:15 UTC; qwerty
Author: Stefan Angrick [aut, cre, cph]
Maintainer: Stefan Angrick <contact@stefanangrick.net>
Repository: CRAN
Date/Publication: 2020-05-25 10:00:10 UTC

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Sun, 24 May 2020

New package mma with initial version 10.3-2
Package: mma
Type: Package
Title: Multiple Mediation Analysis
Version: 10.3-2
Date: 2020-05-18
Author: Qingzhao Yu and Bin Li
Maintainer: Qingzhao Yu <qyu@lsuhsc.edu>
Depends: R (>= 2.14.1), gbm, splines, survival, car, gplots
Imports: plotrix,lattice
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
Encoding: UTF-8
Description: Used for general multiple mediation analysis. The analysis method is described in Yu et al. (2014) <doi:10.4172/2155-6180.1000189> "General Multiple Mediation Analysis With an Application to Explore Racial Disparity in Breast Cancer Survival", published on Journal of Biometrics & Biostatistics, 5(2):189; and Yu et al.(2017) <DOI:10.1016/j.sste.2017.02.001> "Exploring racial disparity in obesity: a mediation analysis considering geo-coded environmental factors", published on Spatial and Spatio-temporal Epidemiology, 21, 13-23.
License: GPL (>= 2)
URL: https://www.r-project.org, https://publichealth.lsuhsc.edu/Faculty_pages/qyu/index.html
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2020-05-19 01:31:02 UTC; qyu
Repository: CRAN
Date/Publication: 2020-05-24 17:40:03 UTC

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New package xROI with initial version 0.9.16
Package: xROI
Title: Delineate Region of Interests (ROI's) and Extract Time-Series Data from Digital Repeat Photography Images
Version: 0.9.16
Date: 2020-05-24
Author: Bijan Seyednasrollah, Thomas Milliman, Andrew D. Richardson
Maintainer: Bijan Seyednasrollah <bijan.s.nasr@gmail.com>
Description: Digital repeat photography and near-surface remote sensing have been used by environmental scientists to study the environmental change for nearly a decade. However, a user-friendly, reliable, and robust platform to extract color-based statistics and time-series from a large stack of images is still lacking. Here, we present an interactive open-source toolkit, called 'xROI', that facilitate the process time-series extraction and improve the quality of the final data. 'xROI' provides a responsive environment for scientists to interactively a) delineate regions of interest (ROI), b) handle field of view (FOV) shifts, and c) extract and export time series data characterizing image color (i.e. red, green and blue channel digital numbers for the defined ROI). Using 'xROI', user can detect FOV shifts without minimal difficulty. The software gives user the opportunity to readjust the mask files or redraw new ones every time an FOV shift occurs. 'xROI' helps to significantly improve data accuracy and continuity.
Depends: R (>= 3.4.0)
Imports: colourpicker, data.table, graphics, jpeg, lubridate, methods, moments, RCurl, raster, rgdal, rjson, sp, stats, stringr, tiff, utils, shiny, shinyjs,
Suggests: knitr, testthat, rmarkdown, shinyBS, shinyAce, shinyTime, shinyFiles, shinydashboard, shinythemes, plotly
License: AGPL-3
Encoding: UTF-8
LazyData: true
BugReports: https://github.com/bnasr/xROI/issues
RoxygenNote: 7.1.0
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-05-24 14:48:57 UTC; bijan
Repository: CRAN
Date/Publication: 2020-05-24 15:20:02 UTC

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New package SparseTSCGM with initial version 3.0
Package: SparseTSCGM
Type: Package
Title: Sparse Time Series Chain Graphical Models
Version: 3.0
Date: 2020-05-23
Depends: R(>= 3.3.2)
Imports: glasso, QUIC, longitudinal, huge, MASS, mvtnorm, network, abind, stats
Author: Fentaw Abegaz and Ernst Wit
Maintainer: Fentaw Abegaz <f.abegaz.yazew@rug.nl>
Description: Computes sparse vector autoregressive coefficients and precision matrices for time series chain graphical models.
License: GPL (>= 3)
NeedsCompilation: yes
Packaged: 2020-05-23 18:13:13 UTC; Fentaw
Repository: CRAN
Date/Publication: 2020-05-24 15:40:06 UTC

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New package ROpenCVLite with initial version 0.4.430
Package: ROpenCVLite
Type: Package
Title: Install 'OpenCV'
Version: 0.4.430
Authors@R: c( person("Simon", "Garnier", email = "garnier@njit.edu", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-3886-3974")), person("Muschelli", "John", email = "muschellij2@gmail.com", role = c("ctb")) )
Maintainer: Simon Garnier <garnier@njit.edu>
Description: Installs 'OpenCV' for use by other packages. 'OpenCV' <https://opencv.org/> is library of programming functions mainly aimed at real-time computer vision. This 'Lite' version contains the stable base version of 'OpenCV' and does not contain any of its externally contributed modules.
License: GPL-3
LazyData: TRUE
Imports: utils, pkgbuild, parallel
SystemRequirements: cmake, C++11
RoxygenNote: 7.1.0
Biarch: true
Encoding: UTF-8
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
URL: https://swarm-lab.github.io/ROpenCVLite/, https://github.com/swarm-lab/ROpenCVLite
BugReports: https://github.com/swarm-lab/ROpenCVLite/issues
NeedsCompilation: no
Packaged: 2020-05-24 12:41:00 UTC; simon
Author: Simon Garnier [aut, cre] (<https://orcid.org/0000-0002-3886-3974>), Muschelli John [ctb]
Repository: CRAN
Date/Publication: 2020-05-24 15:20:09 UTC

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New package ess with initial version 1.0
Package: ess
Title: Efficient Stepwise Selection in Decomposable Models
Version: 1.0
Authors@R: person(given = "Mads", family = "Lindskou", role = c("aut", "cre"), email = "mads@math.aau.dk")
Description: An implementation of the ESS algorithm following Amol Deshpande, Minos Garofalakis, Michael I Jordan (2013) <arXiv:1301.2267>. The ESS algorithm is used for model selection in decomposable graphical models.
URL: https://github.com/mlindsk/ess
Depends: R (>= 3.5.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: Rcpp, igraph, Matrix
LinkingTo: Rcpp
RoxygenNote: 7.1.0
Suggests: tinytest
BugReports: https://github.com/mlindsk/ess/issues
SystemRequirements: C++11
NeedsCompilation: yes
Packaged: 2020-05-23 06:50:04 UTC; mads
Author: Mads Lindskou [aut, cre]
Maintainer: Mads Lindskou <mads@math.aau.dk>
Repository: CRAN
Date/Publication: 2020-05-24 15:20:05 UTC

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New package EcoGenetics with initial version 1.2.1-6
Package: EcoGenetics
Type: Package
Title: Management and Exploratory Analysis of Spatial Data in Landscape Genetics
Version: 1.2.1-6
Date: 2020-05-24
Authors@R: c(person(given = "Leandro", family = "Roser", role = c("aut", "cre"), email = "learoser@gmail.com"), person(given = "Juan", family = "Vilardi", role = "aut"), person(given = "Beatriz", family = "Saidman", role = "aut"), person(given = "Laura", family = "Ferreyra", role = "aut"), person(given = "Thibaut", family = "Jombart", role = "ctb", comment = "author of included adegenet code"), person(given = "Winston", family = "Chang", role = "ctb", comment = "author of the multiplot function included under the name grf.multiplot"))
Maintainer: Leandro Roser <learoser@gmail.com>
Description: Management and exploratory analysis of spatial data in landscape genetics. Easy integration of information from multiple sources with "ecogen" objects.
License: GPL (>= 2)
URL: https://github.com/cran/EcoGenetics, https://leandroroser.github.io/EcoGenetics-Tutorial
LazyLoad: yes
Depends: R (>= 3.0), methods
Imports: edgebundleR, ggplot2, grid, htmlwidgets, igraph, jsonlite, magrittr, networkD3, party, pheatmap, plotly, raster, reshape2, rgdal, rkt, SoDA, sp, parallel, doParallel, foreach
Suggests: adegenet, testthat, covr, vegan, hierfstat
Collate: 'ZZZ.R' 'generics.R' 'auxiliar.R' 'int.genind.R' 'ecogen.1OF6.definition.R' 'ecogen.2OF6.constructor.R' 'ecogen.3OF6.basic.methods.R' 'ecogen.4OF6.brackets.R' 'ecogen.5OF6.get&set.R' 'ecogen.6OF6.converters.R' 'ecopop.1OF6.definition.R' 'ecopop.2OF6.constructor.R' 'ecopop.3OF6.basic.methods.R' 'ecopop.4OF6.brackets.R' 'ecopop.5OF6.get&set.R' 'ecopop.6OF6.converters.R' 'accessors.R' 'classes.R' 'control.R' 'deprecated.R' 'eco.formula.R' 'eco.NDVI.R' 'eco.NDVI.post.R' 'eco.alfreq.R' 'eco.association.R' 'eco.bearing.R' 'eco.cbind.R' 'eco.clear.R' 'eco.convert.R' 'eco.cormantel.R' 'eco.correlog.R' 'eco.detrend.R' 'eco.forestplot.R' 'eco.format.R' 'eco.gsa.R' 'eco.kin.loiselle.R' 'eco.lagweight.R' 'eco.lmtree.R' 'eco.lsa.R' 'eco.malecot.R' 'eco.mantel.R' 'eco.merge.R' 'eco.pairtest.R' 'eco.plotCorrelog.R' 'eco.plotGlobal.R' 'eco.plotLocal.R' 'eco.plotWeight.R' 'eco.post.geneland.R' 'eco.rankplot.R' 'eco.rasterplot.R' 'eco.rbind.R' 'eco.remove.R' 'eco.slide.con.R' 'eco.slide.matrix.R' 'eco.split.R' 'eco.subset.R' 'eco.theilsen.R' 'eco.variogram.R' 'eco.weight.R' 'int.break.R' 'int.convert.R' 'int.crosscor.R' 'int.geary.R' 'int.jackknife.R' 'int.joincount.R' 'int.kin.loiselle.R' 'int.mantel.R' 'int.moran.R' 'int.multitable.R' 'int.order.R' 'int.random.test.R' 'miscellaneous.R' 'fill_ecogen_with_pop.R' 'plot.generic.R' 'plot.methods.R' 'roxygen.auxiliar.R' 'show_summary.methods.R' 'eco.dom_af.R' 'eco.kin.hardy.R' 'eco.nei_dist.R'
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-05-24 06:01:19 UTC; Leandro
LazyData: true
Author: Leandro Roser [aut, cre], Juan Vilardi [aut], Beatriz Saidman [aut], Laura Ferreyra [aut], Thibaut Jombart [ctb] (author of included adegenet code), Winston Chang [ctb] (author of the multiplot function included under the name grf.multiplot)
Repository: CRAN
Date/Publication: 2020-05-24 15:20:17 UTC

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New package bioacoustics with initial version 0.2.4
Package: bioacoustics
Type: Package
Title: Analyse Audio Recordings and Automatically Extract Animal Vocalizations
Version: 0.2.4
Authors@R: c(person("Jean", "Marchal", email = "jean.marchal@wavx.ca", role = c("aut","cre")), person("Francois", "Fabianek", email = "francois.fabianek@wavx.ca", role = "aut"), person("Christopher", "Scott", role = "aut"), person("Chris", "Corben", role = c("ctb", "cph"), email = "chris@hoarybat.com", comment = "Read ZC files, original C code"), person("David", "Riggs", role = c("ctb", "cph"), email = "driggs@myotisoft.com", comment = "Read GUANO metadata, original R code"), person("Peter", "Wilson", role = c("ctb", "cph"), email = "peter@peterwilson.id.au", comment = "Read ZC files, original R code"), person(family = "Wildlife Acoustics, inc.", role = c("ctb", "cph"), comment = "Read WAC files, original C code"), person(family = "WavX, inc.", role = "cph"))
Maintainer: Jean Marchal <jean.marchal@wavx.ca>
Description: Contains all the necessary tools to process audio recordings of various formats (e.g., WAV, WAC, MP3, ZC), filter noisy files, display audio signals, detect and extract automatically acoustic features for further analysis such as classification.
License: GPL-3
Encoding: UTF-8
LazyData: true
SystemRequirements: C++11, cmake, fftw3, GNU make, soxr-lsr
Depends: R (>= 3.3.0)
LinkingTo: Rcpp
Imports: htmltools, graphics, grDevices, methods, moments, Rcpp (>= 0.12.13), stringr, tools, tuneR (>= 1.3.0)
Suggests: knitr, rmarkdown
URL: https://github.com/wavx/bioacoustics/
BugReports: https://github.com/wavx/bioacoustics/issues/
NeedsCompilation: yes
RoxygenNote: 7.1.0
VignetteBuilder: knitr
Biarch: TRUE
Packaged: 2020-05-23 18:35:27 UTC; jean
Author: Jean Marchal [aut, cre], Francois Fabianek [aut], Christopher Scott [aut], Chris Corben [ctb, cph] (Read ZC files, original C code), David Riggs [ctb, cph] (Read GUANO metadata, original R code), Peter Wilson [ctb, cph] (Read ZC files, original R code), Wildlife Acoustics, inc. [ctb, cph] (Read WAC files, original C code), WavX, inc. [cph]
Repository: CRAN
Date/Publication: 2020-05-24 15:40:02 UTC

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New package aslib with initial version 0.1.1
Package: aslib
Title: Interface to the Algorithm Selection Benchmark Library
Description: Provides an interface to the algorithm selection benchmark library at <http://www.aslib.net> and the 'LLAMA' package (<https://cran.r-project.org/package=llama>) for building algorithm selection models; see Bischl et al. (2016) <doi:10.1016/j.artint.2016.04.003>.
Author: Bernd Bischl <bernd_bischl@gmx.net>, Lars Kotthoff <larsko@uwyo.edu>, Pascal Kerschke <kerschke@uni-muenster.de> [ctb]
Maintainer: Lars Kotthoff <larsko@uwyo.edu>
URL: https://github.com/coseal/aslib-r/
BugReports: https://github.com/coseal/aslib-r/issues
License: GPL-3
Imports: BatchExperiments, BatchJobs, BBmisc, checkmate, corrplot, ggplot2, llama, mlr, parallelMap, ParamHelpers, plyr, reshape2, RWeka, stringr, yaml
Suggests: testthat, rpart
LazyData: yes
ByteCompile: yes
Version: 0.1.1
RoxygenNote: 5.0.1
NeedsCompilation: no
Packaged: 2020-05-22 19:44:22 UTC; larsko
Repository: CRAN
Date/Publication: 2020-05-24 15:50:02 UTC

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Fri, 22 May 2020

New package ergMargins with initial version 0.1.1
Package: ergMargins
Type: Package
Title: Process Analysis for Exponential Random Graph Models
Version: 0.1.1
Authors@R: c(person("Scott", "Duxbury",email="sduxburycpt@gmail.com", role=c("aut", "cre", "cph")), person("Bruce", "Desmarais",email="bdesmarais@psu.edu", role=c("ctb", "cph")), person("Philip","Leifeld",email="philip.leifeld@essex.ac.uk",role=c("ctb","cph")))
Maintainer: Scott Duxbury <sduxburycpt@gmail.com>
Description: Calculates marginal effects and conducts process analysis in exponential family random graph models (ERGM). Includes functions to conduct mediation and moderation analyses and to diagnose multicollinearity. URL: <http://github.com/sduxbury/ergMargins>. BugReports: <http://github.com/sduxbury/ergMargins/issues>. Duxbury, Scott W (2019) <doi:10.31235/osf.io/9bs4u>. Long, J. Scott, and Sarah Mustillo (2018) <doi:10.1177/0049124118799374>. Mize, Trenton D. (2019) <doi:10.15195/v6.a4>. Karlson, Kristian Bernt, Anders Holm, and Richard Breen (2012) <doi:10.1177/0081175012444861>. Duxbury, Scott W (2018) <doi:10.1177/0049124118782543>.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Imports: numDeriv, statnet, stats, ergm, Matrix, network, btergm, methods, sna, xergm.common
Suggests: MASS, knitr, rmarkdown
NeedsCompilation: no
Packaged: 2020-05-22 14:01:17 UTC; 15179
Author: Scott Duxbury [aut, cre, cph], Bruce Desmarais [ctb, cph], Philip Leifeld [ctb, cph]
Repository: CRAN
Date/Publication: 2020-05-22 15:00:03 UTC

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New package textrecipes with initial version 0.2.3
Package: textrecipes
Title: Extra 'Recipes' for Text Processing
Version: 0.2.3
Authors@R: person(given = "Emil", family = "Hvitfeldt", role = c("aut", "cre"), email = "emilhhvitfeldt@gmail.com", comment = c(ORCID = "0000-0002-0679-1945"))
Description: Converting text to numerical features requires specifically created procedures, which are implemented as steps according to the 'recipes' package. These steps allows for tokenization, filtering, counting (tf and tfidf) and feature hashing.
License: MIT + file LICENSE
URL: https://github.com/tidymodels/textrecipes, https://textrecipes.tidymodels.org
BugReports: https://github.com/tidymodels/textrecipes/issues
Depends: R (>= 2.10), recipes (>= 0.1.4)
Imports: generics, rlang, tokenizers, dplyr, tibble, tidyr, purrr, SnowballC, stopwords, magrittr, Matrix, stringr, vctrs, Rcpp
Suggests: covr, testthat (>= 2.1.0), knitr, text2vec, rmarkdown, textfeatures (>= 0.3.3), modeldata, spacyr
VignetteBuilder: knitr
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0.9000
SystemRequirements: GNU make, C++11
LinkingTo: Rcpp
NeedsCompilation: yes
Packaged: 2020-05-20 22:38:21 UTC; emilhvitfeldthansen
Author: Emil Hvitfeldt [aut, cre] (<https://orcid.org/0000-0002-0679-1945>)
Maintainer: Emil Hvitfeldt <emilhhvitfeldt@gmail.com>
Repository: CRAN
Date/Publication: 2020-05-22 11:40:06 UTC

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New package outsider.base with initial version 0.1.1
Package: outsider.base
Type: Package
Title: Base Package for 'Outsider'
Version: 0.1.1
Authors@R: c( person("Dom", "Bennett", role = c("aut", "cre"), email = "dominic.john.bennett@gmail.com", comment = c(ORCID = "0000-0003-2722-1359")), person("Hannes", "Hettling", role = "ctb", comment = c(ORCID = "0000-0003-4144-2238")), person("Daniele", "Silvestro", role = "ctb", comment = c(ORCID = "0000-0003-0100-0961")), person("Rutger", "Vos", role = "ctb", comment = c(ORCID = "0000-0001-9254-7318")), person("Alexandre", "Antonelli", role = "ctb", comment = c(ORCID = "0000-0003-1842-9297")), person("Anna", "Krystalli", role = "rev", email = "annakrystalli@googlemail.com"))
Maintainer: Dom Bennett <dominic.john.bennett@gmail.com>
Description: Base package for 'outsider' <https://github.com/ropensci/outsider>. The 'outsider' package and its sister packages enable the installation and running of external, command-line software within R. This base package is a key dependency of the user-facing 'outsider' package as it provides the utilities for interfacing between 'Docker' <https://www.docker.com> and R. It is intended that end-users of 'outsider' do not directly work with this base package.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
SystemRequirements: docker (>=18.0.0)
URL: https://docs.ropensci.org/outsider.base, https://github.com/ropensci/outsider.base
BugReports: https://github.com/ropensci/outsider.base/issues
Language: en-GB
Depends: R (>= 3.3.0)
Imports: utils (>= 3.1), crayon, devtools (>= 1.1), jsonlite (>= 1.1), sys (>= 2.1), yaml (>= 2.0), callr (>= 3.0.0), withr (>= 2.0), tibble, cli, praise
Suggests: ssh, testthat (>= 2.0)
NeedsCompilation: no
Packaged: 2020-05-21 19:36:09 UTC; domben
Author: Dom Bennett [aut, cre] (<https://orcid.org/0000-0003-2722-1359>), Hannes Hettling [ctb] (<https://orcid.org/0000-0003-4144-2238>), Daniele Silvestro [ctb] (<https://orcid.org/0000-0003-0100-0961>), Rutger Vos [ctb] (<https://orcid.org/0000-0001-9254-7318>), Alexandre Antonelli [ctb] (<https://orcid.org/0000-0003-1842-9297>), Anna Krystalli [rev]
Repository: CRAN
Date/Publication: 2020-05-22 08:10:02 UTC

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New package llama with initial version 0.9.3
Package: llama
Type: Package
Title: Leveraging Learning to Automatically Manage Algorithms
Version: 0.9.3
Date: 2020-05-19
Author: Lars Kotthoff [aut,cre], Bernd Bischl [aut], Barry Hurley [ctb], Talal Rahwan [ctb]
Maintainer: Lars Kotthoff <larsko@uwyo.edu>
Description: Provides functionality to train and evaluate algorithm selection models for portfolios.
Depends: R (>= 4.0), mlr (>= 2.5)
Imports: rJava, parallelMap, ggplot2, checkmate, BBmisc, plyr
Suggests: testthat, ParamHelpers
License: BSD_3_clause + file LICENSE
URL: https://bitbucket.org/lkotthoff/llama
NeedsCompilation: no
Packaged: 2020-05-20 21:08:10 UTC; larsko
Repository: CRAN
Date/Publication: 2020-05-22 08:30:02 UTC

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New package eHOF with initial version 1.9
Package: eHOF
Version: 1.9
Encoding: UTF-8
Date: 2020-05-13
Title: Extended HOF (Huisman-Olff-Fresco) Models
Author: Florian Jansen, Jari Oksanen
Maintainer: Florian Jansen <florian.jansen@uni-rostock.de>
Depends: R (>= 2.5.0), mgcv, lattice
Suggests: vegdata, vegan, knitr, testthat
LazyData: yes
VignetteBuilder: knitr
Description: Extended and enhanced hierarchical logistic regression models (called Huisman-Olff-Fresco in biology, see Huisman et al. 1993 Journal of Vegetation Science <doi:10.1111/jvs.12050>) models. Response curves along one-dimensional gradients including no response, monotone, plateau, unimodal and bimodal models.
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2020-05-20 21:45:20 UTC; jansen
Repository: CRAN
Date/Publication: 2020-05-22 08:30:06 UTC

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New package RFmerge with initial version 0.1-10
Package: RFmerge
Type: Package
Title: Merging of Satellite Datasets with Ground Observations using Random Forests
Version: 0.1-10
Author: Mauricio Zambrano-Bigiarini [aut, cre, cph] (<https://orcid.org/0000-0002-9536-643X>), Oscar M. Baez-Villanueva [aut, cph], Juan Giraldo-Osorio [ctb]
Authors@R: c(person("Mauricio Zambrano-Bigiarini", email = "mzb.devel@gmail.com", role=c("aut", "cre", "cph"), comment=c(ORCID = "0000-0002-9536-643X")), person("Oscar M. Baez-Villanueva", email = "obaezvil@th-koeln.de", role=c("aut", "cph")), person("Juan Giraldo-Osorio", email = "j.giraldoo@javeriana.edu.co", role=c("ctb")) )
Maintainer: Mauricio Zambrano-Bigiarini <mzb.devel@gmail.com>
Description: S3 implementation of the Random Forest MErging Procedure (RF-MEP), which combines two or more satellite-based datasets (e.g., precipitation products, topography) with ground observations to produce a new dataset with improved spatio-temporal distribution of the target field. In particular, this package was developed to merge different Satellite-based Rainfall Estimates (SREs) with measurements from rain gauges, in order to obtain a new precipitation dataset where the time series in the rain gauges are used to correct different types of errors present in the SREs. However, this package might be used to merge other hydrological/environmental satellite fields with point observations. For details, see Baez-Villanueva et al. (2020) <doi:10.1016/j.rse.2019.111606>. Bugs / comments / questions / collaboration of any kind are very welcomed.
License: GPL (>= 3)
Depends: R (>= 3.5.0)
Imports: raster, sp, sf, randomForest, zoo, parallel, methods, stats, utils, pbapply
Suggests: knitr, rmarkdown, rgdal
VignetteBuilder: knitr
URL: https://github.com/hzambran/RFmerge
MailingList: https://stat.ethz.ch/mailman/listinfo/r-sig-ecology
BugReports: https://github.com/hzambran/RFmerge/issues
LazyLoad: yes
NeedsCompilation: no
Repository: CRAN
Packaged: 2020-05-21 16:53:52 UTC; hzambran
Date/Publication: 2020-05-22 08:00:02 UTC

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New package DecisionAnalysis with initial version 1.1.0
Package: DecisionAnalysis
Type: Package
Title: Implementation of Multi Objective Decision Analysis
Version: 1.1.0
Authors@R: c( person("Josh", "Deehr", email = "josh.deehr@gmail.com", role = c("aut","cre")), person("Christopher", "Smith", email = "Cms3am@virginia.edu", role = c("aut")), person("Jason", "Freels", email = "auburngrads@live.com", role = c("aut")), person("Emily", "Meyer", email = "emily.meyer@theperducogroup.com", role = c("aut")) )
Maintainer: Josh Deehr <josh.deehr@gmail.com>
BugReports: https://github.com/AFIT-R/DecisionAnalysis
Date: 2020-5-21
Description: Aides in the multi objective decision analysis process by simplifying the creation of value hierarchy tree plots, calculating and plotting single and multi attribute value function scores, and conducting sensitivity analysis. Linear, exponential, and categorical single attribute value functions are supported. For details see Parnell (2013, ISBN:978-1-118-17313-8) Kirkwood (1997, ISBN:0-534-51692-0).
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Depends: R (>= 2.10)
Imports: stats, ggplot2, tidyr, dplyr, graphics, data.tree, gridExtra, viridisLite, Cairo, methods, qpdf, DiagrammeR
RoxygenNote: 6.0.1
Suggests: knitr, rmarkdown, testthat
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-05-22 01:11:38 UTC; ktdeehr
Author: Josh Deehr [aut, cre], Christopher Smith [aut], Jason Freels [aut], Emily Meyer [aut]
Repository: CRAN
Date/Publication: 2020-05-22 08:00:06 UTC

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Thu, 21 May 2020

New package pkgndep with initial version 1.0.0
Package: pkgndep
Type: Package
Title: Check the Heaviness of Package Dependencies
Version: 1.0.0
Date: 2020-05-13
Author: Zuguang Gu
Maintainer: Zuguang Gu <z.gu@dkfz.de>
Depends: R (>= 3.5.0)
Imports: ComplexHeatmap (>= 2.0.0), GetoptLong, utils, grid, crayon, callr
Suggests: knitr
Description: It checks the heaviness of the packages that user's package depends on. For each package listed in the "Depends", "Imports" and "Suggests" fields in the DESCRIPTION file, it opens a new R session, loads the package and counts the number of namespaces that are loaded. The summary of the dependencies is visualized by a customized heatmap. Examples of dependency analysis can be found at <https://jokergoo.github.io/pkgndep/stat/>.
URL: https://github.com/jokergoo/pkgndep
VignetteBuilder: knitr
License: MIT + file LICENSE
NeedsCompilation: no
Packaged: 2020-05-13 18:37:21 UTC; jokergoo
Repository: CRAN
Date/Publication: 2020-05-21 09:30:02 UTC

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Wed, 20 May 2020

New package rRofex with initial version 1.6.9
Package: rRofex
Type: Package
Title: Interface to 'Matba Rofex' Trading API
Version: 1.6.9
Authors@R: c( person("Augusto", "Hassel", role = c("aut", "cre"), email = "ahassel@primary.com.ar"), person("Juan Francisco", "Gomez", role = c("ctb")), person("Matba Rofex", role = c("cph")) )
Description: Execute API calls to the 'Matba Rofex' <https://apihub.primary.com.ar> trading platform. Functionality includes accessing account data and current holdings, retrieving investment quotes, placing and canceling orders, and getting reference data for instruments.
License: MIT + file LICENSE
URL: https://matbarofex.github.io/rRofex, https://github.com/matbarofex/rRofex
BugReports: https://github.com/matbarofex/rRofex/issues
Encoding: UTF-8
LazyData: true
Imports: dplyr, httr, jsonlite, magrittr, tibble, tidyr, rlang, purrr, glue, methods
RoxygenNote: 7.1.0
Collate: 'attach.R' 's4_object.R' 'functions.R' 'functions_helpers.R' 'globals.R' 'rRofex.R'
NeedsCompilation: no
Packaged: 2020-05-13 15:49:20 UTC; augus
Author: Augusto Hassel [aut, cre], Juan Francisco Gomez [ctb], Matba Rofex [cph]
Maintainer: Augusto Hassel <ahassel@primary.com.ar>
Repository: CRAN
Date/Publication: 2020-05-20 15:10:02 UTC

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New package ghypernet with initial version 1.0.0
Package: ghypernet
Type: Package
Title: Fit and Simulate Generalised Hypergeometric Ensembles of Graphs
Version: 1.0.0
Date: 2020-05-11
Authors@R: c( person("Giona", "Casiraghi", email = "giona@ethz.ch", role = c("aut", "cre"), comment = c(ORCID = "0000-0003-0233-5747")), person("Vahan", "Nanumyan", email = "vahan@ethz.ch", role = c('aut'), comment = c(ORCID = "0000-0001-9054-3217")), person("Laurence", "Brandenberger", email = "lbrandenberger@ethz.ch", role = c('aut')), person("Giacomo", "Vaccario", email = "gvaccario@ethz.ch", role = c('ctb')) )
URL: http://ghyper.net
Description: Provides functions for model fitting and selection of generalised hypergeometric ensembles of random graphs (gHypEG). To learn how to use it, check the vignettes for a quick tutorial. Please reference its use as Casiraghi, G., Nanumyan, V. (2019) <doi:10.5281/zenodo.2555300> together with those relevant references from the one listed below. The package is based on the research developed at the Chair of Systems Design, ETH Zurich. Casiraghi, G., Nanumyan, V., Scholtes, I., Schweitzer, F. (2016) <arXiv:1607.02441>. Casiraghi, G., Nanumyan, V., Scholtes, I., Schweitzer, F. (2017) <doi:10.1007/978-3-319-67256-4_11>. Casiraghi, G., (2017) <arxiv:1702.02048> Casiraghi, G., Nanumyan, V. (2018) <arXiv:1810.06495>. Brandenberger, L., Casiraghi, G., Nanumyan, V., Schweitzer, F. (2019) <doi:10.1145/3341161.3342926> Casiraghi, G. (2019) <doi:10.1007/s41109-019-0241-1>.
Depends: R (>= 3.0)
License: AGPL-3
Imports: parallel, plyr, numbers, purrr, extraDistr, dplyr, rlang, reshape2, rootSolve
Suggests: BiasedUrn, igraph, knitr, rmarkdown, ggplot2, texreg, ggraph
VignetteBuilder: knitr
Encoding: UTF-8
RoxygenNote: 7.1.0
Language: en-GB
LazyData: true
NeedsCompilation: no
Packaged: 2020-05-13 16:06:30 UTC; giona
Author: Giona Casiraghi [aut, cre] (<https://orcid.org/0000-0003-0233-5747>), Vahan Nanumyan [aut] (<https://orcid.org/0000-0001-9054-3217>), Laurence Brandenberger [aut], Giacomo Vaccario [ctb]
Maintainer: Giona Casiraghi <giona@ethz.ch>
Repository: CRAN
Date/Publication: 2020-05-20 15:20:02 UTC

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New package EBMAforecast with initial version 1.0.0
Package: EBMAforecast
Type: Package
Title: Estimate Ensemble Bayesian Model Averaging Forecasts using Gibbs Sampling or EM-Algorithms
Version: 1.0.0
Date: 2020-05-20
Authors@R: c(person("Florian M.", "Hollenbach", email = "fhollenbach@tamu.edu", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-9599-556X")), person("Jacob M.", "Montgomery", role = c("aut")), person("Michael D.", "Ward", role = c("aut")))
URL: <https://github.com/fhollenbach/EBMA/>
Description: Create forecasts from multiple predictions using ensemble Bayesian model averaging (EBMA). EBMA models can be estimated using an expectation maximization (EM) algorithm or as fully Bayesian models via Gibbs sampling.
License: GPL (>= 2)
Imports: Rcpp (>= 1.0.2), plyr, graphics, separationplot, Hmisc, abind, gtools, methods
LinkingTo: Rcpp
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
Collate: 'EBMAforecast.R' 'forecastData.R' 'EBMApredict.R' 'RcppExports.R' 'calibrateEnsemble.R' 'compareModels.R' 'document-data.R' 'fitEnsembleLogit.R' 'fitEnsembleNormal.R' 'global.R' 'makeForecastData.R' 'predictLogit.R' 'predictNormal.R' 'summary_plot.R' 'print_show.R' 'utility-functions.R'
NeedsCompilation: yes
Packaged: 2020-05-20 11:01:56 UTC; florianhollenbach
Author: Florian M. Hollenbach [aut, cre] (<https://orcid.org/0000-0002-9599-556X>), Jacob M. Montgomery [aut], Michael D. Ward [aut]
Maintainer: Florian M. Hollenbach <fhollenbach@tamu.edu>
Repository: CRAN
Date/Publication: 2020-05-20 15:40:06 UTC

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New package discnorm with initial version 0.1.0
Package: discnorm
Type: Package
Title: Test for Discretized Normality in Ordinal Data
Version: 0.1.0
Authors@R: c(person("Njål", "Foldnes", email = "njal.foldnes@gmail.com", role = c("aut", "cre")), person("Steffen", "Grønneberg", email = "steffeng@gmail.com", role = c("aut")))
Description: Tests whether multivariate ordinal data may stem from discretizing a multivariate normal distribution. The test is described by Foldnes and Grønneberg (2019) <doi:10.1080/10705511.2019.1673168>.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
Imports: lavaan, arules, sirt, MASS, pbivnorm, psych
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-05-13 18:26:42 UTC; Njaal0
Author: Njål Foldnes [aut, cre], Steffen Grønneberg [aut]
Maintainer: Njål Foldnes <njal.foldnes@gmail.com>
Repository: CRAN
Date/Publication: 2020-05-20 15:30:06 UTC

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New package BayesARIMAX with initial version 0.1.1
Package: BayesARIMAX
Type: Package
Title: Bayesian Estimation of ARIMAX Model
Version: 0.1.1
Authors@R: c(person("Achal", "Lama", role = c("aut", "cre"), email = "achal.lama@icar.gov.in"), person("Kn", "Singh", role = "aut"), person("Bishal", "Gurung", role = "aut", email = "Bishal.Gurung@icar.gov.in"))
Author: Achal Lama [aut, cre], Kn Singh [aut], Bishal Gurung [aut]
Maintainer: Achal Lama <achal.lama@icar.gov.in>
Depends: R (>= 3.3.0),coda,forecast
Description: The Autoregressive Integrated Moving Average (ARIMA) model is very popular univariate time series model. Its application has been widened by the incorporation of exogenous variable(s) (X) in the model and modified as ARIMAX by Bierens (1987) <doi:10.1016/0304-4076(87)90086-8>. In this package we estimate the ARIMAX model using Bayesian framework.
Encoding: UTF-8
LazyData: true
License: GPL-3
NeedsCompilation: no
Packaged: 2020-05-20 05:29:52 UTC; USER
Repository: CRAN
Date/Publication: 2020-05-20 15:40:09 UTC

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New package BacArena with initial version 1.8.2
Package: BacArena
Title: Modeling Framework for Cellular Communities in their Environments
Version: 1.8.2
Authors@R: c( person("Eugen", "Bauer", , "eugen.bauer@uni.lu", role = c("aut")), person("Johannes", "Zimmermann", , "j.zimmermann@iem.uni-kiel.de", role = c("aut", "cre")))
Author: Eugen Bauer [aut], Johannes Zimmermann [aut, cre]
Maintainer: Johannes Zimmermann <j.zimmermann@iem.uni-kiel.de>
Description: Can be used for simulation of organisms living in communities (Bauer and Zimmermann (2017) <doi:10.1371/journal.pcbi.1005544>). Each organism is represented individually and genome scale metabolic models determine the uptake and release of compounds. Biological processes such as movement, diffusion, chemotaxis and kinetics are available along with data analysis techniques.
URL: https://BacArena.github.io/
BugReports: https://github.com/euba/BacArena/issues
Depends: R (>= 3.5.0), sybil (>= 2.1.3), ReacTran (>= 1.4.2), deSolve (>= 1.12), Matrix (>= 1.2)
Imports: methods, utils, stats, graphics, ggplot2, reshape2, glpkAPI, plyr, Rcpp, igraph, stringr, R.matlab
Suggests: parallel, knitr, rmarkdown
LinkingTo: Rcpp, RcppArmadillo, RcppEigen
License: GPL-3 | file LICENSE
VignetteBuilder: knitr
RoxygenNote: 7.0.2
LazyData: true
NeedsCompilation: yes
Packaged: 2020-05-20 10:30:20.501 UTC; jo
Repository: CRAN
Date/Publication: 2020-05-20 15:40:12 UTC

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New package rules with initial version 0.0.1
Package: rules
Title: Model Wrappers for Rule-Based Models
Version: 0.0.1
Authors@R: c( person( given = "Max", family = "Kuhn", email = "max@rstudio.com", comment = c(ORCID = "0000-0003-2402-136X"), role = c("aut", "cre") ), person("RStudio", role = "cph") )
Description: Bindings for additional models for use with the 'parsnip' package. Models include prediction rule ensembles (Friedman and Popescu, 2008) <doi:10.1214/07-AOAS148>, C5.0 rules (Quinlan, 1992 ISBN: 1558602380), and Cubist (Kuhn and Johnson, 2013) <doi:10.1007/978-1-4614-6849-3>.
License: MIT + file LICENSE
URL: https://github.com/tidymodels/rules, https://rules.tidymodels.org
Depends: parsnip (>= 0.1.0)
Suggests: testthat, C50, Cubist, xrf (>= 0.2.0), covr, modeldata, spelling
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0.9000
Imports: purrr, rlang, tibble, dials, tidyr, dplyr
Language: en-US
NeedsCompilation: no
Packaged: 2020-05-09 16:48:31 UTC; max
Author: Max Kuhn [aut, cre] (<https://orcid.org/0000-0003-2402-136X>), RStudio [cph]
Maintainer: Max Kuhn <max@rstudio.com>
Repository: CRAN
Date/Publication: 2020-05-20 15:00:02 UTC

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New package RGISTools with initial version 1.0.2
Type: Package
Package: RGISTools
Title: Handling Multiplatform Satellite Images
Version: 1.0.2
Author: U Pérez - Goya [aut, cre] <unai.perez@unavarra.es>, M Montesino - SanMartin [aut] <manuel.montesino@unavarra.es>, A F Militino [aut] <militino@unavarra.es>, M D Ugarte [aut] <lola@unavarra.es>
Maintainer: U Perez - Goya <unai.perez@unavarra.es>
Description: Downloading, customizing, and processing time series of satellite images for a region of interest. 'RGISTools' functions allow a unified access to multispectral images from Landsat, MODIS and Sentinel repositories. 'RGISTools' also offers capabilities for customizing satellite images, such as tile mosaicking, image cropping and new variables computation. Finally, 'RGISTools' covers the processing, including cloud masking, compositing and gap-filling/smoothing time series of images (Militino et al., 2018 <doi:10.3390/rs10030398> and Militino et al., 2019 <doi:10.1109/TGRS.2019.2904193>).
URL: https://github.com/spatialstatisticsupna/RGISTools#RGISTools
BugReports: https://github.com/spatialstatisticsupna/RGISTools/issues
Depends: R (>= 3.5.0), raster, sf, tmap
Imports: Rdpack, XML, xml2, utils, fields, urltools, rjson, rvest, tools, methods, curl, httr, mapview, sp, stars
Suggests: rgdal
RdMacros: Rdpack
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-05-20 08:53:55 UTC; Unai
Repository: CRAN
Date/Publication: 2020-05-20 14:20:06 UTC

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New package covid19us with initial version 0.1.6
Package: covid19us
Title: Cases of COVID-19 in the United States
Version: 0.1.6
Authors@R: person(given = "Amanda", family = "Dobbyn", role = c("aut", "cre"), email = "amanda.e.dobbyn@gmail.com")
Description: A wrapper around the 'COVID Tracking Project API' <https://covidtracking.com/api/> providing data on cases of COVID-19 in the US.
License: MIT + file LICENSE
Imports: curl (>= 4.3), dplyr (>= 0.8.3), glue (>= 1.3.1), httr (>= 1.4.1), lubridate (>= 1.7.4), magrittr (>= 1.5), purrr (>= 0.3.3), snakecase (>= 0.11.0), stringr (>= 1.4.0), tibble (>= 2.1.3), tidyr (>= 1.0.2)
Suggests: covr (>= 3.4.0), testthat (>= 2.1.0)
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-05-20 04:12:54 UTC; amanda
Author: Amanda Dobbyn [aut, cre]
Maintainer: Amanda Dobbyn <amanda.e.dobbyn@gmail.com>
Repository: CRAN
Date/Publication: 2020-05-20 12:40:02 UTC

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Mon, 18 May 2020

New package sequoia with initial version 2.0.7
Package: sequoia
Type: Package
Title: Pedigree Inference from SNPs
Version: 2.0.7
Date: 2020-05-17
Authors@R: person("Jisca", "Huisman", email = "jisca.huisman@gmail.com", role = c("aut", "cre"))
Author: Jisca Huisman [aut, cre]
Maintainer: Jisca Huisman <jisca.huisman@gmail.com>
Description: Fast multi-generational pedigree inference from incomplete data on hundreds of SNPs, including parentage assignment and sibship clustering. See Huisman (2017) (<DOI:10.1111/1755-0998.12665>, citation('sequoia')) for more information.
License: GPL-2
LazyData: TRUE
Imports: plyr (>= 1.8.0), stats, utils, graphics
RoxygenNote: 7.1.0
Suggests: xlsx, knitr, rmarkdown, bookdown
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2020-05-17 19:07:44 UTC; jisca
Repository: CRAN
Date/Publication: 2020-05-18 18:30:09 UTC

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New package worcs with initial version 0.1.1
Package: worcs
Type: Package
Date: 2020-05-12
Title: Workflow for Open Reproducible Code in Science
Version: 0.1.1
Authors@R: c( person( given = c("Caspar", "J."), family = "van Lissa", email = "c.j.vanlissa@uu.nl", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-0808-5024") ), person( "Aaron", "Peikert", role = c("ctb"), comment = c(ORCID = "0000-0001-7813-818X") ), person( c("Andreas", "M."), "Brandmaier", role = "ctb", comment = c(ORCID = "0000-0001-8765-6982") ) )
Description: Create reproducible and transparent research projects in 'R', with a minimal amount of code. This package is based on the Workflow for Open Reproducible Code in Science (WORCS), a step-by-step procedure based on best practices for Open Science. It includes an 'RStudio' project template, several convenience functions, and all dependencies required to make your project reproducible and transparent. WORCS is explained in the tutorial paper by Van Lissa, Brandmaier, Brinkman, & Vreede (2020) <doi:10.17605/OSF.IO/ZCVBS>.
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
URL: https://github.com/cjvanlissa/worcs
RoxygenNote: 7.1.0
Imports: rmarkdown, prereg, gert, ranger, yaml, digest
Suggests: remotes, renv, knitr, missRanger, testthat (>= 2.1.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-05-12 20:52:01 UTC; Lissa102
Author: Caspar J. van Lissa [aut, cre] (<https://orcid.org/0000-0002-0808-5024>), Aaron Peikert [ctb] (<https://orcid.org/0000-0001-7813-818X>), Andreas M. Brandmaier [ctb] (<https://orcid.org/0000-0001-8765-6982>)
Maintainer: Caspar J. van Lissa <c.j.vanlissa@uu.nl>
Repository: CRAN
Date/Publication: 2020-05-18 15:20:02 UTC

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New package strand with initial version 0.1.1
Package: strand
Type: Package
Title: A Framework for Investment Strategy Simulation
Version: 0.1.1
Date: 2020-05-12
Authors@R: c(person(given = "Jeff", family ="Enos", email = "jeff@strand.tech", role = c("cre", "aut")), person(given = "David", family = "Kane", email = "david@strand.tech", role = c("aut")), person(given = "Strand Technologies, Inc.", role = "cph"))
Description: Provides a framework for performing discrete (share-level) simulations of investment strategies. Simulated portfolios optimize exposure to an input signal subject to constraints such as position size and factor exposure.
License: GPL-3
URL: https://github.com/strand-tech/strand
BugReports: https://github.com/strand-tech/strand/issues
Depends: R (>= 3.5.0)
Imports: R6, Matrix, Rglpk, Rsymphony, dplyr, tidyr, feather, lubridate, rlang, yaml, ggplot2
Suggests: testthat, knitr, rmarkdown, shiny, DT
Encoding: UTF-8
LazyData: true
VignetteBuilder: knitr
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-05-12 21:22:26 UTC; enos
Author: Jeff Enos [cre, aut], David Kane [aut], Strand Technologies, Inc. [cph]
Maintainer: Jeff Enos <jeff@strand.tech>
Repository: CRAN
Date/Publication: 2020-05-18 15:20:06 UTC

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New package SMLE with initial version 0.3.1
Package: SMLE
Title: Joint Feature Screening via Sparse MLE
Version: 0.3.1
Author: Qianxiang Zang,Chen Xu,Kelly Burkett
Maintainer: Qianxiang Zang <qzang023@uottawa.ca>
Imports: foreach, glmnet, mnormt, doParallel
Description: Variable selection techniques are essential tools for model selection and estimation in high-dimensional statistical models. Sparse Maximal Likelihood Estimator (SMLE) (Xu and Chen (2014)<doi:10.1080/01621459.2013.879531>) provides an efficient implementation for the joint feature screening method on high-dimensional generalized linear models. It also conducts a post-screening selection based on user-specified selection criterion. The algorithm uses iterative hard thresholding along with parallel computing.
License: GPL-2
Depends: R (>= 3.2.4)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Repository: CRAN
Packaged: 2020-05-13 04:44:44 UTC; mac
Date/Publication: 2020-05-18 15:40:03 UTC

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New package scipub with initial version 1.0.0
Package: scipub
Title: Summarize Data for Scientific Publication
Version: 1.0.0
Authors@R: person(given = "David", family = "Pagliaccio", role = c("aut", "cre"), email = "david.pagliaccio@gmail.com", comment = c(ORCID = "0000-0002-1214-1965"))
Description: Create and format tables and APA statistics for for scientific publication. This includes making a 'Table 1' to summarize demographics across groups, correlation tables with significance indicated by stars, and extracting formatted statistical summarizes from simple tests for in-text notation. The package also includes functions for Winsorizing data based on a Z-statistic cutoff.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
Language: en-US
VignetteBuilder: knitr
URL: https://github.com/dpagliaccio/scipub, https://dpagliaccio.github.io/scipub/
BugReports: https://github.com/dpagliaccio/scipub/issues
Depends: R (>= 3.6)
Imports: dplyr, forcats, purrr, stats, stringr, tibble, tidyr, tidyselect
Suggests: spelling, ggplot2, htmlTable, knitr, rmarkdown
NeedsCompilation: no
Packaged: 2020-05-10 16:19:57 UTC; david
Author: David Pagliaccio [aut, cre] (<https://orcid.org/0000-0002-1214-1965>)
Maintainer: David Pagliaccio <david.pagliaccio@gmail.com>
Repository: CRAN
Date/Publication: 2020-05-18 15:10:03 UTC

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New package Raquifer with initial version 0.1.0
Package: Raquifer
Type: Package
Title: Estimate the Water Influx into Hydrocarbon Reservoirs
Version: 0.1.0
Date: 2020-05-10
Authors@R: person(given = "Farshad", family = "Tabasinejad", role = c("aut", "cre"), email = "farshad.tabasinejad@susaenergy.com")
Description: Generate a table of cumulative water influx into hydrocarbon reservoirs over time using un-steady and pseudo-steady state models. Van Everdingen, A. F. and Hurst, W. (1949) <doi:10.2118/949305-G>. Fetkovich, M. J. (1971) <doi:10.2118/2603-PA>. Yildiz, T. and Khosravi, A. (2007) <doi:10.2118/103283-PA>.
License: GPL-3
URL: https://susaenergy.github.io/Raquifer_ws/
Imports: Rdpack, magrittr, dplyr, pracma, gsl
RdMacros: Rdpack
Suggests: knitr, rmarkdown, testthat, ggplot2
Language: en-US
Encoding: UTF-8
LazyData: TRUE
VignetteBuilder: knitr
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-05-13 04:29:48 UTC; ftn60
Author: Farshad Tabasinejad [aut, cre]
Maintainer: Farshad Tabasinejad <farshad.tabasinejad@susaenergy.com>
Repository: CRAN
Date/Publication: 2020-05-18 15:30:06 UTC

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New package leaflet.extras2 with initial version 1.0.0
Package: leaflet.extras2
Type: Package
Title: Extra Functionality for 'leaflet' Package
Version: 1.0.0
Authors@R: c( person("Gatscha", "Sebastian", email = "sebastian_gatscha@gmx.at", role = c("aut", "cre")) )
Description: Several 'leaflet' plugins are integrated, which are available as extension to the 'leaflet' package.
License: GPL-3 | file LICENSE
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.1.0), leaflet (>= 2.0.0)
Imports: htmlwidgets, htmltools, magrittr, utils
Suggests: jsonlite, shiny, sf, geojsonsf, sp, testthat (>= 2.1.0), covr
URL: https://trafficonese.github.io/leaflet.extras2, https://github.com/trafficonese/leaflet.extras2
BugReports: https://github.com/trafficonese/leaflet.extras2/issues
RoxygenNote: 7.0.2
NeedsCompilation: no
Packaged: 2020-05-12 18:45:09 UTC; gatscha
Author: Gatscha Sebastian [aut, cre]
Maintainer: Gatscha Sebastian <sebastian_gatscha@gmx.at>
Repository: CRAN
Date/Publication: 2020-05-18 15:10:06 UTC

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New package intcure with initial version 2.1
Encoding: UTF-8
Package: intcure
Title: Mixture Cure Models with Random Effects
Version: 2.1
Authors@R: person("Yingwei", "Peng", role = c("aut", "cre"), email = "yingwei.peng@queensu.ca")
Description: Mixture cure models with random effects to survival data as described in Peng and Taylor (2011) <doi:10.1002/sim.4098>.
Depends: survival, R (>= 3.5.0)
Imports: mvtnorm, cubature
License: GPL-3
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-05-12 20:06:26 UTC; Yingwei
Author: Yingwei Peng [aut, cre]
Maintainer: Yingwei Peng <yingwei.peng@queensu.ca>
Repository: CRAN
Date/Publication: 2020-05-18 15:10:11 UTC

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New package hydraulics with initial version 0.1.0
Package: hydraulics
Type: Package
Title: Basic Pipe Hydraulics
Version: 0.1.0
Author: Ed Maurer [aut, cre]
Maintainer: Ed Maurer <emaurer@scu.edu>
Description: Functions for basic hydraulic calculations related to water flow in circular pipes flowing full (under pressure). This includes friction loss calculations by solving the Darcy-Weisbach equation for head loss, flow or diameter, and plotting a Moody diagram. The Darcy-Weisbach friction factor is calculated using the Colebrook (or Colebrook-White equation), the basis of the Moody diagram, the original citation being Colebrook (1939) <doi:10.1680/ijoti.1939.13150>. The derivation of the Darcy-Weisbach equation and methods for its solution are outlined in many fluid mechanics texts such as Finnemore and Franzini (2002, ISBN:978-0072432022). This package is designed to work similarly to the 'iemisc' package, but with an emphasis on pipe flow.
License: GPL (>= 3)
Depends: R (>= 3.6.0)
Encoding: UTF-8
LazyData: true
Imports: ggplot2, grid, reshape2
Suggests:
RoxygenNote: 7.0.2
NeedsCompilation: no
Packaged: 2020-05-12 20:29:26 UTC; edwinmaurer
Repository: CRAN
Date/Publication: 2020-05-18 15:10:14 UTC

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New package codexcopd with initial version 0.1.0
Package: codexcopd
Type: Package
Title: The CODEX (Comorbidity, Obstruction, Dyspnea, and Previous Severe Exacerbations) Index: Short and Medium-Term Prognosis in Patients Hospitalized for Chronic Obstructive Pulmonary Disease (COPD) Exacerbations
Version: 0.1.0
Authors@R: c( person("Aida", "Kazemi", email = "aidakazemi10@gmail.com", role = c("aut", "cph")), person("Amin", "Adibi", email = "adibi@alumni.ubc.ca", role = c("aut", "cre")))
Maintainer: Amin Adibi <adibi@alumni.ubc.ca>
Description: Predicts 3 to 12 months prognosis in Chronic Obstructive Pulmonary Disease (COPD) patients hospitalized for severe exacerbations, as described in Almagro et al. (2014) <doi:10.1378/chest.13-1328>.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-05-12 21:49:23 UTC; maadibi
Author: Aida Kazemi [aut, cph], Amin Adibi [aut, cre]
Repository: CRAN
Date/Publication: 2020-05-18 15:20:10 UTC

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New package motifcluster with initial version 0.1.0
Package: motifcluster
Title: Motif-Based Spectral Clustering of Weighted Directed Networks
Version: 0.1.0
Authors@R: person(given = "William George", family = "Underwood", role = c("aut", "cre"), email = "wgu2@princeton.edu")
Description: Tools for spectral clustering of weighted directed networks using motif adjacency matrices. Methods perform well on large and sparse networks, and random sampling methods for generating weighted directed networks are also provided. Based on methodology detailed in Underwood, Elliott and Cucuringu (2020) <arXiv:2004.01293>.
URL: https://github.com/wgunderwood/motifcluster
Language: en-US
BugReports: https://github.com/wgunderwood/motifcluster/issues
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
Depends: R (>= 3.6.0)
Imports: igraph (>= 1.2.5), LICORS (>= 0.2.0), Matrix (>= 1.2), RSpectra (>= 0.16.0)
Suggests: covr (>= 3.5.0), knitr (>= 1.28), mclust (>= 5.4.6), rmarkdown (>= 2.1), testthat (>= 2.3.2)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-05-12 17:45:48 UTC; will
Author: William George Underwood [aut, cre]
Maintainer: William George Underwood <wgu2@princeton.edu>
Repository: CRAN
Date/Publication: 2020-05-18 14:50:02 UTC

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New package DRDID with initial version 1.0.0
Package: DRDID
Type: Package
Title: Doubly Robust Difference-in-Differences Estimators
Version: 1.0.0
Authors@R: c(person("Pedro H. C.", "Sant'Anna", email = "pedro.h.santanna@vanderbilt.edu", role = c("aut", "cre")), person("Jun B.", "Zhao", email = "jun.zhao@vanderbilt.edu",role = c("aut")) )
Description: Implements the locally efficient doubly robust difference-in-differences (DiD) estimators for the average treatment effect proposed by Sant'Anna and Zhao (2020) <arXiv:1812.01723>. The estimator combines inverse probability weighting and outcome regression estimators (also implemented in the package) to form estimators with more attractive statistical properties. Two different estimation methods can be used to estimate the nuisance functions.
URL: https://pedrohcgs.github.io/DRDID/, https://github.com/pedrohcgs/DRDID
License: GPL-3
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.4)
Imports: stats, trust, BMisc (>= 1.4.1)
RoxygenNote: 7.1.0
Suggests: knitr, rmarkdown, spelling, testthat, covr
Date: 2020-05-12 13:00
Language: en-US
BugReports: https://github.com/pedrohcgs/DRDID/issues
NeedsCompilation: no
Packaged: 2020-05-12 17:46:49 UTC; santanph
Author: Pedro H. C. Sant'Anna [aut, cre], Jun B. Zhao [aut]
Maintainer: Pedro H. C. Sant'Anna <pedro.h.santanna@vanderbilt.edu>
Repository: CRAN
Date/Publication: 2020-05-18 14:50:10 UTC

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New package arcos with initial version 1.1
Package: arcos
Type: Package
Title: Load ARCOS Prescription Data Prepared by the Washington Post
Version: 1.1
Date: 2020-04-18
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
Imports: stringr, magrittr, jsonlite, dplyr, urltools, vroom
RoxygenNote: 6.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-05-16 20:34:44 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: 2020-05-18 10:40:07 UTC

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New package FeatureImpCluster with initial version 0.1.2
Package: FeatureImpCluster
Title: Feature Importance for Partitional Clustering
Version: 0.1.2
Authors@R: person(given = "Oliver", family = "Pfaffel", role = c("aut", "cre"), email = "opfaffel@gmail.com")
Description: Implements a novel approach for measuring feature importance in k-means clustering. Importance of a feature is measured by the misclassification rate relative to the baseline cluster assignment due to a random permutation of feature values.
License: GPL-3
Encoding: UTF-8
LazyData: true
Suggests: flexclust, clustMixType, knitr, rmarkdown, testthat, attempt, ClustImpute, covr
Imports: ggplot2
RoxygenNote: 7.1.0
Depends: data.table
NeedsCompilation: no
Packaged: 2020-05-11 22:03:22 UTC; opfaf
Author: Oliver Pfaffel [aut, cre]
Maintainer: Oliver Pfaffel <opfaffel@gmail.com>
Repository: CRAN
Date/Publication: 2020-05-18 09:40:02 UTC

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New package zonator with initial version 0.6.0
Package: zonator
Type: Package
Title: Utilities for Zonation Spatial Conservation Prioritization Software
Version: 0.6.0
Date: 2020-05-16
Authors@R: c( person("Joona" , "Lehtomaki", role = c("aut", "cre"), email = "joona.lehtomaki@gmail.com"))
License: FreeBSD
Encoding: UTF-8
Maintainer: Joona Lehtomaki <joona.lehtomaki@gmail.com>
Description: Create new analysis setups and deal with results of Zonation conservation prioritization software <https://github.com/cbig/zonation-core>. This package uses data available in the 'zdat' (7.7 MB) package for building the vignettes.
Imports: ggplot2 (>= 2.0.0), methods, RColorBrewer, raster, reshape2, rgdal
Depends: R (>= 2.15.2)
Suggests: knitr, rasterVis, rmarkdown, testthat, zdat (>= 0.1.0)
StagedInstall: yes
Additional_repositories: https://jlehtoma.github.io/drat
URL: https://cbig.github.io/zonator/
BugReports: https://github.com/cbig/zonator/issues
VignetteBuilder: knitr
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-05-17 13:11:34 UTC; jlehtoma
Author: Joona Lehtomaki [aut, cre]
Repository: CRAN
Date/Publication: 2020-05-18 08:50:02 UTC

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New package maGUI with initial version 2.4
Package: maGUI
Type: Package
Title: A Graphical User Interface for Microarray Data Analysis and Annotation
Version: 2.4
Date: 2020-05-16
Author: Dhammapal Bharne, Vaibhav Vindal
Maintainer: Dhammapal Bharne <dhammapalb@gmail.com>
Imports: Biobase, Biostrings, BiocManager, RSQLite, convert, marray, GEOquery, GEOmetadb, amap, RGtk2, gWidgets2, gWidgets2RGtk2, tcltk, RBGL, WGCNA, Rgraphviz, KEGGREST, KEGGgraph, grDevices, cairoDevice, graphics, stats, utils, methods, pdInfoBuilder, lumi, oligo, graph, limma, affy, genefilter, simpleaffy, impute, beadarray, GOstats, GO.db, globaltest, ssize, Category, annotate
Description: Provides a Graphical User Interface for Analysing DNA Microarray Data. It performs functional enrichment on genes of interest, identifies gene symbols and also builds co-expression network.
License: GPL-2
LazyLoad: yes
NeedsCompilation: no
Repository: CRAN
Packaged: 2020-05-16 18:00:33 UTC; dhamma
Date/Publication: 2020-05-18 08:50:07 UTC

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Sun, 17 May 2020

New package sinx with initial version 0.0.13
Package: sinx
Version: 0.0.13
Date: 2020-05-16
Title: Sino Xmen Said
Authors@R: c( person("Peng", "Zhao", role = c("aut", "cre"), email = "pzhao@pzhao.net") )
Maintainer: Peng Zhao <pzhao@pzhao.net>
Imports: utils, cowsay, jsonlite, xaringan, pagedown, bookdownplus, rosr, crayon, multicolor, rmsfact, clipr
License: GPL-3
Depends: R (>= 3.1.0)
Suggests: knitr, rmarkdown
Description: Displays a pseudorandom message from a database of quotations. It works as an advanced version of the package 'fortunes', while 'sinx' supports multi-byte languages such as Chinese. The databases of 'sinx' can be given in markdown format, which is easier and more friendly than spread sheets for users.
URL: https://github.com/pzhaonet/sinx
BugReports: https://github.com/pzhaonet/sinx/issues
RoxygenNote: 7.1.0
NeedsCompilation: no
LazyData: true
VignetteBuilder: knitr
Packaged: 2020-05-16 10:01:04 UTC; dapen
Author: Peng Zhao [aut, cre]
Repository: CRAN
Date/Publication: 2020-05-17 07:40:02 UTC

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Sat, 16 May 2020

New package SubtypeDrug with initial version 0.1.0
Package: SubtypeDrug
Type: Package
Title: Prioritization of Candidate Cancer Subtype Specific Drugs
Version: 0.1.0
Author: Xudong Han, Junwei Han, Chonghui Liu
Maintainer: Junwei Han <hanjunwei1981@163.com>
Description: A systematic biology tool was developed to prioritize cancer subtype-specific drugs by integrating genetic perturbation, drug action, biological pathway, and cancer subtype. The capabilities of this tool include inferring patient-specific subpathway activity profiles in the context of gene expression profiles with subtype labels, calculating differentially expressed subpathways based on cultured human cells treated with drugs in the 'cMap' (connectivity map) database, prioritizing cancer subtype specific drugs according to drug-disease reverse association score based on subpathway, and visualization of results (Castelo (2013) <doi:10.1186/1471-2105-14-7>; Han et al (2019) <doi:10.1093/bioinformatics/btz894>; Lamb and Justin (2006) <DOI:10.1126/science.1132939>).
License: GPL (>= 2)
Depends: R (>= 2.10)
Encoding: UTF-8
LazyData: true
BugReports: https://github.com/hanjunwei-lab/SubtypeDrug/issues
RoxygenNote: 7.1.0
Imports: BiocGenerics,GSVA,grDevices,graphics,igraph,parallel,pheatmap,rvest,stats,xml2,devtools,ChemmineR
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-05-12 10:49:33 UTC; 12859
Repository: CRAN
Date/Publication: 2020-05-16 09:30:08 UTC

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New package statespacer with initial version 0.1.0
Package: statespacer
Version: 0.1.0
Date: 2020-05-12
Title: State Space Modelling in 'R'
Description: A tool that makes estimating models in state space form a breeze. See "Time Series Analysis by State Space Methods" by Durbin and Koopman (2012, ISBN: 978-0-19-964117-8) for details about the algorithms implemented.
Authors@R: person("Dylan", "Beijers", email = "dylanbeijers@gmail.com", role = c("aut", "cre"))
URL: https://DylanB95.github.io/statespacer, https://github.com/DylanB95/statespacer
BugReports: https://github.com/DylanB95/statespacer/issues
License: MIT + file LICENSE
RoxygenNote: 7.1.0
RdMacros: Rdpack
Depends: R (>= 3.6)
Imports: Rdpack, stats
Suggests: datasets, graphics, knitr, numDeriv (>= 2016.8-1.1), optimx (>= 2020-4.2), rmarkdown, YieldCurve (>= 4.1)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-05-12 13:06:34 UTC; Dylan
Author: Dylan Beijers [aut, cre]
Maintainer: Dylan Beijers <dylanbeijers@gmail.com>
Repository: CRAN
Date/Publication: 2020-05-16 09:40:03 UTC

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New package seqest with initial version 1.0.0
Package: seqest
Type: Package
Title: Sequential Method for Classification and Generalized Estimating Equations Problem
Version: 1.0.0
Authors@R: person("Xiaoba", "Pan", email = "july666@mail.ustc.edu.cn", role = c("aut", "cre"))
Maintainer: Xiaoba Pan <july666@mail.ustc.edu.cn>
Description: Sequential method to solve the the binary classification problem by Wang (2013) <doi:10.1007/s00184-012-0426-4>, multi-class classification problem by Li (2020) <doi:10.1016/j.csda.2020.106911> and the highly stratified multiple-response problem by Chen (2019) <doi:10.1111/biom.13160>.
NeedsCompilation: yes
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Imports: Rcpp (>= 1.0.2), geepack, mvtnorm, nnet, VGAM, MASS, foreach, stats
LinkingTo: Rcpp, RcppArmadillo
RoxygenNote: 6.1.1
Repository: CRAN
Date: 2020-05-10 07:55:10 UTC
Packaged: 2020-05-12 13:51:06 UTC; Administrator
Author: Xiaoba Pan [aut, cre]
Date/Publication: 2020-05-16 09:50:02 UTC

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New package RfEmpImp with initial version 2.0.3
Package: RfEmpImp
Type: Package
Title: Multiple Imputation using Chained Random Forests
Version: 2.0.3
Authors@R: c(person("Shangzhi", "Hong", role = c("aut", "cre"), email = "shangzhi-hong@hotmail.com"), person("Henry S.", "Lynn", role = c("ths")))
Maintainer: Shangzhi Hong <shangzhi-hong@hotmail.com>
Description: Functions for methods for multiple imputation using chained random forests. Implemented algorithms can handle missing data in both continuous and categorical variables by using prediction-based or node-based conditional distributions constructed using random forests. For prediction-based imputation, the method based on the empirical distribution of out-of-bag prediction errors of random forests and the method based on normality assumption are provided. For node-based imputation, the method based on the conditional distribution formed by predicting nodes of random forests and the method based on measures of proximities of random forests are provided. More details of the statistical methods can be found in Hong et al. (2020) <arXiv:2004.14823>.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
Depends: R (>= 3.5.0), mice (>= 3.8.0), ranger (>= 0.12.1)
Suggests: testthat (>= 2.1.0), knitr, rmarkdown
NeedsCompilation: no
URL: https://github.com/shangzhi-hong/RfEmpImp
BugReports: https://github.com/shangzhi-hong/RfEmpImp/issues
VignetteBuilder: knitr
Packaged: 2020-05-12 11:49:23 UTC; HONG
Author: Shangzhi Hong [aut, cre], Henry S. Lynn [ths]
Repository: CRAN
Date/Publication: 2020-05-16 09:30:11 UTC

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New package RecurRisk with initial version 1.0
Package: RecurRisk
Type: Package
Title: Recurrence Risk Assessment Tool
Version: 1.0
Date: 2020-05-11
Author: Fanni Zhang
Maintainer: Fanni Zhang <zhangf@imsweb.com>
Description: Functions to estimate the risk of recurrence using disease-specific survival data. Mariotto AB, Zou Z, Zhang F, et al (2018) <doi:10.1158/1055-9965.EPI-17-1129>.
License: GPL (>= 2)
Imports: SEER2R,flexsurvcure,stats,survival
NeedsCompilation: no
Packaged: 2020-05-12 14:52:07 UTC; zhangf10
Repository: CRAN
Date/Publication: 2020-05-16 09:50:15 UTC

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New package polAr with initial version 0.1.3
Package: polAr
Title: Argentina Political Analysis
Version: 0.1.3
Authors@R: person(given = "Juan Pablo", family = "Ruiz Nicolini", role = c("aut", "cre", "cph"), email = "juanpabloruiznicolini@gmail.com", comment = c(ORCID = "0000-0002-3138-6343"))
Description: Toolbox for the Analysis of Political and Electoral Data from Argentina.
License: MIT + file LICENSE
Encoding: UTF-8
Language: es
URL: https://github.com/electorArg/polAr
BugReports: https://github.com/electorArg/polAr/issues
LazyData: true
Depends: R (>= 2.10)
Imports: geofacet, dplyr, tidyr (>= 1.0.0), magrittr, formattable, readr, stringr, rvest, xml2, glue, tibble, DT, attempt, curl (>= 4.2), assertthat, gt, forcats, ggplot2, ggthemes, purrr, scales, rlang (>= 0.4.3), RColorBrewer, grDevices
Suggests: pkgcond, knitr, rmarkdown, utf8, qpdf
RoxygenNote: 6.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-05-12 14:54:40 UTC; Menta
Author: Juan Pablo Ruiz Nicolini [aut, cre, cph] (<https://orcid.org/0000-0002-3138-6343>)
Maintainer: Juan Pablo Ruiz Nicolini <juanpabloruiznicolini@gmail.com>
Repository: CRAN
Date/Publication: 2020-05-16 09:50:06 UTC

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New package hydroToolkit with initial version 0.1.0
Package: hydroToolkit
Type: Package
Title: Hydrological Tools for Handling Hydro-Meteorological Data from Argentina and Chile
Version: 0.1.0
Date: 2020-05-07
Author: Ezequiel Toum <etoum@mendoza-conicet.gob.ar>
Maintainer: Ezequiel Toum <etoum@mendoza-conicet.gob.ar>
Description: Read, plot, manipulate and process hydro-meteorological data from Argentina and Chile.
Depends: R (>= 2.10)
License: GPL (>= 3)
Imports: ggplot2, plotly, lubridate, utils, methods, readxl, reshape2
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-05-12 15:38:52 UTC; ezequiel
Repository: CRAN
Date/Publication: 2020-05-16 10:00:02 UTC

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New package ggpacman with initial version 0.1.0
Package: ggpacman
Title: A 'ggplot2' and 'gganimate' Version of Pac-Man
Version: 0.1.0
Authors@R: person(given = "Mickaël", family = "Canouil", role = c("aut", "cre"), email = "mickael.canouil@cnrs.fr", comment = c(ORCID = "0000-0002-3396-4549"))
Description: A funny coding challenge to reproduce the game Pac-Man using 'ggplot2' and 'gganimate'. It provides a pre-defined moves set for Pac-Man and the ghosts for the first level of the game Pac-Man as well as polygon datasets to draw ghosts in 'ggplot2'.
License: GPL-3
URL: https://github.com/mcanouil/pacman
BugReports: https://github.com/mcanouil/pacman/issues
Depends: R (>= 3.6.0)
Imports: stats, utils, rlang (>= 0.1.2), magrittr (>= 1.5), dplyr (>= 0.8.5), tidyr (>= 1.0.2), purrr (>= 0.3.3), ggplot2 (>= 3.3.0), ggforce (>= 0.3.1), gganimate (>= 1.0.5)
Suggests: roxygen2 (>= 7.1.0)
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
Collate: 'pacman-package.R' 'compute_points_eaten.R' 'compute_pacman_coord.R' 'compute_ghost_status.R' 'compute_ghost_coord.R' 'animate_pacman.R'
NeedsCompilation: no
Packaged: 2020-05-12 10:31:14 UTC; mcanouil
Author: Mickaël Canouil [aut, cre] (<https://orcid.org/0000-0002-3396-4549>)
Maintainer: Mickaël Canouil <mickael.canouil@cnrs.fr>
Repository: CRAN
Date/Publication: 2020-05-16 09:30:02 UTC

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New package csa with initial version 0.7.0
Package: csa
Title: A Cross-Scale Analysis Tool for Model-Observation Visualization and Integration
Version: 0.7.0
Authors@R: c( person("Yannis", "Markonis", email = "imarkonis@gmail.com", role = c("aut", "cre")), person("Christoforos", "Pappas", email = "christoforos.pappas@umontreal.ca", role = c("aut")), person("Mijael", "Vargas", email = "vargas_godoy@fzp.czu.cz", role = c("ctb")), person("Simon", "Papalexiou", email = "simon@uni.edu", role = c("ctb")), person("Martin", "Hanel", email = "hanel@fzp.czu.cz", role = c("ctb")) )
Description: Integration of Earth system data from various sources is a challenging task. Except for their qualitative heterogeneity, different data records exist for describing similar Earth system process at different spatio-temporal scales. Data inter-comparison and validation are usually performed at a single spatial or temporal scale, which could hamper the identification of potential discrepancies in other scales. 'csa' package offers a simple, yet efficient, graphical method for synthesizing and comparing observed and modelled data across a range of spatio-temporal scales. Instead of focusing at specific scales, such as annual means or original grid resolution, we examine how their statistical properties change across spatio-temporal continuum.
Depends: R (>= 3.4.0)
Imports: grDevices, stats, ggplot2, data.table, scales, reshape2, moments, Lmoments, foreach, ggpubr, raster, doParallel, parallel
License: GPL-2
Encoding: UTF-8
LazyData: true
URL: http://github.com/imarkonis/csa
BugReports: http://github.com/imarkonis/csa/issues
RoxygenNote: 7.0.2
Suggests: testthat (>= 2.1.0), colorspace
NeedsCompilation: no
Packaged: 2020-05-12 14:34:33 UTC; mirovago
Author: Yannis Markonis [aut, cre], Christoforos Pappas [aut], Mijael Vargas [ctb], Simon Papalexiou [ctb], Martin Hanel [ctb]
Maintainer: Yannis Markonis <imarkonis@gmail.com>
Repository: CRAN
Date/Publication: 2020-05-16 09:50:09 UTC

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New package crandep with initial version 0.0.1
Package: crandep
Title: Network Analysis of Dependencies of CRAN Packages
Version: 0.0.1
Authors@R: person("Clement", "Lee", email = "clement.lee.tm@outlook.com", role = c("aut", "cre"))
Description: The dependencies of CRAN packages can be analysed in a network fashion. Through scrapping the page of a package on CRAN, we can obtain the packages that it depends, imports, suggests, etc. By iterating this procedure over a number of packages, we can build the dependency network and represent it by a graph object, most easily through the 'igraph' package. Subsequently, the dependency network can be visualised and analysed using social network analysis methods, enabling us to have a bird's-eye view of the CRAN ecosystem.
Depends: R (>= 3.4)
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Imports: xml2, rvest, stringr, dplyr, igraph
Suggests: ggplot2, tibble, knitr, rmarkdown
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2020-05-12 14:02:31 UTC; clement_lee
Author: Clement Lee [aut, cre]
Maintainer: Clement Lee <clement.lee.tm@outlook.com>
VignetteBuilder: knitr
Repository: CRAN
Date/Publication: 2020-05-16 09:50:12 UTC

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New package AdhereRViz with initial version 0.1.0
Package: AdhereRViz
Type: Package
Title: Interactive Visualisation of Medication Adherence Patterns
Version: 0.1.0
Authors@R: c(person("Dan", "Dediu", role = c("aut", "cre"), email = "ddediu@gmail.com"), person("Alexandra", "Dima", role = "aut", email = "alexadima@gmail.com"), person("Samuel", "Allemann", role = "aut", email = "samuel.allemann@gmx.ch"))
Author: Dan Dediu [aut, cre], Alexandra Dima [aut], Samuel Allemann [aut]
Maintainer: Dan Dediu <ddediu@gmail.com>
Description: Interactive graphical user interface (GUI) for the package 'AdhereR', allowing the user to access different data sources, to explore the patterns of medication use therein, and the computation of various measures of adherence. It is implemented using Shiny and HTML/CSS/JavaScript.
URL: https://github.com/ddediu/AdhereR
License: GPL (>= 2)
LazyData: TRUE
RoxygenNote: 7.1.0
Imports: AdhereR (>= 0.6), lubridate (>= 1.5), parallel (>= 3.0), data.table (>= 1.9), manipulate (>= 1.0), shiny (>= 1.0), shinyWidgets (>= 0.4.4), shinyjs (>= 1.0), V8 (>= 1.5), colourpicker (>= 1.0), viridisLite(>= 0.3), highlight (>= 0.4), clipr (>= 0.4), knitr (>= 1.20), readODS (>= 1.6), readxl (>= 1.2), haven (>= 2.0), DBI (>= 1.0), RMariaDB (>= 1.0.5), RSQLite (>= 2.1), scales (>= 1.0), rsvg (>= 1.3)
Depends: R (>= 3.0)
Suggests: rmarkdown (>= 1.1), R.rsp (>= 0.40)
VignetteBuilder: knitr, R.rsp
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2020-05-12 12:14:41 UTC; ddediu
Repository: CRAN
Date/Publication: 2020-05-16 09:30:14 UTC

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Fri, 15 May 2020

New package swissdd with initial version 1.0.3
Package: swissdd
Type: Package
Title: Get Swiss Federal and Cantonal Vote Results from Opendata.swiss
Version: 1.0.3
Authors@R: c( person("Thomas", "Lo Russo", email = "th.lorusso@gmail.com", role = c("cre","aut")), person("Thomas", "Willi", email = "thomas.willi@uzh.ch", role = "aut"))
Description: Builds upon the real time data service as well as the archive for national votes <https://opendata.swiss/api/3/action/package_show?id=echtzeitdaten-am-abstimmungstag-zu-eidgenoessischen-abstimmungsvorlagen> and cantonal votes <https://opendata.swiss/api/3/action/package_show?id=echtzeitdaten-am-abstimmungstag-zu-kantonalen-abstimmungsvorlagen>. It brings the results of Swiss popular votes, aggregated at the geographical level of choice, into R. Additionally, it allows to retrieve data from the Swissvotes-Database, one of the most comprehensive data platforms on Swiss referendums and initiatives <https://swissvotes.ch/page/dataset/swissvotes_dataset.csv>.
Imports: purrr, dplyr, tidyr (>= 1.0.0), jsonlite, magrittr, tibble, curl
URL: https://github.com/politanch/swissdd
BugReports: https://github.com/politanch/swissdd/issues
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2020-05-12 08:54:05 UTC; tlo1
Author: Thomas Lo Russo [cre, aut], Thomas Willi [aut]
Maintainer: Thomas Lo Russo <th.lorusso@gmail.com>
Repository: CRAN
Date/Publication: 2020-05-15 14:30:02 UTC

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New package ChannelAttributionApp with initial version 1.2
Package: ChannelAttributionApp
Type: Package
Title: Shiny Web Application for the Multichannel Attribution Problem
Version: 1.2
Date: 2020-05-13
Author: Davide Altomare
Maintainer: Davide Altomare <davide.altomare@gmail.com>
Description: Shiny Web Application for the Multichannel Attribution Problem. It is a user-friendly graphical interface for package 'ChannelAttribution'.
License: GPL (>= 2)
URL: http://www.slideshare.net/adavide1982/markov-model-for-the-multichannel-attribution-problem
Imports: ChannelAttribution, shiny, data.table, ggplot2, utils
LazyData: TRUE
NeedsCompilation: no
Packaged: 2020-05-13 20:52:24 UTC; a458057
Repository: CRAN
Date/Publication: 2020-05-15 14:10:09 UTC

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Thu, 14 May 2020

New package bootnet with initial version 1.4.1
Package: bootnet
Type: Package
Title: Bootstrap Methods for Various Network Estimation Routines
Version: 1.4.1
Authors@R: c( person("Sacha", "Epskamp", email = "mail@sachaepskamp.com",role = c("aut", "cre")), person("Eiko I.", "Fried", role = c("ctb")) )
Maintainer: Sacha Epskamp <mail@sachaepskamp.com>
Depends: ggplot2, R (>= 3.0.0)
Imports: methods, igraph, IsingFit, qgraph, dplyr (>= 0.3.0.2), tidyr, gtools, corpcor, IsingSampler, mvtnorm, abind, Matrix, parallel, huge, mgm (>= 1.2), relaimpo, NetworkToolbox (>= 1.1.0), pbapply, graphicalVAR, BDgraph, psychTools, networktools, lavaan, glasso
Description: Bootstrap methods to assess accuracy and stability of estimated network structures and centrality indices <doi:10.3758/s13428-017-0862-1>. Allows for flexible specification of any undirected network estimation procedure in R, and offers default sets for various estimation routines.
License: GPL-2
NeedsCompilation: no
Packaged: 2020-05-15 03:41:19 UTC; ripley
Author: Sacha Epskamp [aut, cre], Eiko I. Fried [ctb]
Repository: CRAN
Date/Publication: 2020-05-15 03:51:01 UTC

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New package dashTable with initial version 4.7.0
Package: dashTable
Title: Core Interactive Table Component for 'dash'
Version: 4.7.0
Description: An interactive table component designed for editing and exploring large datasets, 'dashDataTable' is rendered with standard, semantic HTML <table/> markup, which makes it accessible, responsive, and easy to style. This component was written from scratch in 'React.js' specifically for the 'dash' community. Its API was designed to be ergonomic and its behaviour is completely customizable through its properties.
Depends: R (>= 3.0.2)
Imports:
Suggests: dash, dashHtmlComponents
Authors@R: c(person("Chris", "Parmer", email = "chris@plotly.com", role = c("aut")), person("Ryan Patrick", "Kyle", email = "ryan@plotly.com", role = c("cre"), comment = c(ORCID = "0000-0001-5829-9867")), person(family = "Plotly Technologies, Inc.", role = "cph"))
License: MIT + file LICENSE
Copyright: Plotly Technologies, Inc.
URL: https://github.com/plotly/dash-table
BugReports: https://github.com/plotly/dash-table/issues
Encoding: UTF-8
LazyData: true
KeepSource: true
NeedsCompilation: no
Packaged: 2020-05-14 05:04:34 UTC; rpkyle
Author: Chris Parmer [aut], Ryan Patrick Kyle [cre] (<https://orcid.org/0000-0001-5829-9867>), Plotly Technologies, Inc. [cph]
Maintainer: Ryan Patrick Kyle <ryan@plotly.com>
Repository: CRAN
Date/Publication: 2020-05-14 17:20:03 UTC

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New package compstatr with initial version 0.2.1
Package: compstatr
Type: Package
Title: Tools for St. Louis Crime Data
Version: 0.2.1
Authors@R: c( person("Christopher", "Prener", ,"chris.prener@slu.edu", c("aut", "cre")), person("Cree", "Foeller", ,"cree.foeller@slu.edu", c("aut")), person("Taylor", "Braswell", , , c("com")) )
Description: Provides a set of tools for creating yearly data sets of St. Louis Metropolitan Police Department (SLMPD) crime data, which are available from January 2008 onward as monthly CSV releases on their website (<http:www.slmpd.org/Crimereports.shtml>). Once data are validated and created (monthly data releases have varying numbers of columns as well as different column names and formats), 'compstatr' also provides functions for categorizing and mapping crimes in St. Louis. The categorization tools that are provided will also work with any police department that uses 5 and 6 digit numeric codes to identify specific crimes. These data provide researchers and policy makers detailed data for St. Louis, which in the last several years has had some of the highest or the highest violent crime rates in the United States.
Depends: R (>= 3.4)
License: GPL-3
URL: https://github.com/slu-openGIS/compstatr
BugReports: https://github.com/slu-openGIS/compstatr
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
Imports: dplyr, fs, httr, janitor, lubridate, purrr, rlang, readr, rvest, sf, stringr, tibble, tidyr, xml2
Suggests: testthat, knitr, rmarkdown, covr
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-05-13 15:26:32 UTC; prenercg
Author: Christopher Prener [aut, cre], Cree Foeller [aut], Taylor Braswell [com]
Maintainer: Christopher Prener <chris.prener@slu.edu>
Repository: CRAN
Date/Publication: 2020-05-14 17:30:08 UTC

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New package wbsd with initial version 1.0.0
Package: wbsd
Type: Package
Title: Wild Bootstrap Size Diagnostics
Version: 1.0.0
Date: 2020-05-11
Author: David Preinerstorfer
Maintainer: David Preinerstorfer <david.preinerstorfer@ulb.be>
Description: Implements the diagnostic "theta" developed in Poetscher and Preinerstorfer (2020) "How Reliable are Bootstrap-based Heteroskedasticity Robust Tests?" <arXiv:2005.04089>. This diagnostic can be used to detect and weed out bootstrap-based procedures that provably have size equal to one for a given testing problem. The implementation covers a large variety of bootstrap-based procedures, cf. the above mentioned article for details. A function for computing bootstrap p-values is provided.
License: GPL-2
Imports: methods, stats, Rcpp
LinkingTo: Rcpp, RcppEigen
NeedsCompilation: yes
Packaged: 2020-05-11 14:46:29 UTC; Administrator
Repository: CRAN
Date/Publication: 2020-05-14 08:30:02 UTC

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New package rtodoist with initial version 0.1.0
Package: rtodoist
Title: Create and Manage Todolist using 'Todoist.com' API
Version: 0.1.0
Authors@R: c(person(given = "Cervan", family = "Girard", role = c("cre","aut"), email = "cervan@thinkr.fr", comment = c(ORCID = "0000-0002-4816-4624")), person(given = "Vincent", family = "Guyader", role = "aut", email = "vincent@thinkr.fr", comment = c(ORCID = "0000-0003-0671-9270")), person(given = "ThinkR", role = c("cph", "fnd")))
Description: Allows you to interact with the API of the "Todoist" platform. 'Todoist' <https://todoist.com/> provides an online task manager service for teams.
License: MIT + file LICENSE
Depends: R (>= 3.5.0)
Imports: digest, dplyr, getPass, glue, httr, keyring, magrittr, purrr, utils
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
URL: https://github.com/ThinkR-open/rtodoist
BugReports: https://github.com/ThinkR-open/rtodoist/issues
NeedsCompilation: no
Packaged: 2020-05-11 15:21:20 UTC; cervan
Author: Cervan Girard [cre, aut] (<https://orcid.org/0000-0002-4816-4624>), Vincent Guyader [aut] (<https://orcid.org/0000-0003-0671-9270>), ThinkR [cph, fnd]
Maintainer: Cervan Girard <cervan@thinkr.fr>
Repository: CRAN
Date/Publication: 2020-05-14 08:40:02 UTC

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New package RSqlParser with initial version 1.5
Package: RSqlParser
Type: Package
Title: Parse 'SQL' Statements
Version: 1.5
Author: Subhasree Bose
Maintainer: Subhasree Bose <subhasree10.7@gmail.com>
Description: Parser for 'SQL' statements. Currently, it supports parsing of only 'SELECT' statements.
License: GPL-2
Imports: stringr,stringi
Depends: R (>= 2.1.0)
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
Suggests: knitr, rmarkdown,testthat
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-05-11 15:28:25 UTC; Subhasree
Repository: CRAN
Date/Publication: 2020-05-14 08:40:06 UTC

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Wed, 13 May 2020

New package simode with initial version 1.1.9
Package: simode
Type: Package
Title: Statistical Inference for Systems of Ordinary Differential Equations using Separable Integral-Matching
Version: 1.1.9
Authors@R: c( person("Itai", "Dattner", email = "idattner@stat.haifa.ac.il", role = "aut"), person("Rami", "Yaari", email = "ramiyaari@gmail.com", role = c("aut", "cre")))
Description: Implements statistical inference for systems of ordinary differential equations, that uses the integral-matching criterion and takes advantage of the separability of parameters, in order to obtain initial parameter estimates for nonlinear least squares optimization. Dattner & Yaari (2018) <arXiv:1807.04202>. Dattner et al. (2017) <doi:10.1098/rsif.2016.0525>. Dattner & Klaassen (2015) <doi:10.1214/15-EJS1053>.
Depends: R (>= 3.4.0)
Imports: deSolve, pracma, quadprog
Suggests: parallel, Rcgmin, Rvmmin, R.rsp, knitr, testthat
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
VignetteBuilder: R.rsp
NeedsCompilation: no
Packaged: 2020-05-13 13:51:59 UTC; Owner
Author: Itai Dattner [aut], Rami Yaari [aut, cre]
Maintainer: Rami Yaari <ramiyaari@gmail.com>
Repository: CRAN
Date/Publication: 2020-05-13 23:30:02 UTC

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New package TransPhylo with initial version 1.4.2
Package: TransPhylo
Version: 1.4.2
Date: 2020-05-11
Title: Inference of Transmission Tree from a Dated Phylogeny
Authors@R: c(person("Xavier","Didelot", email="xavier.didelot@gmail.com", comment = c(ORCID = "0000-0003-1885-500X"), role=c("aut", "cre")), person("Yuanwei", "Xu", email = "y.xu@bham.ac.uk", role = c("ctb")))
Maintainer: Xavier Didelot <xavier.didelot@gmail.com>
Description: Inference of transmission tree from a dated phylogeny. Includes methods to simulate and analyse outbreaks. The methodology is described in Didelot et al. (2014) <doi:10.1093/molbev/msu121>, Didelot et al. (2017) <doi:10.1093/molbev/msw275>.
License: GPL (>= 2)
Depends: R (>= 3.0.0)
Imports: Rcpp (>= 0.12.8), stats, graphics, ape
Suggests: knitr, testthat, purrr, coda, grDevices, lattice
LinkingTo: Rcpp
Encoding: UTF-8
RoxygenNote: 6.1.1
SystemRequirements: C++11
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2020-05-11 14:46:12 UTC; Xavier
Author: Xavier Didelot [aut, cre] (<https://orcid.org/0000-0003-1885-500X>), Yuanwei Xu [ctb]
Repository: CRAN
Date/Publication: 2020-05-13 16:00:07 UTC

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New package tabshiftr with initial version 0.1.2
Package: tabshiftr
Title: Reshape Disorganised Messy Data
Version: 0.1.2
Authors@R: c( person("Steffen", "Ehrmann", email = "steffen@funroll-loops.de", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-2958-0796")), person("Abdualmaged", "Alhemiary", role = c("ctb")), person("Amelie", "Haas", role = c("ctb")), person("Annika", "Ertel", role = c("ctb")), person("Arne", "Rümmler", email = "arne.ruemmler@tu-dresden.de", role = c("ctb"), comment = c(ORCID = "0000-0001-8637-9071")) )
Description: Helps the user to build and register schema descriptions of disorganised (messy) tables. Disorganised tables are tables that are not in a topologically coherent form, where packages such as 'tidyr' could be used for reshaping. The schema description documents the arrangement of input tables and is used to reshape them into a standardised (tidy) output format.
URL: https://github.com/EhrmannS/tabshiftr
BugReports: https://github.com/EhrmannS/tabshiftr/issues
Depends: R (>= 2.10)
Language: en-gb
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: checkmate, rlang, tibble, dplyr, tidyr, magrittr, tidyselect, testthat, crayon, methods, purrr, stringr
RoxygenNote: 7.1.0
Suggests: knitr, rmarkdown, bookdown, readr, covr
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-05-11 13:27:19 UTC; se87kuhe
Author: Steffen Ehrmann [aut, cre] (<https://orcid.org/0000-0002-2958-0796>), Abdualmaged Alhemiary [ctb], Amelie Haas [ctb], Annika Ertel [ctb], Arne Rümmler [ctb] (<https://orcid.org/0000-0001-8637-9071>)
Maintainer: Steffen Ehrmann <steffen@funroll-loops.de>
Repository: CRAN
Date/Publication: 2020-05-13 15:10:02 UTC

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New package PASSED with initial version 1.0-1
Package: PASSED
Title: Calculate Power and Sample Size for Two Sample Mean Tests
Version: 1.0-1
Date: 2020-05-04
Authors@R: c(person("Jinpu", "Li", email = "lijinp@health.missouri.edu", role = c("aut", "cre")), person("Ryan", "Knigge", email = "rknigge@health.missouri.edu", role = "aut"), person("Emily", "Leary", email = "LearyE@health.missouri.edu", role = "aut"))
Description: Power calculations are a critical component of any research study to determine the minimum sample size necessary to detect differences between multiple groups. Here we present an 'R' package, 'PASSED', that performs power and sample size calculations for the test of two-sample means or ratios with data following beta, gamma (Chang et al. (2011), <doi:10.1007/s00180-010-0209-1>), normal, Poisson (Gu et al. (2008), <doi:10.1002/bimj.200710403>), binomial, geometric, and negative binomial (Zhu and Lakkis (2014), <doi:10.1002/sim.5947>) distributions.
Depends: R (>= 3.6)
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
Imports: betareg, stats, rootSolve, MESS
Suggests: knitr, rmarkdown, MKmisc
NeedsCompilation: no
Packaged: 2020-05-11 18:27:33 UTC; birdn
Author: Jinpu Li [aut, cre], Ryan Knigge [aut], Emily Leary [aut]
Maintainer: Jinpu Li <lijinp@health.missouri.edu>
Repository: CRAN
Date/Publication: 2020-05-13 15:40:02 UTC

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New package ORdensity with initial version 1.0
Package: ORdensity
Type: Package
Title: Identification of Differentially Expressed Genes
Version: 1.0
Author: José María Martínez Otzeta, Concepción Arenas, Basilio Sierra, Itziar Irigoien
Maintainer: José María Martínez Otzeta <josemaria.martinezo@ehu.eus>
Description: Automated discovery of differentially expressed genes. The method (called ORdensity) is composed of two phases: discovering potential differentially expressed genes and recognizing differentially expressed genes. It makes use of a permutation resampling procedure to build outlying and density indexes. References: a) Irigoien, I. and Arenas, C. (2018). "Identification of differentially expressed genes by means of outlier detection". <doi:10.1186/s12859-018-2318-8>. b) Martínez-Otzeta, J. M., Irigoien, I., Sierra, B., and Arenas, C. (2020). "ORdensity: user-friendly R package to identify differentially expressed genes". <doi:10.1186/s12859-020-3463-4>.
Depends: R (>= 2.10)
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
Imports: cluster, distances, Rfast, plyr, methods, foreach, doRNG, parallel, doParallel
NeedsCompilation: no
Packaged: 2020-05-11 16:15:59 UTC; paxpan
Repository: CRAN
Date/Publication: 2020-05-13 14:40:02 UTC

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New package mosaic.find with initial version 0.1.0
Package: mosaic.find
Type: Package
Title: Finding Rhythmic and Non-Rhythmic Trends in Multi-Omics Data (MOSAIC)
Version: 0.1.0
Authors@R: c(person("Hannah", "De los Santos", email = "delosh@rpi.edu", role = c("aut", "cre", "cph")), person("Kristin", "Bennett", role = c("aut")), person("Jennifer", "Hurley", role = c("aut")), person("R Development Core Team", role = c("aut")))
Maintainer: Hannah De los Santos <delosh@rpi.edu>
Description: Provides a function (mosaic_find()) designed to find rhythmic and non-rhythmic trends in multi-omics time course data using model selection and joint modeling, a method called MOSAIC (Multi-Omics Selection with Amplitude Independent Criteria). For more information, see H. De los Santos et al. (2020) <doi:10.1101/2020.04.27.064147>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
URL: https://github.com/delosh653/MOSAIC
Depends: R (>= 2.10)
Imports: minpack.lm (>= 1.2.1)
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown, ggplot2
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-05-11 15:32:25 UTC; delosh
Author: Hannah De los Santos [aut, cre, cph], Kristin Bennett [aut], Jennifer Hurley [aut], R Development Core Team [aut]
Repository: CRAN
Date/Publication: 2020-05-13 14:20:02 UTC

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New package hettreatreg with initial version 0.1.0
Package: hettreatreg
Type: Package
Title: Heterogeneous Treatment Effects in Regression Analysis
Version: 0.1.0
Authors@R: c( person("Tymon", "Sloczynski", role = c("aut"), email = "tslocz@brandeis.edu"), person("Mark", "McAvoy", role = c("cre"), email = "mcavoy@brandeis.edu"))
Description: Computes diagnostics for linear regression when treatment effects are heterogeneous. The output of 'hettreatreg' represents ordinary least squares (OLS) estimates of the effect of a binary treatment as a weighted average of the average treatment effect on the treated (ATT) and the average treatment effect on the untreated (ATU). The program estimates the OLS weights on these parameters, computes the associated model diagnostics, and reports the implicit OLS estimate of the average treatment effect (ATE). See Sloczynski (2019), <http://people.brandeis.edu/~tslocz/Sloczynski_paper_regression.pdf>.
URL: https://github.com/tslocz/hettreatreg
Depends: R (>= 3.1)
Imports: stats
License: GPL-2
Encoding: UTF-8
LazyData: TRUE
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-05-11 17:27:20 UTC; Maple
Author: Tymon Sloczynski [aut], Mark McAvoy [cre]
Maintainer: Mark McAvoy <mcavoy@brandeis.edu>
Repository: CRAN
Date/Publication: 2020-05-13 14:50:10 UTC

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New package FSK2R with initial version 0.1.1
Package: FSK2R
Type: Package
Title: An Interface Between the 'FSK-ML' Standard and 'R'
Version: 0.1.1
Authors@R: c(person("Alberto", "Garre", email = "garre.alberto@gmail.com", role = c("aut", "cre")), person("Miguel", "de Alba Aparicio", email = "Miguel.de-Alba-Aparicio@bfr.bund.de", role = "aut"), person("Pablo S.", "Fernandez", email = "pablo.fernandez@upct.es", role = "aut"), person("Matthias", "Filter", email = "Matthias.Filter@bfr.bund.de", role = "aut") )
Description: Functions for importing, creating, editing and exporting 'FSK' files <https://foodrisklabs.bfr.bund.de/fsk-ml-food-safety-knowledge-markup-language/> using the 'R' programming environment. Furthermore, it enables users to run simulations contained in the 'FSK' files and visualize the results.
License: GPL-3
Encoding: UTF-8
Imports: XML (>= 3.98), purrr (>= 0.2.4), dplyr (>= 0.7.8), tibble (>= 2.0.0), tidyr (>= 0.7.2), rlang (>= 0.3.0.1), googlesheets (>= 0.3.0), stringr (>= 1.4.0), readxl (>= 1.3.1), readtext (>= 0.7.1), zip (>= 2.0.4), xml2 (>= 1.2.0), rjson (>= 0.2.20), shiny (>= 1.3.2), tools (>= 3.5.3), utils (>= 3.5.3), R.utils (>= 2.9.0)
Suggests: knitr (>= 1.9), rmarkdown (>= 1.12), testthat
VignetteBuilder: knitr
LazyData: true
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-05-11 12:26:02 UTC; alberto
Author: Alberto Garre [aut, cre], Miguel de Alba Aparicio [aut], Pablo S. Fernandez [aut], Matthias Filter [aut]
Maintainer: Alberto Garre <garre.alberto@gmail.com>
Repository: CRAN
Date/Publication: 2020-05-13 15:00:02 UTC

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New package immunarch with initial version 0.6.4
Package: immunarch
Type: Package
Title: Bioinformatics Analysis of T-Cell and B-Cell Immune Repertoires
Version: 0.6.4
Authors@R: c( person("Vadim I.", "Nazarov", , "vdm.nazarov@gmail.com", c("aut", "cre")), person("Vasily O.", "Tsvetkov", , role = "aut"), person("Eugene", "Rumynskiy", , role = "aut"), person("Anna", "Lorenc", , role = "aut"), person("Daniel J.", "Moore", , role = "aut"), person("Victor", "Greiff", , role = "aut"), person("ImmunoMind", role = c("cph", "fnd")) )
Contact: support@immunomind.io
Description: A comprehensive framework for bioinformatics analysis of bulk and single-cell T-cell receptor and antibody repertoires. It provides seamless data loading, analysis and visualisation for AIRR (Adaptive Immune Receptor Repertoire) data, both bulk immunosequencing (RepSeq) and single-cell sequencing (scRNAseq). It implements most of the widely used AIRR analysis methods, such as: clonality analysis, estimation of repertoire similarities in distribution of clonotypes and gene segments, repertoire diversity analysis, annotation of clonotypes using external immune receptor databases and clonotype tracking in vaccination and cancer studies. A successor to our previously published 'tcR' immunoinformatics package (Nazarov 2015) <doi:10.1186/s12859-015-0613-1>.
License: AGPL-3
URL: https://immunarch.com/, https://github.com/immunomind/immunarch
BugReports: https://github.com/immunomind/immunarch/issues
Imports: pheatmap (>= 1.0.12), ggrepel (>= 0.8.0), reshape2 (>= 1.4.2), factoextra (>= 1.0.4), fpc, circlize, MASS (>= 7.3), Rtsne (>= 0.15), readr (>= 1.3.1), readxl (>= 1.3.1), shiny (>= 1.4.0), shinythemes, treemap, airr, ggseqlogo, UpSetR (>= 1.4.0), stringr (>= 1.4.0), ggalluvial (>= 0.10.0), Rcpp (>= 1.0), magrittr, tibble (>= 2.0), methods, scales, ggpubr (>= 0.2), rlang (>= 0.4), plyr, dbplyr (>= 1.4.0)
Depends: R (>= 3.5.0), ggplot2 (>= 3.1.0), dplyr (>= 0.8.0), dtplyr (>= 1.0.0), data.table (>= 1.12.6), gridExtra (>= 2.2.1)
LinkingTo: Rcpp
Suggests: knitr (>= 1.8), roxygen2 (>= 3.0.0), testthat (>= 2.1.0), pkgdown (>= 0.1.0), assertthat
VignetteBuilder: knitr
Encoding: UTF-8
RoxygenNote: 7.1.0
LazyData: true
NeedsCompilation: yes
Packaged: 2020-05-10 23:13:39 UTC; vdn
Author: Vadim I. Nazarov [aut, cre], Vasily O. Tsvetkov [aut], Eugene Rumynskiy [aut], Anna Lorenc [aut], Daniel J. Moore [aut], Victor Greiff [aut], ImmunoMind [cph, fnd]
Maintainer: Vadim I. Nazarov <vdm.nazarov@gmail.com>
Repository: CRAN
Date/Publication: 2020-05-13 08:00:02 UTC

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Tue, 12 May 2020

New package MRReg with initial version 0.1.1
Package: MRReg
Title: MDL Multiresolution Linear Regression Framework
Version: 0.1.1
Authors@R: person(given = "Chainarong", family = "Amornbunchornvej", role = c("aut", "cre"), email = "grandca@gmail.com", comment = c(ORCID = "0000-0003-3131-0370"))
Maintainer: Chainarong Amornbunchornvej <grandca@gmail.com>
Description: We provide the framework to analyze multiresolution partitions (e.g. country, provinces, subdistrict) where each individual data point belongs to only one partition in each layer (e.g. i belongs to subdistrict A, province P, and country Q). We assume that a partition in a higher layer subsumes lower-layer partitions (e.g. a nation is at the 1st layer subsumes all provinces at the 2nd layer). Given N individuals that have a pair of real values (x,y) that generated from independent variable X and dependent variable Y. Each individual i belongs to one partition per layer. Our goal is to find which partitions at which highest level that all individuals in the these partitions share the same linear model Y=f(X) where f is a linear function. The framework deploys the Minimum Description Length principle (MDL) to infer solutions. The publication of this package is at Chainarong Amornbunchornvej, Navaporn Surasvadi, Anon Plangprasopchok, and Suttipong Thajchayapong (2019) <arXiv:1907.05234>.
License: MIT + file LICENSE
URL: https://github.com/DarkEyes/MRReg
BugReports: https://github.com/DarkEyes/MRReg/issues
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.5.0), caret
Imports: igraph, ggplot2 (>= 3.0)
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-05-11 07:14:50 UTC; sai
Author: Chainarong Amornbunchornvej [aut, cre] (<https://orcid.org/0000-0003-3131-0370>)
Repository: CRAN
Date/Publication: 2020-05-12 14:30:02 UTC

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New package rKolada with initial version 0.1.2
Package: rKolada
Type: Package
Title: Access Data from the 'Kolada' Database in R
Version: 0.1.2
Authors@R: person("Love", "Hansson", email = "love.hansson@gmail.com", role = c("aut", "cre"))
Maintainer: Love Hansson <love.hansson@gmail.com>
Description: Methods for downloading and processing data and metadata from 'Kolada', the official Swedish regions and municipalities database.
License: AGPL-3
Encoding: UTF-8
LazyData: true
Suggests: testthat, knitr, rmarkdown, scales
RoxygenNote: 7.1.0
Imports: tibble, dplyr, glue, stringr, httr, jsonlite, magrittr, tidyr, purrr, stringi, ggplot2, rlang
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-05-10 19:45:20 UTC; love
Author: Love Hansson [aut, cre]
Repository: CRAN
Date/Publication: 2020-05-12 13:50:02 UTC

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New package match2C with initial version 0.1.0
Package: match2C
Type: Package
Title: Match One Sample using Two Criteria
Version: 0.1.0
Author: Bo Zhang
Maintainer: Bo Zhang <bozhan@wharton.upenn.edu>
Description: Multivariate matching in observational studies typically has two goals: 1. to construct treated and control groups that have similar distribution of observed covariates and 2. to produce matched pairs or sets that are homogeneous in a few priority variables. This packages implements a network-based method built around a tripartite graph that can simultaneously achieve both goals. A detailed 'RMarkdown' tutorial can be found at <https://github.com/bzhangupenn/match2C/tree/master/tutorial>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
Imports: mvnfast, stats, rcbalance, Rcpp (>= 1.0.3), utils
Suggests: optmatch
LinkingTo: Rcpp
NeedsCompilation: yes
Packaged: 2020-05-10 19:24:48 UTC; zhangb22
Repository: CRAN
Date/Publication: 2020-05-12 13:40:03 UTC

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New package airt with initial version 0.1.0
Package: airt
Type: Package
Title: Evaluation of Algorithm Collections Using Item Response Theory
Version: 0.1.0
Authors@R: person("Sevvandi", "Kandanaarachchi", email = "sevvandik@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-0337-0395"))
Maintainer: Sevvandi Kandanaarachchi <sevvandik@gmail.com>
Description: An evaluation framework for algorithm portfolios using Item Response Theory (IRT). We use polytomous IRT models to evaluate algorithms and introduce algorithm characteristics such as stability, effectiveness and anomalousness (Kandanaarachchi, Smith-Miles 2020) <doi:10.13140/RG.2.2.11363.09760>.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Depends: R (>= 3.4.0)
Imports: pracma, mirt, tidyr
Suggests: knitr, rmarkdown, ggplot2
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-05-11 04:31:33 UTC; Sevvandi
Author: Sevvandi Kandanaarachchi [aut, cre] (<https://orcid.org/0000-0002-0337-0395>)
Repository: CRAN
Date/Publication: 2020-05-12 14:00:02 UTC

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New package shinyreforms with initial version 0.0.1
Package: shinyreforms
Title: Add Forms to your 'Shiny' App
Version: 0.0.1
Author: Piotr Bajger <piotr.bajger@hotmail.com>
Maintainer: Piotr Bajger <piotr.bajger@hotmail.com>
Description: Allows to create modular, reusable 'HTML' forms which can be embedded in your 'shiny' app with minimal effort. Features include conditional code execution on form submission, automatic input validation and input tooltips.
URL: https://github.com/piotrbajger/shinyreforms
Depends: R (>= 3.0)
License: GPL-3
Imports: shiny (>= 1.0.0), htmltools (>= 0.2.6), R6
Suggests: testthat, knitr, rmarkdown
VignetteBuilder: knitr
BugReports: https://github.com/piotrbajger/shinyreforms
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-05-09 11:12:05 UTC; piotrbajger
Repository: CRAN
Date/Publication: 2020-05-12 10:10:03 UTC

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New package shinyobjects with initial version 0.1.0
Package: shinyobjects
Title: Access Reactive Data Interactively
Version: 0.1.0
Authors@R: person("Jake", "Riley", email = "rjake@sas.upenn.edu", role = c("aut", "cre"))
Description: Troubleshooting reactive data in 'shiny' can be difficult. These functions will convert reactive data frames into functions and load all assigned objects into your local environment. If you create a dummy input object, as the function will suggest, you will be able to test your server and ui functions interactively.
BugReports: https://github.com/rjake/shinyobjects/issues
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
Imports: dplyr, glue, knitr, magrittr, pander, readr, rstudioapi, shiny, stringr, styler, tibble, tidyr
VignetteBuilder: knitr
Suggests: rmarkdown, testthat, mockery, spelling, covr
Language: en-US
NeedsCompilation: no
Packaged: 2020-05-10 03:28:22 UTC; foxtr
Author: Jake Riley [aut, cre]
Maintainer: Jake Riley <rjake@sas.upenn.edu>
Repository: CRAN
Date/Publication: 2020-05-12 10:40:02 UTC

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New package RolWinMulCor with initial version 0.1.0
Package: RolWinMulCor
Type: Package
Title: Subroutines to Estimate Rolling Window Multiple Correlation
Version: 0.1.0
Authors@R: c(person("Josue M.", "Polanco-Martinez", role = c("aut", "cph", "cre"), email = "josue.m.polanco@gmail.com"))
Author: Josue M. Polanco-Martinez [aut, cph, cre]
Maintainer: Josue M. Polanco-Martinez <josue.m.polanco@gmail.com>
Depends: R (>= 3.5.0), stats, gtools, pracma, colorspace
Description: Rolling Window Multiple Correlation ('RolWinMulCor') estimates the rolling (running) window correlation for the bi- and multi-variate cases between regular (sampled on identical time points) time series, with especial emphasis to environmental data (although this can be applied to other kinds of data sets). 'RolWinMulCor' is based on the concept of rolling or running window and is useful to evaluate the evolution of correlation through time and time-scales. 'RolWinMulCor' contains four functions: (1) the first two functions are focus on the bi-variate case and one of them produces a simple plot of correlation coefficients and p-values (<=0.05)for only one window-length (time-scale) and the other function produces a heat map for the statistically significant (p-values <=0.05) correlation coefficients taking into account all the possible window-lengths (which are determined by the number of elements of the time series under analysis) or for a band of window-lengths; (2) the second two functions are designed to analyse the multi-variate case and follow the bi-variate case to display visually the results. The four functions contained in 'RolWinMulCor' are highly flexible since this contains a great number of parameters to control the estimation of correlation and the features of the plot output, e.g. to remove the (linear) trend contained in the time series under analysis, to choose different p-value correction methods (which are used to address the multiple comparison problem) or to personalise the plot output (e.g. this can be displayed in the screen or can be saved as PNG, JPEG, EPS or PDF formats). The 'RolWinMulCor' package also provides examples with synthetic and real environmental time series to exemplify its use. Methods derived from H. Abdi. (2007) <https://personal.utdallas.edu/~herve/Abdi-MCC2007-pretty.pdf>, J. M. Polanco-Martinez (2019) <doi:10.1007/s11071-019-04974-y>, and R. Telford (2013) <https://quantpalaeo.wordpress.com/2013/01/04/running-correlations-running-into-problems/>.
License: GPL (>= 2)
Repository: CRAN
Encoding: UTF-8
LazyData: true
Date/Publication: 2020-05-12 10:10:12 UTC
NeedsCompilation: no
Packaged: 2020-05-09 11:12:05 UTC; jomopo

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New package ProcData with initial version 0.2.5
Package: ProcData
Type: Package
Title: Process Data Analysis
Version: 0.2.5
Date: 2020-05-08
Authors@R: c( person("Xueying", "Tang", email = "xueyingtang1989@gmail.com", role = c("aut", "cre")), person("Susu", "Zhang", email = "susu.zhang1992@gmail.com", role = c("aut")), person("Zhi", "Wang", email = "zhiwpku@gmail.com", role=c("aut")), person("Jingchen", "Liu", email = "jcliu@stat.columbia.edu", role=c("aut")), person("Zhiliang", "Ying", email = "zying@stat.columbia.edu", role=c("aut")))
Description: General tools for exploratory process data analysis. Process data refers to the data describing participants' problem solving processes in computer-based assessments. It is often recorded in computer log files. This package provides two action sequence generators and implements two automatic feature extraction methods that compress the information stored in process data, which often has a nonstandard format, into standard numerical vectors. This package also provides recurrent neural network based models that relate response processes with other binary or scale variables of interest. The functions that involve training and evaluating neural networks are wrappers of functions in 'keras'.
BugReports: https://github.com/xytangtang/ProcData/issues
License: GPL (>= 2)
Depends: R (>= 3.5)
Imports: Rcpp (>= 0.12.16), keras (>= 2.2.4)
LinkingTo: Rcpp
SystemRequirements: Python (>= 2.7)
RoxygenNote: 6.1.1
LazyData: true
NeedsCompilation: yes
Packaged: 2020-05-09 03:25:06 UTC; xueyingtang
Author: Xueying Tang [aut, cre], Susu Zhang [aut], Zhi Wang [aut], Jingchen Liu [aut], Zhiliang Ying [aut]
Maintainer: Xueying Tang <xueyingtang1989@gmail.com>
Repository: CRAN
Date/Publication: 2020-05-12 10:10:15 UTC

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New package iNZightTS with initial version 1.5.2
Package: iNZightTS
Type: Package
Title: Time Series for 'iNZight'
Version: 1.5.2
Authors@R: c( person("Tom", "Elliott", role = c("aut", "cre"), email = "tom.elliott@auckland.ac.nz", comment = c(ORCID = "0000-0002-7815-6318")), person("Junjie", "Zeng", role = "aut"), person("Simon", "Potter", role = "aut"), person("David", "Banks", role = "aut"), person("Marco", "Kuper", role = "aut"), person("Dongning", "Zhang", role = "ctb") )
Depends: R (>= 3.2)
Imports: methods, grid, gridExtra, grDevices, graphics, stats, utils, ggplot2, tidyr, dplyr, forcats, magrittr, egg, rlang
Suggests: testthat, covr
Description: Provides a collection of functions for working with time series data, including functions for drawing, decomposing, and forecasting. Includes capabilities to compare multiple series and fit both additive and multiplicative models. Used by 'iNZight', a graphical user interface providing easy exploration and visualisation of data for students of statistics, available in both desktop and online versions. Holt (1957) <doi:10.1016/j.ijforecast.2003.09.015>, Winters (1960) <doi:10.1287/mnsc.6.3.324>, Cleveland, Cleveland, & Terpenning (1990) "STL: A Seasonal-Trend Decomposition Procedure Based on Loess".
BugReports: https://github.com/iNZightVIT/iNZightTS/issues
Contact: inzight_support@stat.auckland.ac.nz
URL: https://www.stat.auckland.ac.nz/~wild/iNZight/
LazyData: true
License: GPL-3
Encoding: UTF-8
Language: en-GB
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-05-10 01:31:30 UTC; emperor
Author: Tom Elliott [aut, cre] (<https://orcid.org/0000-0002-7815-6318>), Junjie Zeng [aut], Simon Potter [aut], David Banks [aut], Marco Kuper [aut], Dongning Zhang [ctb]
Maintainer: Tom Elliott <tom.elliott@auckland.ac.nz>
Repository: CRAN
Date/Publication: 2020-05-12 10:20:09 UTC

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New package dmtools with initial version 0.2.4
Package: dmtools
Title: Tools for Validation the Dataset
Version: 0.2.4
Authors@R: person(given = "Konstantin", family = "Ryabov", role = c("aut", "cre"), email = "chachabooms@gmail.com")
Description: For checking the dataset from EDC(Electronic Data Capture) in clinical trials. 'dmtools' can check laboratory, dates, WBCs(White Blood Cells) count and rename the dataset. Laboratory - does the investigator correctly estimate the laboratory analyzes? Dates - do all dates correspond to the protocol's timeline? WBCs count - do absolute equal (all * relative) / 100? If the clinical trial has different lab reference ranges, 'dmtools' also can help.
Depends: R (>= 3.6)
Imports: magrittr (>= 1.5), dplyr (>= 0.8.3), readxl (>= 1.3.1), purrr (>= 0.3.3), lubridate (>= 1.7.4)
License: MIT + file LICENSE
URL: https://github.com/chachabooms/dmtools
BugReports: https://github.com/chachabooms/dmtools/issues
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
Suggests: testthat, knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-05-10 13:05:54 UTC; X7-KR
Author: Konstantin Ryabov [aut, cre]
Maintainer: Konstantin Ryabov <chachabooms@gmail.com>
Repository: CRAN
Date/Publication: 2020-05-12 11:00:06 UTC

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New package covsim with initial version 0.1.0
Package: covsim
Type: Package
Title: VITA and IG Simulation for Given Covariance and Marginals
Version: 0.1.0
Authors@R: c(person("Njål", "Foldnes", email = "njal.foldnes@gmail.com", role = c("aut", "cre")), person("Steffen", "Grønneberg", email = "steffeng@gmail.com", role = c("aut")))
Description: User specifies population covariance matrix. Marginal information may be fully specified, for which the package implements the VITA (VIne-To-Anything) algorithm. Groenneberg and Foldnes (2017) <doi:10.1007/s11336-017-9569-6>. Alternatively, marginal skewness and kurtosis may be specified, for which the package implements the IG (independent generator) algorithm. Foldnes and Olsson (2016) <doi:10.1080/00273171.2015.1133274>.
License: GPL (>= 2)
Depends: R (>= 3.1.0)
Imports: rvinecopulib (>= 0.5.1.1.0), lavaan (>= 0.6-5), nleqslv, PearsonDS, MASS, stats, Rcpp, gsl
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-05-09 21:26:34 UTC; Njaal0
Author: Njål Foldnes [aut, cre], Steffen Grønneberg [aut]
Maintainer: Njål Foldnes <njal.foldnes@gmail.com>
Repository: CRAN
Date/Publication: 2020-05-12 10:10:06 UTC

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New package buildr with initial version 0.0.4
Package: buildr
Type: Package
Title: Comfort Way to Run Build Scripts
Version: 0.0.4
Author: Jan Netik
Maintainer: Jan Netik <netikja@gmail.com>
Description: Working with reproducible reports or any other similar projects often requires to run the script that builds the output file in a specified way. One can become tired from repeatedly switching to the build script and sourcing it. The 'buildr' package does this one simple thing via 'RStudio' addin – user can set up the keyboard shortcut and run the build script with one keystroke anywhere anytime. The second way is to pass buildr() command to console which does the same thing. Both ways source the build.R (case insensitive) file present in the current working directory.
License: GPL-3
Encoding: UTF-8
LazyData: true
URL: https://github.com/netique/buildr
BugReports: https://github.com/netique/buildr/issues
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-05-09 11:52:33 UTC; netik
Repository: CRAN
Date/Publication: 2020-05-12 10:10:09 UTC

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New package xmlr with initial version 0.1.2
Package: xmlr
Version: 0.1.2
Date: 2020-05-06
Title: Read, Write and Work with 'XML' Data
Authors@R: c( person("Per", "Nyfelt", email = "per@alipsa.se", role = c("cre", "aut")), person("Alipsa HB", email = "info@alipsa.se", role = "cph"), person("Steven", "Brandt", role = "ctb") )
Maintainer: Per Nyfelt <per@alipsa.se>
Depends: R (>= 3.1.0)
Encoding: UTF-8
Description: 'XML' package for creating and reading and manipulating 'XML', with an object model based on 'Reference Classes'.
License: MIT + file LICENSE
URL: https://github.com/Alipsa/xmlr
BugReports: https://github.com/Alipsa/xmlr/issues
Imports: methods
Suggests: testthat, knitr, rmarkdown
Collate: 'xmlr.R' 'utils.R' 'AbstractClass.R' 'Content.R' 'Document.R' 'Text.R' 'Element.R' 'Stack.R' 'DomBuilder.R' 'Parser.R' 'xmlImporter.R' 'xmlConverter.R'
RoxygenNote: 7.1.0
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-05-06 18:45:58 UTC; per
Author: Per Nyfelt [cre, aut], Alipsa HB [cph], Steven Brandt [ctb]
Repository: CRAN
Date/Publication: 2020-05-12 09:30:02 UTC

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New package SBdecomp with initial version 1.0
Package: SBdecomp
Type: Package
Title: Estimation of the Proportion of SB Explained by Confounders
Version: 1.0
Date: 2020-05-08
Author: Layla Parast
Maintainer: Layla Parast <parast@rand.org>
Description: Uses parametric and nonparametric methods to quantify the proportion of the estimated selection bias (SB) explained by each observed confounder when estimating propensity score weighted treatment effects. Parast, L and Griffin, BA (2020). "Quantifying the Bias due to Observed Individual Confounders in Causal Treatment Effect Estimates". Statistics in Medicine, In press (doi to be added when published).
License: GPL
Imports: stats, twang, graphics, survey
NeedsCompilation: no
Packaged: 2020-05-08 22:47:39 UTC; parast
Depends: R (>= 3.5.0)
Repository: CRAN
Date/Publication: 2020-05-12 09:50:10 UTC

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New package RobustBayesianCopas with initial version 1.0
Package: RobustBayesianCopas
Type: Package
Title: Robust Bayesian Copas Selection Model
Version: 1.0
Date: 2020-05-08
Author: Ray Bai
Maintainer: Ray Bai <raybaistat@gmail.com>
Description: Implementation of the robust Bayesian Copas (RBC) selection model for correcting and quantifying publication bias, as introduced in Bai et al. (2020) <arXiv:2005.02930>. This package also implements standard random effects meta-analysis and the Copas-like selection model of Ning et al. (2017) <doi:10.1093/biostatistics/kxx004>.
License: GPL-3
LazyData: true
Depends: R (>= 3.6.0)
Imports: stats, statip, rjags
NeedsCompilation: yes
Repository: CRAN
Packaged: 2020-05-08 21:11:56 UTC; rayba
Date/Publication: 2020-05-12 09:40:06 UTC

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New package piRF with initial version 0.1.0
Package: piRF
Title: Prediction Intervals for Random Forests
Version: 0.1.0
Date: 2020-04-17
Authors@R: c(person(given = "Chancellor", family = "Johnstone", role = c("cre", "aut", "cph"), email = "chancellor.johnstone@gmail.com"), person(given = "Haozhe", family = "Zhang", role = c("aut", "cph"), email = "haozhe.stat@gmail.com"), person(given = "Martin", family = "Wright", role = c("ctb", "cph"), email = "cran@wrig.de"), person(given = "Gregor", family = "DeCillia", role = c("ctb", "cph")))
Maintainer: Chancellor Johnstone <chancellor.johnstone@gmail.com>
Description: Implements multiple state-of-the-art prediction interval methodologies for random forests. These include: quantile regression intervals, out-of-bag intervals, bag-of-observations intervals, one-step boosted random forest intervals, bias-corrected intervals, high-density intervals, and split-conformal intervals. The implementations include a combination of novel adjustments to the original random forest methodology and novel prediction interval methodologies. All of these methodologies can be utilized using solely this package, rather than a collection of separate packages. Currently, only regression trees are supported. Also capable of handling high dimensional data. Roy, Marie-Helene and Larocque, Denis (2019) <doi:10.1177/0962280219829885>. Ghosal, Indrayudh and Hooker, Giles (2018) <arXiv:1803.08000>. Zhu, Lin and Lu, Jiaxin and Chen, Yihong (2019) <arXiv:1905.10101>. Zhang, Haozhe and Zimmerman, Joshua and Nettleton, Dan and Nordman, Daniel J. (2019) <doi:10.1080/00031305.2019.1585288>. Meinshausen, Nicolai (2006) <http://www.jmlr.org/papers/volume7/meinshausen06a/meinshausen06a.pdf>. Romano, Yaniv and Patterson, Evan and Candes, Emmanuel (2019) <arXiv:1905.03222>. Tung, Nguyen Thanh and Huang, Joshua Zhexue and Nguyen, Thuy Thi and Khan, Imran (2014) <doi:10.13140/2.1.2500.8002>.
License: GPL-3
Encoding: UTF-8
Depends: R (>= 2.10)
Suggests: testthat, devtools, foreach, doParallel, hdrcde, rfinterval, ranger
URL: http://github.com/chancejohnstone/piRF
LazyData: true
RoxygenNote: 7.0.2
Imports: Rdpack
RdMacros: Rdpack
NeedsCompilation: no
Packaged: 2020-05-09 00:05:56 UTC; thechanceyman
Author: Chancellor Johnstone [cre, aut, cph], Haozhe Zhang [aut, cph], Martin Wright [ctb, cph], Gregor DeCillia [ctb, cph]
Repository: CRAN
Date/Publication: 2020-05-12 09:50:02 UTC

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New package migrbc with initial version 2.0.8
Package: migrbc
Type: Package
Title: Production Rules Based Classification of Migration
Version: 2.0.8
URL: https://github.com/statisticsnz/migrbc, https://statisticsnz.github.io/migrbc
BugReports: https://github.com/statisticsnz/migrbc/issues
Language: en-US
Authors@R: c( person(given = "Leshi", family = "Chen", email = "leshi.chen@stats.govt.nz", role = c("aut", "cre")), person(given = "Pubudu", family = "Senanayake", email = "pubudu.senanayake@stats.govt.nz", role = c("aut")), person(given = "Del", family = "Robinson", email = "del.robinson@stats.govt.nz", role = c("aut")), person("Statistics New Zealand", role = c("cph")))
Author: Leshi Chen [aut, cre], Pubudu Senanayake [aut], Del Robinson [aut], Statistics New Zealand [cph]
Description: Provides mechanisms for classifying border crossings using a rules-based methodology. The goal of performing this type of classification is to identify any potential long-term migrants. A long-term migration is defined as a border crossing involving a change in residence status. A border crossing counts as a long-term migration to/from a country if it entails a change from non-residence to residence / residence to non-residence. The rules-based classification that used to determine a long-term migration is defined by a threshold duration and a test duration, alternatively named window size. Under a 12/16 rule, for instance, the threshold duration is 12 months and the test duration (window size) is 16 months. With a 9/12 rule, the threshold duration is 9 months and the test duration (window size) is 12 months. For more information about the methodology applied, please visit Stats NZ (2020) <https://www.stats.govt.nz/methods/defining-migrants-using-travel-histories-and-the-1216-month-rule>.
License: MIT + file LICENSE
LinkingTo: Rcpp
Encoding: UTF-8
LazyData: true
NeedsCompilation: yes
Depends: R (>= 3.5)
Imports: Rcpp (>= 1.0), lubridate (>= 1.7), stringr (>= 1.4), dplyr (>= 0.8), methods, parallel, futile.logger
Suggests: magrittr, tools, knitr, rmarkdown, testthat
RoxygenNote: 6.1.1
Collate: 'RcppExports.R' 'check_functions.R' 'plot_mig_hist.R' 'pre_process.R' 'resolve_data.R' 'resolve_data_with_error.R' 'run_rbc.R' 'utility_functions.R' 'migrbc.R'
VignetteBuilder: knitr
Packaged: 2020-05-08 04:28:08 UTC; lchen
Maintainer: Leshi Chen <leshi.chen@stats.govt.nz>
Repository: CRAN
Date/Publication: 2020-05-12 09:40:02 UTC

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New package extendedFamily with initial version 0.1.0
Package: extendedFamily
Type: Package
Title: Additional Families for Generalized Linear Models
Version: 0.1.0
Author: Greg McMahan
Maintainer: Greg McMahan <gmcmacran@gmail.com>
Description: Creates family objects identical to stats family but for new links.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Suggests: testthat, covr
Imports: stats (>= 3.5.3), assertthat (>= 0.2.1)
Depends: R (>= 3.5.0)
NeedsCompilation: no
Packaged: 2020-05-09 17:44:08 UTC; gmcma
Repository: CRAN
Date/Publication: 2020-05-12 10:00:02 UTC

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New package bets.covid19 with initial version 1.0.0
Package: bets.covid19
Title: The BETS Model for Early Epidemic Data
Version: 1.0.0
Date: 2020-05-07
Authors@R: c(person("Qingyuan", "Zhao", email = "qyzhao@statslab.cam.ac.uk", role = c("aut", "cre")),person("Nianqiao", "Ju", email = "nju@g.harvard.edu", role = "aut"))
Description: Implements likelihood inference for early epidemic analysis. BETS is short for the four key epidemiological events being modeled: Begin of exposure, End of exposure, time of Transmission, and time of Symptom onset. The package contains a dataset of the trajectory of confirmed cases during the coronavirus disease (COVID-19) early outbreak. More detail of the statistical methods can be found in Zhao et al. (2020) <arXiv:2004.07743>.
Depends: R (>= 3.4.0),
Imports: stats, rootSolve, parallel
License: CC BY 4.0
URL: https://github.com/qingyuanzhao/bets.covid19
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
NeedsCompilation: no
Packaged: 2020-05-09 14:37:21 UTC; qyzhao
Author: Qingyuan Zhao [aut, cre], Nianqiao Ju [aut]
Maintainer: Qingyuan Zhao <qyzhao@statslab.cam.ac.uk>
Repository: CRAN
Date/Publication: 2020-05-12 09:50:06 UTC

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Mon, 11 May 2020

New package stringfish with initial version 0.1
Package: stringfish
Title: Alt String Implementation
Version: 0.1
Authors@R: c( person("Travers", "Ching", email = "traversc@gmail.com", role = c("aut", "cre", "cph")), person("Phillip", "Hazel", role = c("ctb", "cph"), comment = "Bundled PCRE2 code"), person("Zoltan", "Herczeg", role = c("ctb", "cph"), comment = "Bundled PCRE2 code"), person("University of Cambridge", role = c("cph"), comment = "Bundled PCRE2 code"), person("Tilera Corporation", role = "cph", comment = "Stack-less Just-In-Time compiler bundled with PCRE2"))
Maintainer: Travers Ching <traversc@gmail.com>
Description: Provides an extendable and performant 'alt-string' implementation backed by 'C++' vectors and strings.
License: GPL-3
Biarch: true
Encoding: UTF-8
Depends: R (>= 3.5.0)
SystemRequirements: C++11
LinkingTo: Rcpp (>= 0.12.18.3)
Imports: Rcpp
Suggests: qs, knitr, rmarkdown
VignetteBuilder: knitr
RoxygenNote: 7.1.0
Copyright: This package includes bundled code from the 'PCRE2' library created by Philip Hazel.
URL: https://github.com/traversc/stringfish
BugReports: https://github.com/traversc/stringfish/issues
NeedsCompilation: yes
Packaged: 2020-05-08 20:02:15 UTC; tching
Author: Travers Ching [aut, cre, cph], Phillip Hazel [ctb, cph] (Bundled PCRE2 code), Zoltan Herczeg [ctb, cph] (Bundled PCRE2 code), University of Cambridge [cph] (Bundled PCRE2 code), Tilera Corporation [cph] (Stack-less Just-In-Time compiler bundled with PCRE2)
Repository: CRAN
Date/Publication: 2020-05-11 16:30:02 UTC

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New package wk with initial version 0.2.1
Package: wk
Title: Lightweight Well-Known Geometry Parsing
Version: 0.2.1
Authors@R: c( person(given = "Dewey", family = "Dunnington", role = c("aut", "cre"), email = "dewey@fishandwhistle.net", comment = c(ORCID = "0000-0002-9415-4582")), person(given = "Edzer", family = "Pebesma", role = c("aut"), email = "edzer.pebesma@uni-muenster.de", comment = c(ORCID = "0000-0001-8049-7069")), person("Refractions Research Inc.", role = "cph"), person("Vivid Solutions Inc.", role = "cph") )
Maintainer: Dewey Dunnington <dewey@fishandwhistle.net>
Description: Provides a minimal R and C++ API for parsing well-known binary and well-known text representation of geometries to and from R-native formats. Well-known binary is compact and fast to parse; well-known text is human-readable and is useful for writing tests. These formats are only useful in R if the information they contain can be accessed in R, for which high-performance functions are provided here.
License: LGPL (>= 2.1)
Copyright: file COPYRIGHTS
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
LinkingTo: Rcpp
Imports: Rcpp
Suggests: testthat
URL: https://github.com/paleolimbot/wk
BugReports: https://github.com/paleolimbot/wk/issues
NeedsCompilation: yes
Packaged: 2020-05-08 16:29:50 UTC; dewey
Author: Dewey Dunnington [aut, cre] (<https://orcid.org/0000-0002-9415-4582>), Edzer Pebesma [aut] (<https://orcid.org/0000-0001-8049-7069>), Refractions Research Inc. [cph], Vivid Solutions Inc. [cph]
Repository: CRAN
Date/Publication: 2020-05-11 15:50:02 UTC

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New package rties with initial version 5.0.0
Package: rties
Title: Modeling Interpersonal Dynamics
Version: 5.0.0
Authors@R: c(person("Emily", "Butler", email = "emily.a.butler@gmail.com", role = c("aut", "cre")), person("Steven Boker", role="ctb"))
Maintainer: Emily Butler <emily.a.butler@gmail.com>
Description: The name of this package grew out of our research on temporal interpersonal emotion systems (TIES), hence 'rties'. It provides tools for using a set of models to investigate temporal processes in bivariate (e.g., dyadic) systems. The general approach is to model, one dyad at a time, the dynamics of a variable that is assessed repeatedly from both partners, extract the parameter estimates for each dyad, and then use those parameter estimates as input to a latent profile analysis to extract groups of dyads with qualitatively distinct dynamics. Finally, the profile memberships can be used to either predict, or be predicted by, another variable of interest. Currently, 2 models are supported: 1) inertia-coordination, and 2) a coupled-oscillator. Extended documentation is provided in vignettes. Theoretical background can be found in Butler (2011) <doi:10.1177/1088868311411164> and Butler & Barnard (2019) <doi:10.1097/PSY.0000000000000703>.
Depends: R (>= 2.10)
Imports: DataCombine, DescTools, deSolve, dplyr, ggplot2, gridExtra, interactions, lattice, lme4, MASS, mclust, nlme, nnet, plyr, zoo
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
Suggests: devtools, knitr, rmarkdown, sjmisc, sjPlot
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-05-08 16:25:29 UTC; emily
Author: Emily Butler [aut, cre], Steven Boker [ctb]
Repository: CRAN
Date/Publication: 2020-05-11 16:00:02 UTC

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New package rgenius with initial version 0.1.0
Package: rgenius
Type: Package
Date: 2020-05-02
Title: Get 'Genius' API Lyrics
Version: 0.1.0
Author: Alberto Almuiña <albertogonzalezalmuinha@gmail.com>
Maintainer: Alberto Almuiña <albertogonzalezalmuinha@gmail.com>
Description: Download the lyrics of your favorite songs in text and table formats. Also search for related songs or song information. More information: <https://docs.genius.com/> .
URL: https://github.com/AlbertoAlmuinha/rgenius
BugReports: https://github.com/AlbertoAlmuinha/rgenius/issues
Imports: dplyr, purrr, stringr, httr, rvest, foreach, tibble, parallel, doParallel
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2020-05-08 12:40:14 UTC; albgonzal
Repository: CRAN
Date/Publication: 2020-05-11 15:10:02 UTC

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New package r3PG with initial version 0.1.0
Package: r3PG
Type: Package
Title: Simulating Forest Growth using the 3-PG Model
Description: Provides a flexible and easy-to-use interface for the Physiological Processes Predicting Growth (3-PG) model written in Fortran. The r3PG serves as a flexible and easy-to-use interface for the 3-PGpjs (monospecific, evenaged and evergreen forests) described in Landsberg & Waring (1997) <doi:10.1016/S0378-1127(97)00026-1> and the 3-PGmix (deciduous, uneven-aged or mixed-species forests) described in Forrester & Tang (2016) <doi:10.1016/j.ecolmodel.2015.07.010>.
Date: 2020-04-29
Version: 0.1.0
Authors@R: c( person("Volodymyr", "Trotsiuk", email = "vtrotsiuk@gmail.com", role = c("aut", 'cre'), comment=c(ORCID="0000-0002-8363-656X")), person("Florian", "Hartig", email = "florian.hartig@biologie.uni-regensburg.de", role = c("aut"), comment=c(ORCID="0000-0002-6255-9059")), person("David", "Forrester", email = "david.forrester@wsl.ch", role = c("aut")) )
License: GPL-3
Depends: R (>= 3.5.0)
Imports:
Suggests: knitr (>= 1.15.1), rmarkdown (>= 1.3), R.rsp (>= 0.40.0), testthat (>= 1.0.2), roxygen2, BayesianTools, sensitivity, dplyr, ggplot2
VignetteBuilder: R.rsp
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2.9000
URL: https://github.com/trotsiuk/r3PG
BugReports: https://github.com/trotsiuk/r3PG/issues
NeedsCompilation: yes
Packaged: 2020-05-08 09:30:44 UTC; trotsiuk
Author: Volodymyr Trotsiuk [aut, cre] (<https://orcid.org/0000-0002-8363-656X>), Florian Hartig [aut] (<https://orcid.org/0000-0002-6255-9059>), David Forrester [aut]
Maintainer: Volodymyr Trotsiuk <vtrotsiuk@gmail.com>
Repository: CRAN
Date/Publication: 2020-05-11 15:10:06 UTC

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New package ibb with initial version 0.0.1
Package: ibb
Title: R Wrapper for Istanbul Municipality Open Data Portal
Version: 0.0.1
Authors@R: person(given = "Berk", family = "Orbay", email= "berk.orbay@algopoly.com", role = c("aut", "cre"))
Description: Call wrappers for Istanbul Metropolitan Municipality's Open Data Portal (Turkish: İstanbul Büyükşehir Belediyesi Açık Veri Portalı) at <https://data.ibb.gov.tr/en/>.
License: MIT + file LICENSE
URL: https://github.com/berkorbay/ibb
BugReports: https://github.com/berkorbay/ibb/issues
Encoding: UTF-8
LazyData: true
Imports: jsonlite, httr, xml2, dplyr
Depends: R (>= 3.4)
RoxygenNote: 6.1.1
Suggests: testthat (>= 2.1.0)
NeedsCompilation: no
Packaged: 2020-05-10 20:43:46 UTC; berkorbay
Author: Berk Orbay [aut, cre]
Maintainer: Berk Orbay <berk.orbay@algopoly.com>
Repository: CRAN
Date/Publication: 2020-05-11 15:20:10 UTC

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New package Compack with initial version 0.1.0
Package: Compack
Title: Regression with Compositional Covariates
Version: 0.1.0
Date: 2020-04-21
Authors@R: c( person(given = "Zhe", family = "Sun", email = "zhe.sun@uconn.edu", role = c("aut", "cre"), comment = c(ORCID = "0000-0001-8699-8235") ), person(given = "Kun", family = "Chen", email = "kun.chen@uconn.edu", role = c("aut"), comment = c(ORCID = "0000-0003-3579-5467")) )
Description: Regression methodologies with compositional covariates, including (1) sparse log-contrast regression with compositional covariates proposed by Lin et al. (2014) <doi:10.1093/biomet/asu031>, and (2) sparse log-contrast regression with functional compositional predictors proposed by Sun et al. (2020) <arXiv:1808.02403>.
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
Depends: R (>= 3.4.0)
LinkingTo: Rcpp, RcppArmadillo
Imports: Rcpp, MASS, plyr, splines, fda, orthogonalsplinebasis, methods
Suggests: knitr, rmarkdown
NeedsCompilation: yes
VignetteBuilder: knitr
Packaged: 2020-05-08 18:53:27 UTC; zjiji
Author: Zhe Sun [aut, cre] (<https://orcid.org/0000-0001-8699-8235>), Kun Chen [aut] (<https://orcid.org/0000-0003-3579-5467>)
Maintainer: Zhe Sun <zhe.sun@uconn.edu>
Repository: CRAN
Date/Publication: 2020-05-11 16:00:11 UTC

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New package chromseq with initial version 0.1.3
Package: chromseq
Type: Package
Title: Split Chromosome 'Fasta' File
Description: Chromosome files in the 'Fasta' format usually contain large sequences like human genome. Sometimes users have to split these chromosomes into different files according to their chromosome number. The 'chromseq' can help to handle this. So the selected chromosome sequence can be used for downstream analysis like motif finding. Howard Y. Chang(2019) <doi:10.1038/s41587-019-0206-z>.
Version: 0.1.3
Authors@R: person(given = "Shaoqian", family = "Ma", email = "897341109@qq.com", role = c("aut", "cre"))
License: Artistic-2.0
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
NeedsCompilation: no
URL: https://github.com/MSQ-123/chromseq
BugReports: https://github.com/MSQ-123/chromseq/issues
Depends: R (>= 2.10)
Imports: utils, base
Packaged: 2020-05-08 13:06:01 UTC; lenovo
Author: Shaoqian Ma [aut, cre]
Maintainer: Shaoqian Ma <897341109@qq.com>
Repository: CRAN
Date/Publication: 2020-05-11 15:20:17 UTC

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New package norm2 with initial version 2.0.3
Package: norm2
Type: Package
Title: Analysis of Incomplete Multivariate Data under a Normal Model
Version: 2.0.3
Date: 2020-04-23
Author: Joseph L. Schafer <Joseph.L.Schafer@census.gov>
Maintainer: Joseph L. Schafer <Joseph.L.Schafer@census.gov>
Description: Functions for parameter estimation, Bayesian posterior simulation and multiple imputation from incomplete multivariate data under a normal model.
Depends: R (>= 3.1.0)
Imports: stats
License: GPL-3
LazyLoad: yes
NeedsCompilation: yes
Packaged: 2020-04-23 13:51:37 UTC; schaf310
Repository: CRAN
Date/Publication: 2020-05-11 14:50:02 UTC

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New package FESta with initial version 1.0.0
Package: FESta
Type: Package
Title: Fishing Effort Standardisation
Version: 1.0.0
Authors@R: c( person("Eldho", "Varghese", email = "eldhoiasri@gmail.com" , role = c("aut", "cre")), person("Sathianandan", "T V", email = "tvsedpl@gmail.com" , role = "aut"), person("Jayasankar", "J", email = "jjsankar@gmail.com" , role = "aut"), person("Reshma", "Gills", email = "reshma1818@gmail.com" , role = "ctb") )
Maintainer: Eldho Varghese <eldhoiasri@gmail.com>
Imports: graphics, stats
Description: Original idea was presented in the reference paper. Varghese et al. (2020, 74(1):35-42) "Bayesian State-space Implementation of Schaefer Production Model for Assessment of Stock Status for Multi-gear Fishery". Marine fisheries governance and management practices are very essential to ensure the sustainability of the marine resources. A widely accepted resource management strategy towards this is to derive sustainable fish harvest levels based on the status of marine fish stock. Various fish stock assessment models that describe the biomass dynamics using time series data on fish catch and fishing effort are generally used for this purpose. In the scenario of complex multi-species marine fishery in which different species are caught by a number of fishing gears and each gear harvests a number of species make it difficult to obtain the fishing effort corresponding to each fish species. Since the capacity of the gears varies, the effort made to catch a resource cannot be considered as the sum of efforts expended by different fishing gears. This necessitates standardisation of fishing effort in unit base.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Author: Eldho Varghese [aut, cre], Sathianandan T V [aut], Jayasankar J [aut], Reshma Gills [ctb]
Repository: CRAN
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-05-08 07:53:35 UTC; RESHMA
Date/Publication: 2020-05-11 14:50:06 UTC

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New package xml2relational with initial version 0.1.0
Package: xml2relational
Type: Package
Title: Converting XML Documents into Relational Data Models
Description: Import an XML document with nested object structures and convert it into a relational data model. The result is a set of R dataframes with foreign key relationships. The data model and the data can be exported as SQL code of different SQL flavors.
Version: 0.1.0
Authors@R: person("Joachim", "Zuckarelli", role = c("aut", "cre"), email = "joachim@zuckarelli.de", comment = c(ORCID="0000-0002-9280-3016"))
Maintainer: Joachim Zuckarelli <joachim@zuckarelli.de>
Depends: R (>= 3.5.0)
License: GPL-3
Imports: xml2, stringr, tidyr, fs, stats, utils, lubridate, rlang
Repository: CRAN
BugReports: https://github.com/jsugarelli/xml2relational/issues
URL: https://github.com/jsugarelli/xml2relational/
Encoding: UTF-8
ByteCompile: true
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-05-07 16:02:57 UTC; Joachim
Author: Joachim Zuckarelli [aut, cre] (<https://orcid.org/0000-0002-9280-3016>)
Date/Publication: 2020-05-11 12:40:03 UTC

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New package sistec with initial version 0.0.2
Package: sistec
Type: Package
Title: Tools to Analyze 'Sistec' Datasets
Version: 0.0.2
Authors@R: c( person("Samuel", "Macêdo", email = "samuelmacedo@recife.ifpe.edu.br", role = c("aut", "cre")), person("Carlos", "Patrício", email = "carlos.patricio@vitoria.ifpe.edu.br", role = "aut"), person("Cássio", "Santos", email = "cassiosantos@recife.ifpe.edu.br", role = "aut"), person("Clécio", "Santos", email = "cleciogsantos@vitoria.ifpe.edu.br", role = "aut") )
Maintainer: Samuel Macêdo <samuelmacedo@recife.ifpe.edu.br>
Description: The Brazilian system for diploma registration and validation on technical and superior courses are managing by 'Sistec' platform, see <https://sistec.mec.gov.br/>. This package provides tools for Brazilian institutions to update the student's registration and make data analysis about their situation, retention and drop out.
License: GPL (>= 2)
LazyData: true
URL: https://github.com/r-ifpe/sistec
BugReports: https://github.com/r-ifpe/sistec/issues
Depends: R (>= 3.6)
Imports: dplyr, openxlsx, rlang, shiny, stringr, tcltk, utils
RoxygenNote: 7.1.0
Suggests: testthat
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2020-05-07 19:36:47 UTC; dmmad
Author: Samuel Macêdo [aut, cre], Carlos Patrício [aut], Cássio Santos [aut], Clécio Santos [aut]
Repository: CRAN
Date/Publication: 2020-05-11 12:50:03 UTC

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New package roben with initial version 0.1.0
Package: roben
Type: Package
Title: Robust Bayesian Variable Selection for Gene-Environment Interactions
Version: 0.1.0
Author: Jie Ren, Fei Zhou, Xiaoxi Li, Cen Wu
Maintainer: Jie Ren <jieren@ksu.edu>
Description: Gene-environment (G×E) interactions have important implications to elucidate the etiology of complex diseases beyond the main genetic and environmental effects. Outliers and data contamination in disease phenotypes of G×E studies have been commonly encountered, leading to the development of a broad spectrum of robust penalization methods. Nevertheless, within the Bayesian framework, the issue has not been taken care of in existing studies. We develop a robust Bayesian variable selection method for G×E interaction studies. The proposed Bayesian method can effectively accommodate heavy-tailed errors and outliers in the response variable while conducting variable selection by accounting for structural sparsity. In particular, the spike-and-slab priors have been imposed on both individual and group levels to identify important main and interaction effects. An efficient Gibbs sampler has been developed to facilitate fast computation. The Markov chain Monte Carlo algorithms of the proposed and alternative methods are efficiently implemented in C++.
Depends: R (>= 3.5.0)
License: GPL-2
Encoding: UTF-8
LazyData: true
LinkingTo: Rcpp, RcppArmadillo
Imports: Rcpp, glmnet, stats
RoxygenNote: 7.1.0
Suggests: testthat (>= 2.1.0), covr
URL: https://github.com/jrhub/roben
BugReports: https://github.com/jrhub/roben/issues
NeedsCompilation: yes
Packaged: 2020-05-07 17:21:49 UTC; JieRen
Repository: CRAN
Date/Publication: 2020-05-11 12:30:03 UTC

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New package ORION with initial version 1.0
Package: ORION
Type: Package
Title: Ordinal Relations
Version: 1.0
Date: 2020-04-28
Author: L Lausser, LM Schaefer, HA Kestler
Maintainer: HA Kestler <hans.kestler@uni-ulm.de>
Description: Functions to handle ordinal relations reflected within the feature space. Those function allow to search for ordinal relations in multi-class datasets. One can check whether proposed relations are reflected in a specific feature representation. Furthermore, it provides functions to filter, organize and further analyze those ordinal relations.
License: GPL-2
LazyLoad: yes
Packaged: 2020-05-07 17:36:23 UTC; julian_schwab
Imports: e1071,TunePareto, knitr, rmarkdown, doParallel, igraph, foreach, randomForest
NeedsCompilation: yes
VignetteBuilder: knitr
RoxygenNote: 7.1.0
Repository: CRAN
Date/Publication: 2020-05-11 12:50:17 UTC

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New package guiplot with initial version 0.1.0
Package: guiplot
Type: Package
Title: User-Friendly GUI Plotting Tools
Version: 0.1.0
Author: Fu Yongchao <3212418315@qq.com>
Maintainer: Fu Yongchao <3212418315@qq.com>
Description: Create a user-friendly plotting GUI for R. In addition, one purpose of creating the R package is to facilitate third-party software to call R for drawing, for example, 'Phoenix WinNonlin' software calls R to draw the drug concentration versus time curve.
URL: https://s0521.github.io/guiplot/about/
Imports: shiny(>= 1.0.0), ggplot2 (>= 3.0.0), svglite, DT, rlang (>= 0.3.1),stats, magrittr,R6
License: MIT + file LICENSE
Depends: R (>= 3.6.0)
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
NeedsCompilation: no
Packaged: 2020-05-07 16:14:44 UTC; HASEE
Repository: CRAN
Date/Publication: 2020-05-11 12:30:07 UTC

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New package grizbayr with initial version 1.2.1
Package: grizbayr
Type: Package
Title: Bayesian Inference for A|B and Bandit Marketing Tests
Version: 1.2.1
Author: Ryan Angi
Maintainer: Ryan Angi <rangi@redventures.com>
Description: Uses simple Bayesian conjugate prior update rules to calculate the win probability of each option, value remaining in the test, and percent lift over the baseline for various marketing objectives. References: Fink, Daniel (1997) "A Compendium of Conjugate Priors" <doi:10.1.1.157/5540>. Stucchio, Chris (2015) "Bayesian A/B Testing at VWO" <http://cdn2.hubspot.net/hubfs/310840/VWO_SmartStats_technical_whitepaper.pdf>.
Depends: R (>= 2.10)
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
Imports: purrr, dplyr, tidyr, magrittr, tibble, rlang
Suggests: spelling, knitr, testthat (>= 2.1.0), rmarkdown
Language: en-US
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-05-07 16:10:46 UTC; rangi
Repository: CRAN
Date/Publication: 2020-05-11 12:30:10 UTC

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New package rosr with initial version 0.0.10
Package: rosr
Version: 0.0.10
Date: 2020-05-11
Title: Create Reproducible Research Projects
Authors@R: c( person("Peng", "Zhao", role = c("aut", "cre"), email = "pzhao@pzhao.net") )
Maintainer: Peng Zhao <pzhao@pzhao.net>
Depends: R (>= 3.1.0)
Imports: rmarkdown, bookdown, blogdown, tinytex, mindr, bookdownplus, rstudioapi, htmlwidgets, shiny, devtools, clipr, knitr
Suggests:
Description: Creates reproducible academic projects with integrated academic elements, including datasets, references, codes, images, manuscripts, dissertations, slides and so on. These elements are well connected so that they can be easily synchronized and updated.
License: GPL-3 | file LICENSE
URL: https://github.com/pzhaonet/rosr
BugReports: https://github.com/pzhaonet/rosr/issues
SystemRequirements: pandoc (>= 2.0; https://pandoc.org)
RoxygenNote: 7.1.0
NeedsCompilation: no
LazyData: true
Packaged: 2020-05-11 02:36:07 UTC; dapen
Author: Peng Zhao [aut, cre]
Repository: CRAN
Date/Publication: 2020-05-11 11:10:02 UTC

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New package roptions with initial version 1.0.3
Package: roptions
Title: Option Strategies and Valuation
Version: 1.0.3
Authors@R: person(given = "Anurag", family = "Agrawal", role = c("aut", "cre"), email = "agrawalanurag1999@gmail.com", comment = c(ORCID = "0000-0003-2272-8273"))
Description: Collection of tools to develop options strategies, value option contracts using the Black-Scholes-Merten option pricing model and calculate the option Greeks. Hull, John C. "Options, Futures, and Other Derivatives" (1997, ISBN:0-13-601589-1). Fischer Black, Myron Scholes (1973) "The Pricing of Options and Corporate Liabilities" <doi:10.1086/260062>.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
Imports: purrr, ggplot2, plotly, stats
Depends: R (>= 2.10)
NeedsCompilation: no
Packaged: 2020-05-07 11:07:40 UTC; Kanhaiiya Agrawal
Author: Anurag Agrawal [aut, cre] (<https://orcid.org/0000-0003-2272-8273>)
Maintainer: Anurag Agrawal <agrawalanurag1999@gmail.com>
Repository: CRAN
Date/Publication: 2020-05-11 11:10:06 UTC

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New package nixmass with initial version 1.0-1
Package: nixmass
Version: 1.0-1
Date: 2020-04-29
Title: Snow Water Equivalent Modeling with the 'Delta.snow' Model and Empirical Regression Models
Authors@R: c(person("Harald", "Schellander", role = c("aut", "cre"), email = "harald.schellander@zamg.ac.at"), person("Michael", "Winkler", role = c("ctb")))
Maintainer: Harald Schellander <harald.schellander@zamg.ac.at>
Depends: R (>= 3.5.0)
Imports: graphics,stats,zoo,lubridate,grDevices
LazyData: true
Description: Snow water equivalent is modeled with the process based 'delta.snow' model and empirical regression models using relationships between density and diverse at-site parameters. The methods are described in Winkler et al. (2020) <doi:10.5194/hess-2020-152>, Guyennon et al. (2019) <doi:10.1016/j.coldregions.2019.102859>, Pistocchi (2016) <doi:10.1016/j.ejrh.2016.03.004>, Jonas et al. (2009) <doi:10.1016/j.jhydrol.2009.09.021> and Sturm et al. (2010) <doi:10.1175/2010JHM1202.1>.
License: GPL-2 | GPL-3
NeedsCompilation: no
Packaged: 2020-05-07 12:51:36 UTC; hschellander
Author: Harald Schellander [aut, cre], Michael Winkler [ctb]
Repository: CRAN
Date/Publication: 2020-05-11 11:40:02 UTC

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New package ggstudent with initial version 0.1.1-1
Package: ggstudent
Type: Package
Date: 2020-05-05
Title: Continuous Confidence Interval Plots using t-Distribution
Version: 0.1.1-1
Authors@R: person(given = "Jouni", family = "Helske", role = c("aut", "cre"), email = "jouni.helske@iki.fi", comment = c(ORCID = "0000-0001-7130-793X"))
License: GPL (>= 2)
Description: Provides an extension to 'ggplot2' (Wickham, 2016, <doi:10.1007/978-3-319-24277-4>) for creating two types of continuous confidence interval plots (Violin CI and Gradient CI plots), typically for the sample mean. These plots contain multiple user-defined confidence areas with varying colours, defined by the underlying t-distribution used to compute standard confidence intervals for the mean of the normal distribution when the variance is unknown. Two types of plots are available, a gradient plot with rectangular areas, and a violin plot where the shape (horizontal width) is defined by the probability density function of the t-distribution.
Encoding: UTF-8
Depends: R (>= 3.1.0)
Imports: dplyr, ggplot2, stats
Suggests: scales
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2020-05-07 13:05:21 UTC; jovetale
Author: Jouni Helske [aut, cre] (<https://orcid.org/0000-0001-7130-793X>)
Maintainer: Jouni Helske <jouni.helske@iki.fi>
Repository: CRAN
Date/Publication: 2020-05-11 11:50:02 UTC

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New package DeCAFS with initial version 3.1.4
Package: DeCAFS
Type: Package
Title: Detecting Changes in Autocorrelated and Fluctuating Signals
Version: 3.1.4
Date: 2020-05-07
Authors@R: c(person("Gaetano", "Romano", email = "g.romano@lancaster.ac.uk", role = c("aut", "cre")), person("Guillem", "Rigaill", role = c("aut")), person("Vincent", "Runge", role = c("aut")), person("Paul", "Fearnhead", role = c("aut")))
Maintainer: Gaetano Romano <g.romano@lancaster.ac.uk>
Description: Detect abrupt changes in time series with local fluctuations as a random walk process and autocorrelated noise as an AR(1) process. See Romano, G., Rigaill, G., Runge, V., Fearnhead, P. (2020) <arXiv:2005.01379>.
License: GPL (>= 2)
Imports: Rcpp (>= 1.0.0), ggplot2
LinkingTo: Rcpp
NeedsCompilation: yes
Packaged: 2020-05-07 11:08:51 UTC; romano
Depends: R (>= 2.10)
LazyData: true
BugReports: https://github.com/gtromano/DeCAFS/issues
RoxygenNote: 7.1.0
Author: Gaetano Romano [aut, cre], Guillem Rigaill [aut], Vincent Runge [aut], Paul Fearnhead [aut]
Repository: CRAN
Date/Publication: 2020-05-11 12:00:02 UTC

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New package blindrecalc with initial version 0.1.2
Package: blindrecalc
Type: Package
Title: Blinded Sample Size Recalculation
Version: 0.1.2
Authors@R: c(person(given = "Lukas", family = "Baumann", role = c("aut"), email = "baumann@imbi.uni-heidelberg.de"), person(given = "Maximilian", family = "Pilz", role = c("aut", "cre"), email = "pilz@imbi.uni-heidelberg.de"), person(given = "Institute of Medical Biometry and Informatics - University of Heidelberg", role = c("cph")))
Description: Computation of key characteristics and plots for blinded sample size recalculation. Continuous as well as binary endpoints are supported in superiority and non-inferiority trials. The implemented methods include the approaches by Lu, K. (2019) <doi:10.1002/pst.1737>, Kieser, M. and Friede, T. (2000) <doi:10.1002/(SICI)1097-0258(20000415)19:7%3C901::AID-SIM405%3E3.0.CO;2-L>, Friede, T. and Kieser, M. (2004) <doi:10.1002/pst.140>, Friede, T., Mitchell, C., Mueller-Veltern, G. (2007) <doi:10.1002/bimj.200610373>, and Friede, T. and Kieser, M. (2011) <doi:10.3414/ME09-01-0063>.
License: MIT + file LICENSE
URL: https://github.com/imbi-heidelberg/blindrecalc
Encoding: UTF-8
LazyData: true
Suggests: testthat, covr
Imports: methods, Rcpp
Collate: test_statistics.R methods.R Student.R blindrecalc.R ChiSquare.R ChiSquare_helper.R FarringtonManning.R FarringtonManning_helper.R RcppExports.R
RoxygenNote: 7.1.0
LinkingTo: Rcpp
NeedsCompilation: yes
Packaged: 2020-05-07 12:52:49 UTC; Max
Author: Lukas Baumann [aut], Maximilian Pilz [aut, cre], Institute of Medical Biometry and Informatics - University of Heidelberg [cph]
Maintainer: Maximilian Pilz <pilz@imbi.uni-heidelberg.de>
Repository: CRAN
Date/Publication: 2020-05-11 11:10:14 UTC

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New package Andromeda with initial version 0.1.3
Package: Andromeda
Type: Package
Title: Asynchronous Disk-Based Representation of Massive Data
Version: 0.1.3
Date: 2020-05-07
Authors@R: c( person("Martijn", "Schuemie", , "schuemie@ohdsi.org", role = c("aut", "cre")), person("Marc A.", "Suchard", , "msuchard@ucla.edu", role = c("aut")), person("Observational Health Data Science and Informatics", role = c("cph")) )
Maintainer: Martijn Schuemie <schuemie@ohdsi.org>
Description: Storing very large data objects on a local drive, while still making it possible to manipulate the data in an efficient manner.
License: Apache License 2.0
VignetteBuilder: knitr
URL: https://github.com/OHDSI/Andromeda
BugReports: https://github.com/OHDSI/Andromeda/issues
Depends: dplyr
Imports: RSQLite, DBI, zip, methods, dbplyr, cli, pillar, Rcpp
Suggests: testthat, knitr, rmarkdown, rlang, tibble
LazyData: false
RoxygenNote: 7.1.0
Encoding: UTF-8
LinkingTo: Rcpp
NeedsCompilation: yes
Packaged: 2020-05-07 10:53:13 UTC; MSCHUEMI
Author: Martijn Schuemie [aut, cre], Marc A. Suchard [aut], Observational Health Data Science and Informatics [cph]
Repository: CRAN
Date/Publication: 2020-05-11 11:10:27 UTC

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New package regmedint with initial version 0.1.0
Package: regmedint
Title: Regression-Based Causal Mediation Analysis with an Interaction Term
Version: 0.1.0
Authors@R: c( # http://r-pkgs.had.co.nz/description.html#author person('Kazuki', 'Yoshida', email = 'kazukiyoshida@mail.harvard.edu', role = c('cre','aut'), comment = c(ORCID = '0000-0002-2030-3549')), # person('Maya', 'Mathur', role = c('ctb'), comment = c(ORCID = '0000-0001-6698-2607')) )
Description: 'R' re-implementation of the regression-based causal mediation analysis with a treatment-mediator interaction term, as originally implemented in the 'SAS' macro by Valeri and VanderWeele (2013) <doi:10.1037/a0031034> and Valeri and VanderWeele (2015) <doi:10.1097/EDE.0000000000000253>. Linear and logistic models are supported for the mediator model. Linear, logistic, loglinear, Poisson, negative binomial, Cox, and accelerated failure time (exponential and Weibull) models are supported for the outcome model.
License: GPL-2
Encoding: UTF-8
LazyData: true
Imports: Deriv, MASS, Matrix, assertthat, sandwich, survival
Suggests: boot, furrr, future, geepack, knitr, mice, mitools, modelr, purrr, rlang, stringr, testthat, tidyverse
RoxygenNote: 7.1.0
VignetteBuilder: knitr
URL: https://kaz-yos.github.io/regmedint/
BugReports: https://github.com/kaz-yos/regmedint/issues
Depends: R (>= 2.10)
NeedsCompilation: no
Packaged: 2020-05-07 10:54:41 UTC; kazuki
Author: Kazuki Yoshida [cre, aut] (<https://orcid.org/0000-0002-2030-3549>), Maya Mathur [ctb] (<https://orcid.org/0000-0001-6698-2607>)
Maintainer: Kazuki Yoshida <kazukiyoshida@mail.harvard.edu>
Repository: CRAN
Date/Publication: 2020-05-11 11:00:02 UTC

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New package spant with initial version 1.5.0
Package: spant
Type: Package
Title: MR Spectroscopy Analysis Tools
Version: 1.5.0
Date: 2020-05-10
Authors@R: c( person("Martin", "Wilson", email = "martin@pipegrep.co.uk", role = c("cre", "aut")), person("Yong", "Wang", role = "ctb"), person("John", "Muschelli", role = "ctb"))
Description: Tools for reading, visualising and processing Magnetic Resonance Spectroscopy data. <https://martin3141.github.io/spant/>.
BugReports: https://github.com/martin3141/spant/issues
License: GPL-3
RoxygenNote: 7.1.0
NeedsCompilation: yes
LazyData: yes
Depends: R (>= 2.10)
Imports: abind, plyr, foreach, pracma, stringr, complexplus, signal, matrixcalc, minpack.lm, nnls, utils, graphics, grDevices, smoother, readr, magrittr, ptw, viridisLite, mmand, RNifti, RNiftyReg, fields, MASS, shiny, miniUI, oro.dicom, numDeriv, nloptr, irlba, tibble
Suggests: neurobase, oro.nifti, knitr, rmarkdown, testthat, doParallel
VignetteBuilder: knitr
Encoding: UTF-8
Language: en-GB
Packaged: 2020-05-10 07:43:26 UTC; martin
Author: Martin Wilson [cre, aut], Yong Wang [ctb], John Muschelli [ctb]
Maintainer: Martin Wilson <martin@pipegrep.co.uk>
Repository: CRAN
Date/Publication: 2020-05-11 09:10:02 UTC

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New package condmixt with initial version 1.1
Package: condmixt
Type: Package
Title: Conditional Density Estimation with Neural Network Conditional Mixtures
Version: 1.1
Date: 2020-05-09
Author: Julie Carreau
Maintainer: Julie Carreau <julie.carreau@ird.fr>
Description: Neural network conditional mixtures are mixture models whose parameters are predicted by a neural network. The mixture model can thus change its parameters in response to changes in predictive covariates. Mixtures included are gaussian, log-normal and hybrid Pareto mixtures. The latter relies on the generalized Pareto distribution to account for the presence of large extreme events. The unconditional mixtures are also available.
Depends: evd
License: GPL-2
LazyLoad: yes
NeedsCompilation: yes
Packaged: 2020-05-10 09:07:01 UTC; lili
Repository: CRAN
Date/Publication: 2020-05-11 09:10:08 UTC

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Sat, 09 May 2020

New package gfonts with initial version 0.1.1
Package: gfonts
Title: Offline 'Google' Fonts for 'Markdown' and 'Shiny'
Version: 0.1.1
Authors@R: c( person("Victor", "Perrier", email = "victor.perrier@dreamrs.fr", role = c("aut", "cre")), person("Fanny", "Meyer", role = "aut"), person("Mario", "Ranftl", role = c("ctb", "cph"), comment = "google-webfonts-helper"))
Description: Download 'Google' fonts and generate CSS to use in 'rmarkdown' documents and 'shiny' applications. Some popular fonts are included and ready to use.
URL: https://github.com/dreamRs/gfonts
BugReports: https://github.com/dreamRs/gfonts/issues
License: GPL-3
Encoding: UTF-8
LazyData: true
Depends: R (>= 2.10)
Imports: utils, htmltools, shiny, crul, jsonlite, glue, usethis
RoxygenNote: 7.1.0
Suggests: knitr, rmarkdown, testthat (>= 2.1.0), vcr, covr
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-05-06 18:33:09 UTC; perri
Author: Victor Perrier [aut, cre], Fanny Meyer [aut], Mario Ranftl [ctb, cph] (google-webfonts-helper)
Maintainer: Victor Perrier <victor.perrier@dreamrs.fr>
Repository: CRAN
Date/Publication: 2020-05-09 16:30:03 UTC

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New package tsdf with initial version 1.1-8
Package: tsdf
Type: Package
Title: Two-/Three-Stage Designs for Phase 1&2 Clinical Trials
Version: 1.1-8
Date: 2020-05-09
Author: Wenchuan Guo, Jianan Hui, Bob Zhong
Maintainer: Wenchuan Guo <wguo1017@gmail.com>
Description: Calculate optimal Zhong's two-/three-stage Phase II designs (see Zhong (2012) <doi:10.1016/j.cct.2012.07.006>). Generate Target Toxicity decision table for Phase I dose-finding (two-/three-stage). This package also allows users to run dose-finding simulations based on customized decision table.
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
Suggests: knitr
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-05-09 15:12:21 UTC; guow8
Repository: CRAN
Date/Publication: 2020-05-09 15:40:02 UTC

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New package latticeDensity with initial version 1.1.6
Package: latticeDensity
Type: Package
Title: Density Estimation and Nonparametric Regression on Irregular Regions
Version: 1.1.6
Date: 2020-05-08
Author: Ronald Barry <rpbarry@alaska.edu>
Maintainer: Ronald Barry <rpbarry@alaska.edu>
Depends: R (>= 3.5.0)
Imports: splancs, spdep, spatstat, spam, stats, utils, graphics, grDevices, sp, spatialreg
LazyData: true
Suggests: knitr, devtools, roxygen2, testthat, rmarkdown, rgdal
Encoding: UTF-8
Description: Functions that compute the lattice-based density estimator of Barry and McIntyre, which accounts for point processes in two-dimensional regions with irregular boundaries and holes. The package also implements two-dimensional non-parametric regression for similar regions.
License: GPL-2
URL: www.r-project.org
Packaged: 2020-05-09 05:23:46 UTC; ronaldbarry
Repository: CRAN
Date/Publication: 2020-05-09 15:40:06 UTC
RoxygenNote: 7.1.0
VignetteBuilder: knitr
NeedsCompilation: no

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Fri, 08 May 2020

New package snotelr with initial version 1.0.4
Package: snotelr
Title: Calculate and Visualize 'SNOTEL' Snow Data and Seasonality
Version: 1.0.4
Authors@R: person( family = "Hufkens", given = "Koen", email = "koen.hufkens@gmail.com", role = c("aut", "cre"))
Description: Programmatic interface to the 'SNOTEL' snow data (<https://www.wcc.nrcs.usda.gov/snow/>). Provides easy downloads of snow data into your R work space or a local directory. Additional post-processing routines to extract snow season indexes are provided.
URL: https://github.com/khufkens/snotelr
BugReports: https://github.com/khufkens/snotelr/issues
Depends: R (>= 3.6)
Imports: shiny, xml2, httr, utils, stats, rvest, magrittr, wdman, RSelenium, memoise
Suggests: knitr, rmarkdown, covr, testthat, shinydashboard, leaflet, plotly, DT
VignetteBuilder: knitr
License: AGPL-3
LazyData: true
ByteCompile: true
RoxygenNote: 7.0.2
NeedsCompilation: no
Packaged: 2020-05-08 19:29:09 UTC; khufkens
Author: Koen Hufkens [aut, cre]
Maintainer: Koen Hufkens <koen.hufkens@gmail.com>
Repository: CRAN
Date/Publication: 2020-05-08 23:00:02 UTC

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New package PSSMCOOL with initial version 0.1.0
Package: PSSMCOOL
Type: Package
Title: Features Extracted from Position Specific Scoring Matrix (PSSM)
Version: 0.1.0
Imports: utils, entropy, infotheo, phonTools, dtt
Author: Alireza Mohammadi <alireza691111@gmail.com>
Maintainer: Alireza mohammadi <alireza691111@gmail.com>
Depends: R (>= 3.1.0)
Description: Returns almost all features that has been extracted from Position Specific Scoring Matrix (PSSM) so far, which is a matrix of L rows (L is protein length) and 20 columns produced by 'PSI-BLAST' which is a program to produce PSSM Matrix from multiple sequence alignment of proteins see <https://www.ncbi.nlm.nih.gov/books/NBK2590/> for mor details. some of these features are described in Zahiri, J., et al.(2013) <DOI:10.1016/j.ygeno.2013.05.006>, Saini, H., et al.(2016) <DOI:10.17706/jsw.11.8.756-767>, Ding, S., et al.(2014) <DOI:10.1016/j.biochi.2013.09.013>, Cheng, C.W., et al.(2008) <DOI:10.1186/1471-2105-9-S12-S6>, Juan, E.Y., et al.(2009) <DOI:10.1109/CISIS.2009.194>.
License: GPL-3
URL: http://possum.erc.monash.edu/help.jsp, https://github.com/Alireza9651501005/PSSMCOOL
BugReports: https://github.com/Alireza9651501005/PSSMCOOL/issues
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
Suggests: testthat, spelling, waveslim,
Language: en-US
NeedsCompilation: no
Packaged: 2020-05-07 09:53:23 UTC; Alireza
Repository: CRAN
Date/Publication: 2020-05-08 19:20:06 UTC

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New package covid19nytimes with initial version 0.1.3
Package: covid19nytimes
Title: Pulls the Covid-19 Data from the New York Times Public Data Source
Version: 0.1.3
Authors@R: person(given = "Jarrett", family = "Byrnes", role = c("aut", "cre"), email = "jarrett.byrnes@umb.edu", comment = c(ORCID = "0000-0002-9791-9472"))
Description: Accesses the NY Times Covid-19 county-level data for the US, described in <https://www.nytimes.com/article/coronavirus-county-data-us.html> and available at <https://github.com/nytimes/covid-19-data>. It then returns the data in a tidy data format according to the Covid19R Project data specification. If you plan to use the data or publicly display the data or results, please make sure cite the original NY Times source. Please read and follow the terms laid out in the data license at <https://github.com/nytimes/covid-19-data/blob/master/LICENSE>.
License: MIT + file LICENSE
URL: https://github.com/Covid19R/covid19nytimes
BugReports: https://github.com/Covid19R/covid19nytimes/issues
Depends: R (>= 3.0.2)
Imports: dplyr (>= 0.8.5), magrittr (>= 1.5), readr (>= 1.3.1), rlang (>= 0.4.5), tibble (>= 2.1.3), tidyr (>= 1.0.2)
Suggests: ggplot2 (>= 3.2.1), knitr (>= 1.27), purrr (>= 0.3.3), rmarkdown (>= 2.1), sf (>= 0.8.1), stringr (>= 1.4.0), testthat (>= 2.3.1), tigris
VignetteBuilder: knitr
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-04-29 02:27:12 UTC; jebyrnes
Author: Jarrett Byrnes [aut, cre] (<https://orcid.org/0000-0002-9791-9472>)
Maintainer: Jarrett Byrnes <jarrett.byrnes@umb.edu>
Repository: CRAN
Date/Publication: 2020-05-08 19:20:03 UTC

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New package switchcase with initial version 0.1.0
Package: switchcase
Type: Package
Title: A Simple and Flexible Switch-Case Construct for the 'R' Language
Version: 0.1.0
Authors@R: person("Joachim", "Zuckarelli", role = c("aut", "cre"), email = "joachim@zuckarelli.de", comment = c(ORCID = "0000-0002-9280-3016"))
Maintainer: Joachim Zuckarelli <joachim@zuckarelli.de>
Description: Provides a switch-case construct for 'R', as it is known from other programming languages. It allows to test multiple, similar conditions in an efficient, easy-to-read manner, so nested if-else constructs can be avoided. The switch-case construct is designed as an 'R' function that allows to return values depending on which condition is met and lets the programmer flexibly decide whether or not to leave the switch-case construct after a case block has been executed.
License: GPL-3
BugReports: https://github.com/jsugarelli/switchcase/issues
URL: https://github.com/jsugarelli/switchcase/
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-05-07 07:29:06 UTC; Joachim
Author: Joachim Zuckarelli [aut, cre] (<https://orcid.org/0000-0002-9280-3016>)
Repository: CRAN
Date/Publication: 2020-05-08 18:50:02 UTC

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New package rsleep with initial version 1.0.2
Package: rsleep
Type: Package
Title: Analysis of Sleep Data
Version: 1.0.2
Author: Paul Bouchequet <paul.bouchequet@frenchkpi.com>
Maintainer: Paul Bouchequet <paul.bouchequet@frenchkpi.com>
Description: Provides users functions for sleep data management and analysis such as European Data Format (EDF) to Morpheo Data Format (MDF) conversion: P.Bouchequet, D.Jin, G.Solelhac, M.Chennaoui, D.Leger (2018) <doi:10.1016/j.msom.2018.01.130> "Morpheo Data Format (MDF), un nouveau format de donnees simple, robuste et performant pour stocker et analyser les enregistrements de sommeil". Provides hypnogram statistics computing and visualisation functions from the American Academy of Sleep Medicine (AASM) manual "The AASM Manual for the Scoring of Sleep and Associated Events" <https://aasm.org/clinical-resources/scoring-manual/>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: edfReader, jsonlite, ggplot2, signal, phonTools
Suggests: testthat
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-05-07 08:19:04 UTC; paul
Depends: R (>= 3.5.0)
Repository: CRAN
Date/Publication: 2020-05-08 18:10:02 UTC

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New package Rpvt with initial version 0.1.0
Package: Rpvt
Type: Package
Title: Estimate the PVT Properties of Reservoir Fluids
Version: 0.1.0
Date: 2020-04-30
Authors@R: person(given = "Farshad", family = "Tabasinejad", role = c("aut", "cre"), email = "farshad.tabasinejad@susaenergy.com")
Description: Generate the PVT (Pressure-Volume-Temperature) properties of dry gas, wet gas, black oil, and water samples in a tabular format at a constant temperature from the atmospheric pressure up to the pressure of interest using correlations. Spivey, J. P., McCain Jr., W. D. and North, R. (2004) <doi:10.2118/04-07-05>. Sutton, R. P. (2007) <doi:10.2118/97099-PA>. Vasquez, M., and Beggs, H. D. (1980) <doi:10.2118/6719-PA>.
License: GPL-3
URL: https://susaenergy.github.io/Rpvt_ws/
Imports: Rcpp (>= 1.0.3), Rdpack
RdMacros: Rdpack
LinkingTo: Rcpp, RcppArmadillo
Suggests: testthat, knitr, rmarkdown, ggplot2, magrittr, ggpubr
Language: en-US
Encoding: UTF-8
LazyData: TRUE
VignetteBuilder: knitr
RoxygenNote: 7.1.0
NeedsCompilation: yes
Packaged: 2020-05-07 03:59:02 UTC; ftn60
Author: Farshad Tabasinejad [aut, cre]
Maintainer: Farshad Tabasinejad <farshad.tabasinejad@susaenergy.com>
Repository: CRAN
Date/Publication: 2020-05-08 18:40:05 UTC

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New package rjdmarkdown with initial version 0.1.0
Package: rjdmarkdown
Type: Package
Title: 'rmarkdown' Extension for Formatted 'RJDemetra' Outputs
Version: 0.1.0
Authors@R: c( person("Alain", "Quartier-la-Tente", role = c("aut", "cre"), email = "alain.quartier@yahoo.fr", comment = c(ORCID = "0000-0001-7890-3857")))
Description: Functions to have nice 'rmarkdown' outputs of the seasonal and trading day adjustment models made with 'RJDemetra'.
Depends: R (>= 3.1.1),
Imports: RJDemetra, knitr, kableExtra, magrittr
License: EUPL
URL: https://github.com/AQLT/rjdmarkdown
LazyData: TRUE
BugReports: https://github.com/AQLT/rjdmarkdown/issues
SystemRequirements: Java SE 8 or higher
Encoding: UTF-8
RoxygenNote: 7.0.2
VignetteBuilder: knitr
Suggests: rmarkdown, ggdemetra
NeedsCompilation: no
Packaged: 2020-05-06 23:47:59 UTC; alainquartierlatente
Author: Alain Quartier-la-Tente [aut, cre] (<https://orcid.org/0000-0001-7890-3857>)
Maintainer: Alain Quartier-la-Tente <alain.quartier@yahoo.fr>
Repository: CRAN
Date/Publication: 2020-05-08 18:20:02 UTC

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New package nnlib2Rcpp with initial version 0.1.2
Package: nnlib2Rcpp
Type: Package
Title: A Collection of Neural Networks
Version: 0.1.2
Author: Vasilis Nikolaidis [aut, cph, cre] (<https://orcid.org/0000-0003-1471-8788>)
Maintainer: Vasilis Nikolaidis <vnikolaidis@us.uop.gr>
Description: Another collection of neural networks. Includes versions of 'BP', 'Autoencoder', 'LVQ' (supervised and unsupervised), 'MAM'.
LazyData: true
LinkingTo: Rcpp
Imports: Rcpp , methods
License: MIT + file LICENSE
Authors@R: person(given = "Vasilis", family = "Nikolaidis", email = "vnikolaidis@us.uop.gr", role = c("aut", "cph", "cre"), comment = c(ORCID = "0000-0003-1471-8788"))
URL: https://github.com/VNNikolaidis/nnlib2Rcpp
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2020-05-07 08:04:41 UTC; Billy
Repository: CRAN
Date/Publication: 2020-05-08 19:00:03 UTC

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New package kit with initial version 0.0.1
Package: kit
Type: Package
Title: Data Manipulation Functions Implemented in C
Version: 0.0.1
Date: 2020-05-03
Authors@R: c(person("Morgan", "Jacob", role = c("aut", "cre", "cph"), email = "morgan.emailbox@gmail.com"))
Author: Morgan Jacob [aut, cre, cph]
Maintainer: Morgan Jacob <morgan.emailbox@gmail.com>
Description: Basic functions, implemented in C, for large data manipulation. Fast vectorised ifelse()/nested if()/switch() functions, psum()/pprod() functions equivalent to pmin()/pmax() plus others which are missing from base R. Most of these functions are callable at C level.
License: GPL-3
Depends: R (>= 3.1.0)
Encoding: UTF-8
BugReports: https://github.com/2005m/kit/issues
NeedsCompilation: yes
ByteCompile: TRUE
Repository: CRAN
Packaged: 2020-05-07 08:04:52 UTC; giuliabertuzzi
Date/Publication: 2020-05-08 19:00:06 UTC

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New package boot.heterogeneity with initial version 0.1.0
Package: boot.heterogeneity
Type: Package
Title: A Bootstrap-Based Heterogeneity Test for Meta-Analysis
Version: 0.1.0
Authors@R: c(person("Ge", "Jiang", role = c("aut", "cre"), email = "gejiang2@illinois.edu"), person("Han", "Du", role = "aut", email = "hdu@psych.ucla.edu"), person("Zijun", "Ke", role = "ctb", email = "keziyun@mail.sysu.edu.cn"))
Maintainer: Ge Jiang <gejiang2@illinois.edu>
Description: Implements a bootstrap-based heterogeneity test for standardized mean differences (d), Fisher-transformed Pearson's correlations (r), and natural-logarithm-transformed odds ratio (or) in meta-analysis studies. Depending on the presence of moderators, this Monte Carlo based test can be implemented in the random- or mixed-effects model. This package uses rma() function from the R package 'metafor' to obtain parameter estimates and likelihoods, so installation of R package 'metafor' is required. This approach refers to the studies of Anscombe (1956) <doi:10.2307/2332926>, Haldane (1940) <doi:10.2307/2332614>, Hedges (1981) <doi:10.3102/10769986006002107>, Hedges & Olkin (1985, ISBN:978-0123363800), Silagy, Lancaster, Stead, Mant, & Fowler (2004) <doi:10.1002/14651858.CD000146.pub2>, Viechtbauer (2010) <doi:10.18637/jss.v036.i03>, and Zuckerman (1994, ISBN:978-0521432009).
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
URL: https://github.com/gabriellajg/boot.heterogeneity/
BugReports: https://github.com/gabriellajg/boot.heterogeneity/issues
RoxygenNote: 7.1.0
Depends: R (>= 3.1.0)
Imports: stats, metafor, utils, pbmcapply
Suggests: base, HSAUR2, roxygen2, parallel, knitr, rmarkdown, mc.heterogeneity, testthat
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-05-07 03:14:32 UTC; gejiang
Author: Ge Jiang [aut, cre], Han Du [aut], Zijun Ke [ctb]
Repository: CRAN
Date/Publication: 2020-05-08 18:40:02 UTC

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New package BayesSurvival with initial version 0.1.0
Package: BayesSurvival
Type: Package
Title: Bayesian Survival Analysis for Right Censored Data
Version: 0.1.0
Author: Stephanie van der Pas [aut, cre], Ismael Castillo [aut]
Maintainer: Stephanie van der Pas <svdpas@math.leidenuniv.nl>
Description: Performs unadjusted Bayesian survival analysis for right censored time-to-event data. The main function, BayesSurv(), computes the posterior mean and a credible band for the survival function and for the cumulative hazard, as well as the posterior mean for the hazard, starting from a piecewise exponential (histogram) prior with Gamma distributed heights that are either independent, or have a Markovian dependence structure. A function, PlotBayesSurv(), is provided to easily create plots of the posterior means of the hazard, cumulative hazard and survival function, with a credible band accompanying the latter two. The priors and samplers are described in more detail in Castillo and Van der Pas (2020) "Multiscale Bayesian survival analysis" <arXiv:2005.02889>. In that paper it is also shown that the credible bands for the survival function and the cumulative hazard can be considered confidence bands (under mild conditions) and thus offer reliable uncertainty quantification.
Encoding: UTF-8
License: GPL-3
LazyData: false
Depends: R (>= 3.6.0)
Imports: survival, stats, ggplot2
Suggests: simsurv
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-05-07 08:13:24 UTC; stephanie
Repository: CRAN
Date/Publication: 2020-05-08 18:50:08 UTC

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