Tue, 25 Jun 2019

New package PakPMICS2018 with initial version 0.1.0
Package: PakPMICS2018
Type: Package
Title: Multiple Indicator Cluster Survey (MICS) 2017-18 Data for Punjab, Pakistan
Version: 0.1.0
Authors@R: c(person(c("Muhammad", "Yaseen"), email = "myaseen208@gmail.com", role = c("aut", "cre")))
Author: Muhammad Yaseen [aut, cre]
Maintainer: Muhammad Yaseen <myaseen208@gmail.com>
Description: Provides data set and function for exploration of Multiple Indicator Cluster Survey (MICS) 2017-18 data for Punjab, Pakistan. The results of the present survey are critically important for the purposes of SDG monitoring, as the survey produces information on 32 global SDG indicators. The data was collected from 53,840 households selected at the second stage with systematic random sampling out of a sample of 2,692 clusters selected using Probability Proportional to size sampling. Six questionnaires were used in the survey: (1) a household questionnaire to collect basic demographic information on all de jure household members (usual residents), the household, and the dwelling; (2) a water quality testing questionnaire administered in three households in each cluster of the sample; (3) a questionnaire for individual women administered in each household to all women age 15-49 years; (4) a questionnaire for individual men administered in every second household to all men age 15-49 years; (5) an under-5 questionnaire, administered to mothers (or caretakers) of all children under 5 living in the household; and (6) a questionnaire for children age 5-17 years, administered to the mother (or caretaker) of one randomly selected child age 5-17 years living in the household (<http://www.mics.unicef.org/surveys>).
Depends: R (>= 3.5.0)
Imports: tibble
License: GPL-2
URL: https://github.com/myaseen208/PakPMICS2018, https://myaseen208.github.io/PakPMICS2018/
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Note: Department of Mathematics and Statistics, University of Agriculture Faisalabad, Faisalabad-Pakistan.
Suggests: testthat, R.rsp
VignetteBuilder: R.rsp
NeedsCompilation: no
Packaged: 2019-06-20 01:39:43 UTC; myaseen
Repository: CRAN
Date/Publication: 2019-06-25 15:40:06 UTC

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New package secsse with initial version 2.0.0
Package: secsse
Type: Package
Title: Several Examined and Concealed States-Dependent Speciation and Extinction
Version: 2.0.0
Date: 2019-06-22
License: GPL-3
Authors@R: c( person("Leonel", "Herrera Alsina", email = "leonelhalsina@gmail.com", role = "cre"), person("Paul", "van Els", email = "paulvanels@gmail.com", role = "aut"), person("Rampal", "Etienne", email = "r.s.etienne@rug.nl", role = "aut"))
Description: Simultaneously infers state-dependent diversification across two or more states of a single or multiple traits while accounting for the role of a possible concealed trait. See Herrera-Alsina et al. 2019 Systematic Biology 68: 317-328 <DOI:10.1093/sysbio/syy057>.
Depends: R (>= 3.5.0)
Imports: utils, DDD (>= 4.0), ape, foreach, doParallel, apTreeshape, phylobase, geiger, deSolve
Suggests: diversitree, phytools, testthat, testit, knitr, rmarkdown
Enhances: doMC
NeedsCompilation: yes
Encoding: UTF-8
LazyData: true
VignetteBuilder: knitr
RoxygenNote: 6.1.1
Packaged: 2019-06-23 15:46:35 UTC; rampa
Author: Leonel Herrera Alsina [cre], Paul van Els [aut], Rampal Etienne [aut]
Maintainer: Leonel Herrera Alsina <leonelhalsina@gmail.com>
Repository: CRAN
Date/Publication: 2019-06-25 11:30:03 UTC

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Mon, 24 Jun 2019

New package metapost with initial version 1.0-6
Package: metapost
Type: Package
Title: Interface to 'MetaPost'
Version: 1.0-6
Author: Paul Murrell
Maintainer: Paul Murrell <paul@stat.auckland.ac.nz>
Description: Provides an interface to 'MetaPost' (Hobby, 1998) <http://www.tug.org/docs/metapost/mpman.pdf>. There are functions to generate an R description of a 'MetaPost' curve, functions to generate 'MetaPost' code from an R description, functions to process 'MetaPost' code, and functions to read solved 'MetaPost' paths back into R.
Imports: grid, gridBezier
Suggests: grImport
SystemRequirements: mpost
URL: https://github.com/pmur002/metapost, https://stattech.wordpress.fos.auckland.ac.nz/2018/12/03/2018-12-metapost-three-ways/
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2019-06-24 20:52:29 UTC; pmur002
Repository: CRAN
Date/Publication: 2019-06-24 22:20:03 UTC

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New package mcglm with initial version 0.5.0
Package: mcglm
Type: Package
Title: Multivariate Covariance Generalized Linear Models
Version: 0.5.0
Date: 2019-06-25
Author: Wagner Hugo Bonat [aut, cre], Walmes Marques Zeviani [ctb], Fernando de Pol Mayer [ctb]
Maintainer: Wagner Hugo Bonat <wbonat@ufpr.br>
Authors@R: c(person(c("Wagner","Hugo"), "Bonat", role = c("aut", "cre"), email = "wbonat@ufpr.br"), person(c("Walmes","Marques"), "Zeviani", role = "ctb"), person(c("Fernando", "de Pol"), "Mayer", role = "ctb"))
Description: Fitting multivariate covariance generalized linear models (McGLMs) to data. McGLM is a general framework for non-normal multivariate data analysis, designed to handle multivariate response variables, along with a wide range of temporal and spatial correlation structures defined in terms of a covariance link function combined with a matrix linear predictor involving known matrices. The models take non-normality into account in the conventional way by means of a variance function, and the mean structure is modelled by means of a link function and a linear predictor. The models are fitted using an efficient Newton scoring algorithm based on quasi-likelihood and Pearson estimating functions, using only second-moment assumptions. This provides a unified approach to a wide variety of different types of response variables and covariance structures, including multivariate extensions of repeated measures, time series, longitudinal, spatial and spatio-temporal structures. The package offers a user-friendly interface for fitting McGLMs similar to the glm() R function. See Bonat (2018) <doi:10.18637/jss.v084.i04>, for more information and examples.
Depends: R (>= 3.2.1)
Suggests: testthat, plyr, lattice, latticeExtra, knitr, rmarkdown, MASS, mvtnorm, tweedie, devtools
Imports: stats, Matrix, assertthat, graphics, Rcpp (>= 0.12.16)
License: GPL-3 | file LICENSE
LazyData: TRUE
URL: https://github.com/wbonat/mcglm
BugReports: https://github.com/wbonat/mcglm/issues
Encoding: UTF-8
VignetteBuilder: knitr
RoxygenNote: 6.1.1
LinkingTo: Rcpp, RcppArmadillo
NeedsCompilation: yes
Packaged: 2019-06-24 18:45:49 UTC; wagner
Repository: CRAN
Date/Publication: 2019-06-24 19:30:03 UTC

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New package spatialfusion with initial version 0.6
Package: spatialfusion
Imports: methods, graphics, stats, utils, rstan, sp, geoR, SDraw, fields
Suggests: INLA, testthat, tmap, R.rsp
Depends: R (>= 3.4.0), Rcpp
Type: Package
VignetteBuilder: R.rsp
Title: Multivariate Analysis of Spatial Data Using a Unifying Spatial Fusion Framework
Version: 0.6
Date: 2019-06-21
Authors@R: c( person("Craig", "Wang", email = "craig.wang@uzh.ch", role = c("aut","cre"),comment = c(ORCID = "0000-0003-1804-2463")), person("Reinhard", "Furrer", email = "reinhard.furrer@math.uzh.ch", role = "ctb",comment = c(ORCID = "0000-0002-6319-2332")))
Maintainer: Craig Wang <craig.wang@uzh.ch>
Description: Multivariate modelling of geostatistical (point), lattice (areal) and point pattern data in a unifying spatial fusion framework. Details are given in Wang and Furrer (2019) <arXiv:1906.00364>. Model inference is done using either 'Stan' <https://mc-stan.org/> or 'INLA' <http://www.r-inla.org>.
License: GPL (>= 3)
Encoding: UTF-8
LazyData: TRUE
NeedsCompilation: no
Packaged: 2019-06-21 18:36:19 UTC; crwang
Author: Craig Wang [aut, cre] (<https://orcid.org/0000-0003-1804-2463>), Reinhard Furrer [ctb] (<https://orcid.org/0000-0002-6319-2332>)
Repository: CRAN
Date/Publication: 2019-06-24 18:50:37 UTC

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New package mcgfa with initial version 2.2.1
Package: mcgfa
Version: 2.2.1
Type: Package
Title: Mixtures of Contaminated Gaussian Factor Analyzers
Authors@R: c(person("Martin", "Blostein", role = c("aut", "cre"), email="martin.blostein@gmail.com"), person("Antonio", "Punzo", role = "aut"), person(c("Paul", "D."), "McNicholas", role = c("aut","ths")))
Description: Clustering and classification using the Mixtures of Contaminated Gaussian Factor Analyzers model. Allows for automatic detection of outliers and noise. Punzo, A, Blostein, M, McNicholas, PD (2017) <arXiv:1408.2128v2>.
Imports: stats, parallel
License: GPL (>= 2)
LazyData: TRUE
NeedsCompilation: yes
Packaged: 2019-06-23 20:13:43 UTC; martin
Author: Martin Blostein [aut, cre], Antonio Punzo [aut], Paul D. McNicholas [aut, ths]
Maintainer: Martin Blostein <martin.blostein@gmail.com>
Repository: CRAN
Date/Publication: 2019-06-24 14:30:03 UTC

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New package GenTag with initial version 1.0
Package: GenTag
Type: Package
Title: Generate Color Tag Sequences
Version: 1.0
Date: 2019-06-21
Author: Carlos Biagolini-Jr.
Maintainer: Carlos Biagolini-Jr.<c.biagolini@gmail.com>
Description: Implement a coherent and flexible protocol for animal color tagging. 'GenTag' provides a simple computational routine with low CPU usage to create color sequences for animal tag. First, a single-color tag sequence is created from an algorithm selected by the user, followed by verification of the combination uniqueness. Three methods to produce color tag sequences are provided. Users can modify the main function core to allow a wide range of applications.
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2019-06-23 15:15:06 UTC; biago
Depends: R (>= 3.5.0)
Repository: CRAN
Date/Publication: 2019-06-24 14:20:03 UTC

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New package sensibo.sky with initial version 1.0.0
Package: sensibo.sky
Title: Access to 'Sensibo Sky' API V2 for Air Conditioners Remote Control
Version: 1.0.0
Authors@R: person("Gabriele", "Baldassarre", role = c("aut", "cre"), email = "gabriele@gabrielebaldassarre.com")
Description: Provides an interface to the 'Sensibo Sky' API which allows to remotely control non-smart air conditioning units. See <https://sensibo.com> for more informations.
URL: https://github.com/theclue/sensibo.sky
BugReports: https://github.com/theclue/sensibo.sky/issues
Depends: R (>= 3.0)
License: MIT + file LICENSE
LazyData: true
NeedsCompilation: no
Imports: httr, jsonlite, glue
Suggests: testthat
RoxygenNote: 6.1.1
Packaged: 2019-06-22 12:54:14 UTC; rstudio
Author: Gabriele Baldassarre [aut, cre]
Maintainer: Gabriele Baldassarre <gabriele@gabrielebaldassarre.com>
Repository: CRAN
Date/Publication: 2019-06-24 13:10:03 UTC

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New package mmetrics with initial version 0.1.0
Package: mmetrics
Type: Package
Title: Easy Computation of Marketing Metrics with Different Analysis Axis
Version: 0.1.0
Authors@R: c( person("Shinichi", "Takayanagi", , "shinichi.takayanagi@gmail.com", role = c("aut", "cre")), person("Nagi", "Teramo", , "teramonagi@gmail.com", role = c("aut")), person("Takahiro", "Yoshinaga", , "t.yoshinaga0106@gmail.com", role = c("aut")) )
Description: Provides a mechanism for easy computation of marketing metrics. By default in this package, metrics for digital marketing (e.g. CTR (Click Through Rate), CVR (Conversion Rate), CPC (Cost Per Click) etc) are calculated but you can define your own metrics easily. In addition to that, you can change an analysis axis to calculate these metrics.
URL: https://github.com/shinichi-takayanagi/mmetrics
BugReports: https://github.com/shinichi-takayanagi/mmetrics/issues
License: MIT + file LICENSE
Encoding: UTF-8
Imports: magrittr, dplyr, purrr, stringr, rlang
Suggests: covr, devtools, testthat, knitr, rmarkdown
LazyData: true
RoxygenNote: 6.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-06-23 06:54:12 UTC; stakaya
Author: Shinichi Takayanagi [aut, cre], Nagi Teramo [aut], Takahiro Yoshinaga [aut]
Maintainer: Shinichi Takayanagi <shinichi.takayanagi@gmail.com>
Repository: CRAN
Date/Publication: 2019-06-24 13:30:03 UTC

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New package kernelPSI with initial version 1.0.0
Package: kernelPSI
Title: Post-Selection Inference for Nonlinear Variable Selection
Version: 1.0.0
Date: 2019-06-20
Authors@R: c(person("Lotfi", "Slim", email = "lotfi.slim@mines-paristech.fr", role = c("aut", "cre")), person("Clément", "Chatelain", email = "clement.chatelain@sanofi.com", role = "ctb"), person("Chloé-Agathe", "Azencott", email = "chloe-agathe.azencott@mines-paristech.fr", role ="ctb"), person("Jean-Philippe", "Vert", email = "jpvert@google.com", role ="ctb"))
Description: Different post-selection inference strategies for kernel selection, as described in "kernelPSI: a Post-Selection Inference Framework for Nonlinear Variable Selection", Slim et al., Proceedings of Machine Learning Research, 2019, <http://proceedings.mlr.press/v97/slim19a/slim19a.pdf>. The strategies rest upon quadratic kernel association scores to measure the association between a given kernel and an outcome of interest. The inference step tests for the joint effect of the selected kernels on the outcome. A fast constrained sampling algorithm is proposed to derive empirical p-values for the test statistics.
URL: http://proceedings.mlr.press/v97/slim19a.html
Depends: R (>= 3.5.0)
License: GPL (>= 2)
Imports: Rcpp (>= 1.0.1), CompQuadForm, tmg, pracma, kernlab, lmtest
Suggests: bindata, knitr, rmarkdown, MASS, testthat
Encoding: UTF-8
LinkingTo: Rcpp, RcppArmadillo
VignetteBuilder: knitr
RoxygenNote: 6.1.1
NeedsCompilation: yes
Packaged: 2019-06-22 21:28:24 UTC; lotfislim
Author: Lotfi Slim [aut, cre], Clément Chatelain [ctb], Chloé-Agathe Azencott [ctb], Jean-Philippe Vert [ctb]
Maintainer: Lotfi Slim <lotfi.slim@mines-paristech.fr>
Repository: CRAN
Date/Publication: 2019-06-24 13:20:03 UTC

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New package SeqNet with initial version 1.0.0
Package: SeqNet
Title: Generate RNA-Seq Data from Gene-Gene Association Networks
Version: 1.0.0
Authors@R: c(person("Tyler", "Grimes", role = c("aut", "cre"), email = "tyler.grimes@ufl.edu"), person("Somnath", "Datta", role = c("aut")))
Author: Tyler Grimes [aut, cre], Somnath Datta [aut]
Maintainer: Tyler Grimes <tyler.grimes@ufl.edu>
Description: Methods to generate random gene-gene association networks and simulate RNA-seq data from them. Includes functions to generate random networks of any size and perturb them to obtain differential networks. Network objects are built from individual, overlapping modules that represent pathways. The resulting network has various topological properties that are characteristic of gene regulatory networks. RNA-seq data can be generated such that the association among gene expression profiles reflect the underlying network. A reference RNA-seq dataset can be provided to model realistic marginal distributions. Plotting functions are available to visualize a network, compare two networks, and compare the expression of two genes across multiple networks.
Depends: R (>= 3.5.0)
Imports: fitdistrplus, ggplot2, grDevices, graphics, igraph, mvtnorm, purrr, RColorBrewer, tibble, Rcpp, rlang, stats, utils
Suggests: knitr, rmarkdown, testthat
License: GPL-2 | GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
LinkingTo: Rcpp
NeedsCompilation: yes
Packaged: 2019-06-21 18:24:30 UTC; Grimes
Repository: CRAN
Date/Publication: 2019-06-24 11:10:03 UTC

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New package hagis with initial version 2.0.0
Package: hagis
Title: Analysis of Plant Pathogen Pathotype Complexities, Distributions and Diversity
Version: 2.0.0
Authors@R: c( person(given = "Austin G.", family = "McCoy", role = c("aut", "ccp"), email = "mccoyaus@msu.edu", comment = c(ORCID = "0000-0003-2483-4184")), person(given = "Zachary", family = "Noel", role = c("aut", "ccp"), email = "noelzach@msu.edu", comment = c(ORCID = "0000-0001-6375-8300")), person(given = "Adam H.", family = "Sparks", role = c("aut", "cre"), email = "adam.sparks@usq.edu.au", comment = c(ORCID = "0000-0002-0061-8359")), person(given = "Martin", family = "Chilvers", role = "aut", email = "chilvers@msu.edu ", comment = c(ORCID = "0000-0001-8832-1666")) )
Description: Analysis of plant pathogen pathotype survey data. Functions provided calculate distribution of susceptibilities, distribution of complexities with statistics, pathotype frequency distribution, as well as diversity indices for pathotypes. This package is meant to be a direct replacement for Herrmann, Löwer, Schachtel's (1999) <doi:10.1046/j.1365-3059.1999.00325.x> Habgood-Gilmour Spreadsheet, 'HaGiS', previously used for pathotype analysis.
Depends: R (>= 3.2.0)
Imports: data.table, ggplot2, graphics, pander, stats, utils, vegan
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Suggests: covr, knitr, pkgdown, rmarkdown, testthat, vdiffr
VignetteBuilder: knitr
RoxygenNote: 6.1.1
Language: en-US
URL: https://github.com/openplantpathology/hagis, https://openplantpathology.github.io/hagis/
BugReports: https://github.com/openplantpathology/hagis/issues
X-schema.org-applicationCategory: Tools
X-schema.org-keywords: plant-pathology, pathotype, pathogen-survey, virulence analysis, differential set, assessment scale
X-schema.org-isPartOf: https://openplantpathology.org
NeedsCompilation: no
Packaged: 2019-06-22 03:09:55 UTC; adamsparks
Author: Austin G. McCoy [aut, ccp] (<https://orcid.org/0000-0003-2483-4184>), Zachary Noel [aut, ccp] (<https://orcid.org/0000-0001-6375-8300>), Adam H. Sparks [aut, cre] (<https://orcid.org/0000-0002-0061-8359>), Martin Chilvers [aut] (<https://orcid.org/0000-0001-8832-1666>)
Maintainer: Adam H. Sparks <adam.sparks@usq.edu.au>
Repository: CRAN
Date/Publication: 2019-06-24 11:50:03 UTC

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New package blrm with initial version 1.0-1
Package: blrm
Title: Dose Escalation Design in Phase I Oncology Trial Using Bayesian Logistic Regression Modeling
Version: 1.0-1
Date: 2019-06-16
Author: Furong Sun <furongs@vt.edu>, Zhonggai Li <zli@bostonbiomedical.com>
Depends: R (>= 2.15.1)
Imports: boot, rjags, mvtnorm, openxlsx, reshape2
Description: Plan dose escalation design using adaptive Bayesian logistic regression modeling in Phase I oncology trial.
Maintainer: Furong Sun <furongs@vt.edu>
License: LGPL
NeedsCompilation: no
Packaged: 2019-06-21 18:16:05 UTC; furong
Repository: CRAN
Date/Publication: 2019-06-24 11:00:04 UTC

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Fri, 21 Jun 2019

New package shinyMolBio with initial version 0.1
Package: shinyMolBio
Type: Package
Title: Molecular Biology Visualization Tools for 'Shiny' Apps
Version: 0.1
Date: 2019-06-20
Authors@R: c( person("Konstantin A.", "Blagodatskikh", email = "k.blag@yandex.ru", role = c("cre", "aut")))
Description: Interactive visualization of 'RDML' files via 'shiny' apps. Package provides (1) PCR plate interface with ability to select individual tubes and (2) amplification/melting plots.
License: MIT + file LICENSE
URL: https://github.com/kablag/shinyMolBio
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.4.0)
Imports: dplyr, purrr, checkmate, RDML, shiny, stringr, whisker, plotly, lazyeval, RColorBrewer
Collate: 'global.R' 'pcrPlate-input.R' 'renderCurves.R' 'runExample.R'
Suggests: knitr, chipPCR
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-06-21 08:24:08 UTC; kablag
Author: Konstantin A. Blagodatskikh [cre, aut]
Maintainer: Konstantin A. Blagodatskikh <k.blag@yandex.ru>
Repository: CRAN
Date/Publication: 2019-06-21 16:20:03 UTC

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New package ormPlot with initial version 0.3.2
Package: ormPlot
Type: Package
Title: Advanced Plotting of Ordinal Regression Models
Version: 0.3.2
Authors@R: c(person("Richard", "Meitern", , "richard.meitern@ut.ee", c("aut", "cre")))
Maintainer: Richard Meitern <richard.meitern@ut.ee>
Description: An extension to the Regression Modeling Strategies package that facilitates plotting ordinal regression model predictions together with confidence intervals for each dependent variable level. It also adds a functionality to plot the model summary as a modifiable object.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.5.0)
Imports: ggplot2 (>= 3.1.0), rms (>= 5.1.3), gtable (>= 0.3.0), grid (>= 3.5.0)
Suggests: testthat (>= 2.1.0), vdiffr (>= 0.3.0), knitr (>= 1.22), rmarkdown (>= 1.13), pander (>= 0.6.3)
RoxygenNote: 6.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-06-21 13:16:22 UTC; rix133
Author: Richard Meitern [aut, cre]
Repository: CRAN
Date/Publication: 2019-06-21 16:30:08 UTC

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New package cppRouting with initial version 1.1
Package: cppRouting
Type: Package
Title: Fast Implementation of Dijkstra Algorithm
Version: 1.1
Date: 2019-06-15
Author: Vincent Larmet
Maintainer: Vincent Larmet <larmet.vincent@gmail.com>
Description: Calculation of distances, shortest paths and isochrones on weighted graphs using several variants of Dijkstra algorithm. Proposed algorithms are unidirectional Dijkstra (Dijkstra, E. W. (1959) <doi:10.1007/BF01386390>), bidirectional Dijkstra (Goldberg, Andrew & Fonseca F. Werneck, Renato (2005) <https://pdfs.semanticscholar.org/0761/18dfbe1d5a220f6ac59b4de4ad07b50283ac.pdf>), A* search (P. E. Hart, N. J. Nilsson et B. Raphael (1968) <doi:10.1109/TSSC.1968.300136>), new bidirectional A* (Pijls & Post (2009) <http://repub.eur.nl/pub/16100/ei2009-10.pdf>).
License: GPL (>= 2)
Imports: Rcpp (>= 1.0.1), parallel
LinkingTo: Rcpp
SystemRequirements: GNU make, C++11
RoxygenNote: 6.1.1
URL: https://github.com/vlarmet/cppRouting
Suggests: knitr, rmarkdown, igraph
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2019-06-21 13:53:49 UTC; vlarmet
Repository: CRAN
Date/Publication: 2019-06-21 16:30:12 UTC

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New package rmdcev with initial version 0.9.0
Package: rmdcev
Type: Package
Title: Multiple Discrete-Continuous Extreme Value (MDCEV) Model
Version: 0.9.0
Authors@R: c( person(given = "Patrick", family = "Lloyd-Smith", role = c("aut", "cre"), email = "patrick.lloydsmith@usask.ca"), person("Trustees of", "Columbia University", role = "cph"))
Maintainer: Patrick Lloyd-Smith <patrick.lloydsmith@usask.ca>
Description: Estimates different multiple discrete-continuous extreme value (MDCEV) demand model specifications with observed and unobserved individual heterogeneity (Bhat (2008) <doi:10.1016/j.trb.2007.06.002>). Fixed parameter, latent class, and random parameter models can be estimated. These models are estimated using maximum likelihood or Bayesian estimation techniques and are implemented in 'Stan', which is a C++ package for performing full Bayesian inference (see Stan Development Team (2018) <http://mc-stan.org>). The 'rmdcev' package also includes functions for demand simulation (Pinjari and Bhat (2011) <https://repositories.lib.utexas.edu/handle/2152/23880>) and welfare simulation (Lloyd-Smith (2018) <doi:10.1016/j.jocm.2017.12.002>).
License: MIT + file LICENSE
Depends: R (>= 3.4.0), Rcpp (>= 0.12.0), methods
Imports: rstan (>= 2.18.2), rstantools (>= 1.5.1), dplyr (>= 0.7.8), tidyselect, parallel, stringr, purrr, tibble, tidyr, rlang, utils, stats, tmvtnorm
LinkingTo: BH (>= 1.66.0), Rcpp (>= 0.12.0), RcppEigen (>= 0.3.3.4.0), rstan (>= 2.18.2), StanHeaders (>= 2.18.0)
Encoding: UTF-8
LazyData: true
NeedsCompilation: yes
SystemRequirements: GNU make C++14
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown, testthat
Packaged: 2019-06-20 23:21:03 UTC; Pat
Author: Patrick Lloyd-Smith [aut, cre], Trustees of Columbia University [cph]
Repository: CRAN
Date/Publication: 2019-06-21 15:00:03 UTC

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New package pesel with initial version 0.7.2
Package: pesel
Type: Package
Title: Automatic Estimation of Number of Principal Components in PCA
Version: 0.7.2
Date: 2019-06-17
Author: Piotr Sobczyk, Julie Josse, Malgorzata Bogdan
Maintainer: Piotr Sobczyk <pj.sobczyk@gmail.com>
Description: Automatic estimation of number of principal components in PCA with PEnalized SEmi-integrated Likelihood (PESEL). See Piotr Sobczyk, Malgorzata Bogdan, Julie Josse 'Bayesian dimensionality reduction with PCA using penalized semi-integrated likelihood' (2017) <doi:10.1080/10618600.2017.1340302>.
License: GPL-3
Encoding: UTF-8
URL: https://github.com/psobczyk/pesel
BugReports: https://github.com/psobczyk/pesel/issues
Depends: R (>= 3.1.3),
Imports: stats, graphics
LazyData: TRUE
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-06-20 17:44:21 UTC; piotr
Repository: CRAN
Date/Publication: 2019-06-21 14:40:03 UTC

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New package usdarnass with initial version 0.1.0
Package: usdarnass
Type: Package
Title: USDA NASS Quick Stats API
Version: 0.1.0
Description: An alternative for downloading various United States Department of Agriculture (USDA) data from <https://quickstats.nass.usda.gov/> through R. You must sign up for an API token from the mentioned website in order for this package to work.
URL: https://github.com/rdinter/usdarnass
BugReports: https://github.com/rdinter/usdarnass/issues
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: httr, jsonlite, methods, utils, readr
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown, tidyverse, dplyr, tidyr
VignetteBuilder: knitr
Authors@R: c(person(given = "Robert", family = "Dinterman", role = c("cre", "aut"), email = "robert.dinterman@gmail.com", comment = c(ORCID = "0000-0002-9055-6082")), person(given = "Jonathan", family = "Eyer", role = "aut", email = "jeyer@usc.edu"))
NeedsCompilation: no
Packaged: 2019-06-20 15:22:05 UTC; robert
Author: Robert Dinterman [cre, aut] (<https://orcid.org/0000-0002-9055-6082>), Jonathan Eyer [aut]
Maintainer: Robert Dinterman <robert.dinterman@gmail.com>
Repository: CRAN
Date/Publication: 2019-06-21 08:50:03 UTC

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New package imgw with initial version 0.1.0
Package: imgw
Title: Polish Meteorological and Hydrological Data
Version: 0.1.0
Authors@R: c(person(given = "Bartosz", family = "Czernecki", role = c("aut", "cre"), email = "nwp@amu.edu.pl", comment = c(ORCID = "0000-0001-6496-1386")), person(given = "Arkadiusz", family = "Głogowski", role = "aut"), person(given = "Jakub", family = "Nowosad", role = "aut", email = "nowosad.jakub@gmail.com", comment = c(ORCID = "0000-0002-1057-3721")), person("IMGW-PIB", role = "ctb", comment = "source of the data"))
Description: Download Polish meteorological and hydrological data from the Institute of Meteorology and Water Management - National Research Institute (<https://dane.imgw.pl/>). This package also allows for adding geographical coordinates for each observation.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Depends: R (>= 3.1)
Imports: RCurl, XML
Suggests: testthat
URL: https://imgw.ml
BugReports: https://github.com/bczernecki/imgw/issues
NeedsCompilation: no
Packaged: 2019-06-20 09:48:45 UTC; bartosz
Author: Bartosz Czernecki [aut, cre] (<https://orcid.org/0000-0001-6496-1386>), Arkadiusz Głogowski [aut], Jakub Nowosad [aut] (<https://orcid.org/0000-0002-1057-3721>), IMGW-PIB [ctb] (source of the data)
Maintainer: Bartosz Czernecki <nwp@amu.edu.pl>
Repository: CRAN
Date/Publication: 2019-06-21 08:20:14 UTC

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New package SDMtune with initial version 0.1.0
Package: SDMtune
Type: Package
Title: Species Distribution Model Selection
Version: 0.1.0
Date: 2019-06-20
Authors@R: c( person("Sergio", "Vignali", email = "sergio.vignali@iee.unibe.ch", role = c("aut", "cre"), comment = c(ORCID = "00000-0002-3390-5442")), person("Arnaud", "Barras", role = "aut", comment = c(ORCID = "0000-0003-0850-6965")), person("Veronika", "Braunisch", role = "aut", comment = c(ORCID = "00000-0001-7035-4662")), person("Conservation Biology - University of Bern", role = "fnd") )
Description: User-friendly framework that enables the training and the evaluation of species distribution models (SDMs). The package implements functions for data driven variable selection and model tuning and includes numerous utilities to display the results. All the functions used to select variables or to tune model hyperparameters have an interactive real-time chart displayed in the 'RStudio' viewer pane during their execution. At the moment only the maximum entropy method is available using the 'Java' implementation, Phillips et al. (2006) <doi:10.1016/j.ecolmodel.2005.03.026>, through the 'dismo' package and the 'R' implementation through the 'maxnet' package, Phillips et al. (2017) <doi:10.1111/ecog.03049>. 'SDMtune' uses its own script to predict maxent models, resulting in much faster predictions for large datasets compared to native predictions from the use of the 'Java' software. This reduces considerably the computation time when tuning the model using the AICc.
License: GPL-3
URL: https://consbiol-unibern.github.io/SDMtune/
BugReports: https://github.com/ConsBiol-unibern/SDMtune/issues
Depends: R (>= 3.2.0)
Imports: cli (>= 1.1.0), crayon (>= 1.3.4), dismo (>= 1.1-4), ggplot2 (>= 3.2.0), htmltools (>= 0.3.6), jsonlite (>= 1.6), kableExtra (>= 1.1.0), maxnet (>= 0.1.2), methods, progress (>= 1.2.2), raster (>= 2.9-5), rasterVis (>= 0.45), Rcpp (>= 1.0.1), reshape2 (>= 1.4.3), rgdal (>= 1.4-4), rJava (>= 0.9-11), rstudioapi (>= 0.10), scales (>= 1.0.0), stringr (>= 1.4.0), whisker (>= 0.3-2)
Encoding: UTF-8
LazyData: true
LinkingTo: Rcpp
RoxygenNote: 6.1.1
Suggests: covr, knitr (>= 1.23), maps (>= 3.3.0), pkgdown (>= 1.3.0), rmarkdown (>= 1.13), roxygen2 (>= 6.1.1), snow (>= 0.4-3), testthat (>= 2.1.1), zeallot (>= 0.1.0)
VignetteBuilder: knitr
Collate: 'Maxent_class.R' 'Maxnet_class.R' 'RcppExports.R' 'SDMmodel2MaxEnt.R' 'SWD_class.R' 'SDMmodelCV.R' 'SDMmodel_class.R' 'SDMtune.R' 'SDMtune_class.R' 'aicc.R' 'auc.R' 'chart_utils.R' 'condor.R' 'confMatrix.R' 'corVar.R' 'doJk.R' 'getSubsample.R' 'gridSearch.R' 'maxentTh.R' 'maxentVarImp.R' 'mergeSWD.R' 'modelReport.R' 'optimizeModel.R' 'plotCor.R' 'plotJk.R' 'plotPA.R' 'plotPred.R' 'plotROC.R' 'plotResponse.R' 'plotVarImp.R' 'predict_Maxent.R' 'predict_SDMmodel.R' 'prepareSWD.R' 'randomSearch.R' 'reduceVar.R' 'swd2csv.R' 'thinData.R' 'thresholds.R' 'train.R' 'trainMaxent.R' 'trainMaxnet.R' 'trainValTest.R' 'tss.R' 'utils.R' 'varImp.R' 'varSel.R' 'zzz.R'
NeedsCompilation: yes
Packaged: 2019-06-20 07:08:49 UTC; vignali
Author: Sergio Vignali [aut, cre] (<https://orcid.org/00000-0002-3390-5442>), Arnaud Barras [aut] (<https://orcid.org/0000-0003-0850-6965>), Veronika Braunisch [aut] (<https://orcid.org/00000-0001-7035-4662>), Conservation Biology - University of Bern [fnd]
Maintainer: Sergio Vignali <sergio.vignali@iee.unibe.ch>
Repository: CRAN
Date/Publication: 2019-06-21 08:00:20 UTC

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New package psSubpathway with initial version 0.1.0
Package: psSubpathway
Type: Package
Title: Flexible Identification of Phenotype-Specific Subpathways
Version: 0.1.0
Author: Xudong Han, Junwei Han, Qingfei Kong
Maintainer: Junwei Han <hanjunwei1981@163.com>
Description: A network-based systems biology tool for flexible identification of phenotype-specific subpathways in the cancer gene expression data with multiple categories (such as multiple subtype or developmental stages of cancer). Subtype Set Enrichment Analysis (SubSEA) and Dynamic Changed Subpathway Analysis (DCSA) are developed to flexible identify subtype specific and dynamic changed subpathways respectively. The operation modes include extraction of subpathways from biological pathways, inference of subpathway activities in the context of gene expression data, identification of subtype specific subpathways with SubSEA, identification of dynamic changed subpathways associated with the cancer developmental stage with DCSA, and visualization of the activities of resulting subpathways by using box plots and heat maps. Its capabilities render the tool could find the specific abnormal subpathways in the cancer dataset with multi-phenotype samples.
Depends: R (>= 3.5.0)
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Imports: GSVA, igraph,mpmi, pheatmap
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2019-06-20 00:31:29 UTC; 12859
Repository: CRAN
Date/Publication: 2019-06-21 07:20:04 UTC

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New package frostr with initial version 0.1.0
Package: frostr
Type: Package
Title: R Client to MET Norway's 'Frost' API
Version: 0.1.0
Authors@R: person("Iman", "Ghayoornia", email = "ghayoornia.iman@gmail.com", role = c("aut", "cre"))
Description: An unofficial R client to MET Norway's 'Frost' API <https://frost.met.no/index2.html> to retrieve data as data frames. The 'Frost' API, and the underlying data, is made available by the Norwegian Meteorological Institute (MET Norway). The data and products are distributed under the Norwegian License for Open Data 2.0 (NLOD) <https://data.norge.no/nlod/en/2.0> and Creative Commons 4.0 <https://creativecommons.org/licenses/by/4.0/>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Imports: httr, jsonlite, tibble, tidyr
Suggests: testthat
NeedsCompilation: no
Packaged: 2019-06-19 22:45:25 UTC; ImanGhayoornia
Author: Iman Ghayoornia [aut, cre]
Maintainer: Iman Ghayoornia <ghayoornia.iman@gmail.com>
Repository: CRAN
Date/Publication: 2019-06-21 07:10:03 UTC

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Thu, 20 Jun 2019

New package TSE with initial version 0.1.0
Package: TSE
Type: Package
Title: Total Survey Error
Version: 0.1.0
Authors@R: c(person("Joshua", "Miller", role = c("aut", "cre"), email = "joshlmiller@msn.com"))
Maintainer: Joshua Miller <joshlmiller@msn.com>
Description: Calculates total survey error (TSE) for one or more surveys, using common scale-dependent and/or scale-independent metrics. On TSE, see: Weisberg, Herbert (2005, ISBN:0-226-89128-3); Biemer, Paul (2010) <doi:10.1093/poq/nfq058>.
Note: Package TSE works directly from the data set – no hand calculations required. Just upload a properly structured data set (see TESTNUMB and its documentation), properly input column names (see examples in the functions documentation), and run your functions.
Imports: stats
Depends: R (>= 3.5)
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown
NeedsCompilation: no
Packaged: 2019-06-19 12:21:48 UTC; JOSHUA
Author: Joshua Miller [aut, cre]
Repository: CRAN
Date/Publication: 2019-06-20 09:10:03 UTC

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Wed, 19 Jun 2019

New package SemNetDictionaries with initial version 0.1.2
Package: SemNetDictionaries
Title: Dictionaries for the 'SemNetCleaner' Package
Version: 0.1.2
Date: 2019-06-19
Author: Alexander P. Christensen
Maintainer: Alexander P. Christensen <alexpaulchristensen@gmail.com>
Description: Implements dictionaries that can be used in the 'SemNetCleaner' package. Also includes several functions aimed at facilitating the text cleaning analysis in the 'SemNetCleaner' package. This package is designed to integrate and update word lists and dictionaries based on each user's individual needs by allowing users to store and save their own dictionaries. Dictionaries can be added to the 'SemNetDictionaries' package by submitting user-defined dictionaries to <https://github.com/AlexChristensen/SemNetDictionaries>.
Depends: R (>= 3.5.0)
License: GPL (>= 3.0)
URL: https://github.com/AlexChristensen/SemNetDictionaries
BugReports: https://github.com/AlexChristensen/SemNetDictionaries/issues
NeedsCompilation: no
Encoding: UTF-8
LazyData: true
Imports: tcltk
RoxygenNote: 6.1.1
Packaged: 2019-06-19 17:24:31 UTC; APCHRIST
Repository: CRAN
Date/Publication: 2019-06-19 22:15:19 UTC

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New package lobstr with initial version 1.1.0
Package: lobstr
Title: Visualize R Data Structures with Trees
Version: 1.1.0
Authors@R: c( person("Hadley", "Wickham", , "hadley@rstudio.com", role = c("aut", "cre")), person("RStudio", role = "cph") )
Description: A set of tools for inspecting and understanding R data structures inspired by str(). Includes ast() for visualizing abstract syntax trees, ref() for showing shared references, cst() for showing call stack trees, and obj_size() for computing object sizes.
License: GPL-3
URL: https://github.com/r-lib/lobstr
BugReports: https://github.com/r-lib/lobstr/issues
Depends: R (>= 3.2)
Imports: crayon, Rcpp, rlang (>= 0.3.0)
Suggests: covr, pillar, pkgdown, testthat
LinkingTo: Rcpp
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: yes
Packaged: 2019-06-19 20:40:32 UTC; hadley
Author: Hadley Wickham [aut, cre], RStudio [cph]
Maintainer: Hadley Wickham <hadley@rstudio.com>
Repository: CRAN
Date/Publication: 2019-06-19 22:00:23 UTC

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New package ui with initial version 0.1.0
Package: ui
Title: Uncertainty Intervals and Sensitivity Analysis for Missing Data
Version: 0.1.0
Author: Minna Genbaeck [aut, cre],
Maintainer: Minna Genbaeck <minna.genback@umu.se>
Description: Implements functions to derive uncertainty intervals for (i) regression (linear and probit) parameters when outcome is missing not at random (non-ignorable missingness) introduced in Genbaeck, M., Stanghellini, E., de Luna, X. (2015) <doi:10.1007/s00362-014-0610-x> and Genbaeck, M., Ng, N., Stanghellini, E., de Luna, X. (2018) <doi:10.1007/s10433-017-0448-x>; and (ii) double robust and outcome regression estimators of average causal effects (on the treated) with possibly unobserved confounding introduced in Genbaeck, M., de Luna, X. (2018) <doi:10.1111/biom.13001>.
Depends: R (>= 3.5)
Imports: Matrix, maxLik, mvtnorm, numDeriv, graphics, stats
Suggests: MASS
Encoding: UTF-8
LazyData: true
License: GPL-2
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-06-19 09:28:53 UTC; miahjr04
Repository: CRAN
Date/Publication: 2019-06-19 12:10:03 UTC

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New package shrinkTVP with initial version 1.0.0
Package: shrinkTVP
Type: Package
Title: Efficient Bayesian Inference for Time-Varying Parameter Models with Shrinkage
Version: 1.0.0
Authors@R: c( person("Peter", "Knaus", email = "peter.knaus@wu.ac.at", role = c("aut", "cre"), comment = c(ORCID = "0000-0001-6498-7084")), person("Angela", "Bitto-Nemling", role = "aut"), person("Annalisa", "Cadonna", email = "annalisa.cadonna@wu.ac.at", role = "aut", comment = c(ORCID = "0000-0003-0360-7628")), person("Sylvia", "Frühwirth-Schnatter", email = "sylvia.fruehwirth-schnatter@wu.ac.at", role = "aut", comment = c(ORCID = "0000-0003-0516-5552")), person("Daniel", "Winkler", email = "daniel.winkler@wu.ac.at", role = "ctb"), person("Kemal", "Dingic", role = "ctb"))
Description: Efficient Markov chain Monte Carlo (MCMC) algorithms for fully Bayesian estimation of time-varying parameter models with shrinkage priors. Details on the algorithms used are provided in Bitto and Frühwirth-Schnatter (2019) <doi:10.1016/j.jeconom.2018.11.006>.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.3.0)
Imports: Rcpp, GIGrvg, stochvol, coda, methods, utils
LinkingTo: Rcpp, RcppArmadillo, GIGrvg, RcppProgress, stochvol
RoxygenNote: 6.1.1
Suggests: testthat
NeedsCompilation: yes
Packaged: 2019-06-19 09:59:04 UTC; pknaus
Author: Peter Knaus [aut, cre] (<https://orcid.org/0000-0001-6498-7084>), Angela Bitto-Nemling [aut], Annalisa Cadonna [aut] (<https://orcid.org/0000-0003-0360-7628>), Sylvia Frühwirth-Schnatter [aut] (<https://orcid.org/0000-0003-0516-5552>), Daniel Winkler [ctb], Kemal Dingic [ctb]
Maintainer: Peter Knaus <peter.knaus@wu.ac.at>
Repository: CRAN
Date/Publication: 2019-06-19 12:10:07 UTC

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New package MatchIt.mice with initial version 1.0.3
Type: Package
Package: MatchIt.mice
Title: Selecting Matched Samples from Multiply Imputed Datasets
Description: Selects matched samples from the control and treatment groups of each imputed datasets and estimates the weight of each individual in the complete distribution of control and treatment groups of the imputed datasets. Please see the package GitHub page <https://github.com/FarhadPishgar/MatchIt.mice/> for more details.
Version: 1.0.3
Author: Farhad Pishgar
Maintainer: Farhad Pishgar <Farhad.Pishgar@Gmail.com>
URL: https://github.com/FarhadPishgar/MatchIt.mice
BugReports: https://github.com/FarhadPishgar/MatchIt.mice/issues
Depends: R (>= 2.10)
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: mice, MatchIt
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-06-19 09:35:45 UTC; Farhad
Repository: CRAN
Date/Publication: 2019-06-19 12:10:19 UTC

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New package shinymanager with initial version 1.0
Package: shinymanager
Title: Authentication Management for 'Shiny' Applications
Version: 1.0
Authors@R: c( person("Benoit", "Thieurmel", email = "benoit.thieurmel@datastorm.fr", role = c("aut", "cre")), person("Victor", "Perrier", email = "victor.perrier@dreamRs.fr", role = c("aut")) )
Description: Simple and secure authentification mechanism for single 'Shiny' applications. Credentials are stored in an encrypted 'SQLite' database. Source code of main application is protected until authentication is successful.
License: GPL-3
URL: https://github.com/datastorm-open/shinymanager
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Imports: R6, shiny, htmltools, DT (>= 0.5), DBI, RSQLite, openssl, R.utils, billboarder
Suggests: keyring, testthat (>= 2.1.0)
NeedsCompilation: no
Packaged: 2019-06-18 09:15:34 UTC; Datastorm
Author: Benoit Thieurmel [aut, cre], Victor Perrier [aut]
Maintainer: Benoit Thieurmel <benoit.thieurmel@datastorm.fr>
Repository: CRAN
Date/Publication: 2019-06-19 11:20:04 UTC

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New package portfolioBacktest with initial version 0.1.0
Package: portfolioBacktest
Title: Automated Backtesting of Portfolios over Multiple Datasets
Version: 0.1.0
Date: 2019-06-19
Description: Automated backtesting of multiple portfolios over multiple datasets of stock prices in a rolling-window fashion. Intended for researchers and practitioners to backtest a set of different portfolios, as well as by a course instructor to assess the students in their portfolio design in a fully automated and convenient manner, with results conveniently formatted in tables and plots. Each portfolio design is easily defined as a function that takes as input a window of the stock prices and outputs the portfolio weights. Multiple portfolios can be easily specified as a list of functions or as files in a folder. Multiple datasets can be conveniently extracted randomly from different markets, different time periods, and different subsets of the stock universe. The results can be later assessed and ranked with tables based on a number of performance criteria (e.g., expected return, volatility, Sharpe ratio, drawdown, turnover rate, return on investment, computational time, etc.), as well as plotted in a number of ways with nice barplots and boxplots.
Authors@R: c( person(c("Daniel", "P."), "Palomar", role = c("cre", "aut"), email = "daniel.p.palomar@gmail.com"), person("Rui", "Zhou", role = "aut", email = "rzhouae@connect.ust.hk") )
Maintainer: Daniel P. Palomar <daniel.p.palomar@gmail.com>
URL: https://CRAN.R-project.org/package=portfolioBacktest, https://github.com/dppalomar/portfolioBacktest
BugReports: https://github.com/dppalomar/portfolioBacktest/issues
License: GPL-3 | file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Depends: R (>= 2.10)
Imports: doSNOW, evaluate, foreach, PerformanceAnalytics, quantmod, R.utils, snow, utils, xts, zoo
Suggests: CVXR, DT, ggplot2, gridExtra, knitr, prettydoc, readtext, rmarkdown, R.rsp, stringi, testthat
VignetteBuilder: knitr, rmarkdown, R.rsp
NeedsCompilation: no
Packaged: 2019-06-19 05:30:35 UTC; palomar
Author: Daniel P. Palomar [cre, aut], Rui Zhou [aut]
Repository: CRAN
Date/Publication: 2019-06-19 11:40:02 UTC

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New package nlMS with initial version 1.0
Package: nlMS
Type: Package
Title: Non-Linear Model Selection
Version: 1.0
Author: Carme Font <carme.font.moragon@gmail.com>
Maintainer: Carme Font <carme.font.moragon@gmail.com>
Description: Package to select best model among several linear and nonlinear models. The main function uses the gnls() function from the 'nlme' package to fit the data to nine regression models, named: "linear", "quadratic", "cubic", "logistic", "exponential", "power", "monod", "haldane", "logit".
License: GPL-3
Imports: nlme, stats, graphics, grDevices
NeedsCompilation: no
Packaged: 2019-06-03 10:07:56 UTC; cfont
Repository: CRAN
Date/Publication: 2019-06-19 11:50:02 UTC

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New package wwntests with initial version 1.0.0
Package: wwntests
Type: Package
Title: Hypothesis Tests for Functional Time Series
Version: 1.0.0
Author: Daniel Petoukhov [aut, cre]
Maintainer: Daniel Petoukhov <dvpetouk@uwaterloo.ca>
Authors@R: person("Daniel", "Petoukhov", email = "dvpetouk@uwaterloo.ca", role = c("aut", "cre"))
Description: Provides an array of white noise hypothesis tests for functional data and related visualizations. These include tests based on the norms of autocovariance operators that are built under both strong and weak white noise assumptions. Additionally, tests based on the spectral density operator and on principal component dimensional reduction are included, which are built under strong white noise assumptions. These methods are described in Kokoszka et al. (2017) <doi:10.1016/j.jmva.2017.08.004>, Characiejus and Rice (2019) <doi:10.1016/j.ecosta.2019.01.003>, and Gabrys and Kokoszka (2007) <doi:10.1198/016214507000001111>, respectively.
License: GPL-3
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.4.0)
Imports: sde, stats, ftsa, rainbow, MASS, graphics
Suggests: testthat, knitr, rmarkdown, fOptions, CompQuadForm, tensorA
RoxygenNote: 6.1.1
VignetteBuilder: knitr
BugReports: https://github.com/jimthemadmanlahey/wwntests/issues
NeedsCompilation: no
Packaged: 2019-06-18 22:08:43 UTC; daniel
Repository: CRAN
Date/Publication: 2019-06-19 10:50:03 UTC

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New package StratifiedMedicine with initial version 0.1.0
Package: StratifiedMedicine
Type: Package
Title: Stratified Medicine
Version: 0.1.0
Author: Thomas Jemielita [aut, cre]
Maintainer: Thomas Jemielita <thomasjemielita@gmail.com>
Description: A toolkit for stratified medicine, subgroup identification, and precision medicine. Current tools include (1) filtering models (reduce covariate space), (2) patient-level estimate models (counterfactual patient-level quantities, for example the individual treatment effect), (3) subgroup identification models (find subsets of patients with similar treatment effects), and (4) parameter estimation and inference (for the overall population and discovered subgroups). These tools can directly feed into stratified medicine algorithms including PRISM (patient identifiers for stratified medicine; Jemielita and Mehrotra 2019 (in progress)). PRISM is a flexible and general framework which accepts user-created models/functions. This package is in beta and will be continually updated.
License: GPL-3
Encoding: UTF-8
LazyData: true4
Depends: R (>= 3.1),
Imports: dplyr, partykit, rpart, ranger, BART, grf, survival, survRM2, glmnet, ggplot2, mvtnorm, coin, TH.data
RoxygenNote: 6.1.1
URL: https://github.com/thomasjemielita/StratifiedMedicine
Suggests: knitr, rmarkdown, MASS
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-06-18 20:23:22 UTC; thoma
Repository: CRAN
Date/Publication: 2019-06-19 09:50:03 UTC

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New package mixSPE with initial version 0.1.1
Package: mixSPE
Type: Package
Title: Mixtures of Power Exponential and Skew Power Exponential Distributions for Use in Model-Based Clustering and Classification
Version: 0.1.1
Date: 2019-06-18
Author: Utkarsh J. Dang[aut, cre], Michael P. B. Gallaugher[ctb], Ryan P. Browne[aut, cre], and Paul D. McNicholas[aut]
Maintainer: Utkarsh J. Dang <udang@binghamton.edu>
Description: Mixtures of skewed and elliptical distributions are implemented using mixtures of multivariate skew power exponential and power exponential distributions, respectively. A generalized expectation-maximization framework is used for parameter estimation. Methodology for mixtures of power exponential distributions is from Dang et al. (2015) <doi: 10.1111/biom.12351>.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Imports: mvtnorm
Suggests: testthat
NeedsCompilation: no
Packaged: 2019-06-18 15:20:36 UTC; udang
Repository: CRAN
Date/Publication: 2019-06-19 09:10:02 UTC

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New package lgrdata with initial version 0.1.1
Package: lgrdata
Type: Package
Title: Example Datasets for a Learning Guide to R
Version: 0.1.1
Authors@R: c(person("Remko", "Duursma", email = "remkoduursma@gmail.com", role = c("aut", "cre")), person("Jeff","Powell", role="ctb"))
Description: A largish collection of example datasets, including several classics. Many of these datasets are well suited for regression, classification, and visualization.
Encoding: UTF-8
Depends: R (>= 2.10)
Suggests: ggplot2
LazyData: false
License: CC0
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-06-18 17:44:42 UTC; remko
Author: Remko Duursma [aut, cre], Jeff Powell [ctb]
Maintainer: Remko Duursma <remkoduursma@gmail.com>
Repository: CRAN
Date/Publication: 2019-06-19 09:40:03 UTC

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New package klustR with initial version 0.1.0
Package: klustR
Title: D3 Dynamic Cluster Visualizations
Description: Used to create dynamic, interactive 'D3.js' based parallel coordinates and principal component plots in 'R'. The plots make visualizing k-means or other clusters simple and informative.
Version: 0.1.0
Authors@R: person("McKay", "Davis", email = "mckaymdavis@gmail.com", role = c("aut", "cre"))
URL: https://mckaymdavis.github.io/klustR/, https://github.com/McKayMDavis/klustR
BugReports: https://github.com/McKayMDavis/klustR/issues
License: GPL (>= 3)
Depends: R (>= 3.6.0)
Imports: htmlwidgets (>= 0.3.2), jsonlite
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-06-18 18:01:08 UTC; mckaydavis
Author: McKay Davis [aut, cre]
Maintainer: McKay Davis <mckaymdavis@gmail.com>
Repository: CRAN
Date/Publication: 2019-06-19 09:40:08 UTC

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New package gert with initial version 0.1
Package: gert
Type: Package
Title: Simple Git Client
Version: 0.1
Author: Jeroen Ooms
Maintainer: Jeroen Ooms <jeroen@berkeley.edu>
Description: Minimal git client for R based on 'libgit2' <https://libgit2.org/>. This package requires a somewhat recent version of 'libgit2' is installed on the system.
License: MIT + file LICENSE
SystemRequirements: libgit2 (>= 0.26): libgit2-devel (rpm) or libgit2-dev (deb)
URL: http://github.com/r-lib/gert (devel), https://libgit2.org (upstream)
BugReports: http://github.com/r-lib/gert/issues
Encoding: UTF-8
RoxygenNote: 6.1.1
Imports: credentials (>= 1.0), askpass, openssl
Suggests: testthat
NeedsCompilation: yes
Packaged: 2019-06-18 14:16:33 UTC; jeroen
Repository: CRAN
Date/Publication: 2019-06-19 09:00:03 UTC

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New package BisqueRNA with initial version 1.0
Package: BisqueRNA
Title: Decomposition of Bulk Expression with Single-Cell Sequencing
Version: 1.0
Authors@R: c( person(given = 'Brandon', family = 'Jew', email = 'brandon.jew@ucla.edu', role = c('aut', 'cre')), person(given = 'Marcus', family = 'Alvarez', role = 'aut') )
Description: Provides tools to accurately estimate cell type abundances from heterogeneous bulk expression. A reference-based method utilizes single-cell information to generate a signature matrix and transformation of bulk expression for accurate regression based estimates. A marker-based method utilizes known cell-specific marker genes to measure relative abundances across samples. For more details, see Jew and Alvarez et al (2019) <doi:10.1101/669911>.
Depends: R (>= 3.5.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Imports: Biobase, lsei, methods, stats
Suggests: Seurat, plyr, knitr, rmarkdown, testthat
URL: https://www.biorxiv.org/content/10.1101/669911v1
BugReports: https://github.com/cozygene/bisque/issues
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-06-18 17:27:50 UTC; bjew
Author: Brandon Jew [aut, cre], Marcus Alvarez [aut]
Maintainer: Brandon Jew <brandon.jew@ucla.edu>
Repository: CRAN
Date/Publication: 2019-06-19 09:30:09 UTC

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New package scriptName with initial version 1.0.1
Package: scriptName
Title: Determine a Script's Filename from Within the Script Itself
Description: A small set of functions wrapping up the call stack and command line inspection needed to determine a running script's filename from within the script itself.
Version: 1.0.1
Authors@R: c( person("Thomas", "Sibley", email = "trsibley@uw.edu", role = c("aut", "cre")), person("University of Washington", role = c("cph")), person("Travers", "Ching", email = "traversc@gmail.com", role = c("ctb")) )
License: MIT + file LICENSE
URL: https://github.com/MullinsLab/scriptName
BugReports: https://github.com/MullinsLab/scriptName/issues
Imports: rlang (>= 0.1.0), purrr (>= 0.2.3)
Suggests: testthat, devtools
RoxygenNote: 6.1.1
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2019-06-19 06:36:17 UTC; tom
Author: Thomas Sibley [aut, cre], University of Washington [cph], Travers Ching [ctb]
Maintainer: Thomas Sibley <trsibley@uw.edu>
Repository: CRAN
Date/Publication: 2019-06-19 07:40:03 UTC

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Tue, 18 Jun 2019

New package treeplyr with initial version 0.1.6
Package: treeplyr
Type: Package
Title: 'dplyr' Functionality for Matched Tree and Data Objects
Version: 0.1.6
Date: 2019-06-18
Author: Josef Uyeda
Maintainer: Josef Uyeda <josef.uyeda@gmail.com>
Description: Matches phylogenetic trees and trait data, and allows simultaneous manipulation of the tree and data using 'dplyr'.
License: GPL-2 | GPL-3
Depends: ape (>= 3.0-6), dplyr (>= 0.8.0), R (>= 3.1.2)
Imports: Rcpp (>= 0.10.3), lazyeval, phytools, geiger
LinkingTo: Rcpp
URL: https://github.com/uyedaj/treeplyr
BugReports: https://github.com/uyedaj/treeplyr/issues
RoxygenNote: 6.1.1
NeedsCompilation: yes
Packaged: 2019-06-18 19:20:42 UTC; juyeda
Repository: CRAN
Date/Publication: 2019-06-18 21:50:03 UTC

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New package srm with initial version 0.1-166
Package: srm
Type: Package
Title: Structural Equation Modeling for the Social Relations Model
Version: 0.1-166
Date: 2019-06-18 10:32:43
Author: Steffen Nestler [aut], Alexander Robitzsch [aut, cre], Oliver Luedtke [aut]
Maintainer: Alexander Robitzsch <robitzsch@ipn.uni-kiel.de>
Description: Provides functionality for structural equation modeling for the social relations model (Warner, Kenny, & Soto, 1979, <doi:10.1037/0022-3514.37.10.1742>). Maximum likelihood estimation (Gill & Swartz, 2001, <doi:10.2307/3316080>; Nestler, 2018, <doi:10.3102/1076998617741106>) and least squares estimation is supported (Bond & Malloy, 2018, <doi:10.1016/B978-0-12-811967-9.00014-X>).
Depends: R (>= 3.1)
Imports: Rcpp, stats, utils
Enhances: amen, TripleR
LinkingTo: Rcpp, RcppArmadillo
License: GPL (>= 2)
URL: https://github.com/alexanderrobitzsch/srm, https://sites.google.com/site/alexanderrobitzsch2/software
NeedsCompilation: yes
Packaged: 2019-06-18 08:33:56 UTC; sunpn563
Repository: CRAN
Date/Publication: 2019-06-18 16:10:02 UTC

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New package NonProbEst with initial version 0.1.0
Package: NonProbEst
Type: Package
Title: Estimation in Nonprobability Sampling
Version: 0.1.0
Author: Luis Castro Martín <luiscastro193@gmail.com>, Ramón Ferri García <rferri@ugr.es> and María del Mar Rueda <mrueda@ugr.es>
Maintainer: Luis Castro Martín <luiscastro193@gmail.com>
Description: Different inference procedures are proposed in the literature to correct for selection bias that might be introduced with non-random selection mechanisms. A class of methods to correct for selection bias is to apply a statistical model to predict the units not in the sample (super-population modeling). Other studies use calibration or Statistical Matching (statistically match nonprobability and probability samples). To date, the more relevant methods are weighting by Propensity Score Adjustment (PSA). The Propensity Score Adjustment method was originally developed to construct weights by estimating response probabilities and using them in Horvitz–Thompson type estimators. This method is usually used by combining a non-probability sample with a reference sample to construct propensity models for the non-probability sample. Calibration can be used in a posterior way to adding information of auxiliary variables. Propensity scores in PSA are usually estimated using logistic regression models. Machine learning classification algorithms can be used as alternatives for logistic regression as a technique to estimate propensities. The package 'NonProbEst' implements some of these methods and thus provides a wide options to work with data coming from a non-probabilistic sample.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Imports: caret, sampling, e1071
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-06-18 09:45:56 UTC; luis
Repository: CRAN
Date/Publication: 2019-06-18 16:10:13 UTC

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New package AlphaPart with initial version 0.6.0
Package: AlphaPart
Title: Partition/Decomposition of Additive Genetic Values by Paths of Information
Description: Additive genetic (breeding) value represents a sum of additive gene effects over whole genome and can be inferred from phenotype values of relatives via pedigree based mixed models. The partitioning method is described in Garcia-Cortes et al. (2008) <DOI:10.1017/S175173110800205X>.
Author: Gregor Gorjanc, Jana Obsteter
Maintainer: Gregor Gorjanc <gregor.gorjanc@roslin.ed.ac.uk>
License: GPL (>= 2)
LazyLoad: yes
Imports: directlabels (>= 1.1), gdata (>= 2.6.0), ggplot2 (>= 0.8.9), pedigree (>= 1.3.1), quadprog (>= 1.5-3), Rcpp (>= 0.9.4), reshape
Suggests: RColorBrewer (>= 1.0-2), truncnorm (>= 1.0-5), knitr, rmarkdown, testthat
LinkingTo: Rcpp
Version: 0.6.0
Date: 2019-05-20
NeedsCompilation: yes
Packaged: 2019-06-18 10:46:09 UTC; jana
VignetteBuilder: knitr
RoxygenNote: 6.1.1
Encoding: UTF-8
Repository: CRAN
Date/Publication: 2019-06-18 16:30:03 UTC

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New package websocket with initial version 1.0.0
Package: websocket
Version: 1.0.0
Title: 'WebSocket' Client Library
Description: Provides a 'WebSocket' client interface for R. 'WebSocket' is a protocol for low-overhead real-time communication: <https://en.wikipedia.org/wiki/WebSocket>.
Authors@R: c( person("Alan", "Dipert", role = c("aut", "cre"), email = "alan@rstudio.com"), person("Barbara", "Borges", role = c("aut")), person("Winston", "Chang", role = c("aut"), email = "winston@rstudio.com"), person("Joe", "Cheng", role = c("aut"), email = "joe@rstudio.com"), person(family = "RStudio", role = "cph"), person("Peter", "Thorson", role = c("ctb", "cph"), comment = "WebSocket++ library"), person("René", "Nyffenegger", role = c("ctb", "cph"), comment = "Base 64 library"), person("Micael", "Hildenborg", role = c("ctb", "cph"), comment = "SHA1 library"), person(family = "Aladdin Enterprises", role = "cph", comment = "MD5 library"), person("Bjoern", "Hoehrmann", role = c("ctb", "cph"), comment = "UTF8 Validation library"))
License: GPL-2
Encoding: UTF-8
LazyData: true
ByteCompile: true
Imports: Rcpp, R6, later
LinkingTo: Rcpp, BH, AsioHeaders
SystemRequirements: GNU make, OpenSSL >= 1.0.1
RoxygenNote: 6.1.1
Collate: 'RcppExports.R' 'websocket.R'
Suggests: testthat, knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2019-06-07 20:02:23 UTC; alan
Author: Alan Dipert [aut, cre], Barbara Borges [aut], Winston Chang [aut], Joe Cheng [aut], RStudio [cph], Peter Thorson [ctb, cph] (WebSocket++ library), René Nyffenegger [ctb, cph] (Base 64 library), Micael Hildenborg [ctb, cph] (SHA1 library), Aladdin Enterprises [cph] (MD5 library), Bjoern Hoehrmann [ctb, cph] (UTF8 Validation library)
Maintainer: Alan Dipert <alan@rstudio.com>
Repository: CRAN
Date/Publication: 2019-06-18 15:10:03 UTC

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New package RadioGx with initial version 0.0.1
Package: RadioGx
Type: Package
Title: Analysis of Large-Scale Radio-Genomic Data
Version: 0.0.1
Date: 2019-05-31
Authors@R: c( person("Venkata","Manem", email = "mail2mvskumar@gmail.com", role = c("aut")), person("Petr","Smirnov", email = "petr.smirnov@uhnresearch.ca", role = c("aut")), person("Ian","Smith", email = "ianc.smith@mail.utoronto.ca", role = c("aut")), person("Meghan","Lambie", email = "megan.lambie@mail.utoronto.ca", role = c("aut")), person("Christopher","Eeles", email = "christopher.eeles@uhnresearch.ca", role = c("aut")), person("Scott", "Bratman", email = "scott.bratman@rmp.uhn.ca", role = c("aut")), person("Benjamin","Haibe-Kains", email = "benjamin.haibe.kains@utoronto.ca", role = c("aut","cre")) )
Description: Computational tool box for radio-genomic analysis which integrates radio-response data, radio-biological modelling and comprehensive cell line annotations for hundreds of cancer cell lines. The 'RadioSet' class enables creation and manipulation of standardized datasets including information about cancer cells lines, radio-response assays and dose-response indicators. Included methods allow fitting and plotting dose-response data using established radio-biological models along with quality control to validate results. Additional functions related to fitting and plotting dose response curves, quantifying statistical correlation and calculating area under the curve (AUC) or survival fraction (SF) are included. For more details please see the included documentation, references, as well as: Manem, V. et al (2018) <doi:10.1101/449793>.
License: GPL-3
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.5.0), CoreGx
Imports: PharmacoGx, Biobase, RColorBrewer, caTools, magicaxis, methods, reshape2, KernSmooth, cluster, Matrix, scales
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-06-17 17:21:50 UTC; chris
Author: Venkata Manem [aut], Petr Smirnov [aut], Ian Smith [aut], Meghan Lambie [aut], Christopher Eeles [aut], Scott Bratman [aut], Benjamin Haibe-Kains [aut, cre]
Maintainer: Benjamin Haibe-Kains <benjamin.haibe.kains@utoronto.ca>
Repository: CRAN
Date/Publication: 2019-06-18 15:50:02 UTC

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New package neatRanges with initial version 0.1.0
Package: neatRanges
Type: Package
Title: Tidy Up Date/Time Ranges
Version: 0.1.0
Author: Aljaz Jelenko [aut, cre]
Maintainer: Aljaz Jelenko <aljaz.jelenko@amis.net>
BugReports: https://github.com/arg0naut91/neatRanges/issues
Description: Collapse, partition, combine, fill gaps in and expand date/time ranges.
URL: https://github.com/arg0naut91/neatRanges
License: MIT + file LICENSE
Depends: R (>= 3.1.0)
Imports: data.table
Encoding: UTF-8
LazyData: true
Suggests: testthat
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-06-17 17:30:36 UTC; aljaz_000
Repository: CRAN
Date/Publication: 2019-06-18 15:30:03 UTC

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New package gausscov with initial version 0.0.1
Package: gausscov
Title: The Gaussian Covariate Method for Variable Selection
Version: 0.0.1
Authors@R: person("Laurie", "Davies", role = c("aut","cre"),email ="laurie.davies@uni-due.de")
Author: Laurie Davies [aut, cre]
Maintainer: Laurie Davies <laurie.davies@uni-due.de>
Description: Given the standard linear model the traditional way of deciding whether to include the jth covariate is to apply the F-test to decide whether the corresponding beta coefficient is zero. The Gaussian covariate method is completely different. The question as to whether the beta coefficient is or is not zero is replaced by the question as to whether the covariate is better or worse than i.i.d. Gaussian noise. The P-value for the covariate is the probability that Gaussian noise is better. Surprisingly this can be given exactly and it is the same a the P-value for the classical model based on the F-distribution. The Gaussian covariate P-value is model free, it is the same for any data set. Using the idea it is possible to do covariate selection for a small number of covariates 25 by considering all subsets. Post selection inference causes no problems as the P-values hold whatever the data. The idea extends to stepwise regression again with exact probabilities. In the simplest version the only parameter is a specified cut-off P-value which can be interpreted as the probability of a false positive being included in the final selection. For more information see the website below and the accompanying papers: L. Davies and L. Duembgen, "A Model-free Approach to Linear Least Squares Regression with Exact Probabilities and Applications to Covariate Selection", 2019, <arXiv:1906.01990>. L. Davies, "Lasso, Knockoff and Gaussian covariates: A comparison", 2018, <arXiv:1807.09633v4>.
License: GPL-3
Depends: R (>= 2.10), stats
Encoding: UTF-8
RoxygenNote: 6.1.1
NeedsCompilation: yes
Packaged: 2019-06-17 13:42:00 UTC; laurie
Repository: CRAN
Date/Publication: 2019-06-18 15:30:07 UTC

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New package FEprovideR with initial version 0.1.0
Package: FEprovideR
Title: Fixed Effects Logistic Model with High-Dimensional Parameters
Version: 0.1.0
Authors@R: c( person(given = "Kevin(Zhi)", family = "He", role = c("aut"), email = "kevinhe@umich.edu"), person(given = "Wenbo", family = "Wu", role = c("aut"), email = "wenbowu@umich.edu"), person(given = "Michael", family = "Kleinsasser", role = c("cre"), email = "mkleinsa@umich.edu"))
Description: A structured profile likelihood algorithm for the logistic fixed effects model and an approximate expectation maximization (EM) algorithm for the logistic mixed effects model. Based on He, K., Kalbfleisch, J.D., Li, Y. and Li, Y. (2013) <doi:10.1007/s10985-013-9264-6>.
License: GPL-2
Imports: ggplot2, Matrix, poibin
Encoding: UTF-8
LazyData: true
BugReports: https://github.com/umich-biostatistics/FEprovideR/issues
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-06-17 16:34:39 UTC; mkleinsa
Author: Kevin(Zhi) He [aut], Wenbo Wu [aut], Michael Kleinsasser [cre]
Maintainer: Michael Kleinsasser <mkleinsa@umich.edu>
Depends: R (>= 3.5.0)
Repository: CRAN
Date/Publication: 2019-06-18 15:20:03 UTC

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New package rskey with initial version 0.4.1
Package: rskey
Title: Create Custom 'Rstudio' Keyboard Shortcuts
Version: 0.4.1
Date: 2019-05-24
Authors@R: person("Berry", "Boessenkool", email = "berry-b@gmx.de", role = c("aut", "cre"))
Description: Create custom keyboard shortcuts to examine code selected in the 'Rstudio' editor. F3 can for example yield 'str(selection)' and F7 open the source code of CRAN and base package functions on 'github'.
Imports: graphics, utils, shiny (>= 0.13), miniUI (>= 0.1.1), rstudioapi (>= 0.5), berryFunctions (>= 1.17.21)
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
BugReports: https://github.com/brry/rskey/issues
NeedsCompilation: no
Packaged: 2019-05-24 20:33:29 UTC; Berry
Author: Berry Boessenkool [aut, cre]
Maintainer: Berry Boessenkool <berry-b@gmx.de>
Repository: CRAN
Date/Publication: 2019-06-18 14:30:03 UTC

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New package dataesgobr with initial version 1.0.0
Package: dataesgobr
Title: Access and Use Spain Government's API
Version: 1.0.0
Authors@R: c(person("Adrian", "Perez", email = "adrianpelopez@gmail.com", role = "cre"), person("Francisco", "Charte", email = "francisco@fcharte.com", role = "aut"))
Description: Functions intended to work with the API of the Spain Government <https://datos.gob.es/en/apidata> that allows you to download, analyze and generate information through datasets obtained from the API. The API containing information about multiples topics from the municipalities and organizations of Spain, it is possible to find URIs corresponding to the primary sector taxonomy and the identification of geographical coverage defined in Annexes IV and V <https://www.boe.es/diario_boe/txt.php?id=BOE-A-2013-2380> (NTI).
License: LGPL (>= 3) | file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Imports: stringr, dplyr, readr, httr, stringi, jsonlite, graphics, readxl, readODS, yaml, shiny, shinythemes, shinycssloaders, shinyjs, DT, shinyFiles
Suggests: testthat
NeedsCompilation: no
Packaged: 2019-06-17 08:18:49 UTC; adpl
Author: Adrian Perez [cre], Francisco Charte [aut]
Maintainer: Adrian Perez <adrianpelopez@gmail.com>
Repository: CRAN
Date/Publication: 2019-06-18 14:50:03 UTC

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New package APFr with initial version 1.0.2
Package: APFr
Type: Package
Title: Multiple Testing Approach using Average Power Function (APF) and Bayes FDR Robust Estimation
Version: 1.0.2
Date: 2019-06-14
Authors@R: c(person("Nicolò", "Margaritella", email = "N.Margaritella@sms.ed.ac.uk", role = c("cre", "aut")), person("Piero", "Quatto", role = "aut"))
Author: Nicolò Margaritella [cre, aut], Piero Quatto [aut]
Maintainer: Nicolò Margaritella <N.Margaritella@sms.ed.ac.uk>
Depends: R (>= 3.5.0)
Imports: stats (>= 3.5.2), graphics (>= 3.5.2)
Description: Implements a multiple testing approach to the choice of a threshold gamma on the p-values using the Average Power Function (APF) and Bayes False Discovery Rate (FDR) robust estimation. Function apf_fdr() estimates both quantities from either raw data or p-values. Function apf_plot() produces smooth graphs and tables of the relevant results. Details of the methods can be found in Quatto P, Margaritella N, et al. (2019) <doi:10.1177/0962280219844288>.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-06-17 07:49:35 UTC; Nico
Repository: CRAN
Date/Publication: 2019-06-18 12:20:07 UTC

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Mon, 17 Jun 2019

New package rjdqa with initial version 0.1.0
Package: rjdqa
Type: Package
Title: Quality Assessment for Seasonal Adjustment
Version: 0.1.0
Authors@R: c( person("Alain", "Quartier-la-Tente", role = c("aut", "cre"), email = "alain.quartier@yahoo.fr"))
Description: Add-in to the 'RJDemetra' package on seasonal adjustments. It allows to produce quality assessments outputs (dashboards, quality report matrix, etc.).
License: EUPL
Depends: R (>= 3.1.1), RJDemetra,
Imports: plotrix, utils, graphics, stats
Encoding: UTF-8
URL: https://github.com/AQLT/rjdqa
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-06-16 08:36:41 UTC; alainquartierlatente
Author: Alain Quartier-la-Tente [aut, cre]
Maintainer: Alain Quartier-la-Tente <alain.quartier@yahoo.fr>
Repository: CRAN
Date/Publication: 2019-06-17 16:30:03 UTC

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New package quietR with initial version 0.1.0
Package: quietR
Type: Package
Title: Simplify Output Verbosity
Version: 0.1.0
Authors@R: person("Thomas", "Johnson", email = "thomascjohnson@gmail.com", role = c("aut", "cre"))
Maintainer: Thomas Johnson <thomascjohnson@gmail.com>
Description: Simplifies output suppression logic in R packages, as it's common to develop some form of it in R. 'quietR' intends to simplify that problem and allow a set of simple toggle functions to be used to suppress console output.
License: MIT + file LICENSE
URL: https://github.com/thomascjohnson/quietR
BugReports: https://github.com/thomascjohnson/quietR/issues
Encoding: UTF-8
LazyData: true
Suggests: testthat
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-06-16 19:21:14 UTC; thom
Author: Thomas Johnson [aut, cre]
Repository: CRAN
Date/Publication: 2019-06-17 16:40:03 UTC

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New package roxygen2md with initial version 1.0.0
Package: roxygen2md
Title: 'Roxygen' to 'Markdown'
Version: 1.0.0
Date: 2019-05-29
Authors@R: c(person(given = "Kirill", family = "Müller", role = c("aut", "cre"), email = "krlmlr+r@mailbox.org"), person(given = "Heather", family = "Turner", role = "ctb"))
Description: Converts elements of 'roxygen' documentation to 'markdown'.
License: GPL-3
URL: https://roxygen2md.r-lib.org, https://github.com/r-lib/roxygen2md
BugReports: https://github.com/r-lib/roxygen2md/issues
Imports: desc, devtools, enc, rex, rlang, tibble, usethis, withr
Suggests: rstudioapi, testthat
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-06-15 13:49:43 UTC; kirill
Author: Kirill Müller [aut, cre], Heather Turner [ctb]
Maintainer: Kirill Müller <krlmlr+r@mailbox.org>
Repository: CRAN
Date/Publication: 2019-06-17 15:40:03 UTC

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New package rless with initial version 0.1.0
Package: rless
Title: Leaner Style Sheets
Version: 0.1.0
Authors@R: c( person("Jonas", "Vaclavek", , "jonas.vaclavek@gmail.com", role = c("aut", "cre")), person("Jakub", "Kuzilek", role = c("aut")) )
Description: Converts LESS to CSS. It uses V8 engine, where LESS parser is run. Functions for LESS text, file or folder conversion are provided.
Depends: R (>= 3.4)
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: V8
RoxygenNote: 6.1.1
Suggests: testthat, knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-06-15 18:24:05 UTC; Jerryna
Author: Jonas Vaclavek [aut, cre], Jakub Kuzilek [aut]
Maintainer: Jonas Vaclavek <jonas.vaclavek@gmail.com>
Repository: CRAN
Date/Publication: 2019-06-17 16:00:02 UTC

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New package vivo with initial version 0.1.0
Package: vivo
Title: Local Variable Importance via Oscillations of Ceteris Paribus Profiles
Version: 0.1.0
Authors@R: c(person("Anna", "Kozak", email = "anna1993kozak@gmail.com", role = c("aut", "cre")), person("Przemyslaw", "Biecek", role = c("aut", "ths")))
Description: Provides an easy to calculate variable importance measure based on Ceteris Paribus plot and is calculated in eight variants. We obtain eight variants measure through the possible combinations of three parameters such as absolute_deviation, point and density.
Depends: R (>= 3.0)
License: GPL-2
Encoding: UTF-8
LazyData: true
Imports: ggplot2, dplyr, ingredients
Suggests: knitr, rmarkdown, DALEX, mlbench, randomForest, gridExtra, grid, lattice, testthat
VignetteBuilder: knitr
RoxygenNote: 6.1.1
URL: https://github.com/MI2DataLab/vivo
BugReports: https://github.com/MI2DataLab/vivo/issues
NeedsCompilation: no
Packaged: 2019-06-15 10:15:18 UTC; Anna Kozak
Author: Anna Kozak [aut, cre], Przemyslaw Biecek [aut, ths]
Maintainer: Anna Kozak <anna1993kozak@gmail.com>
Repository: CRAN
Date/Publication: 2019-06-17 14:30:03 UTC

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New package git2rdata with initial version 0.1
Package: git2rdata
Title: Store and Retrieve Data.frames in a Git Repository
Version: 0.1
Authors@R: c( person( "Thierry", "Onkelinx", role = c("aut", "cre"), email = "thierry.onkelinx@inbo.be", comment = c(ORCID = "0000-0001-8804-4216")), person( "Floris", "Vanderhaeghe", role = "ctb", email = "floris.vanderhaeghe@inbo.be", comment = c(ORCID = "0000-0002-6378-6229")), person( "Peter", "Desmet", role = "ctb", email = "peter.desmet@inbo.be", comment = c(ORCID = "0000-0002-8442-8025")), person( "Research Institute for Nature and Forest", role = c("cph", "fnd"), email = "info@inbo.be"))
Description: Make versioning of data.frame easy and efficient using git repositories.
Depends: R (>= 3.5.0)
Imports: assertthat, git2r (>= 0.23.0), methods, yaml
Suggests: spelling, ggplot2, knitr, microbenchmark, rmarkdown, testthat
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
URL: https://github.com/ropensci/git2rdata, https://doi.org/10.5281/zenodo.1485309
BugReports: https://github.com/ropensci/git2rdata/issues
Collate: 'clean_data_path.R' 'git2rdata-package.R' 'write_vc.R' 'is_git2rdata.R' 'is_git2rmeta.R' 'list_data.R' 'meta.R' 'prune.R' 'read_vc.R' 'recent_commit.R' 'reexport.R' 'relabel.R' 'upgrade_data.R'
VignetteBuilder: knitr
Language: en-GB
NeedsCompilation: no
Packaged: 2019-06-15 09:44:56 UTC; thierry_onkelinx
Author: Thierry Onkelinx [aut, cre] (<https://orcid.org/0000-0001-8804-4216>), Floris Vanderhaeghe [ctb] (<https://orcid.org/0000-0002-6378-6229>), Peter Desmet [ctb] (<https://orcid.org/0000-0002-8442-8025>), Research Institute for Nature and Forest [cph, fnd]
Maintainer: Thierry Onkelinx <thierry.onkelinx@inbo.be>
Repository: CRAN
Date/Publication: 2019-06-17 14:20:04 UTC

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Sat, 15 Jun 2019

New package unikn with initial version 0.1.0
Package: unikn
Type: Package
Title: Graphical Elements of the University of Konstanz's Corporate Design
Version: 0.1.0
Date: 2019-06-14
Authors@R: c(person("Hansjoerg", "Neth", role = c("aut", "cre"), email = "h.neth@uni.kn"), person("Nico", "Gradwohl", role = "aut"))
Author: Hansjoerg Neth [aut, cre], Nico Gradwohl [aut]
Maintainer: Hansjoerg Neth <h.neth@uni.kn>
Description: Define and use graphical elements of corporate design manuals in R. The 'unikn' package provides color functions (by defining dedicated colors and color palettes, and commands for changing, viewing, and using them) and styled text elements (e.g., for marking, underlining, or plotting colored titles). The pre-defined range of colors and text functions is based on the corporate design of the University of Konstanz <https://www.uni-konstanz.de/>, but can be adapted and extended for other institutions and purposes.
Depends: R (>= 3.4.0)
Imports: utils
Suggests: knitr, rmarkdown, roxygen2, spelling
Collate: 'color_def_1.R' 'color_def_2.R' 'color_util.R' 'color_fun.R' 'plot_util.R' 'plot_box.R' 'plot_box_calls.R' 'plot_text.R' 'plot_text_calls.R' 'start_unikn.R'
Encoding: UTF-8
LazyData: true
License: CC BY-SA 4.0
URL: https://github.com/hneth/unikn
BugReports: https://github.com/hneth/unikn/issues
VignetteBuilder: knitr
RoxygenNote: 6.1.1
Language: en-US
NeedsCompilation: no
Packaged: 2019-06-14 17:02:37 UTC; hneth
Repository: CRAN
Date/Publication: 2019-06-15 08:20:03 UTC

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New package NST with initial version 2.0.3
Package: NST
Type: Package
Title: Normalized Stochasticity Ratio
Version: 2.0.3
Date: 2019-6-14
Author: Daliang Ning
Maintainer: Daliang Ning <ningdaliang@ou.edu>
Imports: vegan,parallel,permute,ape
Depends: R (>= 3.1.0)
Description: To estimate ecological stochasticity in community assembly. Understanding the community assembly mechanisms controlling biodiversity patterns is a central issue in ecology. Although it is generally accepted that both deterministic and stochastic processes play important roles in community assembly, quantifying their relative importance is challenging. The new index, normalized stochasticity ratio (NST), is to estimate ecological stochasticity, i.e. relative importance of stochastic processes, in community assembly. With functions in this package, NST can be calculated based on different similarity metrics and/or different null model algorithms, as well as some previous indexes, e.g. previous Stochasticity Ratio (ST), Standard Effect Size (SES), modified Raup-Crick metrics (RC). Functions for permutational test and bootstrapping analysis are also included. Previous ST is published by Zhou et al (2014) <doi:10.1073/pnas.1324044111>. NST is modified from ST by considering two alternative situations and normalizing the index to range from 0 to 1 which will be published soon (Ning et al 2019). A modified version, MST, is a special case of NST, used in some recent or upcoming publications, e.g. Liang et al (2019) <doi:10.1101/638908>. SES is calculated as described in Kraft et al (2011) <doi:10.1126/science.1208584>. RC is calculated as reported by Chase et al (2011) <doi:10.1890/es10-00117.1> and Stegen et al (2013) <doi:10.1038/ismej.2013.93>.
License: GPL-2
NeedsCompilation: no
Packaged: 2019-06-14 18:35:15 UTC; ndl81
Repository: CRAN
Date/Publication: 2019-06-15 08:30:03 UTC

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New package modelDown with initial version 1.0.1
Package: modelDown
Title: Make Static HTML Website for Predictive Models
Version: 1.0.1
Authors@R: c(person("Przemysław", "Biecek", email = "przemyslaw.biecek@gmail.com", role = c("aut")), person("Magda", "Tatarynowicz", email = "magda.tatarynowicz@gmail.com", role = c("aut")), person("Kamil", "Romaszko", email = "kamil.romaszko@gmail.com", role = c("aut", "cre")), person("Mateusz", "Urbański", email = "matiszak@gmail.com", role = c("aut")))
Description: Website generator with HTML summaries for predictive models. This package uses 'DALEX' explainers to describe global model behavior. We can see how well models behave (tabs: Model Performance, Auditor), how much each variable contributes to predictions (tabs: Variable Response) and which variables are the most important for a given model (tabs: Variable Importance). We can also compare Concept Drift for pairs of models (tabs: Drifter). Additionally, data available on the website can be easily recreated in current R session. Work on this package was financially supported by the NCN Opus grant 2017/27/B/ST6/01307 at Warsaw University of Technology, Faculty of Mathematics and Information Science.
Depends: R (>= 3.4.0)
License: Apache License 2.0
Encoding: UTF-8
LazyData: true
Imports: DALEX (>= 0.2.8), auditor (>= 0.3.0), ggplot2 (>= 3.1.0), whisker (>= 0.3-2), DT (>= 0.4), kableExtra (>= 0.9.0), psych (>= 1.8.4), archivist (>= 2.1.0), svglite (>= 1.2.1), devtools (>= 2.0.1), breakDown (>= 0.1.6), drifter (>= 0.2.1)
Suggests: ranger, testthat, useful
RoxygenNote: 6.1.1
URL: https://github.com/MI2DataLab/modelDown
BugReports: https://github.com/MI2DataLab/modelDown/issues
NeedsCompilation: no
Packaged: 2019-06-14 22:09:40 UTC; Kamil
Author: Przemysław Biecek [aut], Magda Tatarynowicz [aut], Kamil Romaszko [aut, cre], Mateusz Urbański [aut]
Maintainer: Kamil Romaszko <kamil.romaszko@gmail.com>
Repository: CRAN
Date/Publication: 2019-06-15 08:50:02 UTC

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New package uplifteval with initial version 0.1.0
Package: uplifteval
Type: Package
Title: Uplift Model Evaluation with Plots and Metrics
Version: 0.1.0
Author: Roland Stevenson
Maintainer: Roland Stevenson <roland@rmg-services.com>
Description: Provides a variety of plots and metrics to evaluate uplift models including the 'R uplift' package's Qini metric and Qini plot, a port of the 'python pylift' module's plotting function, and an alternative plot (in beta) useful for continuous outcomes. Background: Radcliffe (2007) <https://pdfs.semanticscholar.org/147b/32f3d56566c8654a9999c5477dded233328e.pdf>.
License: GPL-3
URL: https://github.com/ras44/uplifteval
BugReports: https://github.com/ras44/uplifteval/issues
Encoding: UTF-8
LazyData: true
Suggests: testthat, knitr, rmarkdown, grf, tweedie, qpdf
Depends: R (>= 3.0.0),
Imports: ggplot2, whisker, gridExtra, dplyr
RoxygenNote: 6.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-06-14 16:37:51 UTC; rstevenson
Repository: CRAN
Date/Publication: 2019-06-15 07:50:03 UTC

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New package tsibbledata with initial version 0.1.0
Package: tsibbledata
Version: 0.1.0
Title: Diverse Datasets for 'tsibble'
Description: Provides diverse datasets in the 'tsibble' data structure. These datasets are useful for learning and demonstrating how tidy temporal data can tidied, visualised, and forecasted.
Authors@R: c( person("Mitchell", "O'Hara-Wild", email = "mail@mitchelloharawild.com", role = c("aut", "cre")), person("Rob", "Hyndman", role = "aut"), person("Earo", "Wang", role = "aut") )
Depends: R (>= 3.1.3)
Imports: tsibble (>= 0.8.0)
Suggests: ggplot2
ByteCompile: true
License: GPL-3
URL: http://tsibbledata.tidyverts.org/
BugReports: https://github.com/tidyverts/tsibbledata/issues
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-06-14 09:31:58 UTC; mitchell
Author: Mitchell O'Hara-Wild [aut, cre], Rob Hyndman [aut], Earo Wang [aut]
Maintainer: Mitchell O'Hara-Wild <mail@mitchelloharawild.com>
Repository: CRAN
Date/Publication: 2019-06-15 07:30:03 UTC

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New package rjwsacruncher with initial version 0.1.0
Package: rjwsacruncher
Title: Interface to the 'JWSACruncher' of 'JDemetra+'
Version: 0.1.0
Authors@R: c(person("Alain", "Quartier-la-Tente", role = c("aut", "cre"), email = "alain.quartier@yahoo.fr"))
Description: 'JDemetra+' (<https://github.com/jdemetra/jdemetra-app>) is the seasonal adjustment software officially recommended to the members of the European Statistical System and the European System of Central Banks. Seasonal adjustment models performed with 'JDemetra+' can be stored into workspaces. 'JWSACruncher' (<https://github.com/jdemetra/jwsacruncher/releases>) is a console tool that re-estimates all the multi-processing defined in a workspace and to export the result. 'rjwsacruncher' allows to launch easily the 'JWSACruncher'.
URL: https://github.com/AQLT/rjwsacruncher
BugReports: https://github.com/AQLT/rjwsacruncher/issues
Imports: XML
Suggests: knitr, rmarkdown
License: GPL-3
VignetteBuilder: knitr
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-06-11 19:09:51 UTC; alainquartierlatente
Author: Alain Quartier-la-Tente [aut, cre]
Maintainer: Alain Quartier-la-Tente <alain.quartier@yahoo.fr>
Repository: CRAN
Date/Publication: 2019-06-15 07:30:11 UTC

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New package DDPNA with initial version 0.2.1
Package: DDPNA
Type: Package
Title: Disease-Related Differential Proteins and Co-Expression Network Analysis
Version: 0.2.1
Date: 2019-6-5
Authors@R: c(person("Kefu","Liu",email="liukefu19@163.com",role=c("aut","cre")))
Author: Kefu Liu [aut, cre]
Maintainer: Kefu Liu <liukefu19@163.com>
URL: http://github.com/liukf10/DDPNA
BugReports: https://github.com/liukf10/DDPNA/issues
Description: Functions designed to connect disease-related differential proteins and co-expression network. It provides the basic statics analysis included t test, ANOVA analysis. The network construction is not offered by the package, you can used 'WGCNA' package which you can learn in Peter et al. (2008) <doi:10.1186/1471-2105-9-559>. It also provides module analysis included PCA analysis, two enrichment analysis, Planner maximally filtered graph extraction and hub analysis.
Imports: stats, ggplot2, ggalt, MEGENA, igraph, Hmisc, utils, grDevices, plyr, scales, grid, VennDiagram
Suggests: WGCNA, Biostrings, impute, ggfortify
License: GPL-2
Encoding: UTF-8
Depends: R (>= 3.5)
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-06-14 15:07:20 UTC; lkf
Repository: CRAN
Date/Publication: 2019-06-15 07:40:03 UTC

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Fri, 14 Jun 2019

New package gear with initial version 0.1.4
Package: gear
Type: Package
Title: Geostatistical Analysis in R
Version: 0.1.4
Date: 2019-06-14
Author: Joshua French
Maintainer: Joshua French <joshua.french@ucdenver.edu>
Description: Implements common geostatistical methods in a clean, straightforward, efficient manner. The methods are discussed in Schabenberger and Gotway (2004, <ISBN:9781584883227>) and Waller and Gotway (2004, <ISBN:9780471387718>). This package is a quasi-reboot of the 'SpatialTools' package.
License: GPL (>= 2)
Imports: sp, parallel, lattice, stats, optimx
Suggests: testthat, gstat, geoR, spam, Matrix
Encoding: UTF-8
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-06-14 20:24:05 UTC; jfrench
Repository: CRAN
Date/Publication: 2019-06-14 22:50:14 UTC

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New package EloRating with initial version 0.46.8
Package: EloRating
Type: Package
Title: Animal Dominance Hierarchies by Elo Rating
Version: 0.46.8
Date: 2019-06-14
Author: Christof Neumann & Lars Kulik
Maintainer: Christof Neumann <christofneumann1@gmail.com>
Description: Provides functions to quantify animal dominance hierarchies. The major focus is on Elo rating and its ability to deal with temporal dynamics in dominance interaction sequences. For static data, David's score and de Vries' I&SI are also implemented. In addition, the package provides functions to assess transitivity, linearity and stability of dominance networks. See Neumann et al (2011) <doi:10.1016/j.anbehav.2011.07.016> for an introduction.
License: GPL (>= 2)
LazyData: true
RoxygenNote: 6.1.1
Depends: zoo, sna, network, R (>= 3.2.0)
Suggests: testthat, knitr, aniDom
LinkingTo: Rcpp, RcppArmadillo
Imports: Rcpp, Rdpack
NeedsCompilation: yes
VignetteBuilder: knitr
Encoding: UTF-8
RdMacros: Rdpack
URL: https://github.com/gobbios/EloRating
Packaged: 2019-06-14 20:15:26 UTC; cn
Repository: CRAN
Date/Publication: 2019-06-14 22:35:17 UTC

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New package TestDimorph with initial version 0.1.0
Package: TestDimorph
Type: Package
Title: Analysis of the Interpopulation Degree of Sexual Dimorphism using Summary Statistics
Version: 0.1.0
Authors@R: c(person(given = "Bassam", family = "A. Abulnoor", role = c("aut", "cre"), email = "bas12@fayoum.edu.eg"), person(given = "MennattAllah", family = "H. Attia", role = c("aut"), email = "mennatt.hassan@alexmed.edu.eg"), person(given = "Lyle", family = "W. Konigsberg", role = c("ctb","dtc"), email = " lylek@illinois.edu", comment = c("The authors would like to express their endless gratitude to prof. Konigsberg for his contribution to this package with authentic code used in the multivariate and extract_sum functions, datasets used in the examples and for his overall valuable work in the field of physical anthropology without which this package wouldn't have been possible")))
Maintainer: Bassam A. Abulnoor <bas12@fayoum.edu.eg>
Description: Provides two approaches of comparison; the univariate and the multivariate analysis in two or more populations. Since the main obstacle of performing systematic comparisons in anthropological studies is the absence of raw data, the current package offer a solution for this problem by allowing the use of published summary statistics of metric data (mean, standard deviation and sex specific sample size) as illustrated by the works of Greene, D. L. (1989) <doi:10.1002/ajpa.1330790113> and Konigsberg, L. W. (1991) <doi:10.1002/ajpa.1330840110>.
Imports: biotools,plyr,rowr,stats,utils,reshape2,purrr
Suggests: Rdpack,corrplot
Depends: R (>= 2.10)
RdMacros: Rdpack
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-06-14 14:34:27 UTC; Bassam
Author: Bassam A. Abulnoor [aut, cre], MennattAllah H. Attia [aut], Lyle W. Konigsberg [ctb, dtc] (The authors would like to express their endless gratitude to prof. Konigsberg for his contribution to this package with authentic code used in the multivariate and extract_sum functions, datasets used in the examples and for his overall valuable work in the field of physical anthropology without which this package wouldn't have been possible)
Repository: CRAN
Date/Publication: 2019-06-14 15:30:08 UTC

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New package CoreGx with initial version 0.1.0
Package: CoreGx
Type: Package
Title: Classes and Functions to Serve as the Basis for Other 'Gx' Packages
Version: 0.1.0
Date: 2019-05-29
Authors@R: c( person("Petr","Smirnov", email = "petr.smirnov@uhnresearch.ca", role = c("aut")), person("Ian","Smith", email = "ianc.smith@mail.utoronto.ca", role = c("aut")), person("Christopher", "Eeles", , email = "christopher.eeles@uhnresearch.ca", role = c("aut")), person("Benjamin", "Haibe-Kains", email = "benjamin.haibe.kains@utoronto.ca", role = c("aut", "cre")) )
Description: A collection of functions and classes which serve as the foundation for our lab's suite of R packages, such as 'PharmacoGx' and 'RadioGx'. This package was created to abstract shared functionality from other lab package releases to increase ease of maintainability and reduce code repetition in current and future 'Gx' suite programs. Major features include a 'CoreSet' class, from which 'RadioSet' and 'PharmaSet' are derived, along with get and set methods for each respective slot. Additional functions related to fitting and plotting dose response curves, quantifying statistical correlation and calculating area under the curve (AUC) or survival fraction (SF) are included. For more details please see the included documentation, as well as: Smirnov, P., Safikhani, Z., El-Hachem, N., Wang, D., She, A., Olsen, C., Freeman, M., Selby, H., Gendoo, D., Grossman, P., Beck, A., Aerts, H., Lupien, M., Goldenberg, A. (2015) <doi:10.1093/bioinformatics/btv723>. Manem, V., Labie, M., Smirnov, P., Kofia, V., Freeman, M., Koritzinksy, M., Abazeed, M., Haibe-Kains, B., Bratman, S. (2018) <doi:10.1101/449793>.
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.5.0)
Imports: lsa, methods, piano, Biobase, stats, rlang
Suggests: PharmacoGx
License: GPL-3
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-06-14 13:45:55 UTC; chris
Author: Petr Smirnov [aut], Ian Smith [aut], Christopher Eeles [aut], Benjamin Haibe-Kains [aut, cre]
Maintainer: Benjamin Haibe-Kains <benjamin.haibe.kains@utoronto.ca>
Repository: CRAN
Date/Publication: 2019-06-14 15:10:07 UTC

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New package ceRtainty with initial version 1.0.0
Package: ceRtainty
Type: Package
Title: Certainty Equivalent
Version: 1.0.0
Authors@R: person(given= "Ariel", family= "Soto-Caro", role = c("aut", "cre"), email = "arielsotocaro@gmail.com", comment= c(ORCID = "0000-0001-7008-4009"))
Description: Compute the certainty equivalents and premium risks as tools for risk-efficiency analysis. For more technical information, please refer to: Hardaker, Richardson, Lien, & Schumann (2004) <doi:10.1111/j.1467-8489.2004.00239.x>, and Richardson, & Outlaw (2008) <doi:10.2495/RISK080231>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: dplyr, tidyr, RColorBrewer, stats, base
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-06-14 14:01:42 UTC; Ariel
Author: Ariel Soto-Caro [aut, cre] (<https://orcid.org/0000-0001-7008-4009>)
Maintainer: Ariel Soto-Caro <arielsotocaro@gmail.com>
Repository: CRAN
Date/Publication: 2019-06-14 14:40:03 UTC

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New package catfun with initial version 0.1.4
Package: catfun
Type: Package
Title: Categorical Data Analysis
Version: 0.1.4
Author: Nick Williams
Maintainer: Nick Williams <ntwilliams.personal@gmail.com>
Description: Includes wrapper functions around existing functions for the analysis of categorical data and introduces functions for calculating risk differences and matched odds ratios. R currently supports a wide variety of tools for the analysis of categorical data. However, many functions are spread across a variety of packages with differing syntax and poor compatibility with each another. prop_test() combines the functions binom.test(), prop.test() and BinomCI() into one output. prop_power() allows for power and sample size calculations for both balanced and unbalanced designs. riskdiff() is used for calculating risk differences and matched_or() is used for calculating matched odds ratios. For further information on methods used that are not documented in other packages see Nathan Mantel and William Haenszel (1959) <doi:10.1093/jnci/22.4.719> and Alan Agresti (2002) <ISBN:0-471-36093-7>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: epitools, DescTools, cli, magrittr, Hmisc, broom, rlang
RoxygenNote: 6.1.1
Suggests: testthat, dplyr, forcats
NeedsCompilation: no
Packaged: 2019-06-14 13:52:19 UTC; niw4001
Repository: CRAN
Date/Publication: 2019-06-14 14:10:03 UTC

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New package subgxe with initial version 0.9.0
Package: subgxe
Title: Combine Multiple GWAS by Using Gene-Environment Interactions
Version: 0.9.0
Authors@R: c(person("Youfei", "Yu", role = "aut", email = "youfeiyu@umich.edu"), person("Alexander", "Rix", role = "cre", email = "alexrix@umich.edu"))
Description: Classical methods for combining summary data from genome-wide association studies (GWAS) only use marginal genetic effects and power can be compromised in the presence of heterogeneity. 'subgxe' is a R package that implements p-value assisted subset testing for association (pASTA), a method developed by Yu et al. (2019) <doi:10.1159/000496867>. pASTA generalizes association analysis based on subsets by incorporating gene-environment interactions into the testing procedure.
License: GPL-3
URL: https://github.com/umich-cphds/subgxe
BugReports: https://github.com/umich-cphds/subgxe/issues
Suggests: lmtest, knitr, rmarkdown
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-06-14 11:26:19 UTC; alexrix
Author: Youfei Yu [aut], Alexander Rix [cre]
Maintainer: Alexander Rix <alexrix@umich.edu>
Repository: CRAN
Date/Publication: 2019-06-14 13:30:03 UTC

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New package replicateBE with initial version 1.0.8
Encoding: UTF-8
Package: replicateBE
Version: 1.0.8
Date: 2019-06-14
Title: Average Bioequivalence with Expanding Limits (ABEL)
Authors@R: c(person("Helmut", "Schütz", email = "helmut.schuetz@bebac.at", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-1167-7880")), person("Michael", "Tomashevskiy", email = "mittyright@yandex.ru", role = "ctb"), person("Detlew", "Labes", email = "DetlewLabes@gmx.de", role = "ctb"))
Imports: readxl (>= 1.0.0), PowerTOST (>= 1.3.3), lmerTest, nlme, graphics, grDevices
Suggests: knitr, rmarkdown, testthat, devtools
Description: Performs comparative bioavailability-calculations for the EMA's Average Bioequivalence with Expanding Limits (ABEL). Implemented are 'Method A' and 'Method B', detection of outliers. If the design allows, assessment of the empiric Type I Error and iteratively adjusting alpha to preserve the consumer risk. Average Bioequivalence (ABE) - optionally with tighter (EMA: NTIDs) or wider limits (GCC: Cmax) - is implemented as well.
License: GPL (>= 3)
ByteCompile: yes
LazyData: true
VignetteBuilder: knitr
URL: https://github.com/Helmut01/replicateBE
BugReports: https://github.com/Helmut01/replicateBE/issues
NeedsCompilation: no
Packaged: 2019-06-14 13:36:17 UTC; HS
Author: Helmut Schütz [aut, cre] (<https://orcid.org/0000-0002-1167-7880>), Michael Tomashevskiy [ctb], Detlew Labes [ctb]
Maintainer: Helmut Schütz <helmut.schuetz@bebac.at>
Repository: CRAN
Date/Publication: 2019-06-14 13:50:03 UTC

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New package metapro with initial version 1.5.8
Package: metapro
Type: Package
Title: Robust P-Value Combination Methods
Version: 1.5.8
Author: Sora Yoon <yoonsora1@unist.ac.kr>
Maintainer: Sora Yoon <yoonsora1@unist.ac.kr>
Description: The meta-analysis is performed to increase the statistical power by integrating the results from several experiments. The p-values are often combined in meta-analysis when the effect sizes are not available. The 'metapro' R package provides not only traditional methods (Becker BJ (1994, ISBN:0-87154-226-9), Mosteller, F. & Bush, R.R. (1954, ISBN:0201048523) and Lancaster HO (1949, ISSN:00063444)), but also new methods such as weighted Fisher’s method and ordmeta we developed. While the (weighted) Z-method is suitable for finding features effective in most experiments, (weighted) Fisher’s method and ordmeta are useful for detecting partially associated features. Thus, the users can choose the function based on their purpose.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Imports: metap, stats, rSymPy
RoxygenNote: 6.1.1
URL: https://github.com/unistbig/metapro
NeedsCompilation: no
Packaged: 2019-06-14 11:38:47 UTC; node02
Repository: CRAN
Date/Publication: 2019-06-14 13:30:07 UTC

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New package rock with initial version 0.0.1
Package: rock
Title: Reproducible Open Coding Kit
Version: 0.0.1
Authors@R: person(given = "Gjalt-Jorn Ygram", family = "Peters", role = c("aut", "cre"), email = "gjalt-jorn@behaviorchange.eu")
Maintainer: Gjalt-Jorn Ygram Peters <gjalt-jorn@behaviorchange.eu>
Description: The Reproducible Open Coding Kit ('ROCK', and this package, 'rock') was developed to facilitate reproducible and open coding, specifically geared towards qualitative research methods. Although it is a general-purpose toolkit, three specific applications have been implemented, specifically an interface to the 'rENA' package that implements Epistemic Network Analysis ('ENA'), means to process notes from Cognitive Interviews ('CIs'), and means to work with a decentralized construct taxonomy ('DCT').
BugReports: https://gitlab.com/r-packages/rock/issues
URL: https://r-packages.gitlab.io/rock
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Depends: R (>= 3.0.0)
Imports: data.tree (>= 0.7.8), dplyr (>= 0.7.8), DiagrammeR (>= 1.0.0), glue (>= 1.3.0), graphics (>= 3.0.0), purrr (>= 0.2.5), stats (>= 3.0.0), utils (>= 3.5.0), yum (>= 0.0.1)
Suggests: covr, knitr, rENA (>= 0.1.6), rmarkdown, testthat
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-06-13 15:38:11 UTC; micro
Author: Gjalt-Jorn Ygram Peters [aut, cre]
Repository: CRAN
Date/Publication: 2019-06-14 11:30:03 UTC

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New package rflexscan with initial version 0.1
Package: rflexscan
Type: Package
Title: The Flexible Spatial Scan Statistic
Version: 0.1
Date: 2019-06-12
Author: Takahiro Otani, Kunihiko Takahashi
Maintainer: Takahiro Otani <otani@med.nagoya-u.ac.jp>
Description: Functions for the detection of spatial clusters using the flexible spatial scan statistic developed by Tango and Takahashi (2005) <doi:10.1186/1476-072X-4-11>.
URL: https://tkhrotn.github.io/rflexscan/
License: GPL-3
Depends: R (>= 3.1.0)
Imports: Rcpp, igraph, rgdal, grDevices, sp
LinkingTo: Rcpp
Suggests: knitr, rmarkdown, spdep, spData
RoxygenNote: 6.1.1
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2019-06-13 14:09:10 UTC; otani
Repository: CRAN
Date/Publication: 2019-06-14 11:30:07 UTC

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New package DRHotNet with initial version 1.0
Package: DRHotNet
Title: Differential Risk Hotspots in a Linear Network
Version: 1.0
Author: Alvaro Briz-Redon
Maintainer: Alvaro Briz-Redon <alvaro.briz@uv.es>
Description: Performs the identification of differential risk hotspots given a marked point pattern (Diggle 2013) <doi:10.1201/b15326> lying on a linear network (Baddeley, Rubak and Turner 2015) <doi:10.1201/b19708>. The algorithm makes use of a network-constrained version of kernel density estimation (McSwiggan, Baddeley and Nair 2017) <doi:10.1111/sjos.12255>, and then follows a statistical approach to approximate the probability of ocurrence across space for the type of event specified by the user through the marks of the pattern (Kelsall and Diggle 1995) <doi:10.2307/3318678>. The final goal is to detect microzones of the road network where the type of event indicated by the user is overrepresented, considering the network structure provided.
Depends: R (>= 3.5.0)
Imports: spatstat, spdep, raster, maptools, sp, utils, stats
License: GPL-2
LazyData: true
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown
NeedsCompilation: no
Packaged: 2019-06-11 17:18:17 UTC; Usuario
Repository: CRAN
Date/Publication: 2019-06-14 12:00:15 UTC

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New package basetheme with initial version 0.1.0
Package: basetheme
Title: Themes for Base Graphics Plots
Version: 0.1.0
Authors@R: person("Karolis", "Koncevičius", email = "karolis.koncevicius@gmail.com", role = c("aut", "cre"))
Maintainer: Karolis Koncevičius <karolis.koncevicius@gmail.com>
Description: Functions to create and select graphical themes for the base plotting system. Contains: 1) several custom pre-made themes 2) mechanism for creating new themes by making persistent changes to the graphical parameters of base plots.
Depends: R (>= 3.2.2)
License: GPL-2
Encoding: UTF-8
LazyData: true
URL: https://github.com/KKPMW/basetheme
BugReports: https://github.com/KKPMW/basetheme/issues
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-06-10 21:01:52 UTC; karolis
Author: Karolis Koncevičius [aut, cre]
Repository: CRAN
Date/Publication: 2019-06-14 12:00:03 UTC

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New package tidyrules with initial version 0.1.0
Package: tidyrules
Type: Package
Title: Obtain Rules from Rule Based Models as Tidy Dataframe
Version: 0.1.0
Authors@R: c( person("Srikanth", "Komala Sheshachala", email = "sri.teach@gmail.com", role = c("aut", "cre")), person("Amith Kumar", "Ullur Raghavendra", email = "amith54@gmail.com", role = c("aut")) )
Maintainer: Srikanth Komala Sheshachala <sri.teach@gmail.com>
Depends: R (>= 3.6.0),
Imports: tibble (>= 2.0.1), stringr (>= 1.3.1), magrittr (>= 1.5), purrr (>= 0.3.2), assertthat (>= 0.2.0), partykit (>= 1.2.2),
Suggests: AmesHousing (>= 0.0.3), dplyr (>= 0.8), C50 (>= 0.1.2), Cubist (>= 0.2.2), rpart (>= 1.2.2), rpart.plot (>= 3.0.7), rsample (>= 0.0.2), testthat (>= 2.0.1), MASS (>= 7.3.50), mlbench (>= 2.1.1), knitr (>= 1.23), rmarkdown (>= 1.13), pander (>= 0.6.3),
Description: Utility to convert text based summary of rule based models to a tidy dataframe (where each row represents a rule) with related metrics such as support, confidence and lift. Rule based models from these packages are supported: 'C5.0', 'rpart' and 'Cubist'.
URL: https://github.com/talegari/tidyrules
BugReports: https://github.com/talegari/tidyrules/issues
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-06-14 03:45:09 UTC; srikanth
Author: Srikanth Komala Sheshachala [aut, cre], Amith Kumar Ullur Raghavendra [aut]
Repository: CRAN
Date/Publication: 2019-06-14 10:40:03 UTC

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New package FisPro with initial version 1.0
Package: FisPro
Type: Package
Title: Fuzzy Inference System Design and Optimization
Version: 1.0
Authors@R: c( person("Serge", "Guillaume", email = "serge.guillaume@irstea.fr", role = "aut"), person("Brigitte", "Charnomordic", email = "brigitte.charnomordic@inra.fr", role = "aut"), person("Jean-Luc", "Lablée", email = "jean-luc.lablee@irstea.fr", role = c("aut", "cre")), person("Hazaël", "Jones", email = "hazael.jones@supagro.fr", role = "ctb"), person("Lydie", "Desperben", role = "ctb"), person("IRSTEA", role = "cph", comment = "Institut national de Recherche en Sciences et Technologies pour l'Environnement et l'Agriculture, France"), person("INRA", role = "cph", comment = "Institut National de la Recherche Agronomique, France"))
Author: Serge Guillaume [aut], Brigitte Charnomordic [aut], Jean-Luc Lablée [aut, cre], Hazaël Jones [ctb], Lydie Desperben [ctb], IRSTEA [cph] (Institut national de Recherche en Sciences et Technologies pour l'Environnement et l'Agriculture, France), INRA [cph] (Institut National de la Recherche Agronomique, France)
Maintainer: Jean-Luc Lablée <jean-luc.lablee@irstea.fr>
URL: https://www.fispro.org
Description: Fuzzy inference systems are based on fuzzy rules, which have a good capability for managing progressive phenomenons. This package is a basic implementation of the main functions to use a Fuzzy Inference System (FIS) provided by the open source software 'FisPro' <https://www.fispro.org>. 'FisPro' allows to create fuzzy inference systems and to use them for reasoning purposes, especially for simulating a physical or biological system.
License: CeCILL
Encoding: UTF-8
Depends: R (>= 3.3.0)
Imports: methods, Rdpack, Rcpp (>= 1.0.0)
RdMacros: Rdpack
LinkingTo: Rcpp
NeedsCompilation: yes
Suggests: testthat
RoxygenNote: 6.1.1
Packaged: 2019-06-14 06:41:49 UTC; jean-luc.lablee
Repository: CRAN
Date/Publication: 2019-06-14 10:40:08 UTC

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New package EFA.MRFA with initial version 1.0.5
Package: EFA.MRFA
Type: Package
Title: Dimensionality Assessment Using Minimum Rank Factor Analysis
Version: 1.0.5
Date: 2019-06-14
Author: David Navarro-Gonzalez, Urbano Lorenzo-Seva
Maintainer: David Navarro-Gonzalez <david.navarro@urv.cat>
Description: Performs parallel analysis (Timmerman & Lorenzo-Seva, 2011 <doi:10.1037/a0023353>) and hull method (Lorenzo-Seva, Timmerman, & Kiers, 2011 <doi:10.1080/00273171.2011.564527>) for assessing the dimensionality of a set of variables using minimum rank factor analysis (see ten Berge & Kiers, 1991 <doi:10.1007/BF02294464> for more information). The package also includes the option to compute minimum rank factor analysis by itself, as well as the greater lower bound calculation.
Depends: R (>= 2.10)
Imports: stats, optimbase, psych, scales, PCovR, ggplot2, reshape2
License: GPL-3
Encoding: UTF-8
NeedsCompilation: no
LazyData: true
RoxygenNote: 6.0.1
Packaged: 2019-06-14 09:05:40 UTC; dng
Repository: CRAN
Date/Publication: 2019-06-14 10:50:03 UTC

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New package STOPES with initial version 0.1
Package: STOPES
Type: Package
Title: Selection Threshold Optimized Empirically via Splitting
Version: 0.1
Date: 2019-05-15
Author: Marinela Capanu, Mihai Giurcanu, Colin Begg, and Mithat Gonen
Maintainer: Marinela Capanu <capanum@mskcc.org>
Imports: changepoint, glmnet, MASS
Description: A variable selection procedure for low to moderate size linear regressions models. This method repeatedly splits the data into two sets, one for estimation and one for validation, to obtain an empirically optimized threshold which is then used to screen for variables to include in the final model.
License: GPL-2
NeedsCompilation: no
Packaged: 2019-06-13 17:20:14 UTC; mgiurcanu
Repository: CRAN
Date/Publication: 2019-06-14 08:10:03 UTC

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New package ScorePlus with initial version 0.1
Package: ScorePlus
Title: Implementation of SCORE, SCORE+ and Mixed-SCORE
Version: 0.1
Authors@R: c(person("Jiashun Jin", role = 'aut', email = "jiashun@jiashun@cmu.edu"), person("Zheng Tracy Ke", role = 'aut', email = "zke@fas.harvard.edu"), person("Shengming Luo", role = c('aut', 'cre'), email = "shengmil@andrew.cmu.edu"))
Maintainer: Shengming Luo <shengmil@andrew.cmu.edu>
Description: Implementation of community detection algorithm SCORE in the paper J. Jin (2015) <arXiv:1211.5803>, and SCORE+ in J. Jin, Z. Ke and S. Luo (2018) <arXiv:1811.05927>. Membership estimation algorithm called Mixed-SCORE in J. Jin, Z. Ke and S. Luo (2017) <arXiv:1708.07852>.
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Imports: utils, combinat, limSolve, RSpectra, igraph, igraphdata, stats
NeedsCompilation: no
Packaged: 2019-06-13 19:09:09 UTC; lsm
Author: Jiashun Jin [aut], Zheng Tracy Ke [aut], Shengming Luo [aut, cre]
Repository: CRAN
Date/Publication: 2019-06-14 08:40:03 UTC

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New package RBF with initial version 1.0.0
Package: RBF
Type: Package
Title: Robust Backfitting
Version: 1.0.0
Date: 2019-06-11
Authors@R: c(person("Matias", "Salibian-Barrera", role = c("cre"), email = "matias@stat.ubc.ca"), person("Alejandra", "Martinez", role=c("aut"), email="ale_m_martinez@hotmail.com") )
Description: A robust backfitting algorithm for additive models based on (robust) local polynomial kernel smoothers. It includes both bounded and re-descending (kernel) M-estimators, and it computes predictions for points outside the training set if desired. See Boente, Martinez and Salibian-Barrera (2017) <doi:10.1080/10485252.2017.1369077> for details.
License: GPL (>= 3.0)
RoxygenNote: 6.1.1
Encoding: UTF-8
Imports: stats, graphics
NeedsCompilation: yes
Packaged: 2019-06-13 18:51:08 UTC; matias
Author: Matias Salibian-Barrera [cre], Alejandra Martinez [aut]
Maintainer: Matias Salibian-Barrera <matias@stat.ubc.ca>
Repository: CRAN
Date/Publication: 2019-06-14 08:20:03 UTC

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New package utile.visuals with initial version 0.1.1
Package: utile.visuals
Title: Creating Visuals for Publication
Version: 0.1.1
Authors@R: c(person('Eric', 'Finnesgard', email = 'finnesgard.eric@mayo.edu', role = c('aut', 'cre')))
Description: A small set of functions for making visuals for publication in 'ggplot2'. Key functions include geom_stepconfint() for drawing a step confidence interval on a Kaplan-Meir curve and theme_white()/theme_black() which are minimalist 'ggplot2' themes with transparent backgrounds.
License: LGPL (>= 2)
Encoding: UTF-8
LazyData: TRUE
Depends: R (>= 3.4.0)
Imports: ggplot2
Suggests: survival, broom
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-06-13 16:41:09 UTC; m130239
Author: Eric Finnesgard [aut, cre]
Maintainer: Eric Finnesgard <finnesgard.eric@mayo.edu>
Repository: CRAN
Date/Publication: 2019-06-14 07:40:03 UTC

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New package sugarbag with initial version 0.1.0
Package: sugarbag
Title: Create Tessellated Hexagon Maps
Version: 0.1.0
Authors@R: c(person("Stephanie", "Kobakian", email = "stephanie.kobakian@gmail.com", role = c("aut", "cre")), person("Dianne", "Cook", role = c("aut", "ths")))
Description: Create a hexagon tilegram from spatial polygons. Each polygon is represented by a hexagon tile, placed as close to it's original centroid as possible, with a focus on maintaining spatial relationship to a focal point. Developed to aid visualisation and analysis of spatial distributions across Australia, which can be challenging due to the concentration of the population on the coast and wide open interior.
URL: https://srkobakian.github.io/sugarbag/, https://github.com/srkobakian/sugarbag
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.5.0)
Imports: dplyr (>= 0.7.8), geosphere (>= 1.5), purrr (>= 0.2.5), rlang, rmapshaper (>= 0.4.1), sf (>= 0.7), tibble (>= 1.4.2), tidyr (>= 0.8)
RoxygenNote: 6.1.1
Suggests: ggplot2 (>= 3.1.0), knitr, pkgdown, rmarkdown, spData, testthat (>= 2.1.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-06-06 03:02:18 UTC; steff
Author: Stephanie Kobakian [aut, cre], Dianne Cook [aut, ths]
Maintainer: Stephanie Kobakian <stephanie.kobakian@gmail.com>
Repository: CRAN
Date/Publication: 2019-06-14 08:00:02 UTC

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Thu, 13 Jun 2019

New package variantspark with initial version 0.1.1
Package: variantspark
Type: Package
Title: A 'Sparklyr' Extension for 'VariantSpark'
Version: 0.1.1
Authors@R: c( person("Samuel", "Macêdo", email = "samuelmacedo@recife.ifpe.edu.br", role = c("aut", "cre")), person("Javier", "Luraschi", email = "javier@rstudio.com", role = "aut") )
Maintainer: Samuel Macêdo <samuelmacedo@recife.ifpe.edu.br>
Description: This is a 'sparklyr' extension integrating 'VariantSpark' and R. 'VariantSpark' is a framework based on 'scala' and 'spark' to analyze genome datasets, see <https://bioinformatics.csiro.au/>. It was tested on datasets with 3000 samples each one containing 80 million features in either unsupervised clustering approaches and supervised applications, like classification and regression. The genome datasets are usually writing in VCF, a specific text file format used in bioinformatics for storing gene sequence variations. So, 'VariantSpark' is a great tool for genome research, because it is able to read VCF files, run analyses and return the output in a 'spark' data frame.
License: Apache License 2.0 | file LICENSE
LazyData: true
Imports: sparklyr (>= 1.0.1)
RoxygenNote: 6.1.1
Suggests: testthat
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2019-06-11 23:30:12 UTC; dmmad
Author: Samuel Macêdo [aut, cre], Javier Luraschi [aut]
Repository: CRAN
Date/Publication: 2019-06-13 16:20:03 UTC

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New package scModels with initial version 1.0.0
Package: scModels
Title: Fitting Discrete Distribution Models to Count Data
Version: 1.0.0
Maintainer: Lisa Amrhein <amrheinlisa@gmail.com>
Authors@R: c( person("Lisa", "Amrhein", email="amrheinlisa@gmail.com", role=c("aut", "cre")), person("Kumar", "Harsha", email="kumar.harsha@tum.de", role="aut"), person("Christiane", "Fuchs", email="christiane.fuchs@helmholtz-muenchen.de", role="aut"), person("Pavel", "Holoborodko", email="pavel@holoborodko.com", role="ctb", comment="Author and copyright holder of 'mpreal.h'"))
License: GPL-3
Description: Provides functions for fitting discrete distribution models to count data. Included are the Poisson, the negative binomial and, most importantly, a new implementation of the Poisson-beta distribution (density, distribution and quantile functions, and random number generator) together with a needed new implementation of Kummer's function (also: confluent hypergeometric function of the first kind). Three different implementations of the Gillespie algorithm allow data simulation based on the basic, switching or bursting mRNA generating processes. Moreover, likelihood functions for four variants of each of the three aforementioned distributions are also available. The variants include one population and two population mixtures, both with and without zero-inflation. The package depends on the 'MPFR' libraries which need to be installed separately (see description at <https://github.com/fuchslab/scModels>). This package is supplement to the paper "A mechanistic model for the negative binomial distribution of single-cell mRNA counts" by Lisa Amrhein, Kumar Harsha and Christiane Fuchs (2019) <doi:10.1101/657619> available on bioRxiv.
Depends: R (>= 3.1.0)
LazyData: true
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown, testthat
LinkingTo: Rcpp
Imports: Rcpp
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2019-06-13 14:01:09 UTC; kumarharsha
Author: Lisa Amrhein [aut, cre], Kumar Harsha [aut], Christiane Fuchs [aut], Pavel Holoborodko [ctb] (Author and copyright holder of 'mpreal.h')
Repository: CRAN
Date/Publication: 2019-06-13 16:10:03 UTC

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New package nomnoml with initial version 0.1.0
Package: nomnoml
Type: Package
Title: Sassy 'UML' Diagrams
Version: 0.1.0
Authors@R: c( person("Javier", "Luraschi", email = "javier@rstudio.com", role = c("aut", "cre")), person("Daniel", "Kallin", role = c("ctb"), comment = "nomnoml.js library, http://nomnoml.com") )
Maintainer: Javier Luraschi <javier@rstudio.com>
Description: A tool for drawing sassy 'UML' diagrams based on a simple syntax, see <http://www.nomnoml.com>. Supports styling, R Markdown and exporting diagrams in the PNG format.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.1.2)
Imports: htmlwidgets, png, webshot
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown
NeedsCompilation: no
Packaged: 2019-06-12 16:13:35 UTC; javierluraschi
Author: Javier Luraschi [aut, cre], Daniel Kallin [ctb] (nomnoml.js library, http://nomnoml.com)
Repository: CRAN
Date/Publication: 2019-06-13 16:20:07 UTC

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New package HiResTEC with initial version 0.58
Package: HiResTEC
Type: Package
Title: Non-Targeted Fluxomics on High-Resolution Mass-Spectrometry Data
Version: 0.58
Date: 2019-06-13
Authors@R: c(person("Jan", "Lisec", role = c("aut", "cre"), email = "jan.lisec@bam.de"), person("Friederike", "Hoffmann", role = c("aut"), email = "Friederike.Hoffmann@charite.de"))
Maintainer: Jan Lisec <jan.lisec@bam.de>
Description: Identifying labeled compounds in a 13C-tracer experiment in non-targeted fashion is a cumbersome process. This package facilitates such type of analyses by providing high level quality control plots, deconvoluting and evaluating spectra and performing a multitude of tests in an automatic fashion. The main idea is to use changing intensity ratios of ion pairs from peak list generated with 'xcms' as candidates and evaluate those against base peak chromatograms and spectra information within the raw measurement data automatically. The functionality is described in Hoffmann et al. (2018) <doi:10.1021/acs.analchem.8b00356>.
License: GPL-3
URL: https://pubs.acs.org/doi/10.1021/acs.analchem.8b00356
LazyData: TRUE
Depends: R(>= 2.10.0)
biocViews:
Imports: plyr, openxlsx, InterpretMSSpectrum, Rdisop, beeswarm, Biobase
Suggests: xcms
RoxygenNote: 6.1.1
NeedsCompilation: yes
Packaged: 2019-06-13 12:45:04 UTC; jlisec
Author: Jan Lisec [aut, cre], Friederike Hoffmann [aut]
Repository: CRAN
Date/Publication: 2019-06-13 15:40:16 UTC

More information about HiResTEC at CRAN
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New package SimJoint with initial version 0.1.1
Package: SimJoint
Type: Package
Title: Simulate Joint Distribution
Version: 0.1.1
Author: Charlie Wusuo Liu
Maintainer: Charlie Wusuo Liu <liuwusuo@gmail.com>
Description: Simulate joint distribution given nonparametric marginals and their covariance structure characterized by a correlation matrix. The simulator engages the problem from a purely computational perspective. It assumes no statistical models such as copulas and parametric distributions, and can approximate the target correlations regardless of theoretical feasibility. The algorithm integrates and advances the Iman-Conover (1982) approach (<doi:10.1080/03610918208812265>) and the Ruscio-Kaczetow (2008) iteration (<doi:10.1080/00273170802285693>). The package is implemented in C++ and carefully designed toward computing speed, suitable for large input in a manycore environment. Precision of the approximation and computing speed both outperform various CRAN packages to date by a substantial margin. Benchmarks are detailed in function examples.
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: Rcpp (>= 1.0.0), RcppParallel,
LinkingTo: Rcpp, RcppParallel, RcppArmadillo
SystemRequirements: GNU make
Suggests: R.rsp
VignetteBuilder: R.rsp
NeedsCompilation: yes
Packaged: 2019-06-12 05:18:03 UTC; Charlie
Repository: CRAN
Date/Publication: 2019-06-13 13:10:14 UTC

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New package archetypal with initial version 1.0.0
Package: archetypal
Version: 1.0.0
Title: Finds the Archetypal Analysis of a Data Frame
Description: Performs archetypal analysis by using Convex Hull approximation under a full control of all algorithmic parameters. It contains functions useful for finding the proper initial approximation, the optimal number of archetypes and function for applying main algorithm. Morup, M., Hansen, LK (2012) <doi:10.1016/j.neucom.2011.06.033>. Hochbaum, DS, Shmoys, DB (1985) <doi:10.1287/moor.10.2.180>. Eddy, WF(1977) <doi:10.1145/355759.355768>. Barber, CB, Dobkin, DP, Huhdanpaa, HT (1996) <doi:10.1145/235815.235821>. Christopoulos, DT (2016) <doi:10.2139/ssrn.3043076> .
Authors@R: c( person("Demetris", "Christopoulos", email = "dchristop@econ.uoa.gr", role = c("aut", "cre")), person("David", "Midgley", email = "david.midgley@insead.edu", role = c("ctb")), person("INSEAD Fontainebleau France", role = c("fnd", "cph")) )
Maintainer: Demetris Christopoulos <dchristop@econ.uoa.gr>
Depends: R (>= 3.1.0)
Imports: Matrix, geometry, inflection, doParallel, lpSolve, methods
Suggests: knitr, rmarkdown, plot3D
VignetteBuilder: knitr
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
ByteCompile: true
NeedsCompilation: no
Packaged: 2019-06-12 10:34:23 UTC; demetris_ws
Author: Demetris Christopoulos [aut, cre], David Midgley [ctb], INSEAD Fontainebleau France [fnd, cph]
Repository: CRAN
Date/Publication: 2019-06-13 13:20:07 UTC

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New package JSmediation with initial version 0.1.0
Package: JSmediation
Version: 0.1.0
Title: Mediation Analysis Using Joint Significance
Authors@R: c( person("Cédric", "Batailler", email = "cedric.batailler@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0003-0553-6827")), person("Dominique", "Muller", role = "aut", comment = c(ORCID = "0000-0001-9544-5317")), person("Vincent", "Yzerbyt", role = "aut"), person("Charles", "Judd", role = "aut"), person("Arnold", "Ho", role = "dtc"), person("Nour", "Kteily", role = "dtc"), person("Jacqueline", "Chen", role = "dtc"), person("Simone", "Dohle", role = "dtc"), person("Michael", "Siegrist", role = "dtc") )
Description: A set of helper functions to conduct joint-significance tests for mediation analysis, as recommended by Yzerbyt, Muller, Batailler, & Judd. (2018) <doi:10.1037/pspa0000132>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
ByteCompile: true
RoxygenNote: 6.1.1
Depends: R (>= 2.10)
URL: https://github.com/cedricbatailler/JSmediation
BugReports: https://github.com/cedricbatailler/JSmediation/issues
Imports: rlang (>= 0.1.2), dplyr, magrittr, purrr, glue, broom, tibble, stats, MASS, data.table, knitr
Suggests: rmarkdown, testthat, covr, roxygen2
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-06-11 12:41:14 UTC; batailce
Author: Cédric Batailler [aut, cre] (<https://orcid.org/0000-0003-0553-6827>), Dominique Muller [aut] (<https://orcid.org/0000-0001-9544-5317>), Vincent Yzerbyt [aut], Charles Judd [aut], Arnold Ho [dtc], Nour Kteily [dtc], Jacqueline Chen [dtc], Simone Dohle [dtc], Michael Siegrist [dtc]
Maintainer: Cédric Batailler <cedric.batailler@gmail.com>
Repository: CRAN
Date/Publication: 2019-06-13 12:10:03 UTC

More information about JSmediation at CRAN
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New package CGGP with initial version 1.0.0
Package: CGGP
Type: Package
Title: Composite Grid Gaussian Processes
Version: 1.0.0
Authors@R: c( person("Collin", "Erickson", email = "collinberickson@gmail.com", role = c("aut", "cre")), # Creator is who gets bothered with issues person("Matthew", "Plumlee", role = c("aut")) ) # Maintainer: Who to complain to <yourfault@somewhere.net>
Description: Run computer experiments using the adaptive composite grid algorithm with a Gaussian process model. The algorithm works best when running an experiment that can evaluate thousands of points from a deterministic computer simulation. This package is an implementation of a forthcoming paper by Plumlee, Erickson, Ankenman, et al. For a preprint of the paper, contact the maintainer of this package.
License: GPL-3
Imports: Rcpp (>= 0.12.18)
LinkingTo: Rcpp, RcppArmadillo
Suggests: testthat, covr, ggplot2, reshape2, plyr, MASS, knitr
URL: https://github.com/CollinErickson/CGGP
BugReports: https://github.com/CollinErickson/CGGP/issues
Encoding: UTF-8
RoxygenNote: 6.1.1
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2019-06-11 14:24:22 UTC; cbe117
Author: Collin Erickson [aut, cre], Matthew Plumlee [aut]
Maintainer: Collin Erickson <collinberickson@gmail.com>
Repository: CRAN
Date/Publication: 2019-06-13 12:20:03 UTC

More information about CGGP at CRAN
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New package its.analysis with initial version 1.4.0
Package: its.analysis
Type: Package
Title: Running Interrupted Time Series Analysis
Version: 1.4.0
Author: Patrick English
Maintainer: Patrick English <p.english@exeter.ac.uk>
Description: Two functions for running and then post-estimating an Interrupted Time Series Analysis model. This is a solution for running time series analyses on temporally short data. See English (2019) 'The its.analysis R package - Modelling short time series data' <https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3398189> for an overview of the method.
Imports: plyr, car, stats, graphics, grDevices, forecast, boot, ggplot2
License: MIT + file LICENCE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1.9000
NeedsCompilation: no
Packaged: 2019-06-10 09:43:20 UTC; patrickenglish
Repository: CRAN
Date/Publication: 2019-06-13 11:40:03 UTC

More information about its.analysis at CRAN
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Wed, 12 Jun 2019

New package pwr2ppl with initial version 0.1.1
Package: pwr2ppl
Type: Package
Title: Power Analyses for Common Designs (Power to the People)
Version: 0.1.1
Author: Chris Aberson
Maintainer: Chris Aberson <cla18@humboldt.edu>
Description: Statistical power analysis for designs including t-tests, correlations, multiple regression, ANOVA, mediation, and logistic regression. Functions accompany Aberson (2019) <doi:10.4324/9781315171500>.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Imports: car (>= 3.0-0), MASS (>= 7.3-51), dplyr (>= 0.8.0), tidyr (>= 0.8.0), ez (>= 0.4.3), nlme (>= 3.1-139), phia (>= 0.2-0), afex (>= 0.22-1), MBESS (>= 4.5.0), lavaan (>= 0.6-2), stats (>= 3.5.0)
NeedsCompilation: no
Packaged: 2019-06-11 03:40:53 UTC; Chris Aberson
Repository: CRAN
Date/Publication: 2019-06-12 13:30:02 UTC

More information about pwr2ppl at CRAN
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New package cblasr with initial version 1.0.0
Package: cblasr
Type: Package
Title: The C Interface to 'BLAS' Routines
Version: 1.0.0
Authors@R: c(person("Yi", "Pan", email = "ypan1988@gmail.com", role = c("aut", "cre")), person("Keita", "Teranishi", role = c("aut")))
Maintainer: Yi Pan <ypan1988@gmail.com>
Description: Provides the 'cblas.h' header file as C interface to the underlying internal 'BLAS' library in R. 'CBLAS' <https://www.netlib.org/blas/cblas.h> is a collection of wrappers originally written by Keita Teranishi and provides a C interface to the FORTRAN 'BLAS' library <https://www.netlib.org/blas/>. Note that as internal 'BLAS' library provided by R <https://svn.r-project.org/R/trunk/src/include/R_ext/BLAS.h> is used and only the double precision / double complex 'BLAS' routines are supported.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Imports: Rcpp (>= 1.0.0)
LinkingTo: Rcpp
RoxygenNote: 6.1.1
NeedsCompilation: yes
Packaged: 2019-06-10 19:21:45 UTC; pany
Author: Yi Pan [aut, cre], Keita Teranishi [aut]
Repository: CRAN
Date/Publication: 2019-06-12 13:10:02 UTC

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New package textdata with initial version 0.1.0
Package: textdata
Title: Download and Load Various Text Datasets
Version: 0.1.0
Authors@R: c(person(given = "Emil", family = "Hvitfeldt", role = c("aut", "cre"), email = "emilhhvitfeldt@gmail.com", comment = c(ORCID = "0000-0002-0679-1945")), person(given = "Julia", family = "Silge", role = c("ctb"), email = "julia.silge@gmail.com", comment = c(ORCID = "0000-0002-3671-836X")))
Description: Provides a framework to download, parse, and store text datasets on the disk and load them when needed. Includes various sentiment lexicons and labeled text data sets for classification and analysis.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: fs, readr, tibble, rappdirs
RoxygenNote: 6.1.1
Collate: 'dataset_sentence_polarity.R' 'lexicon_bing.R' 'lexicon_loughran.R' 'lexicon_afinn.R' 'download_functions.R' 'info.R' 'load_dataset.R' 'printer.R' 'process_functions.R'
Suggests: knitr, rmarkdown, testthat (>= 2.1.0)
VignetteBuilder: knitr
URL: https://github.com/EmilHvitfeldt/textdata
BugReports: https://github.com/EmilHvitfeldt/textdata/issues
NeedsCompilation: no
Packaged: 2019-06-11 16:54:10 UTC; emilhvitfeldthansen
Author: Emil Hvitfeldt [aut, cre] (<https://orcid.org/0000-0002-0679-1945>), Julia Silge [ctb] (<https://orcid.org/0000-0002-3671-836X>)
Maintainer: Emil Hvitfeldt <emilhhvitfeldt@gmail.com>
Repository: CRAN
Date/Publication: 2019-06-12 12:20:03 UTC

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Tue, 11 Jun 2019

New package regressoR with initial version 1.1.7
Title: Regression Data Analysis System
Package: regressoR
Type: Package
Version: 1.1.7
Authors@R: c( person("Oldemar", "Rodriguez R.", email = "oldemar.rodriguez@ucr.ac.cr", role = c("aut","cre")), person("Andres", "Navarro D.", role = c("ctb","prg")), person("Diego", "Jimenez A.", role = c("ctb","prg")))
Depends: R (>= 3.5)
Imports: shiny (>= 1.2.0), shinyAce (>= 0.3.3), shinydashboardPlus (>= 0.6.0), shinyWidgets (>= 0.4.4), shinyjs (>= 1.0), flexdashboard (>= 0.5.1.1), neuralnet (>= 1.44.2), rpart (>= 4.1-13), rattle (>= 5.2.0), xgboost (>= 0.81.0.1), colourpicker (>= 1.0), DT (>= 0.5), randomForest (>= 4.6-14), e1071 (>= 1.7-0.1), kknn (>= 1.3.1), corrplot (>= 0.84), ROCR (>= 1.0-7), glmnet (>= 2.0-16), gbm (>= 2.1.5), pls (>= 2.7-1), zip (>= 2.0.0), ggplot2 (>= 3.1.0), dplyr (>= 0.8.0.1), htmltools (>= 0.3.6)
Suggests: forcats, gridExtra, tibble, scales, scatterplot3d, psych, dummies, testthat
Description: Perform a supervised data analysis on a database through a 'shiny' graphical interface. It includes methods such as linear regression, penalized regression, k-nearest neighbors, decision trees, ada boosting, extreme gradient boosting, random forest, neural networks, deep learning and support vector machines.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
URL: http://www.promidat.com
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-06-05 14:58:05 UTC; promidat04
Author: Oldemar Rodriguez R. [aut, cre], Andres Navarro D. [ctb, prg], Diego Jimenez A. [ctb, prg]
Maintainer: Oldemar Rodriguez R. <oldemar.rodriguez@ucr.ac.cr>
Repository: CRAN
Date/Publication: 2019-06-11 17:20:04 UTC

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New package ForecastFramework with initial version 0.10.1
Package: ForecastFramework
Title: A Basis for Modular Model Creation
Version: 0.10.1
Authors@R: c( person("Joshua", "Kaminsky", email = "jkaminsky@jhu.edu", role = c("aut", "cre")), person("Justin", "Lessler", email = "justin@jhu.edu", role = c("aut")), person("Nicholas", "Reich", email = "nick@schoolph.umass.edu", role = c("aut")))
Maintainer: Joshua Kaminsky <jkaminsky@jhu.edu>
Description: Create modular models. Quickly prototype models whose input includes (multiple) time series data. Create pieces of model use cases separately, and swap out particular models as desired. Create modeling competitions, data processing pipelines, and re-useable models.
Depends: R6
Imports: abind,lubridate,dplyr,reshape2,magrittr,tibble
Suggests: testthat,knitr,rmarkdown,DAAG
Enhances: surveillance
Encoding: UTF-8
License: GPL-3
LazyData: true
RoxygenNote: 6.1.1
Collate: 'AbstractClasses.R' 'DataContainers.R' 'Forecasts.R' 'SimulatedIncidenceMatrix.R' 'IncidenceForecast.R' 'IncidenceMatrix.R' 'Models.R' 'SimpleForecast.R' 'MoveAheadModel.R' 'ObservationList.R'
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-06-11 16:34:13 UTC; jkaminsky
Author: Joshua Kaminsky [aut, cre], Justin Lessler [aut], Nicholas Reich [aut]
Repository: CRAN
Date/Publication: 2019-06-11 17:30:02 UTC

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New package leafR with initial version 0.1.4
Package: leafR
Type: Package
Title: Calculates the Leaf Area Index (LAD) and Other Related Functions
Version: 0.1.4
Authors@R: c( person(given="Danilo Roberti Alves de", family="Almeida", email="daniloflorestas@gmail.com", role=c("aut", "cre"), comment=c(ORCID="https://orcid.org/0000-0002-8747-0085")), person(given="Scott Christopher", family="Stark", email="scottcstark@gmail.com", role=c("aut"), comment=c(ORCID="https://orcid.org/0000-0002-1305-1793")), person(given="Carlos Alberto", family="Silva", email="carlos_engflorestal@outlook.com", role=c("aut"), comment=c(ORCID="https://orcid.org/0000-0002-7844-3560")), person(given="Caio", family="Hamamura", email="caiohamamura@gmail.com", role=c("aut"), comment=c(ORCID="https://orcid.org/0000-0001-6149-5885")) )
Description: A set of functions for analyzing the structure of forests based on the leaf area density (LAD) and leaf area index (LAI) measures calculated from Airborne Laser Scanning (ALS), i.e., scanning lidar (Light Detection and Ranging) data. The methodology is discussed and described in Almeida et al. (2019) <doi:10.3390/rs11010092> and Stark et al. (2012) <doi:10.1111/j.1461-0248.2012.01864.x>.
Imports: lidR, sp, data.table, raster, lazyeval
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-06-09 02:46:16 UTC; caioh
Author: Danilo Roberti Alves de Almeida [aut, cre] (<https://orcid.org/0000-0002-8747-0085>), Scott Christopher Stark [aut] (<https://orcid.org/0000-0002-1305-1793>), Carlos Alberto Silva [aut] (<https://orcid.org/0000-0002-7844-3560>), Caio Hamamura [aut] (<https://orcid.org/0000-0001-6149-5885>)
Maintainer: Danilo Roberti Alves de Almeida <daniloflorestas@gmail.com>
Repository: CRAN
Date/Publication: 2019-06-11 10:40:03 UTC

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New package bvartools with initial version 0.0.1
Package: bvartools
Title: Bayesian Inference of Vector Autoregressive Models
Version: 0.0.1
Date: 2019-06-09
Authors@R: person("Franz X.", "Mohr", email = "bvartools@outlook.com", role = c("aut","cre"))
Description: Assists in the set-up of algorithms for Bayesian inference of vector autoregressive (VAR) models. Functions for posterior simulation, forecasting, impulse response analysis and forecast error variance decomposition are largely based on the introductory texts of Koop and Korobilis (2010) <doi:10.1561/0800000013> and Luetkepohl (2007, ISBN: 9783540262398).
License: GPL (>= 2)
Depends: R (>= 3.3.0)
Imports: coda, graphics, Rcpp (>= 0.12.14), stats
LinkingTo: Rcpp, RcppArmadillo
Encoding: UTF-8
RoxygenNote: 6.1.1
URL: https://github.com/franzmohr/bvartools
BugReports: https://github.com/franzmohr/bvartools/issues
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2019-06-09 08:44:14 UTC; franz
Author: Franz X. Mohr [aut, cre]
Maintainer: Franz X. Mohr <bvartools@outlook.com>
Repository: CRAN
Date/Publication: 2019-06-11 10:10:19 UTC

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New package sass with initial version 0.1.1
Type: Package
Package: sass
Version: 0.1.1
Title: Syntactically Awesome Style Sheets (Sass) for R
Description: An 'SCSS' compiler, powered by the 'libSass' library. With this, R developers can use variables, inheritance, and functions to generate dynamic style sheets. The package uses the Sass CSS extension language, which is stable, powerful, and CSS compatible.
Authors@R: c( person("Richard", "Iannone", , "rich@rstudio.com", c("aut", "cre"), comment = c(ORCID = "0000-0003-3925-190X")), person("Timothy", "Mastny", , "tim.mastny@gmail.com", "aut"), person("Barret", "Schloerke", , "barret@rstudio.com", "aut", comment = c(ORCID = "0000-0001-9986-114X")), person("Joe", "Cheng", , "joe@rstudio.com", c("aut", "rev")), person(family = "RStudio", role = c("cph", "fnd")), person(family = "Sass Open Source Foundation", role = c("ctb", "cph"), comment = "LibSass library"), person("Hampton", "Catlin", role = c("ctb", "cph"), comment = "LibSass library"), person("Nathan", "Weizenbaum", role = c("ctb", "cph"), comment = "LibSass library"), person("Chris", "Eppstein", role = c("ctb", "cph"), comment = "LibSass library") )
License: MIT + file LICENSE
URL: https://github.com/rstudio/sass
BugReports: https://github.com/rstudio/sass/issues
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
SystemRequirements: GNU make
Imports: digest
Suggests: testthat, knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2019-06-09 03:38:17 UTC; rich
Author: Richard Iannone [aut, cre] (<https://orcid.org/0000-0003-3925-190X>), Timothy Mastny [aut], Barret Schloerke [aut] (<https://orcid.org/0000-0001-9986-114X>), Joe Cheng [aut, rev], RStudio [cph, fnd], Sass Open Source Foundation [ctb, cph] (LibSass library), Hampton Catlin [ctb, cph] (LibSass library), Nathan Weizenbaum [ctb, cph] (LibSass library), Chris Eppstein [ctb, cph] (LibSass library)
Maintainer: Richard Iannone <rich@rstudio.com>
Repository: CRAN
Date/Publication: 2019-06-11 10:00:03 UTC

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New package pcFactorStan with initial version 0.11
Package: pcFactorStan
Title: Stan Models for the Pairwise Comparison Factor Model
Version: 0.11
Authors@R: c(person(given = c("Joshua", "N."), family = "Pritikin", role = c("aut", "cre"), email = "jpritikin@pobox.com", comment = c(ORCID = "0000-0002-9862-5484")), person(given = c("Daniel C."), family = "Furr", role="ctb", email = "danielcfurr@berkeley.edu"), person("Trustees of Columbia University", role="cph"))
Description: Provides convenience functions and pre-programmed Stan models related to the pairwise comparison factor model. Its purpose is to make fitting pairwise comparison data using Stan easy.
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
LinkingTo: Rcpp (>= 0.12.0), RcppEigen (>= 0.3.3.3.0), StanHeaders (>= 2.18.0), BH (>= 1.66.0), rstan (>= 2.18.1)
Imports: rstan (>= 2.18), reshape2, mvtnorm, igraph
Depends: R (>= 3.4), methods, Rcpp (>= 0.12.0)
Suggests: knitr, rmarkdown, testthat, shiny, ggplot2, covr, qgraph
SystemRequirements: GNU make
VignetteBuilder: knitr
NeedsCompilation: yes
URL: https://github.com/jpritikin/pcFactorStan
BugReports: https://github.com/jpritikin/pcFactorStan/issues
RoxygenNote: 6.1.1
Packaged: 2019-06-08 12:00:51 UTC; joshua
Author: Joshua N. Pritikin [aut, cre] (<https://orcid.org/0000-0002-9862-5484>), Daniel C. Furr [ctb], Trustees of Columbia University [cph]
Maintainer: Joshua N. Pritikin <jpritikin@pobox.com>
Repository: CRAN
Date/Publication: 2019-06-11 09:40:03 UTC

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New package PakPMICS2018mn with initial version 0.1.0
Package: PakPMICS2018mn
Type: Package
Title: Multiple Indicator Cluster Survey (MICS) 2017-18 Men Questionnaire Data for Punjab, Pakistan
Version: 0.1.0
Authors@R: c( person(c("Muhammad", "Yaseen"), email = "myaseen208@gmail.com", role = c("aut", "cre")) , person(c("Muhammad", "Usman"), email = "usmann75@hotmail.com", role = c("ctb")) )
Author: Muhammad Yaseen [aut, cre], Muhammad Usman [ctb]
Maintainer: Muhammad Yaseen <myaseen208@gmail.com>
Description: Provides data set and function for exploration of Multiple Indicator Cluster Survey (MICS) 2017-18 Men questionnaire data for Punjab, Pakistan. The results of the present survey are critically important for the purposes of Sustainable Development Goals (SDGs) monitoring, as the survey produces information on 32 global Sustainable Development Goals (SDGs) indicators. The data was collected from 53,840 households selected at the second stage with systematic random sampling out of a sample of 2,692 clusters selected using probability proportional to size sampling. Six questionnaires were used in the survey: (1) a household questionnaire to collect basic demographic information on all de jure household members (usual residents), the household, and the dwelling; (2) a water quality testing questionnaire administered in three households in each cluster of the sample; (3) a questionnaire for individual women administered in each household to all women age 15-49 years; (4) a questionnaire for individual men administered in every second household to all men age 15-49 years; (5) an under-5 questionnaire, administered to mothers (or caretakers) of all children under 5 living in the household; and (6) a questionnaire for children age 5-17 years, administered to the mother (or caretaker) of one randomly selected child age 5-17 years living in the household (<http://www.mics.unicef.org/surveys>).
Depends: R (>= 3.5.0)
Imports: tibble
License: GPL-2
URL: https://github.com/myaseen208/PakPMICS2018mn, https://myaseen208.github.io/PakPMICS2018mn/
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Note: Department of Mathematics and Statistics, University of Agriculture Faisalabad, Faisalabad-Pakistan.
Suggests: testthat, R.rsp
VignetteBuilder: R.rsp
NeedsCompilation: no
Packaged: 2019-06-08 13:10:59 UTC; myaseen
Repository: CRAN
Date/Publication: 2019-06-11 09:40:09 UTC

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Sun, 09 Jun 2019

New package motmot with initial version 2.1.2
Package: motmot
Type: Package
Title: Models of Trait Macroevolution on Trees
Version: 2.1.2
Depends: R (>= 2.10.0), ape (>= 3.0-7)
Date: 2019-06-02
Author: Mark Puttick [aut, cre, cph], Gavin Thomas [aut, cph], Rob Freckleton [aut, cph], Magnus Clarke [ctb], Travis Ingram [ctb], David Orme [ctb], Emmanuel Paradis [ctb]
Maintainer: Mark Puttick <marknputtick@gmail.com>
Description: Functions for fitting models of trait evolution on phylogenies for continuous traits. The majority of functions described in Thomas and Freckleton (2011) <doi:10.1111/j.2041-210X.2011.00132.x> and include functions that allow for tests of variation in the rates of trait evolution.
License: GPL (>= 2)
Repository: CRAN
URL: https://puttickbiology.wordpress.com/motmot/
RoxygenNote: 6.1.1
LazyData: true
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
LinkingTo: Rcpp
Imports: Rcpp, coda, ks, mvtnorm, caper, methods
Encoding: UTF-8
SystemRequirements: C++11
NeedsCompilation: yes
Packaged: 2019-06-09 08:01:44 UTC; markputtick
Date/Publication: 2019-06-09 16:00:02 UTC

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Sat, 08 Jun 2019

New package PakPMICS2018mm with initial version 0.1.0
Package: PakPMICS2018mm
Type: Package
Title: Multiple Indicator Cluster Survey (MICS) 2017-18 Maternal Mortality Questionnaire Data for Punjab, Pakistan
Version: 0.1.0
Authors@R: c( person(c("Muhammad", "Yaseen"), email = "myaseen208@gmail.com", role = c("aut", "cre")) , person(c("Muhammad", "Usman"), email = "usmann75@hotmail.com", role = c("ctb")) )
Author: Muhammad Yaseen [aut, cre], Muhammad Usman [ctb]
Maintainer: Muhammad Yaseen <myaseen208@gmail.com>
Description: Provides data set and function for exploration of Multiple Indicator Cluster Survey (MICS) 2017-18 Maternal Mortality questionnaire data for Punjab, Pakistan. The results of the present survey are critically important for the purposes of Sustainable Development Goals (SDGs) monitoring, as the survey produces information on 32 global Sustainable Development Goals (SDGs) indicators. The data was collected from 53,840 households selected at the second stage with systematic random sampling out of a sample of 2,692 clusters selected using probability proportional to size sampling. Six questionnaires were used in the survey: (1) a household questionnaire to collect basic demographic information on all de jure household members (usual residents), the household, and the dwelling; (2) a water quality testing questionnaire administered in three households in each cluster of the sample; (3) a questionnaire for individual women administered in each household to all women age 15-49 years; (4) a questionnaire for individual men administered in every second household to all men age 15-49 years; (5) an under-5 questionnaire, administered to mothers (or caretakers) of all children under 5 living in the household; and (6) a questionnaire for children age 5-17 years, administered to the mother (or caretaker) of one randomly selected child age 5-17 years living in the household (<http://www.mics.unicef.org/surveys>).
Depends: R (>= 3.5.0)
Imports: tibble
License: GPL-2
URL: https://github.com/myaseen208/PakPMICS2018mm, https://myaseen208.github.io/PakPMICS2018mm/
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Note: Department of Mathematics and Statistics, University of Agriculture Faisalabad, Faisalabad-Pakistan.
Suggests: testthat, R.rsp
VignetteBuilder: R.rsp
NeedsCompilation: no
Packaged: 2019-06-08 05:31:19 UTC; myaseen
Repository: CRAN
Date/Publication: 2019-06-08 09:40:03 UTC

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New package Rinstapkg with initial version 0.1.0
Package: Rinstapkg
Title: An Implementation of the 'Instagram' API Using Tidy Principles
Version: 0.1.0
Date: 2019-06-07
Description: Provides functions to use the 'Instagram' API to get feed and user information, but also performs basic in-app functionality such as liking, commenting, following, and blocking. Use of this package means that you will not use it to spam, harass, or perform other nefarious acts. For more details on how to use the API please see this package's website <https://eric88tchong.github.io/Rinstapkg/> for more information, documentation, and examples.
Authors@R: c( person("Eric", "Tchong", , "est2fr@virginia.edu", c("aut", "cre")), person(c("Steven", "M."), "Mortimer", , "reportmort@gmail.com", c("ctb")), person("Jennifer", "Bryan", , "jenny@rstudio.com", c("ctb", "cph")), person("Joanna", "Zhao", , "joanna.zhao@alumni.ubc.ca", c("ctb", "cph")) )
URL: https://github.com/eric88tchong/Rinstapkg
BugReports: https://github.com/eric88tchong/Rinstapkg/issues
Encoding: UTF-8
Depends: R (>= 3.1.0)
License: MIT + file LICENSE
LazyData: true
Imports: methods, httr, dplyr, jsonlite, purrr, readr, lubridate, digest, uuid, rlang
Suggests: knitr, testthat, rmarkdown, here
VignetteBuilder: knitr
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-06-07 14:00:20 UTC; steven.mortimer
Author: Eric Tchong [aut, cre], Steven M. Mortimer [ctb], Jennifer Bryan [ctb, cph], Joanna Zhao [ctb, cph]
Maintainer: Eric Tchong <est2fr@virginia.edu>
Repository: CRAN
Date/Publication: 2019-06-08 08:20:04 UTC

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New package missSBM with initial version 0.2.0
Package: missSBM
Type: Package
Title: Handling Missing Data in Stochastic Block Models
Version: 0.2.0
Authors@R: c( person("Julien", "Chiquet", role = c("aut", "cre"), email = "julien.chiquet@inra.fr", comment = c(ORCID = "0000-0002-3629-3429")), person("Pierre", "Barbillon", role = c("aut"), email = "pierre.barbillon@agroparistech.fr", comment = c(ORCID = "0000-0002-7766-7693")), person("Timothée", "Tabouy", role = c("aut"), email = "timothee.tabouy@agroparistech.fr") )
Maintainer: Julien Chiquet <julien.chiquet@inra.fr>
Description: When a network is partially observed (here, NAs in the adjacency matrix rather than 1 or 0 due to missing information between node pairs), it is possible to account for the underlying process that generates those NAs. 'missSBM' adjusts the popular stochastic block model from network data sampled under various missing data conditions, as described in Tabouy, Barbillon and Chiquet (2019) <doi:10.1080/01621459.2018.1562934>.
URL: https://jchiquet.github.io/missSBM
BugReports: https://github.com/jchiquet/missSBM/issues
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Depends: R (>= 3.4.0)
Imports: Rcpp, methods, ape, igraph, nloptr, corrplot, R6, magrittr
LinkingTo: Rcpp, RcppArmadillo
Collate: 'RcppExports.R' 'SBM-Class.R' 'SBM_fit-Class.R' 'SBM_fit_covariates-Class.R' 'SBM_fit_nocovariate-Class.R' 'SBM_sampler-Class.R' 'er_network.R' 'estimate.R' 'frenchblog2007.R' 'missSBM-package.R' 'utils_missSBM.R' 'networkSampling-Class.R' 'networkSampling_fit-Class.R' 'missSBM_fit-Class.R' 'missSBM_collection-Class.R' 'networkSampler-Class.R' 'prepare_data.R' 'sample.R' 'sampledNetwork-Class.R' 'simulate.R' 'utils-pipe.R' 'utils_initialization.R' 'war.R'
Suggests: aricode, blockmodels, testthat, covr, knitr, rmarkdown, ggplot2
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2019-06-07 12:08:02 UTC; jchiquet
Author: Julien Chiquet [aut, cre] (<https://orcid.org/0000-0002-3629-3429>), Pierre Barbillon [aut] (<https://orcid.org/0000-0002-7766-7693>), Timothée Tabouy [aut]
Repository: CRAN
Date/Publication: 2019-06-08 08:10:03 UTC

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Fri, 07 Jun 2019

New package vanddraabe with initial version 1.1.1
Package: vanddraabe
Type: Package
Title: Identification and Statistical Analysis of Conserved Waters Near Proteins
Description: Identify and analyze conserved waters within crystallographic protein structures and molecular dynamics simulation trajectories. Statistical parameters for each water cluster, informative graphs, and a PyMOL session file to visually explore the conserved waters and protein are returned. Hydrophilicity is the propensity of waters to congregate near specific protein atoms and is related to conserved waters. An informatics derived set of hydrophilicity values are provided based on a large, high-quality X-ray protein structure dataset.
Version: 1.1.1
Date: 2019-06-10
Depends: R (>= 3.6.0)
Imports: bio3d (>= 2.3-4), cowplot (>= 0.9.4), fastcluster (>= 1.1.25), ggplot2 (>= 3.1.1), openxlsx (>= 4.1.0), reshape2 (>= 1.4.3), scales (>= 1.0.0)
Suggests: knitr, rmarkdown, testthat
Authors@R: person("Emilio Xavier", "Esposito", email = "emilio@exeResearch.com", role = c("aut", "cre"))
URL: http://vanddraabe.com, https://github.com/exeResearch/vanddraabe/
BugReports: https://github.com/exeResearch/vanddraabe/issues
License: MIT + file LICENSE
LazyData: TRUE
RoxygenNote: 6.1.1
VignetteBuilder: knitr
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2019-06-07 13:35:50 UTC; emilioxavieresposito
Author: Emilio Xavier Esposito [aut, cre]
Maintainer: Emilio Xavier Esposito <emilio@exeResearch.com>
Repository: CRAN
Date/Publication: 2019-06-07 22:00:03 UTC

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New package RandomCoefficients with initial version 0.0.2
Package: RandomCoefficients
Title: Adaptive Estimation in the Linear Random Coefficients Models
Version: 0.0.2
Authors@R: c(person("Christophe", "Gaillac", email = "christophe.gaillac@ensae.fr", role = c("aut", "cre")),person("Eric", "Gautier", email = "eric.gautier@tse-fr.eu", role = c("aut")))
Description: We implement adaptive estimation of the joint density linear model where the coefficients - intercept and slopes - are random and independent from regressors which support is a proper subset. The estimator proposed in Gaillac and Gautier (2019) <arXiv:1905.06584> is based on Prolate Spheroidal Wave Functions which are computed efficiently in 'RandomCoefficients'. This package also provides a parallel implementation of the estimator.
Depends: R (>= 3.0.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
RoxygenNote: 6.1.0
Imports: snowfall, stats, orthopolynom, polynom, fourierin, sfsmisc, tmvtnorm, rdetools, ks, statmod, RCEIM, robustbase, VGAM
NeedsCompilation: no
Packaged: 2019-06-05 12:55:26 UTC; gaillac
Author: Christophe Gaillac [aut, cre], Eric Gautier [aut]
Maintainer: Christophe Gaillac <christophe.gaillac@ensae.fr>
Repository: CRAN
Date/Publication: 2019-06-07 14:00:03 UTC

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New package isocat with initial version 0.2.3
Package: isocat
Type: Package
Title: Isotope Clustering and Assignment Tools
Version: 0.2.3
Authors@R: person("Caitlin", "Campbell", email = "caitjcampbell@gmail.com", role = c("aut", "cre"))
Description: This resource provides tools to create, compare, and post-process spatial isotope assignment models of animal origin. It generates probability-of-origin maps for individuals based on user-provided tissue and environment isotope values (e.g., as generated by IsoMAP, Bowen [2010] <doi:10.1111/2041-210X.12147>) using the framework established in Bowen (2014) <doi:10.1111/2041-210X.12147>. The package 'isocat' can then quantitatively compare and cluster these maps to group individuals by similar origin. It also includes techniques for applying four approaches (cumulative sum, odds ratio, quantile only, and quantile simulation) with which users can summarize geographic origins and probable distance traveled by individuals.
License: CC0
Encoding: UTF-8
Language: en-US
LazyData: true
RoxygenNote: 6.1.1
Depends: R (>= 2.10), utils, raster
Imports: stats, plyr, dplyr, sp, magrittr, foreach
Suggests: dendextend, doParallel, ggplot2, gridExtra, kableExtra, knitr, parallel, purrr, pvclust, rmarkdown, rasterVis, viridisLite
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-06-06 15:52:00 UTC; ccampbell
Author: Caitlin Campbell [aut, cre]
Maintainer: Caitlin Campbell <caitjcampbell@gmail.com>
Repository: CRAN
Date/Publication: 2019-06-07 11:50:03 UTC

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New package PakPMICS2018hh with initial version 0.1.0
Package: PakPMICS2018hh
Type: Package
Title: Multiple Indicator Cluster Survey (MICS) 2017-18 Household Questionnaire Data for Punjab, Pakistan
Version: 0.1.0
Authors@R: c( person(c("Muhammad", "Yaseen"), email = "myaseen208@gmail.com", role = c("aut", "cre")) , person(c("Muhammad", "Usman"), email = "usmann75@hotmail.com", role = c("ctb")) )
Author: Muhammad Yaseen [aut, cre], Muhammad Usman [ctb]
Maintainer: Muhammad Yaseen <myaseen208@gmail.com>
Description: Provides data set and function for exploration of Multiple Indicator Cluster Survey (MICS) 2017-18 Household questionnaire data for Punjab, Pakistan. The results of the present survey are critically important for the purposes of Sustainable Development Goals (SDGs) monitoring, as the survey produces information on 32 global Sustainable Development Goals (SDGs) indicators. The data was collected from 53,840 households selected at the second stage with systematic random sampling out of a sample of 2,692 clusters selected using probability proportional to size sampling. Six questionnaires were used in the survey: (1) a household questionnaire to collect basic demographic information on all de jure household members (usual residents), the household, and the dwelling; (2) a water quality testing questionnaire administered in three households in each cluster of the sample; (3) a questionnaire for individual women administered in each household to all women age 15-49 years; (4) a questionnaire for individual men administered in every second household to all men age 15-49 years; (5) an under-5 questionnaire, administered to mothers (or caretakers) of all children under 5 living in the household; and (6) a questionnaire for children age 5-17 years, administered to the mother (or caretaker) of one randomly selected child age 5-17 years living in the household (<http://www.mics.unicef.org/surveys>).
Depends: R (>= 3.5.0)
Imports: tibble
License: GPL-2
URL: https://github.com/myaseen208/PakPMICS2018hh, https://myaseen208.github.io/PakPMICS2018hh/
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Note: Department of Mathematics and Statistics, University of Agriculture Faisalabad, Faisalabad-Pakistan.
Suggests: testthat, R.rsp
VignetteBuilder: R.rsp
NeedsCompilation: no
Packaged: 2019-06-07 08:27:31 UTC; myaseen
Repository: CRAN
Date/Publication: 2019-06-07 10:30:03 UTC

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New package RtextSummary with initial version 0.1.0
Package: RtextSummary
Type: Package
Title: Summarizes Text by Extracting Relevant Sentences
Version: 0.1.0
Authors@R: c( person("Suryavanshi", "Abhijit", role = c("aut", "cre"), email = "abhi.surya@gmail.com") )
Description: Build a text summary by extracting relevant sentences from your text. The training dataset should consist of several documents, each document should have sentences separated by a period. While fitting the model, the 'term frequency - inverse document frequency' (TF-IDF) matrix that reflects how important a word is to a document is calculated first. Then vector representations for words are obtained from the 'global vectors for word representation' algorithm (GloVe). While applying the model on new data, the GloVe word vectors for each word are weighted by their TF-IDF weights and averaged to give a sentence vector or a document vector. The magnitude of this sentence vector gives the importance of that sentence within the document. Another way to obtain the importance of the sentence is to calculate cosine similarity between the sentence vector and the document vector. The output can either be at the sentence level (sentences and weights are returned) or at a document level (the summary for each document is returned). It is useful to first get a sentence level output and get quantiles of the sentence weights to determine a cutoff threshold for the weights. This threshold can then be used in the document level output. This method is a variation of the TF-IDF extractive summarization method mentioned in a review paper by Gupta (2010) <doi:10.4304/jetwi.2.3.258-268>.
License: GPL-3
Encoding: UTF-8
LazyData: false
Imports: R6, mlapi, stringr, tidyr, tokenizers, text2vec, Matrix.utils, dplyr
Depends: R (>= 2.10)
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2019-06-06 16:03:15 UTC; ASuryav1
Author: Suryavanshi Abhijit [aut, cre]
Maintainer: Suryavanshi Abhijit <abhi.surya@gmail.com>
Repository: CRAN
Date/Publication: 2019-06-07 08:30:03 UTC

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New package Patterns with initial version 1.0
Package: Patterns
Type: Package
Title: Deciphering Biological Networks with Patterned Heterogeneous Measurements
Version: 1.0
Date: 2019-05-27
Depends: R (>= 2.10)
biocViews:
Imports: abind, animation, Biobase, c060, cluster, elasticnet, glmnet, gplots, graphics, grDevices, grid, igraph, jetset, KernSmooth, lars, lattice, limma, magic, methods, Mfuzz, movMF, msgps, nnls, pixmap, plotrix, SelectBoost, splines, spls, stats4, survival, tnet, VGAM, WGCNA
Suggests: repmis, biomaRt, R.rsp, CascadeData, knitr, rmarkdown
Authors@R: c( person(given = "Frederic", family= "Bertrand", role = c("cre", "aut"), email = "frederic.bertrand@math.unistra.fr", comment = c(ORCID = "0000-0002-0837-8281")), person(given = "Myriam", family= "Maumy-Bertrand", role = c("aut"), email = "myriam.maumy-bertrand@math.unistra.fr", comment = c(ORCID = "0000-0002-4615-1512")))
Author: Frederic Bertrand [cre, aut] (<https://orcid.org/0000-0002-0837-8281>), Myriam Maumy-Bertrand [aut] (<https://orcid.org/0000-0002-4615-1512>)
Maintainer: Frederic Bertrand <frederic.bertrand@math.unistra.fr>
Description: A modeling tool dedicated to biological network modeling. It allows for single or joint modeling of, for instance, genes and proteins. It starts with the selection of the actors that will be the used in the reverse engineering upcoming step. An actor can be included in that selection based on its differential measurement (for instance gene expression or protein abundance) or on its time course profile. Wrappers for actors clustering functions and cluster analysis are provided. It also allows reverse engineering of biological networks taking into account the observed time course patterns of the actors. Many inference functions are provided and dedicated to get specific features for the inferred network such as sparsity, robust links, high confidence links or stable through resampling links. Some simulation and prediction tools are also available for cascade networks. Example of use with microarray or RNA-Seq data are provided.
License: GPL (>= 2)
Encoding: UTF-8
Collate: global.R micro_array.R network.R micro_array-network.R micropredict.R
Classification/MSC: 62J05, 62J07, 62J99, 92C42
VignetteBuilder: knitr
RoxygenNote: 6.1.1
URL: http://www-irma.u-strasbg.fr/~fbertran/, https://github.com/fbertran/Patterns
BugReports: https://github.com/fbertran/Patterns/issues
NeedsCompilation: no
Packaged: 2019-06-06 20:27:04 UTC; fbertran
Repository: CRAN
Date/Publication: 2019-06-07 08:10:03 UTC

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New package splithalfr with initial version 1.0.10
Package: splithalfr
Title: Extensible Bootstrapped Split-Half Reliabilities
Version: 1.0.10
Date: 2019-06-06
Author: Thomas Pronk [aut, cre]
Authors@R: person("Thomas", "Pronk", email = "pronkthomas@gmail.com", role = c("aut", "cre"))
Description: Calculates scores and estimates bootstrapped split-half reliabilities for reaction time tasks and questionnaires. The 'splithalfr' can be extended with custom scoring algorithms for user-provided datasets. For more information, see Parsons, Kruijt, & Fox (2018) <doi:10.31234/osf.io/6ka9z>.
Depends: R (>= 3.6)
License: GPL-3
Encoding: UTF-8
LazyData: true
Suggests: psych (>= 1.8.12), knitr (>= 1.20), rmarkdown (>= 1.10), testthat (>= 2.1.0)
Imports: dplyr (>= 0.8.1), rlang (>= 0.3.4)
RoxygenNote: 6.1.1.9000
VignetteBuilder: knitr
URL: https://thomaspronk.com, https://www.uva.nl/en/profile/p/r/t.pronk/t.pronk.html
NeedsCompilation: no
Packaged: 2019-06-06 15:32:58 UTC; Thomas
Maintainer: Thomas Pronk <pronkthomas@gmail.com>
Repository: CRAN
Date/Publication: 2019-06-07 08:00:03 UTC

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New package phenofit with initial version 0.2.5-2
Package: phenofit
Type: Package
Title: Extract Remote Sensing Vegetation Phenology
Version: 0.2.5-2
Authors@R: c( person("Dongdong", "Kong", role = c("aut", "cre"), email = "kongdd.sysu@gmail.com"), person("Jianjian", "Cui", role = c("aut"), email = "cuijj6@mail2.sysu.edu.cn"), person("Mingzhong", "Xiao", role = c("aut"), email = "xmingzh@mail2.sysu.edu.cn"), person("Yongqiang", "Zhang", role = c("aut"), email = "yongqiang.zhang2014@gmail.com"), person("Xihui", "Gu", role = c("aut"), email = "guxh@cug.edu.cn"))
Description: The merits of 'TIMESAT' and 'phenopix' are adopted. Besides, a simple and growing season dividing method and a practical snow elimination method based on Whittaker were proposed. 7 curve fitting methods and 4 phenology extraction methods were provided. Parameters boundary are considered for every curve fitting methods according to their ecological meaning. And 'optimx' is used to select best optimization method for different curve fitting methods. Reference: Dongdong Kong, R package: A state-of-the-art Vegetation Phenology extraction package, phenofit version 0.2.3, <https://github.com/kongdd/phenofit>; Zhang, Q., Kong, D., Shi, P., Singh, V.P., Sun, P., 2018. Vegetation phenology on the Qinghai-Tibetan Plateau and its response to climate change (1982–2013). Agric. For. Meteorol. 248, 408–417. <doi:10.1016/j.agrformet.2017.10.026>.
License: GPL-2 | file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
LinkingTo: Rcpp, RcppArmadillo
Depends: R (>= 3.1)
Imports: Rcpp, tibble, dplyr, purrr, stringr, tidyr, ggplot2, lubridate, data.table, spam, grid, gridExtra, magrittr, plyr, reshape2, zoo, optimx, ucminf, numDeriv, grDevices, utils, stats, shiny, jsonlite, foreach, iterators
Suggests: knitr, rmarkdown, testthat
URL: https://github.com/kongdd/phenofit
BugReports: https://github.com/kongdd/phenofit/issues
NeedsCompilation: yes
Packaged: 2019-06-07 01:03:59 UTC; kongd
Author: Dongdong Kong [aut, cre], Jianjian Cui [aut], Mingzhong Xiao [aut], Yongqiang Zhang [aut], Xihui Gu [aut]
Maintainer: Dongdong Kong <kongdd.sysu@gmail.com>
Repository: CRAN
Date/Publication: 2019-06-07 08:00:08 UTC

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New package PakPMICS2018fs with initial version 0.1.0
Package: PakPMICS2018fs
Type: Package
Title: Multiple Indicator Cluster Survey (MICS) 2017-18 Children Age 5-17 Questionnaire Data for Punjab, Pakistan
Version: 0.1.0
Author: Muhammad Yaseen [aut, cre], Muhammad Usman [ctb]
Maintainer: Muhammad Yaseen <myaseen208@gmail.com>
Description: Provides data set and function for exploration of Multiple Indicator Cluster Survey (MICS) 2017-18 Children Age 5-17 questionnaire data for Punjab, Pakistan. The results of the present survey are critically important for the purposes of Sustainable Development Goals (SDGs) monitoring, as the survey produces information on 32 global Sustainable Development Goals (SDGs) indicators. The data was collected from 53,840 households selected at the second stage with systematic random sampling out of a sample of 2,692 clusters selected using probability proportional to size sampling. Six questionnaires were used in the survey: (1) a household questionnaire to collect basic demographic information on all de jure household members (usual residents), the household, and the dwelling; (2) a water quality testing questionnaire administered in three households in each cluster of the sample; (3) a questionnaire for individual women administered in each household to all women age 15-49 years; (4) a questionnaire for individual men administered in every second household to all men age 15-49 years; (5) an under-5 questionnaire, administered to mothers (or caretakers) of all children under 5 living in the household; and (6) a questionnaire for children age 5-17 years, administered to the mother (or caretaker) of one randomly selected child age 5-17 years living in the household (<http://www.mics.unicef.org/surveys>).
Depends: R (>= 3.5.0)
Imports: tibble
License: GPL-2
URL: https://github.com/myaseen208/PakPMICS2018fs, https://myaseen208.github.io/PakPMICS2018fs/
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Note: Department of Mathematics and Statistics, University of Agriculture Faisalabad, Faisalabad-Pakistan.
Suggests: testthat, R.rsp
VignetteBuilder: R.rsp
NeedsCompilation: no
Packaged: 2019-06-06 13:27:47 UTC; myaseen
Repository: CRAN
Date/Publication: 2019-06-07 07:50:14 UTC

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New package ncdfgeom with initial version 1.0.0
Package: ncdfgeom
Type: Package
Title: 'NetCDF' Geometry and Time Series
Version: 1.0.0
Date: 2019-06-05
Authors@R: c(person("David", "Blodgett", role = c("aut", "cre"), email = "dblodgett@usgs.gov"), person("Luke", "Winslow", role = "ctb"))
Description: Tools to create time series and geometry 'NetCDF' files.
URL: https://code.usgs.gov/water/ncdfgeom
BugReports: https://github.com/USGS-R/ncdfgeom/issues
Imports: RNetCDF, ncmeta, sf, dplyr, methods
Depends: R (>= 3.0)
Suggests: testthat, knitr, rmarkdown, pkgdown, tidyverse, sp, geoknife, ncdf4, jsonlite
License: CC0
LazyData: TRUE
Encoding: UTF-8
VignetteBuilder: knitr
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-06-06 14:32:54 UTC; dblodgett
Author: David Blodgett [aut, cre], Luke Winslow [ctb]
Maintainer: David Blodgett <dblodgett@usgs.gov>
Repository: CRAN
Date/Publication: 2019-06-07 07:50:03 UTC

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New package cpd with initial version 0.1.0
Package: cpd
Type: Package
Title: Complex Pearson Distributions
Version: 0.1.0
Date: 2019-05-28
Authors@R: c(person("Silverio", "Vilchez-Lopez", role = c("aut", "cre"), email = "svilchez@ujaen.es"), person("Maria Jose", "Olmo-Jimenez", role = "aut", email = "mjolmo@ujaen.es"), person("Jose", "Rodriguez-Avi", role = "aut", email = "jravi@ujaen.es") )
Description: Probability mass function, distribution function, quantile function and random generation for the Complex Triparametric Pearson (CTP) and Complex Biparametric Pearson (CBP) distributions developed by Rodriguez-Avi et al (2003) <doi:10.1007/s00362-002-0134-7>, Rodriguez-Avi et al (2004) <doi:10.1007/BF02778271> and Olmo-Jimenez et al (2018) <doi:10.1080/00949655.2018.1482897>. The package also contains maximum-likelihood fitting functions for these models.
Depends: R (>= 2.5.0)
Imports: fAsianOptions, Rdpack
RdMacros: Rdpack
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-06-06 18:30:31 UTC; svilc_000
Author: Silverio Vilchez-Lopez [aut, cre], Maria Jose Olmo-Jimenez [aut], Jose Rodriguez-Avi [aut]
Maintainer: Silverio Vilchez-Lopez <svilchez@ujaen.es>
Repository: CRAN
Date/Publication: 2019-06-07 08:00:14 UTC

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Thu, 06 Jun 2019

New package CircSpaceTime with initial version 0.9.0
Package: CircSpaceTime
Type: Package
Title: Spatial and Spatio-Temporal Bayesian Model for Circular Data
Version: 0.9.0
Authors@R: c(person("Giovanna", "Jona Lasinio", email = "giovanna.jonalasinio@uniroma1.it", role = c("aut"), comment = c(ORCID = "0000-0001-8912-5018")), person("Gianluca", "Mastrantonio", email = "gianluca.mastrantonio@polito.it", role = c("aut"), comment = c(ORCID = "0000-0002-2963-6729")), person("Mario", "Santoro", email = "santoro.ma@gmail.com", role = c("aut", "cre"), comment = c(ORCID = c("0000-0001-6626-9430"))))
BugReports: https://github.com/santoroma/CircSpaceTime
Description: Implementation of Bayesian models for spatial and spatio-temporal interpolation of circular data using Gaussian Wrapped and Gaussian Projected distributions. We developed the methods described in Jona Lasinio G. et al. (2012) <doi: 10.1214/12-aoas576>, Wang F. et al. (2014) <doi: 10.1080/01621459.2014.934454> and Mastrantonio G. et al. (2016) <doi: 10.1007/s11749-015-0458-y>.
License: GPL-3
Encoding: UTF-8
LazyData: true
URL: https://github.com/santoroma/CircSpaceTime
Suggests: foreach, iterators, parallel, doParallel, gridExtra
LinkingTo: Rcpp, RcppArmadillo, RInside
Imports: Rcpp (>= 0.12.14), circular, RInside, coda, ggplot2
RoxygenNote: 6.1.0
NeedsCompilation: yes
Packaged: 2019-06-06 09:07:05 UTC; harlok
Author: Giovanna Jona Lasinio [aut] (<https://orcid.org/0000-0001-8912-5018>), Gianluca Mastrantonio [aut] (<https://orcid.org/0000-0002-2963-6729>), Mario Santoro [aut, cre] (<https://orcid.org/0000-0001-6626-9430>)
Maintainer: Mario Santoro <santoro.ma@gmail.com>
Depends: R (>= 2.10)
Repository: CRAN
Date/Publication: 2019-06-06 15:12:15 UTC

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New package stabreg with initial version 0.1.2
Package: stabreg
Type: Package
Title: Linear Regression with the Stable Distribution
Version: 0.1.2
Authors@R: c(person("Oleg Kopylov", role = c("aut", "cre"), email = "okopy@protonmail.com"), person("Sebastian Ament", role = "ctb"))
Maintainer: Oleg Kopylov <okopy@protonmail.com>
Description: Efficient regression for heavy-tailed and skewed data following a stable distribution. Generalized regression where the skewness and tail parameter of residuals are dependent on regressors is also available. Includes fast calculation of stable densities. Calculation of densities is based on efficient numerical methods from Ament and O'Neil (2017) <doi:10.1007/s11222-017-9725-y>. Parts of the code have been ported to C from Ament's 'Matlab' code available at <https://gitlab.com/s_ament/qastable>.
Encoding: UTF-8
LazyData: true
License: GPL-3
NeedsCompilation: yes
Imports: numDeriv
Packaged: 2019-06-05 17:21:06 UTC; oleg
Author: Oleg Kopylov [aut, cre], Sebastian Ament [ctb]
Repository: CRAN
Date/Publication: 2019-06-06 14:20:03 UTC

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New package spinBayes with initial version 0.1.0
Package: spinBayes
Type: Package
Title: Semi-Parametric Gene-Environment Interaction via Bayesian Variable Selection
Version: 0.1.0
Author: Jie Ren, Fei Zhou, Xiaoxi Li, Cen Wu, Yu Jiang
Maintainer: Jie Ren <jieren@ksu.edu>
Description: Many complex diseases are known to be affected by the interactions between genetic variants and environmental exposures beyond the main genetic and environmental effects. Existing Bayesian methods for gene-environment (G×E) interaction studies are challenged by the high-dimensional nature of the study and the complexity of environmental influences. We have developed a novel and powerful semi-parametric Bayesian variable selection method that can accommodate linear and nonlinear G×E interactions simultaneously (Ren et al. (2019) <arXiv:1906.01057>). Furthermore, the proposed method can conduct structural identification by distinguishing nonlinear interactions from main effects only case within Bayesian framework. Spike-and-slab priors are incorporated on both individual and group level to shrink coefficients corresponding to irrelevant main and interaction effects to zero exactly. 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, splines, MASS, glmnet, utils
URL: https://github.com/jrhub/spinBayes
BugReports: https://github.com/jrhub/spinBayes/issues
RoxygenNote: 6.1.1
NeedsCompilation: yes
Packaged: 2019-06-05 19:52:21 UTC; JieRen
Repository: CRAN
Date/Publication: 2019-06-06 14:40:03 UTC

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New package EstimationTools with initial version 1.1.0
Package: EstimationTools
Type: Package
Title: Maximum Likelihood Estimation for Probability Functions from Data Sets
Version: 1.1.0
Authors@R: person("Jaime", "Mosquera", email = "jmosquerag@unal.edu.co", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-1684-4756"))
Imports: Rdpack, knitr, rmarkdown
RdMacros: Rdpack
Suggests: gamlss.dist
Depends: R (>= 3.3.0), stats, DEoptim, boot, numDeriv, BBmisc
Description: A routine for parameter estimation for any probability density or mass function implemented in R via maximum likelihood (ML) given a data set. This routine is a wrapper function specifically developed for ML estimation. There are included optimization procedures such as 'nlminb' and 'optim' from base package, and 'DEoptim' Mullen (2011) <doi: 10.18637/jss.v040.i06>. Standard errors are estimated with 'numDeriv' Gilbert (2011) <http://CRAN.R-project.org/package=numDeriv>.
License: GPL-3
URL: https://github.com/Jaimemosg/EstimationTools
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-06-05 21:14:40 UTC; USUARIO
Author: Jaime Mosquera [aut, cre] (<https://orcid.org/0000-0002-1684-4756>)
Maintainer: Jaime Mosquera <jmosquerag@unal.edu.co>
Repository: CRAN
Date/Publication: 2019-06-06 14:52:16 UTC

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New package bimets with initial version 1.4.0
Package: bimets
Type: Package
Title: Time Series and Econometric Modeling
Version: 1.4.0
Date: 2019-05-12
Authors@R: c(person("Andrea", "Luciani", email = "andrea.luciani@bancaditalia.it", role = c("aut", "cre")), person("Roberto", "Stok", email = "roberto.stok@bancaditalia.it", role = c("aut")), person("Bank of Italy",role = c("cph")))
Maintainer: Andrea Luciani <andrea.luciani@bancaditalia.it>
Author: Andrea Luciani [aut, cre], Roberto Stok [aut], Bank of Italy [cph]
ByteCompile: no
Description: Time series analysis, (dis)aggregation and manipulation, e.g. time series extension, merge, projection, lag, lead, delta, moving and cumulative average and product, selection by index, date and year-period, conversion to daily, monthly, quarterly, (semi)annually. Simultaneous equation models definition, estimation, simulation and forecasting with coefficient restrictions, error autocorrelation, exogenization, add-factors, impact and interim multipliers analysis, conditional equation evaluation, endogenous targeting and model renormalization.
Depends: R (>= 3.3), xts, zoo
Imports: stats
LazyData: true
License: EUPL
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2019-06-05 14:14:42 UTC; m025732
Repository: CRAN
Date/Publication: 2019-06-06 14:10:07 UTC

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New package TopicScore with initial version 0.0.1
Package: TopicScore
Title: The Topic SCORE Algorithm to Fit Topic Models
Version: 0.0.1
Authors@R: c(person("Minzhe", "Wang", role = c("aut", "cre"), email = "minzhew@uchicago.edu"), person("Tracy", "Ke", role = "aut"))
Description: Provides implementation of the "Topic SCORE" algorithm that is proposed by Tracy Ke and Minzhe Wang. The singular value decomposition step is optimized through the usage of svds() function in 'RSpectra' package, on a 'dgRMatrix' sparse matrix. Also provides a column-wise error measure in the word-topic matrix A, and an algorithm for recovering the topic-document matrix W given A and D based on quadratic programming. The details about the techniques are explained in the paper "A new SVD approach to optimal topic estimation" by Tracy Ke and Minzhe Wang (2017) <arXiv:1704.07016>.
Depends: R (>= 3.5.0)
License: MIT + file LICENSE
LazyData: true
RoxygenNote: 6.1.1
Imports: utils, stats, graphics, RSpectra, combinat, quadprog, methods, Matrix, slam
Author: Minzhe Wang [aut, cre], Tracy Ke [aut]
Maintainer: Minzhe Wang <minzhew@uchicago.edu>
NeedsCompilation: no
Packaged: 2019-06-04 15:32:17 UTC; greenlink
Repository: CRAN
Date/Publication: 2019-06-06 11:12:14 UTC

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Wed, 05 Jun 2019

New package clustermq with initial version 0.8.8
Package: clustermq
Title: Evaluate Function Calls on HPC Schedulers (LSF, SGE, SLURM, PBS/Torque)
Version: 0.8.8
Authors@R: c( person('Michael', 'Schubert', email='mschu.dev@gmail.com', role = c('aut', 'cre', 'cph'), comment = c(ORCID='0000-0002-6862-5221') ), person('EMBL', role = c('cph', 'fnd')) )
Maintainer: Michael Schubert <mschu.dev@gmail.com>
Description: Evaluate arbitrary function calls using workers on HPC schedulers in single line of code. All processing is done on the network without accessing the file system. Remote schedulers are supported via SSH.
URL: https://github.com/mschubert/clustermq
BugReports: https://github.com/mschubert/clustermq/issues
Depends: R (>= 3.0.2)
Imports: narray, progress, purrr, R6, rzmq (>= 0.9.4), utils
License: Apache License (== 2.0) | file LICENSE
LazyData: true
Encoding: UTF-8
Suggests: devtools, dplyr, foreach, iterators, knitr, parallel, roxygen2 (>= 5.0.0), testthat, tools
VignetteBuilder: knitr
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-06-05 18:19:42 UTC; mschu
Author: Michael Schubert [aut, cre, cph] (<https://orcid.org/0000-0002-6862-5221>), EMBL [cph, fnd]
Repository: CRAN
Date/Publication: 2019-06-05 22:00:39 UTC

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New package promotionImpact with initial version 0.1.2
Package: promotionImpact
Type: Package
Title: Analysis & Measurement of Promotion Effectiveness
Version: 0.1.2
Date: 2019-05-16
Authors@R: c( person("Nahyun", "Kim", email = "nhkim1302@ncsoft.com", role = c("cre", "aut")), person("Hyemin", "Um", email = "windy0126@ncsoft.com", role = "aut"), person("Eunjo", "Lee", email = "gimmesilver@ncsoft.com", role = "aut"), person(family = "NCSOFT Corporation", role = "cph") )
Description: Analysis and measurement of promotion effectiveness on a given target variable (e.g. daily sales). After converting promotion schedule into dummy or smoothed predictor variables, the package estimates the effects of these variables controlled for trend/periodicity/structural change using prophet by Taylor and Letham (2017) <doi:10.7287/peerj.preprints.3190v2> and some prespecified variables (e.g. start of a month).
Depends: R (>= 3.5.0), Rcpp (>= 0.12.17), dplyr (>= 0.7.6), ggplot2 (>= 3.0.0), scales (>= 1.0.0)
Imports: KernSmooth (>= 2.23.15), data.table (>= 1.11.4), ggpubr (>= 0.1.8), reshape2 (>= 1.4.3), stringr (>= 1.3.1), strucchange (>= 1.5.1), lmtest (>= 0.9), crayon (>= 1.3.4), prophet (>= 0.3.0.1)
License: BSD_3_clause + file LICENSE
URL: https://github.com/ncsoft/promotionImpact
LazyData: true
RoxygenNote: 6.1.1
Encoding: UTF-8
Author: Nahyun Kim [cre, aut], Hyemin Um [aut], Eunjo Lee [aut], NCSOFT Corporation [cph]
Maintainer: Nahyun Kim <nhkim1302@ncsoft.com>
NeedsCompilation: no
Packaged: 2019-06-05 01:43:34 UTC; nhkim1302
Repository: CRAN
Date/Publication: 2019-06-05 12:40:09 UTC

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New package ICODS with initial version 1.0
Package: ICODS
Type: Package
Title: Data Analysis for ODS and Case-Cohort Designs with Interval-Censoring
Version: 1.0
Date: 2019-6-05
Author: Shannon T. Holloway, Qingning Zhou, Jianwen Cai, Haibo Zhou
Maintainer: Shannon T. Holloway <sthollow@ncsu.edu>
Description: Sieve semiparametric likelihood methods for analyzing interval-censored failure time data from an outcome-dependent sampling (ODS) design and from a case-cohort design. Zhou, Q., Cai, J., and Zhou, H. (2018) <doi:10.1111/biom.12744>; Zhou, Q., Zhou, H., and Cai, J. (2017) <doi:10.1093/biomet/asw067>.
License: GPL-2
Depends: methods, stats, MASS
NeedsCompilation: no
Repository: CRAN
Encoding: UTF-8
RoxygenNote: 6.1.1
Collate: 'myOptim.R' 'minObj.R' 'baseInfo.R' 'CaseCohort_Obj.R' 'CaseCohort_gr.R' 'CaseCohort_fn.R' 'class_ICODS.R' 'CaseCohort_class.R' 'bernstein.R' 'CaseCohortIC.R' 'CaseCohort_data.R' 'ODSDesign_Obj.R' 'ODSDesign_class.R' 'ODSDesignIC.R' 'ODSDesign_data.R' 'ODSDesign_fn.R' 'ODSDesign_gr.R' 'testInputData.R'
Packaged: 2019-06-05 12:16:40 UTC; sthollow
Date/Publication: 2019-06-05 13:00:06 UTC

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New package gradeR with initial version 1.0.0
Package: gradeR
Title: Helps Grade Assignment Submissions that are R Scripts
Version: 1.0.0
Authors@R: person("Taylor", "Brown", email = "trb5me@virginia.edu", role = c("aut", "cre"))
Description: After being given the location of your students' submissions and a test file, the function runs each .R file, and evaluates the results from all the given tests. Results are neatly returned in a data frame that has a row for each student, and a column for each test.
Depends: R (>= 3.4)
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Imports: testthat, methods
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-06-04 16:37:40 UTC; t
Author: Taylor Brown [aut, cre]
Maintainer: Taylor Brown <trb5me@virginia.edu>
Repository: CRAN
Date/Publication: 2019-06-05 11:30:03 UTC

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Tue, 04 Jun 2019

New package utile.tables with initial version 0.1.4
Package: utile.tables
Title: Tools for Building Tables for Publication
Version: 0.1.4
Authors@R: c(person('Eric', 'Finnesgard', email = 'finnesgard.eric@mayo.edu', role = c('aut', 'cre')))
Description: A collection of functions to make building customized ready-to-export tables for publication purposes easier or expedite summarization of a large dataset for review. Includes methods for automatically building a table from data or building the table row-by-row. Key functions include build_row() & build_table() for summarizing columns of data overall or by stratum with appropriate testing and build_event_row() & build_event_table() for creating tables that summarize time-to-event model (Cox PH) parameters, supporting both univariate and multivariate methods.
License: LGPL (>= 2)
Encoding: UTF-8
LazyData: TRUE
Depends: R (>= 3.4.0)
Imports: tibble, utile.tools(>= 0.1.2), dplyr, tidyr, rlang, survival, purrr
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-06-04 14:35:47 UTC; m130239
Author: Eric Finnesgard [aut, cre]
Maintainer: Eric Finnesgard <finnesgard.eric@mayo.edu>
Repository: CRAN
Date/Publication: 2019-06-04 15:30:03 UTC

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New package rerddapXtracto with initial version 0.3.5
Package: rerddapXtracto
Type: Package
Title: Extracts Environmental Data from 'ERDDAP' Web Services
Version: 0.3.5
Authors@R: person("Roy", "Mendelssohn", email = "roy.mendelssohn@noaa.gov", role = c("aut","cre"))
Description: Contains three functions that access environmental data from any 'ERDDAP' data web service. The rxtracto() function extracts data along a trajectory for a given "radius" around the point. The rxtracto_3D() function extracts data in a box. The rxtractogon() function extracts data in a polygon. All of those three function use the 'rerddap' package to extract the data, and should work with any 'ERDDAP' server. There are also two functions, plotBBox() and plotTrack() that use the 'plotdap' package to simplify the creation of maps of the data.
URL: https://github.com/rmendels/rerddapXtracto
BugReports: https://github.com/rmendels/rerddapXtracto/issues
Depends: R(>= 3.5.0)
License: CC0
Imports: abind, dplyr, ggplot2, httr, methods, ncdf4, parsedate, plotdap, readr, rerddap (>= 0.6.0), sp, stats,
Suggests: gganimate, knitr, mapdata, rmarkdown
RoxygenNote: 6.1.1
Encoding: UTF-8
LazyData: TRUE
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-06-03 21:05:32 UTC; rmendels
Author: Roy Mendelssohn [aut, cre]
Maintainer: Roy Mendelssohn <roy.mendelssohn@noaa.gov>
Repository: CRAN
Date/Publication: 2019-06-04 14:30:03 UTC

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New package jenkins with initial version 1.0
Package: jenkins
Type: Package
Title: Simple Jenkins Client
Version: 1.0
Author: Jeroen Ooms
Maintainer: Jeroen Ooms <jeroen@berkeley.edu>
Description: Manage jobs and builds on your Jenkins CI server <https://jenkins.io/>. Create and edit projects, schedule builds, manage the queue, download build logs, and much more.
License: MIT + file LICENSE
URL: https://docs.ropensci.org/jenkins/ (website), https://github.com/ropensci/jenkins
BugReports: https://github.com/ropensci/jenkins/issues
Encoding: UTF-8
Imports: curl, jsonlite
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-06-04 12:09:33 UTC; jeroen
Repository: CRAN
Date/Publication: 2019-06-04 15:00:03 UTC

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New package jackalope with initial version 0.1.0
Package: jackalope
Type: Package
Title: A Swift, Versatile Phylogenomic and High-Throughput Sequencing Simulator
Version: 0.1.0
Authors@R: person(c("Lucas", "A."), "Nell", email = "lucas@lucasnell.com", role = c("cph", "aut", "cre"), comment = c(ORCID = "0000-0003-3209-0517"))
Description: Simply and efficiently simulates (i) variants from reference genomes and (ii) reads from both Illumina <https://www.illumina.com/> and Pacific Biosciences (PacBio) <https://www.pacb.com/> platforms. It can either read reference genomes from FASTA files or simulate new ones. Genomic variants can be simulated using summary statistics, phylogenies, Variant Call Format (VCF) files, and coalescent simulations—the latter of which can include selection, recombination, and demographic fluctuations. 'jackalope' can simulate single, paired-end, or mate-pair Illumina reads, as well as PacBio reads. These simulations include sequencing errors, mapping qualities, multiplexing, and optical/polymerase chain reaction (PCR) duplicates. Simulating Illumina sequencing is based on ART by Huang et al. (2012) <doi:10.1093/bioinformatics/btr708>. PacBio sequencing simulation is based on SimLoRD by Stöcker et al. (2016) <doi:10.1093/bioinformatics/btw286>. All outputs can be written to standard file formats.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Depends: R (>= 2.10)
biocViews:
Imports: ape, R6, Rcpp (>= 0.12.11), RcppProgress (>= 0.1), zlibbioc
LinkingTo: Rcpp, RcppArmadillo, RcppProgress, Rhtslib, zlibbioc
SystemRequirements: C++11
RoxygenNote: 6.1.1
Suggests: coala, knitr, scrm, testthat, vcfR
VignetteBuilder: knitr
URL: https://github.com/lucasnell/jackalope
BugReports: https://github.com/lucasnell/jackalope/issues
NeedsCompilation: yes
Packaged: 2019-06-04 09:23:11 UTC; lucasnell
Author: Lucas A. Nell [cph, aut, cre] (<https://orcid.org/0000-0003-3209-0517>)
Maintainer: Lucas A. Nell <lucas@lucasnell.com>
Repository: CRAN
Date/Publication: 2019-06-04 14:50:04 UTC

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New package clrdag with initial version 0.6.0
Package: clrdag
Type: Package
Title: Constrained Likelihood Ratio Tests for a Directed Acyclic Graph
Version: 0.6.0
Date: 2019-05-23
Author: Chunlin Li, Xiaotong Shen, Wei Pan
Maintainer: Chunlin Li <li000007@umn.edu>
Depends: R (>= 3.5.0)
Imports: Rcpp (>= 1.0.1)
LinkingTo: Rcpp, RcppArmadillo
Description: Provides MLEdag() for constrained maximum likelihood estimation and likelihood ratio test of a large directed acyclic graph. The algorithms are described in the paper by Li, Shen, and Pan (2019) <doi:10.1080/01621459.2019.1623042>.
License: GPL (>= 2)
URL: https://github.com/chunlinli/clrdag
BugReports: https://github.com/chunlinli/clrdag/issues
NeedsCompilation: yes
Packaged: 2019-06-04 09:04:20 UTC; li000007
Repository: CRAN
Date/Publication: 2019-06-04 14:40:03 UTC

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New package QTOCen with initial version 0.1.1
Package: QTOCen
Type: Package
Title: Quantile-Optimal Treatment Regimes with Censored Data
Version: 0.1.1
Authors@R: c(person("Yu", "Zhou", , "zhou0269@umn.edu", role = c("cre", "aut")), person("Lan", "Wang", , "wangx346@umn.edu ", role = "ctb"))
Author: Yu Zhou [cre, aut], Lan Wang [ctb]
Maintainer: Yu Zhou <zhou0269@umn.edu>
Description: Provides methods for estimation of mean- and quantile-optimal treatment regimes from censored data. Specifically, we have developed distinct functions for three types of right censoring for static treatment using quantile criterion: (1) independent/random censoring, (2) treatment-dependent random censoring, and (3) covariates-dependent random censoring. It also includes a function to estimate quantile-optimal dynamic treatment regimes for independent censored data. Finally, this package also includes a simulation data generative model of a dynamic treatment experiment proposed in literature.
License: GPL (>= 2)
LazyData: TRUE
Imports: survival, rgenoud (>= 5.8), quantreg (>= 5.18), stats, grDevices, methods, Rdpack, MatrixModels
RdMacros: Rdpack
Depends: R (>= 3.3), utils
RoxygenNote: 6.1.1
Suggests: parallel, stringr, testthat, faraway, quantoptr (>= 0.1.3), survminer
NeedsCompilation: no
Encoding: UTF-8
Packaged: 2019-06-03 15:56:38 UTC; yuzhou
Repository: CRAN
Date/Publication: 2019-06-04 12:10:10 UTC

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New package purrrogress with initial version 0.1.0
Package: purrrogress
Title: Add Progress Bars to Mapping Functions
Version: 0.1.0
Authors@R: person(given = "Andrew", family = "Redd", role = c("aut", "cre"), email = "andrew.redd@hsc.utah.edu", comment = c(ORCID = "0000-0002-6149-2438"))
Description: Provides functions to easily add progress bars to apply calls.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: R6, assertthat, glue, hms, methods, pkgcond, purrr, testextra, utils, rlang
RoxygenNote: 6.1.1
Language: en-US
Suggests: covr, datasets, stringi, testthat, tibble
Enhances: dplyr
URL: https://github.com/halpo/purrrogress
BugReports: https://github.com/halpo/purrrogress/issues
NeedsCompilation: no
Packaged: 2019-06-03 19:29:25 UTC; u0092104
Author: Andrew Redd [aut, cre] (<https://orcid.org/0000-0002-6149-2438>)
Maintainer: Andrew Redd <andrew.redd@hsc.utah.edu>
Repository: CRAN
Date/Publication: 2019-06-04 12:30:03 UTC

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New package cluscov with initial version 1.1.0
Package: cluscov
Type: Package
Title: Clustered Covariate Regression
Version: 1.1.0
Date: 2019-05-31
Author: Emmanuel S Tsyawo [aut, cre], Abdul-Nasah Soale [aut]
Maintainer: Emmanuel S Tsyawo <estsyawo@temple.edu>
Description: Clustered covariate regression enables estimation and inference in both linear and non-linear models with linear predictor functions even when the design matrix is column rank deficient. Routines in this package implement algorithms in Soale and Tsyawo (2019) <doi:10.13140/RG.2.2.32355.81441>.
License: GPL-2
Encoding: UTF-8
LazyData: true
Imports: quantreg, MASS, stats, utils
RoxygenNote: 6.1.1
NeedsCompilation: yes
Packaged: 2019-06-03 19:16:51 UTC; Selorm
Repository: CRAN
Date/Publication: 2019-06-04 12:30:07 UTC

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New package ace2fastq with initial version 0.5.1
Package: ace2fastq
Type: Package
Title: ACE File to FASTQ Converter
Version: 0.5.1
Authors@R: person("Reinhard", "Simon", email = "rsimon64@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-4608-9077") )
Description: The ACE file format is currently used in genomics to store contigs from ABI sequencing machines. To the best of our knowledge, no R function is available to convert this format into the more popular fastq file format. The development was motivated in the context of the analysis of 16S metagenomic data by the need to convert the ACE files received from a sequencing service for further analysis.
Imports: stringr
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Suggests: testthat, knitr, rmarkdown, covr
VignetteBuilder: knitr
URL: https://github.com/c5sire/ace2fastq
BugReports: https://github.com/c5sire/ace2fastq/issues
NeedsCompilation: no
Packaged: 2019-06-03 15:51:10 UTC; Reinhard
Author: Reinhard Simon [aut, cre] (<https://orcid.org/0000-0002-4608-9077>)
Maintainer: Reinhard Simon <rsimon64@gmail.com>
Repository: CRAN
Date/Publication: 2019-06-04 12:10:06 UTC

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New package zen4R with initial version 0.1
Package: zen4R
Version: 0.1
Date: 2019-06-03
Title: Interface to 'Zenodo' REST API
Authors@R: c(person("Emmanuel", "Blondel", role = c("aut", "cre"), email = "emmanuel.blondel1@gmail.com", comment = c(ORCID = "0000-0002-5870-5762")))
Maintainer: Emmanuel Blondel <emmanuel.blondel1@gmail.com>
Depends: R (>= 3.3.0), methods
Imports: R6, httr, jsonlite
Suggests: testthat
Description: Provides an Interface to 'Zenodo' (<https://zenodo.org>) REST API, including management of depositions, attribution of DOIs by 'Zenodo' and upload of files.
License: MIT + file LICENSE
URL: https://github.com/eblondel/zen4R
BugReports: https://github.com/eblondel/zen4R/issues
LazyLoad: yes
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-06-03 13:10:31 UTC; manub
Author: Emmanuel Blondel [aut, cre] (<https://orcid.org/0000-0002-5870-5762>)
Repository: CRAN
Date/Publication: 2019-06-04 11:50:03 UTC

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New package sbscrapeR with initial version 1.0.0
Package: sbscrapeR
Title: Social Blade Scraper
Version: 1.0.0
Authors@R: person("Benjamin", "Smith", email = "benyamindsmith@gmail.com", role = c("aut", "cre"))
Description: A set of web-scraping functions for easily getting the monthly statistics of content producers on on-line platforms tracked by <https://socialblade.com>.
Depends: R (>= 3.5.0)
License: CC0
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Imports: rvest, xml2, lubridate, magrittr
NeedsCompilation: no
Packaged: 2019-05-31 22:19:41 UTC; elisheva
Author: Benjamin Smith [aut, cre]
Maintainer: Benjamin Smith <benyamindsmith@gmail.com>
Repository: CRAN
Date/Publication: 2019-06-04 11:30:02 UTC

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New package NeuralSens with initial version 0.0.2
Package: NeuralSens
Version: 0.0.2
Title: Sensitivity Analysis of Neural Networks
Date: 2019-05-11
Description: Analysis functions to quantify inputs importance in neural network models. Functions are available for calculating and plotting the inputs importance and obtaining the activation function of each neuron layer and its derivatives. The importance of a given input is defined as the distribution of the derivatives of the output with respect to that input in each training data point.
Author: José Portela González [aut], Jaime Pizarroso Gonzalo [ctb, cre]
Maintainer: Jaime Pizarroso Gonzalo <jpizarroso@alu.comillas.edu>
Imports: ggplot2, gridExtra, NeuralNetTools, reshape2, caret, fastDummies, stringr
Suggests: h2o, neural, RSNNS, nnet, neuralnet
RoxygenNote: 6.1.1
NeedsCompilation: no
URL: https://github.com/JaiPizGon/NeuralSens
BugReports: https://github.com/JaiPizGon/NeuralSens/issues
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Authors@R: c( person(given = "José", family = "Portela González", email = "Jose.Portela@iit.comillas.edu", role = "aut"), person(given = "Jaime", family = "Pizarroso Gonzalo", email = "jpizarroso@alu.comillas.edu", role = c("ctb", "cre")) )
Packaged: 2019-06-03 14:29:53 UTC; jaime
Repository: CRAN
Date/Publication: 2019-06-04 12:00:03 UTC

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New package manhplot with initial version 1.0
Package: manhplot
Type: Package
Title: The Manhattan++ Plot
Depends: R (>= 3.4.0)
Version: 1.0
Date: 2019-05-14
Author: Chris Grace <cgrace@well.ox.ac.uk>
Maintainer: Chris Grace <cgrace@well.ox.ac.uk>
Description: This plot integrates annotation into a manhattan plot. The plot is implemented as a heatmap, which is binned using -log10(p-value) and chromosome position. Annotation currently supported is minor allele frequency and gene function high impact variants.
License: GPL (>= 2)
RoxygenNote: 6.1.1
Imports: reshape2, ggplot2, ggrepel, gridExtra
Suggests: R.utils, testthat
URL: https://github.com/cgrace1978/manhplot/
BugReports: https://github.com/cgrace1978/manhplot/issues
NeedsCompilation: no
Packaged: 2019-06-03 10:11:42 UTC; cgrace
Repository: CRAN
Date/Publication: 2019-06-04 11:40:03 UTC

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New package iCARH with initial version 1.0.0
Package: iCARH
Version: 1.0.0
Date: 2019-05-21
Title: Integrative Conditional Autoregressive Horseshoe Model
Authors@R: c(person("Takoua", "Jendoubi", role = c("aut", "cre"), email = "t.jendoubi14@imperial.ac.uk"), person("Timothy M.D.", "Ebbels", role = c("aut"), email = "t.ebbels@imperial.ac.uk") )
Description: Implements the integrative conditional autoregressive horseshoe model discussed in Jendoubi, T., & Ebbels, T. (2018). "Integrative analysis of time course metabolic data and biomarker discovery". arXiv preprint <arXiv:1801.07767>. The model consists in three levels: Metabolic pathways level modeling interdependencies between variables via a conditional auto-regressive (CAR) component , integrative analysis level to identify potential associations between heterogeneous omic variables via a Horseshoe prior and experimental design level to capture experimental design conditions through a mixed-effects model. The package also provides functions to simulate data from the model, construct pathway matrices, post process and plot model parameters.
Depends: rstan, MASS, stats, ggplot2
Imports: RCurl, KEGGgraph, igraph, reshape2, mc2d, abind, Matrix
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
License: GPL (>= 3)
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-06-03 10:34:44 UTC; takoua
Author: Takoua Jendoubi [aut, cre], Timothy M.D. Ebbels [aut]
Maintainer: Takoua Jendoubi <t.jendoubi14@imperial.ac.uk>
Repository: CRAN
Date/Publication: 2019-06-04 11:50:07 UTC

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New package cascsim with initial version 0.3
Package: cascsim
Title: Casualty Actuarial Society Individual Claim Simulator
Version: 0.3
Authors@R: c( person("Robert", "Bear", email = "rbear@reserveprism.com", role = "aut"), person("Kailan", "Shang", email = "klshang81@gmail.com", role = c("aut","cre")), person("Hai", "You", email = "hyou@reserveprism.com", role = "aut"), person("Brian", "Fannin", email = "bfannin@casact.org", role = "ctb"))
Description: It is an open source insurance claim simulation engine sponsored by the Casualty Actuarial Society. It generates individual insurance claims including open claims, reopened claims, incurred but not reported claims and future claims. It also includes claim data fitting functions to help set simulation assumptions. It is useful for claim level reserving analysis. Parodi (2013) <https://www.actuaries.org.uk/documents/triangle-free-reserving-non-traditional-framework-estimating-reserves-and-reserve-uncertainty>.
Depends: R (>= 3.4.0)
Imports: parallel, R2HTML, fitdistrplus, moments, copula, scatterplot3d, methods
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-06-03 04:35:02 UTC; Kailan
Author: Robert Bear [aut], Kailan Shang [aut, cre], Hai You [aut], Brian Fannin [ctb]
Maintainer: Kailan Shang <klshang81@gmail.com>
Repository: CRAN
Date/Publication: 2019-06-04 11:40:06 UTC

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Mon, 03 Jun 2019

New package robcp with initial version 0.2.4
Package: robcp
Title: Robust Change-Point Tests
Version: 0.2.4
Authors@R: c(person("Sheila", "Goerz", email = "sheila.goerz@tu-dortmund.de", role = c("aut", "cre")), person("Alexander", "Duerre", email = "alexander.duerre@udo.edu", role = "ctb"))
Description: Provides robust methods to detect change-points in uni- or multivariate time series. They can cope with corrupted data and heavy tails. One can detect changes in location, scale and dependence structure of a possibly multivariate time series. Procedures are based on Huberized versions of CUSUM tests proposed in Duerre and Fried (2019) <arXiv:1905.06201>.
Depends: R (>= 3.3.1)
License: GPL-3
Encoding: UTF-8
LazyData: true
NeedsCompilation: yes
Packaged: 2019-06-03 18:02:21 UTC; Sheila
Author: Sheila Goerz [aut, cre], Alexander Duerre [ctb]
Maintainer: Sheila Goerz <sheila.goerz@tu-dortmund.de>
Repository: CRAN
Date/Publication: 2019-06-03 23:50:14 UTC

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New package PowerfulMaxEigenpair with initial version 0.1.0
Package: PowerfulMaxEigenpair
Type: Package
Title: Powerful Algorithm for Maximal Eigenpair
Version: 0.1.0
Date: 2019-06-03
Author: Yueshuang Li <liyueshuang@mail.bnu.edu.cn> and Xiaojun Mao <maoxj@fudan.edu.cn>
Maintainer: Xiaojun Mao <maoxj@fudan.edu.cn>
Description: An implementation for using powerful algorithm to compute the maximal eigenpair of Hermitizable tridiagonal matrices in R. It provides two algorithms to find the maximal and the next to maximal eigenpairs under the tridiagonal matrix. Besides, it also provides two auxiliary algorithms to generate tridiagonal matrix and solve the linear equation by Thomas algorithm. Several examples are included in the vignettes to illustrate the usage of the functions.
License: MIT + file LICENSE
URL: http://github.com/mxjki/PowerfulMaxEigenpair
BugReports: http://github.com/mxjki/PowerfulMaxEigenpair/issues
Depends: R (>= 3.6.0), stats
Encoding: UTF-8
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-06-03 13:59:54 UTC; xiaojunmao
Repository: CRAN
Date/Publication: 2019-06-03 17:20:03 UTC

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New package nlr with initial version 0.1-2
Package: nlr
Type: Package
Title: Nonlinear Regression Modelling using Robust Methods
Version: 0.1-2
Date: 2019-06-03
Author: Hossein Riazoshams
Maintainer: Hossein Riazoshams <riazihosein@gmail.com>
Description: Non-Linear Robust package is developed to handle the problem of outliers in nonlinear regression, using robust statistics. It covers classic methods in nonlinear regression as well. It has facilities to fit models in the case of auto correlated and heterogeneous variance cases, while it include tools to detecting outliers in nonlinear regression. (Riazoshams H, Midi H, and Ghilagaber G, (2018, ISBN:978-1-118-73806-1). Robust Nonlinear Regression, with Application using R, John Wiley and Sons.)
License: GPL-2
LazyData: yes
Imports: MASS,nlme, robcor, TSA,tseries,stats, GA, quantreg
Depends: R (>= 3.6.0), methods
URL: http://www.riazoshams.com/nlr/
NeedsCompilation: no
Packaged: 2019-06-03 16:02:21 UTC; HRIAZ
Repository: CRAN
Date/Publication: 2019-06-03 18:00:03 UTC

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New package multicross with initial version 1.0.0
Package: multicross
Type: Package
Title: A Graph-Based Test for Comparing Multivariate Distributions in the Multi Sample Framework
Version: 1.0.0
Author: Somabha Mukherjee <somabha@wharton.upenn.edu> Divyansh Agarwal <divyansh.agarwal@pennmedicine.upenn.edu> Bhaswar Bhattacharya <bhaswar@wharton.upenn.edu> Nancy R. Zhang <nzh@wharton.upenn.edu>
Maintainer: Divyansh Agarwal <divyansh.agarwal@pennmedicine.upenn.edu>
Description: We introduce a nonparametric, graphical test based on optimal matching for assessing whether multiple unknown multivariate probability distributions are equal. This method is consistent, and does not make any distributional assumptions on the data. Our procedure combines data that belong to different classes or groups to create a graph on the pooled data, and then utilizes the number of edges connecting data points from different classes to examine equality of distributions among the classes.
License: GPL-2
Encoding: UTF-8
LazyData: true
Imports: nbpMatching (>= 1.5.1), crossmatch (>= 1.3-1), MASS (>= 7.3-49), stats (>= 3.5.0),
Suggests: ape
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-06-01 11:46:59 UTC; divyanshagarwal
Repository: CRAN
Date/Publication: 2019-06-03 14:40:07 UTC

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New package json64 with initial version 0.1.3
Package: json64
Type: Package
Title: A 'Base64' Encode/Decode Package with Support for JSON Output/Input and UTF-8
Version: 0.1.3
Author: Mauricio Santelices
Maintainer: Mauricio Santelices <m.santelicesa@gmail.com>
Description: Encode/Decode 'base64', with support for JSON format, using two functions: j_encode() and j_decode(). 'Base64' is a group of similar binary-to-text encoding schemes that represent binary data in an ASCII string format by translating it into a radix-64 representation, used when there is a need to encode binary data that needs to be stored and transferred over media that are designed to deal with textual data, ensuring that the data will remain intact and without modification during transport. <https://developer.mozilla.org/en-US/docs/Web/API/WindowBase64/Base64_encoding_and_decoding> On the other side, JSON (JavaScript Object Notation) is a lightweight data-interchange format. Easy to read, write, parse and generate. It is based on a subset of the JavaScript Programming Language. JSON is a text format that is completely language independent but uses conventions that are familiar to programmers of the C-family of languages, including C, C++, C#, Java, JavaScript, Perl, Python, and many others. JSON structure is built around name:value pairs and ordered list of values. <https://www.json.org> The first function, j_encode(), let you transform a data.frame or list to a 'base64' encoded JSON (or JSON string). The j_decode() function takes a 'base64' string (could be an encoded JSON) and transform it to a data.frame (or list, depending of the JSON structure).
License: MIT + file LICENSE
Imports: jsonlite
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-06-01 16:36:04 UTC; Mauricio
Repository: CRAN
Date/Publication: 2019-06-03 14:20:03 UTC

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New package swissdd with initial version 1.0.0
Package: swissdd
Type: Package
Title: Get Swiss Federal and Cantonal Vote Results from Opendata.swiss
Imports: purrr, dplyr, tidyr, jsonlite, magrittr, tibble, curl
Version: 1.0.0
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.
URL: https://github.com/politanch/swissdd
BugReports: https://github.com/politanch/swissdd/issues
License: GPL-2
Encoding: UTF-8
Suggests: testthat
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-05-31 14:01:59 UTC; tlo1
Author: Thomas Lo Russo [cre, aut], Thomas Willi [aut]
Maintainer: Thomas Lo Russo <th.lorusso@gmail.com>
Repository: CRAN
Date/Publication: 2019-06-03 13:10:03 UTC

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New package pinochet with initial version 0.1.0
Package: pinochet
Type: Package
Title: Data About the Victims of the Pinochet Regime, 1973-1990
Version: 0.1.0
Authors@R: c( person(given = "Danilo", family = "Freire", email = "danilofreire@gmail.com", role = c("aut", "cre")), person(given = "Lucas", family = "Mingardi", email = "lucasmingardi@gmail.com", role = "aut"), person(given = "Robert", family = "McDonnell", email = "robertmylesmcdonnell@gmail.com", role = "aut") )
Description: Packages data about the victims of the Pinochet regime as compiled by the Chilean National Commission for Truth and Reconciliation Report (1991, ISBN:9780268016463).
License: MIT + file LICENSE
URL: http://github.com/danilofreire/pinochet
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1.9000
Depends: R (>= 3.5.0)
Suggests: devtools, kableExtra, knitr, lubridate, rmarkdown, rnaturalearthdata, sf, tidyverse, testthat
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-05-31 23:15:42 UTC; politicaltheory
Author: Danilo Freire [aut, cre], Lucas Mingardi [aut], Robert McDonnell [aut]
Maintainer: Danilo Freire <danilofreire@gmail.com>
Repository: CRAN
Date/Publication: 2019-06-03 13:50:03 UTC

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New package PakPMICS2018bh with initial version 0.1.0
Package: PakPMICS2018bh
Type: Package
Title: Multiple Indicator Cluster Survey (MICS) 2017-18 Birth History of Children Questionnaire Data for Punjab, Pakistan
Version: 0.1.0
Author: Muhammad Yaseen [aut, cre] , Muhammad Usman [ctb]
Maintainer: Muhammad Yaseen <myaseen208@gmail.com>
Description: Provides data set and function for exploration of Multiple Indicator Cluster Survey (MICS) 2017-18 Household questionnaire data for Punjab, Pakistan. The results of the present survey are critically important for the purposes of SDG monitoring, as the survey produces information on 32 global SDG indicators. The data was collected from 53,840 households selected at the second stage with systematic random sampling out of a sample of 2,692 clusters selected using Probability Proportional to size sampling. Six questionnaires were used in the survey: (1) a household questionnaire to collect basic demographic information on all de jure household members (usual residents), the household, and the dwelling; (2) a water quality testing questionnaire administered in three households in each cluster of the sample; (3) a questionnaire for individual women administered in each household to all women age 15-49 years; (4) a questionnaire for individual men administered in every second household to all men age 15-49 years; (5) an under-5 questionnaire, administered to mothers (or caretakers) of all children under 5 living in the household; and (6) a questionnaire for children age 5-17 years, administered to the mother (or caretaker) of one randomly selected child age 5-17 years living in the household (<http://www.mics.unicef.org/surveys>).
Depends: R (>= 3.5.0)
Imports: tibble
License: GPL-2
URL: https://github.com/myaseen208/PakPMICS2018bh, https://myaseen208.github.io/PakPMICS2018bh/
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Note: Department of Mathematics and Statistics, University of Agriculture Faisalabad, Faisalabad-Pakistan.
Suggests: testthat, R.rsp
VignetteBuilder: R.rsp
NeedsCompilation: no
Packaged: 2019-06-01 06:03:34 UTC; myaseen
Repository: CRAN
Date/Publication: 2019-06-03 14:00:03 UTC

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New package lmboot with initial version 0.0.1
Package: lmboot
Type: Package
Title: Bootstrap in Linear Models
Version: 0.0.1
Date: 2019-05-13
Authors@R: person("Megan", "Heyman", email="heyman@rose-hulman.edu", role=c("aut","cre"))
Description: Various efficient and robust bootstrap methods are implemented for linear models with least squares estimation. Functions within this package allow users to create bootstrap sampling distributions for model parameters, test hypotheses about parameters, and visualize the bootstrap sampling or null distributions. Methods implemented for linear models include the wild bootstrap by Wu (1986) <doi:10.1214/aos/1176350142>, the residual and paired bootstraps by Efron (1979, ISBN:978-1-4612-4380-9), the delete-1 jackknife by Quenouille (1956) <doi:10.2307/2332914>, and the Bayesian bootstrap by Rubin (1981) <doi:10.1214/aos/1176345338>.
Depends: R (>= 3.5.0)
Imports: evd (>= 2.3.0), stats (>= 3.6.0)
License: GPL-2
RoxygenNote: 6.1.1
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2019-05-31 16:54:35 UTC; heyman
Author: Megan Heyman [aut, cre]
Maintainer: Megan Heyman <heyman@rose-hulman.edu>
Repository: CRAN
Date/Publication: 2019-06-03 13:10:11 UTC

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New package gargle with initial version 0.1.3
Package: gargle
Title: Utilities for Working with Google APIs
Version: 0.1.3
Authors@R: c(person(given = "Jennifer", family = "Bryan", role = c("aut", "cre"), email = "jenny@rstudio.com", comment = c(ORCID = "0000-0002-6983-2759")), person(given = "Craig", family = "Citro", role = "aut", email = "craigcitro@google.com"), person(given = "Hadley", family = "Wickham", role = "aut", email = "hadley@rstudio.com", comment = c(ORCID = "0000-0003-4757-117X")), person(given = "Google Inc", role = "cph"), person(given = "RStudio", role = c("cph", "fnd")))
Description: Provides utilities for working with Google APIs <https://developers.google.com/apis-explorer>. This includes functions and classes for handling common credential types and for preparing, executing, and processing HTTP requests.
License: MIT + file LICENSE
URL: https://gargle.r-lib.org, https://github.com/r-lib/gargle
BugReports: https://github.com/r-lib/gargle/issues
Depends: R (>= 3.2)
Imports: fs (>= 1.3.1), glue (>= 1.3.0), httr (>= 1.4.0), jsonlite, rlang, stats, withr
Suggests: covr, knitr, rmarkdown, sodium, testthat
VignetteBuilder: knitr
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-05-27 16:19:50 UTC; jenny
Author: Jennifer Bryan [aut, cre] (<https://orcid.org/0000-0002-6983-2759>), Craig Citro [aut], Hadley Wickham [aut] (<https://orcid.org/0000-0003-4757-117X>), Google Inc [cph], RStudio [cph, fnd]
Maintainer: Jennifer Bryan <jenny@rstudio.com>
Repository: CRAN
Date/Publication: 2019-06-03 13:10:16 UTC

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New package volesti with initial version 1.0.2
Package: volesti
Type: Package
License: LGPL-3
Title: Volume Approximation and Sampling of Convex Polytopes
Author: Vissarion Fisikopoulos <vissarion.fisikopoulos@gmail.com> [aut, cph, cre], Apostolos Chalkis <tolis.chal@gmail.com> [cph, aut], contributors in file inst/AUTHORS
Copyright: file inst/COPYRIGHTS
Description: Provides an R interface for 'volesti' C++ package. 'volesti' computes estimations of volume of polytopes given by a set of points or linear inequalities or Minkowski sum of segments (zonotopes). There are two algorithms for volume estimation (I.Z. Emiris and V. Fisikopoulos (2014) <arXiv:1312.2873> and B. Cousins, S. Vempala (2016) <arXiv:1409.6011>) as well as algorithms for sampling, rounding and rotating polytopes. Moreover, 'volesti' provides algorithms for estimating copulas (L. Cales, A. Chalkis, I.Z. Emiris, V. Fisikopoulos (2018) <arXiv:1803.05861>).
Version: 1.0.2
Date: 2019-05-10
Maintainer: Vissarion Fisikopoulos <vissarion.fisikopoulos@gmail.com>
Depends: Rcpp (>= 0.12.17)
Imports: methods
LinkingTo: Rcpp, RcppEigen, BH
Suggests: testthat
Encoding: UTF-8
RoxygenNote: 6.1.1
BugReports: https://github.com/GeomScale/volume_approximation/issues
NeedsCompilation: yes
Packaged: 2019-06-03 11:34:53 UTC; vissarion
Repository: CRAN
Date/Publication: 2019-06-03 12:50:03 UTC

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New package LeMaRns with initial version 0.1.0
Package: LeMaRns
Title: Length-Based Multispecies Analysis by Numerical Simulation
Version: 0.1.0
Date: 2019-06-01
Authors@R: c(person("Michael A.", "Spence", email = "michael.spence@cefas.co.uk", role = c("aut", "cre"),comment = c(ORCID = "0000-0002-3445-7979")), person("Hayley J.", "Bannister", email = "hayley.bannister@cefas.co.uk", role = c("aut"),comment = c(ORCID = "0000-0002-2546-5168")), person("Johnathan E.", "Ball", email = "johnathan.ball@cefas.co.uk", role = c("aut")), person("Paul J.", "Dolder", email = "paul.dolder@cefas.co.uk", role = c("aut"),comment = c(ORCID = "0000-0002-4179-712X")), person("Robert B.", "Thorpe", email = "robert.thorpe@cefas.co.uk", role = c("aut"),comment = c(ORCID = "0000-0001-8193-6932")),person("Christopher A.", "Griffiths", email = "chris.griffiths@cefas.co.uk", role = c("ctb")))
Description: Set up, run and explore the outputs of the Length-based Multispecies model (LeMans; Hall et al. 2006 <doi:10.1139/f06-039>), focused on the marine environment.
Depends: R (>= 3.5.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
LinkingTo: Rcpp, RcppArmadillo
Imports: Rcpp, abind, methods
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
Collate: 'NS_par.R' 'RcppExports.R' 'calc_M1.R' 'calc_Q.R' 'calc_growth.R' 'calc_indicators.R' 'calc_mature.R' 'param_setup.R' 'run_LeMans.R' 'calc_output.R' 'calc_phi.R' 'calc_prefs.R' 'calc_ration_growthfac.R' 'calc_recruits.R' 'calc_suit_vect.R' 'get_Catch.R' 'get_SSB.R' 'get_indicators.R' 'other.R' 'plot_SSB.R' 'plot_indicators.R'
NeedsCompilation: yes
Packaged: 2019-05-31 13:11:50 UTC; HB04
Author: Michael A. Spence [aut, cre] (<https://orcid.org/0000-0002-3445-7979>), Hayley J. Bannister [aut] (<https://orcid.org/0000-0002-2546-5168>), Johnathan E. Ball [aut], Paul J. Dolder [aut] (<https://orcid.org/0000-0002-4179-712X>), Robert B. Thorpe [aut] (<https://orcid.org/0000-0001-8193-6932>), Christopher A. Griffiths [ctb]
Maintainer: Michael A. Spence <michael.spence@cefas.co.uk>
Repository: CRAN
Date/Publication: 2019-06-03 12:40:09 UTC

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New package justifier with initial version 0.1.0
Package: justifier
Title: Human and Machine-Readable Justifications and Justified Decisions Based on 'YAML'
Version: 0.1.0
Authors@R: person(given = "Gjalt-Jorn Ygram", family = "Peters", role = c("aut", "cre"), email = "gjalt-jorn@behaviorchange.eu")
Maintainer: Gjalt-Jorn Ygram Peters <gjalt-jorn@behaviorchange.eu>
Description: Leverages the 'yum' package to implement a 'YAML' ('YAML Ain't Markup Language', a human friendly standard for data serialization; see <https:yaml.org>) standard for documenting justifications, such as for decisions taken during the planning, execution and analysis of a study or during the development of a behavior change intervention as illustrated by Marques & Peters (2019) <doi:10.17605/osf.io/ndxha>. These justifications are both human- and machine-readable, facilitating efficient extraction and organisation.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
URL: https://r-packages.gitlab.io/justifier
BugReports: https://gitlab.com/r-packages/justifier/issues
Suggests: covr, knitr, rmarkdown, testthat
Imports: data.tree (>= 0.7.8), DiagrammeR (>= 1.0.0), purrr (>= 0.3.0), ufs (>= 0.2.0), yum (>= 0.0.1)
VignetteBuilder: knitr
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-05-31 10:52:20 UTC; gjalt
Author: Gjalt-Jorn Ygram Peters [aut, cre]
Repository: CRAN
Date/Publication: 2019-06-03 12:30:18 UTC

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New package GuessCompx with initial version 1.0.3
Package: GuessCompx
Type: Package
Title: Empirically Estimates Algorithm Complexity
Version: 1.0.3
Author: Marc Agenis <marc.agenis@gmail.com> and Neeraj Bokde <neerajdhanraj@gmail.com>
Maintainer: Marc Agenis <marc.agenis@gmail.com>
Description: Make an empirical guess on the time and memory complexities of an algorithm or a function. Tests multiple, increasing size random samples of your data and tries to fit various complexity functions o(n), o(n2), o(log(n)), etc. Based on best fit, it predicts the full computation time on your whole dataset. Results are plotted with 'ggplot2'.
BugReports: https://github.com/agenis/GuessCompx/issues
URL: https://github.com/agenis/GuessCompx
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Imports: dplyr, reshape2, ggplot2, lubridate, boot
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-05-31 12:02:07 UTC; Neeraj
Repository: CRAN
Date/Publication: 2019-06-03 12:50:34 UTC

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New package grangers with initial version 0.1.0
Package: grangers
Title: Inference on Granger-Causality in the Frequency Domain
Version: 0.1.0
Author: Matteo Farne' <matteo.farne2@unibo.it>, Angela Montanari <angela.montanari@unibo.it>
Maintainer: Matteo Farne' <matteo.farne2@unibo.it>
Description: Contains five functions performing the calculation of unconditional and conditional Granger-causality spectra, bootstrap inference on both, and inference on the difference between them via the bootstrap approach of Farne' and Montanari, 2018 <arXiv:1803.00374>.
Depends: R (>= 3.5)
License: GPL (>= 2)
URL: https://github.com/MatFar88/grangers
Imports: vars, tseries
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-05-30 23:14:59 UTC; Calif
Repository: CRAN
Date/Publication: 2019-06-03 12:50:13 UTC

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New package gen2stage with initial version 1.0
Package: gen2stage
Type: Package
Title: Generalized Two-Stage Designs for Phase II Single-Arm Studies
Version: 1.0
Depends: R (>= 2.0.0), graphics, stats, clinfun
Author: Seongho Kim
Maintainer: Seongho Kim <biostatistician.kim@gmail.com>
Description: One can find single-stage and two-stage designs for a phase II single-arm study with either efficacy or safety/toxicity endpoints as described in Kim and Wong (2019) <doi:10.29220/CSAM.2019.26.2.163>.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2019-05-31 14:38:22 UTC; kimse
Repository: CRAN
Date/Publication: 2019-06-03 12:50:22 UTC

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New package cpsurvsim with initial version 1.1.0
Package: cpsurvsim
Type: Package
Title: Simulating Survival Data from Change-Point Hazard Distributions
Version: 1.1.0
Date: 2019-05-07
Author: Camille Hochheimer [aut, cre]
Authors@R: person("Camille", "Hochheimer", email = "hochheimercj@vcu.edu", role = c("aut", "cre"))
Maintainer: Camille Hochheimer <hochheimercj@vcu.edu>
Description: Simulates time-to-event data with type I right censoring using two methods: the inverse CDF method and our proposed memoryless method. The latter method takes advantage of the memoryless property of survival and simulates a separate distribution between change-points. We include two parametric distributions: exponential and Weibull. Inverse CDF method draws on the work of Rainer Walke (2010), <https://www.demogr.mpg.de/papers/technicalreports/tr-2010-003.pdf>.
Depends: R (>= 3.5.0)
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
Imports: plyr (>= 1.8.0), stats, Hmisc, knitr (>= 1.21)
Suggests: rmarkdown
RoxygenNote: 6.1.1
VignetteBuilder: knitr
URL: http://github.com/camillejo/cpsurvsim
BugReports: http://github.com/camillejo/cpsurvsim/issues
NeedsCompilation: no
Packaged: 2019-05-31 15:46:32 UTC; Camille
Repository: CRAN
Date/Publication: 2019-06-03 13:00:07 UTC

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New package utile.tools with initial version 0.1.2
Package: utile.tools
Version: 0.1.2
Date: 2019-05-29
Title: Tools for Summarizing Data for Publication
Description: A variety of tools for preparing and summarizing data for publication purposes. Function verbs include "tabulate" for creating usable tabulated data from models, "paste" for generating human-readable statistics from a variety of summarizable data types, "calc" for reliably calculating differences between data points, and "test" for conducting simple statistical tests which return human-readable results.
Authors@R: c(person('Eric', 'Finnesgard', email = 'finnesgard.eric@mayo.edu', role = c('aut', 'cre')))
License: LGPL (>= 2)
Encoding: UTF-8
LazyData: TRUE
Depends: R (>= 3.4.0)
Imports: tibble, dplyr, lubridate, rlang, glue, purrr, stringr, survival
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-05-30 11:46:10 UTC; m130239
Author: Eric Finnesgard [aut, cre]
Maintainer: Eric Finnesgard <finnesgard.eric@mayo.edu>
Repository: CRAN
Date/Publication: 2019-06-03 11:50:03 UTC

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New package mSimCC with initial version 0.0.1
Package: mSimCC
Type: Package
Title: Micro Simulation Model for Cervical Cancer Prevention
Version: 0.0.1
Date: 2019-05-23
Author: David Moriña, Pedro Puig and Mireia Diaz
Maintainer: David Moriña Soler <david.morina@uab.cat>
Description: Micro simulation model to reproduce natural history of cervical cancer and cost-effectiveness evaluation of prevention strategies. See Georgalis L, de Sanjose S, Esnaola M, Bosch F X, Diaz M (2016) <doi:10.1097/CEJ.0000000000000202> for more details.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.1.1), parallel, doParallel, foreach
NeedsCompilation: yes
Packaged: 2019-06-03 05:29:47 UTC; dmorinya
Repository: CRAN
Date/Publication: 2019-06-03 11:20:03 UTC

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New package bayesreg with initial version 1.1
Package: bayesreg
Type: Package
Title: Bayesian Regression Models with Global-Local Shrinkage Priors
Version: 1.1
Date: 2019-06-03
Author: Daniel F. Schmidt [aut, cph, cre], Enes Makalic [aut, cph]
Maintainer: Daniel F. Schmidt <daniel.schmidt@monash.edu>
Description: Fits linear or logistic regression model using Bayesian global-local shrinkage prior hierarchies as described in Polson and Scott (2010) <doi:10.1093/acprof:oso/9780199694587.003.0017>. Handles ridge, lasso, horseshoe and horseshoe+ regression with logistic, Gaussian, Laplace or Student-t distributed targets using the algorithms summarized in Makalic and Schmidt (2016) <arXiv:1611.06649>.
License: GPL (>= 3)
Imports: stats (>= 3.0), pgdraw (>= 1.0)
Authors@R: c( person("Daniel F. Schmidt", email="daniel.schmidt@monash.edu", role = c("aut","cph","cre")), person("Enes Makalic", email="emakalic@unimelb.edu.au", role=c("aut","cph")) )
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-06-03 06:32:33 UTC; Daniel
Repository: CRAN
Date/Publication: 2019-06-03 11:30:19 UTC

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Sun, 02 Jun 2019

New package climwin with initial version 1.2.1
Package: climwin
Type: Package
Title: Climate Window Analysis
Version: 1.2.1
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, plyr, numDeriv, RcppRoll, nlme
Suggests: testthat, knitr, rmarkdown
License: GPL-2
Repository: CRAN
LazyData: True
VignetteBuilder: knitr
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-05-31 20:34:54 UTC; Liam
Date/Publication: 2019-06-02 16:00:06 UTC

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Fri, 31 May 2019

New package ggResidpanel with initial version 0.3.0
Package: ggResidpanel
Type: Package
Title: Panels and Interactive Versions of Diagnostic Plots using 'ggplot2'
Version: 0.3.0
Authors@R: c(person("Katherine", "Goode", email = "kgoode@iastate.edu", role = c("aut", "cre")), person("Kathleen", "Rey", email = "kprey@iastate.edu", role = c("aut")))
Description: An R package for creating panels of diagnostic plots for residuals from a model using ggplot2 and plotly to analyze residuals and model assumptions from a variety of viewpoints. It also allows for the creation of interactive diagnostic plots.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
URL: https://goodekat.github.io/ggResidpanel/
Imports: cowplot, ggplot2, grDevices, grid, MASS, plotly, qqplotr, stats, stringr
RoxygenNote: 6.1.1
Suggests: dplyr, forcats, knitr, lme4, lmerTest, nlme, randomForest, rmarkdown, rpart, testthat, vdiffr, wesanderson
VignetteBuilder: knitr
Depends: R (>= 3.0.0)
NeedsCompilation: no
Packaged: 2019-05-31 22:03:46 UTC; kgoode
Author: Katherine Goode [aut, cre], Kathleen Rey [aut]
Maintainer: Katherine Goode <kgoode@iastate.edu>
Repository: CRAN
Date/Publication: 2019-05-31 23:20:04 UTC

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New package table.express with initial version 0.1.0
Package: table.express
Type: Package
Title: Building 'data.table' Expressions with Data Manipulation Verbs
Description: A specialization of 'dplyr' data manipulation verbs that parse and build expressions which are ultimately evaluated by 'data.table', letting it handle all optimizations. A set of additional verbs are also provided to facilitate some common operations on a subset of the data.
Version: 0.1.0
Depends: R (>= 3.1.0)
Imports: utils, data.table (>= 1.9.8), dplyr, magrittr, R6, rlang (>= 0.3.0), tidyselect
Suggests: knitr, rex, rmarkdown, testthat
Date: 2019-05-29
Authors@R: c( person("Alexis", "Sarda-Espinosa", role=c("cre", "aut"), email="alexis.sarda@gmail.com") )
BugReports: https://github.com/asardaes/table.express/issues
License: MPL-2.0
URL: https://asardaes.github.io/table.express, https://github.com/asardaes/table.express
Language: en-US
Encoding: UTF-8
LazyData: TRUE
RoxygenNote: 6.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-05-29 16:43:49 UTC; oso_a
Author: Alexis Sarda-Espinosa [cre, aut]
Maintainer: Alexis Sarda-Espinosa <alexis.sarda@gmail.com>
Repository: CRAN
Date/Publication: 2019-05-31 16:20:03 UTC

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New package studentlife with initial version 1.0.0
URL: https://github.com/Frycast/studentlife
BugReports: https://github.com/Frycast/studentlife/issues
Package: studentlife
Type: Package
Title: Tidy Handling and Navigation of the Student-Life Dataset
Version: 1.0.0
Authors@R: c(person("Daniel", "Fryer", role = c("aut", "cre"), email = "d.fryer@latrobe.edu.au", comment = c(ORCID = "0000-0001-6032-0522")))
Description: Download, navigate and analyse the Student-Life dataset. The Student-Life dataset contains passive and automatic sensing data from the phones of a class of 48 Dartmouth college students. It was collected over a 10 week term. Additionally, the dataset contains ecological momentary assessment results along with pre-study and post-study mental health surveys. The intended use is to assess mental health, academic performance and behavioral trends. The raw dataset and additional information is available at <https://studentlife.cs.dartmouth.edu/>.
Depends: R (>= 3.4.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: purrr (>= 0.3.2), readr (>= 1.3.1), tidyr (>= 0.8.3), dplyr (>= 0.8.0.1), jsonlite (>= 1.6), tibble (>= 2.0.1), R.utils (>= 2.8.0), skimr (>= 1.0.5), visdat (>= 0.5.3), ggplot2 (>= 3.1.1), crayon (>= 1.3.4)
RoxygenNote: 6.1.1
Suggests: testthat
NeedsCompilation: no
Packaged: 2019-05-29 05:51:22 UTC; Doony
Author: Daniel Fryer [aut, cre] (<https://orcid.org/0000-0001-6032-0522>)
Maintainer: Daniel Fryer <d.fryer@latrobe.edu.au>
Repository: CRAN
Date/Publication: 2019-05-31 16:20:10 UTC

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New package MultiwayRegression with initial version 1.2
Package: MultiwayRegression
Type: Package
Title: Perform Tensor-on-Tensor Regression
Version: 1.2
Date: 2019-05-28
Author: Eric F. Lock
Maintainer: Eric F. Lock <elock@umn.edu>
Description: Functions to predict one multi-way array (i.e., a tensor) from another multi-way array, using a low-rank CANDECOMP/PARAFAC (CP) factorization and a ridge (L_2) penalty [Lock, EF (2018) <doi:10.1080/10618600.2017.1401544>]. Also includes functions to sample from the Bayesian posterior of a tensor-on-tensor model.
License: GPL-3
Imports: MASS
Depends: R(>= 2.10.0)
NeedsCompilation: no
Packaged: 2019-05-29 01:42:10 UTC; bowenli
Repository: CRAN
Date/Publication: 2019-05-31 16:10:03 UTC

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New package eoffice with initial version 0.1.5
Package: eoffice
Type: Package
Title: Export or Import Graph and Tables to 'Microsoft' Office
Version: 0.1.5
Author: Kai Guo
Maintainer: Kai Guo <guokai8@gmail.com>
Description: Provides wrap functions to export and import graphics and data frames in R to 'microsoft' office. And This package also provide write out figures with lots of different formats. Since people may work on the platform without GUI support, the package also provide function to easily write out figures to lots of different type of formats.
License: GPL-2
Imports: officer, rvg, flextable, broom, dplyr, magrittr, htmlwidgets, plotly, ggplotify, R.devices, devEMF
Depends:
Encoding: UTF-8
LazyData: true
Suggests: knitr, rmarkdown, ggplot2
VignetteBuilder: knitr
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-05-29 18:33:25 UTC; bioguo
Repository: CRAN
Date/Publication: 2019-05-31 16:30:03 UTC

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New package datos with initial version 0.1.0
Package: datos
Title: Traduce al Español Varios Conjuntos de Datos de Práctica
Version: 0.1.0
Authors@R: c(person(given = "Edgar", family = "Ruiz", role = c("aut", "cre"), email = "edgararuiz@gmail.com"), person(given = "Riva", family = "Quiroga", role = "aut", email = "riva.quiroga@uc.cl"), person(given = "Mauricio", family = "Vargas", role = "aut", email = "mvargas@dcc.uchile.cl"), person(given = "Mauro", family = "Lepore", role = "aut", email = "maurolepore@gmail.com"), person(given = "Rayna", family = "Harris", role = "ctb", email = "rayna.harris@gmail.com"), person(given = "Daniela", family = "Vasquez", role = "ctb", email = "daniela.vazquez@gmail.com") )
Description: Provee una versión traducida de los siguientes conjuntos de datos: 'airlines', 'airports', 'babynames', 'Batting', 'diamonds', 'faithful', 'flights', 'gapminder', 'gss_cat', 'iris', 'mpg', 'mtcars', 'atmos', 'planes', 'presidential', 'table1', 'table2', 'table3', 'table4a', 'table4b', 'table5', 'vehicles','weather', 'who'. English: It provides a Spanish translated version of the datasets listed above.
License: CC0
Depends: R (>= 3.5.0)
Imports: yaml, tibble
Suggests: babynames, fueleconomy, nycflights13, nasaweather, Lahman, ggplot2, gapminder, forcats, tidyr, testthat (>= 2.1.0), covr
ByteCompile: true
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
URL: https://github.com/cienciadedatos/datos
BugReports: https://github.com/cienciadedatos/datos/issues
Language: es
NeedsCompilation: no
Packaged: 2019-05-29 19:16:00 UTC; edgar
Author: Edgar Ruiz [aut, cre], Riva Quiroga [aut], Mauricio Vargas [aut], Mauro Lepore [aut], Rayna Harris [ctb], Daniela Vasquez [ctb]
Maintainer: Edgar Ruiz <edgararuiz@gmail.com>
Repository: CRAN
Date/Publication: 2019-05-31 16:40:04 UTC

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New package rstanemax with initial version 0.1.0
Package: rstanemax
Version: 0.1.0
Title: Emax Model Analysis with 'Stan'
Description: Perform sigmoidal Emax model fit using 'Stan' in a formula notation, without writing 'Stan' model code.
Authors@R: c( person("Kenta", "Yoshida", , "6.kurabupasu@gmail.com", c("aut", "cre"), comment = c(ORCID = "0000-0003-4967-3831")), person("Trustees of Columbia University", role = "cph", comment="src/init.cpp, tools/make_cc.R, R/stanmodels.R"))
Encoding: UTF-8
License: GPL-3 | file LICENSE
LazyData: true
ByteCompile: true
Depends: R (>= 3.4.0), methods,Rcpp (>= 1.0.0)
Imports: rstan (>= 2.18.2), rstantools (>= 1.5.1), magrittr (>= 1.5), dplyr (>= 0.8.0), tidyr (>= 0.8.0), ggplot2 (>= 2.2.1)
LinkingTo: StanHeaders (>= 2.18.1), rstan (>= 2.18.2), BH (>= 1.69.0-1), Rcpp (>= 1.0.0), RcppEigen (>= 0.3.3.5.0)
SystemRequirements: GNU make
NeedsCompilation: yes
RoxygenNote: 6.1.1
Suggests: testthat, knitr, rmarkdown, spelling
VignetteBuilder: knitr
Language: en-US
URL: https://github.com/yoshidk6/rstanemax
BugReports: https://github.com/yoshidk6/rstanemax/issues
Packaged: 2019-05-29 06:30:42 UTC; yoshidk6
Author: Kenta Yoshida [aut, cre] (<https://orcid.org/0000-0003-4967-3831>), Trustees of Columbia University [cph] (src/init.cpp, tools/make_cc.R, R/stanmodels.R)
Maintainer: Kenta Yoshida <6.kurabupasu@gmail.com>
Repository: CRAN
Date/Publication: 2019-05-31 15:50:03 UTC

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New package qMRI with initial version 1.0
Package: qMRI
Type: Package
Title: Methods for Quantitative Magnetic Resonance Imaging (qMRI)
Version: 1.0
Date: 2019-05-08
Authors@R: c(person("Joerg", "Polzehl", role = c("aut"), email = "joerg.polzehl@wias-berlin.de"), person("Karsten", "Tabelow", role = c("aut", "cre"), email = "karsten.tabelow@wias-berlin.de"), person("WIAS Berlin", role = c("cph", "fnd")))
Maintainer: Karsten Tabelow <karsten.tabelow@wias-berlin.de>
Depends: R (>= 3.5), awsMethods (>= 1.0)
Imports: oro.nifti (>= 0.9), stringr, dti (>= 1.4), aws (>= 2.2), adimpro (>= 0.9)
LazyData: TRUE
Description: Implementation of methods for estimation of quantitative maps from Multi-Parameter Mapping (MPM) acquisitions (Weiskopf et al. (2013) <doi:10.3389/fnins.2013.00095>) including adaptive smoothing methods in the framework of the ESTATICS model (Estimating the apparent transverse relaxation time (R2*) from images with different contrasts, Weiskopf et al. (2014) <doi:10.3389/fnins.2014.00278>). The smoothing method is described in Mohammadi et al. (2017). <doi:10.20347/WIAS.PREPRINT.2432>.
License: GPL (>= 2)
Copyright: This package is Copyright (C) 2015-2019 Weierstrass Institute for Applied Analysis and Stochastics.
URL: http://www.wias-berlin.de/research/ats/imaging/
NeedsCompilation: yes
Packaged: 2019-05-31 13:29:17 UTC; polzehl
Author: Joerg Polzehl [aut], Karsten Tabelow [aut, cre], WIAS Berlin [cph, fnd]
Repository: CRAN
Date/Publication: 2019-05-31 15:50:09 UTC

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New package EIX with initial version 1.0
Package: EIX
Title: Explain Interactions in 'XGBoost'
Version: 1.0
Authors@R: c( person("Ewelina", "Karbowiak", email = "ewelina.karbowiak12@gmail.com", role = c("aut", "cre")), person("Przemyslaw", "Biecek", email = "przemyslaw.biecek@gmail.com", role = c("aut","ths")) )
Description: Structure mining from 'XGBoost' and 'LightGBM' models. Key functionalities of this package cover: visualisation of tree-based ensembles models, identification of interactions, measuring of variable importance, measuring of interaction importance, explanation of single prediction with break down plots (based on 'xgboostExplainer' and 'breakDown' packages). To download the 'LightGBM' use the following link: <https://github.com/Microsoft/LightGBM>. 'EIX' is a part of the 'DrWhy.AI' universe.
Depends: R (>= 3.4.0)
License: GPL-2
Encoding: UTF-8
LazyData: true
Imports: MASS, ggplot2, data.table, purrr, xgboost, DALEX, ggrepel, ggiraphExtra, iBreakDown, Matrix, tidyr, scales
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown, lightgbm,
VignetteBuilder: knitr
URL: https://github.com/ModelOriented/EIX
BugReports: https://github.com/ModelOriented/EIX/issues
NeedsCompilation: no
Packaged: 2019-05-28 13:29:00 UTC; hp
Author: Ewelina Karbowiak [aut, cre], Przemyslaw Biecek [aut, ths]
Maintainer: Ewelina Karbowiak <ewelina.karbowiak12@gmail.com>
Repository: CRAN
Date/Publication: 2019-05-31 15:40:10 UTC

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New package drifter with initial version 0.2.1
Package: drifter
Title: Concept Drift and Concept Shift Detection for Predictive Models
Version: 0.2.1
Authors@R: person("Przemyslaw", "Biecek", email = "przemyslaw.biecek@gmail.com", role = c("aut", "cre"))
Description: Concept drift refers to the change in the data distribution or in the relationships between variables over time. 'drifter' calculates distances between variable distributions or variable relations and identifies both types of drift. Key functions are: calculate_covariate_drift() checks distance between corresponding variables in two datasets, calculate_residuals_drift() checks distance between residual distributions for two models, calculate_model_drift() checks distance between partial dependency profiles for two models, check_drift() executes all checks against drift. 'drifter' is a part of the 'DrWhy.AI' universe (Biecek 2018) <arXiv:1806.08915>.
Depends: R (>= 3.1)
License: GPL
Encoding: UTF-8
LazyData: true
Imports: DALEX, dplyr, tidyr, ingredients
Suggests: testthat, ranger
RoxygenNote: 6.1.1
URL: https://ModelOriented.github.io/drifter/
BugReports: https://github.com/ModelOriented/drifter/issues
NeedsCompilation: no
Packaged: 2019-05-27 19:38:51 UTC; pbiecek
Author: Przemyslaw Biecek [aut, cre]
Maintainer: Przemyslaw Biecek <przemyslaw.biecek@gmail.com>
Repository: CRAN
Date/Publication: 2019-05-31 09:30:03 UTC

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New package colocr with initial version 0.1.0
Package: colocr
Type: Package
Title: Conduct Co-Localization Analysis of Fluorescence Microscopy Images
Version: 0.1.0
License: GPL-3
Authors@R: person("Mahmoud", "Ahmed", email = "mahmoud.s.fahmy@students.kasralainy.edu.eg", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-4377-6541"))
URL: https://github.com/ropensci/colocr
BugReports: https://github.com/ropensci/colocr/issues
Description: Automate the co-localization analysis of fluorescence microscopy images. Selecting regions of interest, extract pixel intensities from the image channels and calculate different co-localization statistics. The methods implemented in this package are based on Dunn et al. (2011) <doi:10.1152/ajpcell.00462.2010>.
Encoding: UTF-8
LazyData: true
Suggests: testthat, shinytest, covr, knitr, rmarkdown, devtools, purrr, shinyBS
RoxygenNote: 6.1.1
Imports: imager, magick, shiny, scales, magrittr
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-05-28 01:18:54 UTC; rstudio
Author: Mahmoud Ahmed [aut, cre] (<https://orcid.org/0000-0002-4377-6541>)
Maintainer: Mahmoud Ahmed <mahmoud.s.fahmy@students.kasralainy.edu.eg>
Repository: CRAN
Date/Publication: 2019-05-31 09:40:03 UTC

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New package beastier with initial version 2.0.14
Package: beastier
Type: Package
Title: Call 'BEAST2'
Version: 2.0.14
Authors@R: c( person("Richèl J.C.", "Bilderbeek", email = "richel@richelbilderbeek.nl", role = c("aut", "cre"), comment = c(ORCID = "0000-0003-1107-7049")), person("Joëlle", "Barido-Sottani", role = "rev", comment = "Joëlle reviewed the package for rOpenSci, see https://github.com/ropensci/onboarding/issues/209"), person("David", "Winter", role = "rev", comment = "David reviewed the package for rOpenSci, see https://github.com/ropensci/onboarding/issues/209"))
Maintainer: Richèl J.C. Bilderbeek <richel@richelbilderbeek.nl>
Description: 'BEAST2' (<http://www.beast2.org>) is a widely used Bayesian phylogenetic tool, that uses DNA/RNA/protein data and many model priors to create a posterior of jointly estimated phylogenies and parameters. 'BEAST2' is a command-line tool. This package provides a way to call 'BEAST2' from an 'R' function call.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Imports: ape, phangorn, rappdirs, rJava, stringr, xml2
Suggests: beautier, hunspell, knitr, rmarkdown, spelling, testit, testthat, tracerer
URL: https://github.com/ropensci/beastier
BugReports: https://github.com/ropensci/beastier
Language: en-US
VignetteBuilder: knitr
SystemRequirements: BEAST2 (http://www.beast2.org/)
NeedsCompilation: no
Packaged: 2019-05-28 06:23:48 UTC; richel
Author: Richèl J.C. Bilderbeek [aut, cre] (<https://orcid.org/0000-0003-1107-7049>), Joëlle Barido-Sottani [rev] (Joëlle reviewed the package for rOpenSci, see https://github.com/ropensci/onboarding/issues/209), David Winter [rev] (David reviewed the package for rOpenSci, see https://github.com/ropensci/onboarding/issues/209)
Repository: CRAN
Date/Publication: 2019-05-31 10:00:03 UTC

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New package NPMLENCC with initial version 1.0
Package: NPMLENCC
Title: Non-Parametric Maximum Likelihood Estimate for Cohort Samplings
Version: 1.0
Description: To compute the non-parametric maximum likelihood estimates (NPMLEs) and penalized NPMLEs with SCAD, HARD and LASSO penalties for nested case-control or case-cohort sampling design with time matching under Cox's regression model. It also proposes the standard error formula for estimator using observed profile likelihood. For details about (penalized) NPNLEs see the original paper "Penalized Full Likelihood Approach to Variable Selection for Cox's Regression Model under Nested Case-Control Sampling" by Wang et al. (2019) <doi:10.1007/s10985-019-09475-z>.
Author: Jie-Huei Wang, Chun-Hao Pan, I-Shou Chang, and Chao A. Hsiung
Maintainer: Jie-Huei Wang <jhwang@stat.sinica.edu.tw>
Date: 2019-05-27
Depends: R (>= 3.4.3), MASS, survival, splines
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Repository: CRAN
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-05-27 07:32:16 UTC; user
Date/Publication: 2019-05-31 08:30:03 UTC

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New package BayesianPower with initial version 0.1.6
Package: BayesianPower
Type: Package
Title: Sample Size and Power for Comparing Inequality Constrained Hypotheses
Version: 0.1.6
Author: Fayette Klaassen
Maintainer: Fayette Klaassen <klaassen.fayette@gmail.com>
Description: A collection of methods to determine the required sample size for the evaluation of inequality constrained hypotheses by means of a Bayes factor. Alternatively, for a given sample size, the unconditional error probabilities or the expected conditional error probabilities can be determined. Additional material on the methods in this package is available in Klaassen, F., Hoijtink, H. & Gu, X. (2019) <doi:10.31219/osf.io/d5kf3>.
License: LGPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown, testthat
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-05-27 17:25:42 UTC; 4104803
Repository: CRAN
Date/Publication: 2019-05-31 08:50:15 UTC

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Thu, 30 May 2019

New package SSDM with initial version 0.2.5
Package: SSDM
Type: Package
Title: Stacked Species Distribution Modelling
Version: 0.2.5
Author: Sylvain Schmitt, Robin Pouteau, Dimitri Justeau, Florian de Boissieu, Philippe Birnbaum
Maintainer: Sylvain Schmitt <sylvain.m.schmitt@gmail.com>
URL: https://github.com/sylvainschmitt/SSDM
BugReports: https://github.com/sylvainschmitt/SSDM/issues
Description: Allows to map species richness and endemism based on stacked species distribution models (SSDM). Individuals SDMs can be created using a single or multiple algorithms (ensemble SDMs). For each species, an SDM can yield a habitat suitability map, a binary map, a between-algorithm variance map, and can assess variable importance, algorithm accuracy, and between- algorithm correlation. Methods to stack individual SDMs include summing individual probabilities and thresholding then summing. Thresholding can be based on a specific evaluation metric or by drawing repeatedly from a Bernoulli distribution. The SSDM package also provides a user-friendly interface.
License: GPL (>= 3) | file LICENSE
LazyData: TRUE
Imports: sp (>= 1.2.0), raster (>= 2.9-5), methods (>= 3.2.2), SDMTools (>= 1.1.221), mgcv (>= 1.8.7), earth (>= 4.4.3), rpart (>= 4.1.10), gbm (>= 2.1.1), randomForest (>= 4.6.10), dismo (>= 1.0.12), nnet (>= 7.3.10), e1071 (>= 1.6.7), shiny (>= 0.12.2), shinydashboard (>= 0.5.1), gplots (>= 0.1.0), shinyFiles (>= 0.7.0), spThin (>= 0.1.0)
Depends: R (>= 3.2.2)
Collate: 'SDM.R' 'Algorithm.SDM.R' 'Ensemble.SDM.R' 'Env.R' 'Occurrences.R' 'PA.select.R' 'SSDM.R' 'Stacked.SDM.R' 'checkargs.R' 'data.values.R' 'ensemble.R' 'modelling.R' 'ensemble_modelling.R' 'evaluate.R' 'evaluate.axes.R' 'get_PA.R' 'get_model.R' 'gui.R' 'load_model.R' 'load_occ.R' 'load_var.R' 'mapDiversity.R' 'plot.model.R' 'project.R' 'save.model.R' 'stack_modelling.R' 'stacking.R' 'update.stack.R' 'zzz.R'
Suggests: testthat, knitr, rmarkdown, rgdal
RoxygenNote: 6.1.1
VignetteBuilder: knitr, rmarkdown
NeedsCompilation: no
Packaged: 2019-05-29 22:55:39 UTC; sylvain
Repository: CRAN
Date/Publication: 2019-05-30 13:20:21 UTC

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New package spp with initial version 1.16.0
Package: spp
Type: Package
Title: ChIP-Seq Processing Pipeline
Version: 1.16.0
Author: Peter K
Depends: R (>= 3.3.0), Rcpp
Imports: Rsamtools, caTools, parallel, graphics, stats
Suggests: methods
LinkingTo: Rcpp, BH (>= 1.66)
OS_type: unix
Maintainer: Peter Kharchenko <spppackage.maintenance@gmail.com>
Description: Analysis of ChIP-seq and other functional sequencing data [Kharchenko PV (2008) <DOI:10.1038/nbt.1508>].
License: GPL-2
LazyLoad: yes
Note: revised for compliance with CRAN by K.Pal and C.M.Livi
NeedsCompilation: yes
Packaged: 2019-05-30 07:46:25 UTC; clivi
Repository: CRAN
Date/Publication: 2019-05-30 13:20:04 UTC

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New package WgtEff with initial version 0.1
Package: WgtEff
Title: Functions for Weighting Effects
Version: 0.1
Authors@R: c(person("Joshua", "Miller", role = c("aut", "cre"), email = "joshlmiller@msn.com"))
Description: Functions for determining the effect of data weights on the variance of survey data: Users will load a data set which has a weights column, and the package will calculate the design effect (DEFF), weighting loss, root design effect (DEFT), effective sample size (ESS), and/or weighted margin of error.
Imports: stats
Depends: R (>= 3.5)
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-05-30 02:29:25 UTC; JOSHUA
Author: Joshua Miller [aut, cre]
Maintainer: Joshua Miller <joshlmiller@msn.com>
Repository: CRAN
Date/Publication: 2019-05-30 08:30:03 UTC

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Wed, 29 May 2019

New package rCBA with initial version 0.4.3
Package: rCBA
Title: CBA Classifier
Version: 0.4.3
Authors@R: c(person("Jaroslav", "Kuchar", email = "jaroslav.kuchar@gmail.com", role = c("aut", "cre")), person("Tomas", "Kliegr", email="kliegr@gmail.com", role = c("ctb")))
Author: Jaroslav Kuchar [aut, cre], Tomas Kliegr [ctb]
Maintainer: Jaroslav Kuchar <jaroslav.kuchar@gmail.com>
URL: https://github.com/jaroslav-kuchar/rCBA
BugReports: https://github.com/jaroslav-kuchar/rCBA/issues
Description: Provides implementations of a classifier based on the "Classification Based on Associations" (CBA). It can be used for building classification models from association rules. Rules are pruned in the order of precedence given by the sort criteria and a default rule is added. The final classifier labels provided instances. CBA was originally proposed by Liu, B. Hsu, W. and Ma, Y. Integrating Classification and Association Rule Mining. Proceedings KDD-98, New York, 27-31 August. AAAI. pp80-86 (1998, ISBN:1-57735-070-7).
Depends: R (>= 3.1.3), rJava, arules
Imports: R.utils, TunePareto, methods, stats, utils
License: Apache License (== 2.0)
LazyData: true
SystemRequirements: Java (>= 8)
RoxygenNote: 6.1.1
Encoding: UTF-8
Collate: 'init.R' 'build.R' 'buildFPGrowth.R' 'classification.R' 'fpgrowth.R' 'pruning.R' 'utils.R'
NeedsCompilation: no
Packaged: 2019-05-29 21:21:38 UTC; jaroslav.kuchar
Repository: CRAN
Date/Publication: 2019-05-29 21:50:03 UTC

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New package SRTtools with initial version 1.0.0
Package: SRTtools
Type: Package
Title: Adjust Srt File to Get Better Experience when Watching Movie
Version: 1.0.0
Date: 2019-05-22
Authors@R: c(person("Jim", "Chen", role = c("aut", "cre"), email = "jim71183@gmail.com"))
Description: Srt file is a common subtitle format for videos, it contains subtitle and when the subtitle showed. This package is for ealign time of srt file, and also change color, style and position of subtitle in videos, the srt file will be read as a vector into R, and can be write into srt file after modified using this package.
License: GPL (>= 2)
Imports: magrittr (>= 1.5)
RoxygenNote: 6.1.1
Encoding: UTF-8
Depends: R (>= 2.10)
URL: https://github.com/ChiHangChen/SRTtools
BugReports: https://github.com/ChiHangChen/SRTtools/issues
NeedsCompilation: no
Packaged: 2019-05-27 09:25:42 UTC; ChiHang
Author: Jim Chen [aut, cre]
Maintainer: Jim Chen <jim71183@gmail.com>
Repository: CRAN
Date/Publication: 2019-05-29 13:10:03 UTC

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New package MCDA with initial version 0.0.20
Package: MCDA
Version: 0.0.20
Date: 2019-05-29
Title: Support for the Multicriteria Decision Aiding Process
Author: Patrick Meyer, Sébastien Bigaret, Richard Hodgett, Alexandru-Liviu Olteanu
Maintainer: Patrick Meyer <patrick.meyer@imt-atlantique.fr>
Description: Support for the analyst in a Multicriteria Decision Aiding (MCDA) process with algorithms, preference elicitation and data visualisation functions. Sébastien Bigaret, Richard Hodgett, Patrick Meyer, Tatyana Mironova, Alexandru Olteanu (2017) Supporting the multi-criteria decision aiding process : R and the MCDA package, Euro Journal On Decision Processes, Volume 5, Issue 1 - 4, pages 169 - 194 <doi:10.1007/s40070-017-0064-1>.
Imports: Rglpk, glpkAPI, methods, RColorBrewer, combinat
Suggests: Rgraphviz, cplexAPI
License: EUPL (== 1.1)
Encoding: UTF-8
URL: https://github.com/paterijk/MCDA
NeedsCompilation: no
Packaged: 2019-05-29 12:35:56 UTC; pat
Repository: CRAN
Date/Publication: 2019-05-29 13:30:10 UTC

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New package IOHanalyzer with initial version 0.1.1
Package: IOHanalyzer
Type: Package
Title: Data Analysis Part of 'IOHprofiler'
Version: 0.1.1
Author: Hao Wang [cre, aut], Diederick Vermetten [aut], Carola Doerr [aut], Thomas Bäck [aut]
Maintainer: Hao Wang <h.wang@liacs.leidenuniv.nl>
Authors@R: c( person("Hao", "Wang", email = "h.wang@liacs.leidenuniv.nl", role = c("cre","aut")), person("Diederick", "Vermetten", email="d.vermetten@gmail.com", role = "aut"), person("Carola", "Doerr", email = "Carola.Doerr@mpi-inf.mpg.de", role = "aut"), person("Thomas", "Bäck", email="t.h.w.baeck@liacs.leidenuniv.nl", role = "aut"))
Description: The data analysis module for the Iterative Optimization Heuristics Profiler ('IOHprofiler'). This module provides statistical analysis methods for the benchmark data generated by optimization heuristics, which can be visualized through a web-based interface. The benchmark data is usually generated by the experimentation module, called 'IOHexperimenter'. 'IOHanalyzer' also supports the widely used 'COCO' (Comparing Continuous Optimisers) data format for benchmarking.
License: BSD_3_clause + file LICENSE
Encoding: UTF-8
LazyData: true
URL: http://iohprofiler.liacs.nl, https://github.com/IOHprofiler/IOHAnalyzer
BugReports: https://github.com/IOHprofiler/IOHAnalyzer/issues
Imports: Rcpp, magrittr, dplyr, data.table, ggplot2, plotly, colorspace, colorRamps, RColorBrewer, shiny, withr, shinydashboard, markdown, reshape2, shinyjs, colourpicker, bsplus, DT
LinkingTo: Rcpp
SystemRequirements: C++11
RoxygenNote: 6.1.1
Suggests: testthat
Depends: R (>= 2.10)
NeedsCompilation: yes
Packaged: 2019-05-29 11:47:00 UTC; diedi
Repository: CRAN
Date/Publication: 2019-05-29 13:40:14 UTC

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New package robsurvey with initial version 0.1.0
Package: robsurvey
Type: Package
Title: Robust Survey Statistics Estimation
Version: 0.1.0
Authors@R: c( person("Beat", "Hulliger", email = "beat.hulliger@fhnw.ch", role = "aut"), person("Tobias", "Schoch", email = "tobias.schoch@gmail.com", role = "aut"), person("Martin", "Sterchi", email = "martin.sterchi@fhnw.ch", role = "cre"))
Description: Multiple functions to compute robust survey statistics. The package supports the computations of robust means, totals, and ratios. Available methods are Huber M-estimators, trimming, and winsorization. The package 'robsurvey' complements the 'survey' package. The package additionally includes a weighted version of the resistant line function of base R (line()), as well as two median based simple regression estimators. The methods are described in Hulliger (1995) <https://www150.statcan.gc.ca/n1/en/catalogue/12-001-X199500114407/>.
License: MIT + file LICENSE
URL: https://github.com/martinSter/robsurvey
BugReports: https://github.com/martinSter/robsurvey/issues
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.6.0)
Imports: survey (>= 3.35-1), stats, graphics, utils
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown, testthat
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2019-05-27 07:46:10 UTC; martin.sterchi
Author: Beat Hulliger [aut], Tobias Schoch [aut], Martin Sterchi [cre]
Maintainer: Martin Sterchi <martin.sterchi@fhnw.ch>
Repository: CRAN
Date/Publication: 2019-05-29 13:00:03 UTC

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New package psychTools with initial version 1.9.5.26
Package: psychTools
Version: 1.9.5.26
Date: 2019-05-26
Title: Tools to Accompany the 'psych' Package for Psychological Research
Authors@R: person("William", "Revelle", role =c("aut","cre"), email="revelle@northwestern.edu", comment=c(ORCID = "0000-0003-4880-9610") )
Description: Support functions, data sets, and vignettes for the 'psych' package. Contains several of the biggest data sets for the 'psych' package as well as one vignette. A few helper functions for file manipulation are included as well. For more information, see the <https://personality-project.org/r> web page.
License: GPL (>= 2)
Imports: foreign,psych
Suggests: parallel, GPArotation, lavaan
LazyData: true
ByteCompile: TRUE
URL: https://personality-project.org/r/psych https://personality-project.org/r/psych-manual.pdf
NeedsCompilation: no
Packaged: 2019-05-26 23:17:21 UTC; WR
Author: William Revelle [aut, cre] (<https://orcid.org/0000-0003-4880-9610>)
Maintainer: William Revelle <revelle@northwestern.edu>
Depends: R (>= 2.10)
Repository: CRAN
Date/Publication: 2019-05-29 12:40:03 UTC

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New package gpuR with initial version 2.0.2
Package: gpuR
Type: Package
Title: GPU Functions for R Objects
Description: Provides GPU enabled functions for R objects in a simple and approachable manner. New gpu* and vcl* classes have been provided to wrap typical R objects (e.g. vector, matrix), in both host and device spaces, to mirror typical R syntax without the need to know OpenCL.
Version: 2.0.2
Date: 2019-05-03
Author: Charles Determan Jr.
Maintainer: Charles Determan Jr. <cdetermanjr@gmail.com>
VignetteBuilder: knitr
License: GPL (>= 2)
Encoding: UTF-8
Depends: R (>= 3.0.2), methods, utils
Imports: Rcpp (>= 0.12.15), assertive
LinkingTo: Rcpp (>= 0.12.15), RcppEigen (>= 0.3.3.4.0), RViennaCL (>= 1.7.1.7), BH
NeedsCompilation: yes
Suggests: testthat, knitr
URL: http://github.com/cdeterman/gpuR
BugReports: http://github.com/cdeterman/gpuR/issues/new
SystemRequirements: C++11 (supporting at least std=c++0x), OpenCL shared library (provided by an SDK such as AMD/NVIDIA) and OpenCL headers including the C++ header file (provided by Khronos if not by SDK)
RoxygenNote: 6.1.1
Packaged: 2019-05-24 14:26:52 UTC; y66534
Repository: CRAN
Date/Publication: 2019-05-29 08:10:03 UTC

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Tue, 28 May 2019

New package motmot with initial version 2.1
Package: motmot
Type: Package
Title: Models of Trait Macroevolution on Trees
Version: 2.1
Depends: R (>= 2.10.0), ape (>= 3.0-7)
Date: 2019-05-28
Author: Mark Puttick [aut, cre, cph], Gavin Thomas [aut, cph], Rob Freckleton [aut, cph], Magnus Clarke [ctb], Travis Ingram [ctb], David Orme [ctb], Emmanuel Paradis [ctb]
Maintainer: Mark Puttick <marknputtick@gmail.com>
Description: Functions for fitting models of trait evolution on phylogenies for continuous traits. The majority of functions described in Thomas and Freckleton (2011) <doi:10.1111/j.2041-210X.2011.00132.x> and include functions that allow for tests of variation in the rates of trait evolution.
License: GPL (>= 2)
Repository: CRAN
URL: https://puttickbiology.wordpress.com/motmot/
RoxygenNote: 6.1.1
LazyData: true
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
LinkingTo: Rcpp
Imports: Rcpp, coda, ks, mvtnorm, caper, methods
Encoding: UTF-8
SystemRequirements: C++11
NeedsCompilation: yes
Packaged: 2019-05-28 15:51:25 UTC; markputtick
Date/Publication: 2019-05-28 21:00:13 UTC

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New package trinROC with initial version 0.3
Package: trinROC
Title: Statistical Tests for Assessing Trinormal ROC Data
Version: 0.3
Authors@R: c(person("Samuel", "Noll", email = "uncle.sam@gmx.net", role = c("aut")), person("Reinhard", "Furrer", role = c("ctb", "cre"), email = "reinhard.furrer@math.uzh.ch"), person("Benjamin", "Reiser", role = c("ctb")), person("Christos T.", "Nakas", role = c("ctb"), email = "cnakas@uth.gr"))
Description: Several statistical test functions as well as a function for exploratory data analysis to investigate classifiers allocating individuals to one of three disjoint and ordered classes. In a single classifier assessment the discriminatory power is compared to classification by chance. In a comparison of two classifiers the null hypothesis corresponds to equal discriminatory power of the two classifiers.
Depends: R (>= 3.3.0)
Imports: ggplot2, rgl, gridExtra
License: LGPL-2.1
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Suggests: testthat, knitr, rmarkdown, MASS, reshape
VignetteBuilder: knitr
URL: https://git.math.uzh.ch/reinhard.furrer/trinROC
NeedsCompilation: no
Packaged: 2019-05-27 17:57:10 UTC; furrer
Author: Samuel Noll [aut], Reinhard Furrer [ctb, cre], Benjamin Reiser [ctb], Christos T. Nakas [ctb]
Maintainer: Reinhard Furrer <reinhard.furrer@math.uzh.ch>
Repository: CRAN
Date/Publication: 2019-05-28 16:20:04 UTC

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New package volesti with initial version 1.0.1
Package: volesti
Type: Package
License: LGPL-3
Title: Volume Approximation and Sampling of Convex Polytopes
Author: Vissarion Fisikopoulos <vissarion.fisikopoulos@gmail.com> [aut, cph, cre], Apostolos Chalkis <tolis.chal@gmail.com> [cph, aut], contributors in file inst/AUTHORS
Copyright: file inst/COPYRIGHTS
Description: Provides an R interface for 'volesti' C++ package. 'volesti' computes estimations of volume of polytopes given by a set of points or linear inequalities or Minkowski sum of segments (zonotopes). There are two algorithms for volume estimation (I.Z. Emiris and V. Fisikopoulos (2014) <arXiv:1312.2873> and B. Cousins, S. Vempala (2016) <arXiv:1409.6011>) as well as algorithms for sampling, rounding and rotating polytopes. Moreover, 'volesti' provides algorithms for estimating copulas (L. Cales, A. Chalkis, I.Z. Emiris, V. Fisikopoulos (2018) <arXiv:1803.05861>).
Version: 1.0.1
Date: 2019-05-10
Maintainer: Vissarion Fisikopoulos <vissarion.fisikopoulos@gmail.com>
Depends: Rcpp (>= 0.12.17)
Imports: methods
LinkingTo: Rcpp, RcppEigen, BH
Suggests: testthat
Encoding: UTF-8
RoxygenNote: 6.1.1
BugReports: https://github.com/GeomScale/volume_approximation/issues
NeedsCompilation: yes
Packaged: 2019-05-28 09:11:38 UTC; vissarion
Repository: CRAN
Date/Publication: 2019-05-28 13:20:02 UTC

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New package swirlify with initial version 0.5.3
Package: swirlify
Title: A Toolbox for Writing 'swirl' Courses
Description: A set of tools for writing and sharing interactive courses to be used with swirl.
URL: http://swirlstats.com
Version: 0.5.3
License: MIT + file LICENSE
Authors@R: c( person("Sean", "Kross", , "sean@seankross.com", c("aut", "cre")), person("Nick", "Carchedi", role = "aut"), person("Chih-Cheng", "Liang", role = "ctb"), person("Wush", "Wu", role = "ctb") )
Depends: R (>= 3.2.0)
Imports: swirl (>= 2.4.2), stringr, yaml, rmarkdown, whisker, shiny, shinyAce, base64enc, readr
Encoding: UTF-8
Suggests: testthat, digest
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-05-27 21:42:38 UTC; sean
Author: Sean Kross [aut, cre], Nick Carchedi [aut], Chih-Cheng Liang [ctb], Wush Wu [ctb]
Maintainer: Sean Kross <sean@seankross.com>
Repository: CRAN
Date/Publication: 2019-05-28 07:40:03 UTC

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New package mnlogit with initial version 1.2.6
Package: mnlogit
Type: Package
Title: Multinomial Logit Model
Version: 1.2.6
Date: 2019-5-26
Suggests: VGAM, nnet
Imports: mlogit, lmtest, Formula, stats
Author: Asad Hasan, Wang Zhiyu, Alireza S. Mahani
Maintainer: Asad Hasan <asadhasan32@gmail.com>
Description: Time and memory efficient estimation of multinomial logit models using maximum likelihood method. Numerical optimization performed by Newton-Raphson method using an optimized, parallel C++ library to achieve fast computation of Hessian matrices. Motivated by large scale multiclass classification problems in econometrics and machine learning.
License: GPL (>= 2)
NeedsCompilation: yes
Repository: CRAN
Packaged: 2019-05-27 23:23:42 UTC; ahasan
Date/Publication: 2019-05-28 08:00:03 UTC

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Mon, 27 May 2019

New package packagefinder with initial version 0.1.4
Package: packagefinder
Type: Package
Title: Comfortable Search for R Packages on CRAN Directly from the R Console
Version: 0.1.4
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: Search for R packages on CRAN directly from the R console, based on the packages' titles, short and long descriptions, or other fields. Combine multiple keywords with logical operators ('and', 'or'), view detailed information on any package and keep track of the latest package contributions to CRAN.
License: GPL-3
Encoding: UTF-8
BugReports: https://github.com/jsugarelli/packagefinder/issues
URL: https://github.com/jsugarelli/packagefinder/, http://www.zuckarelli.de/packagefinder/tutorial.html, https://www.youtube.com/watch?v=66Mes6_hYno
Repository: CRAN
LazyData: true
Imports: httr, utils, jsonlite, pander, formattable, stringr, crayon, lubridate, tidyr
Depends: tools (>= 3.4.0)
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2019-05-27 19:51:52 UTC; Joachim
Author: Joachim Zuckarelli [aut, cre] (<https://orcid.org/0000-0002-9280-3016>)
Date/Publication: 2019-05-27 21:10:03 UTC

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New package kmi with initial version 0.5.5
Package: kmi
Version: 0.5.5
Title: Kaplan-Meier Multiple Imputation for the Analysis of Cumulative Incidence Functions in the Competing Risks Setting
Author: Arthur Allignol <arthur.allignol@gmail.com>
Maintainer: Arthur Allignol <arthur.allignol@gmail.com>
Imports: mitools,survival,stats
Description: Performs a Kaplan-Meier multiple imputation to recover the missing potential censoring information from competing risks events, so that standard right-censored methods could be applied to the imputed data sets to perform analyses of the cumulative incidence functions (Allignol and Beyersmann, 2010 <doi:10.1093/biostatistics/kxq018>).
License: GPL (>= 2)
URL: https://github.com/aallignol/kmi
BugReports: https://github.com/aallignol/kmi/issues
NeedsCompilation: no
Packaged: 2019-05-27 20:17:42 UTC; arthur
Repository: CRAN
Date/Publication: 2019-05-27 21:10:13 UTC

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New package rnn with initial version 0.9.8
Package: rnn
Title: Recurrent Neural Network
Version: 0.9.8
Authors@R: c(person("Bastiaan", "Quast", email = "bquast@gmail.com", role = c("aut", "cre")), person("Dimitri", "Fichou", email = "dimitrifichou@gmail.com", role = "aut"))
Description: Implementation of a Recurrent Neural Network architectures in native R, including Long Short-Term Memory (Hochreiter and Schmidhuber, <doi:10.1162/neco.1997.9.8.1735>), Gated Recurrent Unit (Chung et al., <arXiv:1412.3555>) and vanilla RNN.
Depends: R (>= 3.2.2)
License: GPL-3
LazyData: true
RoxygenNote: 6.1.1
URL: http://qua.st/rnn, https://github.com/bquast/rnn
BugReports: https://github.com/bquast/rnn/issues
Imports: sigmoid, shiny
Suggests: testthat, knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-05-27 14:29:36 UTC; bquast
Author: Bastiaan Quast [aut, cre], Dimitri Fichou [aut]
Maintainer: Bastiaan Quast <bquast@gmail.com>
Repository: CRAN
Date/Publication: 2019-05-27 16:11:46 UTC

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New package SelectBoost with initial version 1.4.0
Package: SelectBoost
Type: Package
Title: A General Algorithm to Enhance the Performance of Variable Selection Methods in Correlated Datasets
Version: 1.4.0
Date: 2019-05-04
Depends: R (>= 2.10)
Imports: lars, glmnet, igraph, parallel, msgps, Rfast, methods, Cascade, graphics, grDevices
Suggests: knitr, rmarkdown, mixOmics, CascadeData
Authors@R: c( person(given = "Frederic", family= "Bertrand", role = c("cre", "aut"), email = "frederic.bertrand@math.unistra.fr", comment = c(ORCID = "0000-0002-0837-8281")), person(given = "Myriam", family= "Maumy-Bertrand", role = c("aut"), email = "myriam.maumy-bertrand@math.unistra.fr", comment = c(ORCID = "0000-0002-4615-1512")), person(given = "Ismail", family= "Aouadi", role = c("ctb"), email = "i.aouadi@unistra.fr"), person(given = "Nicolas", family= "Jung", role = c("ctb"), email = "nicolas.jung@unistra.fr"))
Author: Frederic Bertrand [cre, aut] (<https://orcid.org/0000-0002-0837-8281>), Myriam Maumy-Bertrand [aut] (<https://orcid.org/0000-0002-4615-1512>), Ismail Aouadi [ctb], Nicolas Jung [ctb]
Maintainer: Frederic Bertrand <frederic.bertrand@math.unistra.fr>
Description: An implementation of the selectboost algorithm (Aouadi et al. 2018, <arXiv:1810.01670>), which is a general algorithm that improves the precision of any existing variable selection method. This algorithm is based on highly intensive simulations and takes into account the correlation structure of the data. It can either produce a confidence index for variable selection or it can be used in an experimental design planning perspective.
License: GPL-3
Encoding: UTF-8
Classification/MSC: 62H11, 62J12, 62J99
VignetteBuilder: knitr
RoxygenNote: 6.1.1
URL: https://github.com/fbertran/SelectBoost, http://www-irma.u-strasbg.fr/~fbertran/
BugReports: https://github.com/fbertran/SelectBoost/issues
NeedsCompilation: no
Packaged: 2019-05-21 08:19:09 UTC; fbertran
Repository: CRAN
Date/Publication: 2019-05-27 09:20:03 UTC

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