Thu, 21 Jun 2018

New package Rsmlx with initial version 1.0.1
Package: Rsmlx
Type: Package
Title: R Speaks 'Monolix'
Version: 1.0.1
Authors@R: c( person( "Marc", "Lavielle", role = c("aut","cre"), email = "Marc.Lavielle@inria.fr" ), person( "Jonathan", "Chauvin", role = c("aut"), email = "Jonathan.Chauvin@lixoft.com" ), person( "Duc-Dung", "Tran", role = c("ctb"), email = "duc-dung.tran@polytechnique.edu" ))
Description: Provides methods for model building and model evaluation of mixed effects models using 'Monolix' <http://monolix.lixoft.com>. 'Monolix' is a software tool for nonlinear mixed effects modeling that must have been installed in order to use 'Rsmlx'. Among other tasks, 'Rsmlx' performs statistical tests for model assessment, bootstrap simulation and likelihood profiling for computing confidence intervals. 'Rsmlx' also proposes several automatic covariate search methods for mixed effects models.
URL: http://rsmlx.webpopix.org
SystemRequirements: 'Monolix' (<http://monolix.lixoft.com>)
Depends: R (>= 3.0.0)
Imports: MASS, RJSONIO, ggplot2, gridExtra, tools, methods, graphics, grDevices, utils, stats, tcltk
Collate: APITools.R displayTools.R MlxEnvironment.R APIManager.R ProjectManagement.R Scenario.R Settings2.R PopulationParameters.R IndividualModel.R CovariateModel.R ObservationModel.R Results.R MlxCore.R bootstrap.R buildmlx.R confintmlx.R correlationModelSelection.R covariateModelSelection.R covariateSearch.R errorModelSelection.R llp.R newConnectors.R setSettings.R testmlx.R initializeRsmlx.R
License: BSD_2_clause + file LICENSE
Copyright: Inria
NeedsCompilation: no
Encoding: UTF-8
RoxygenNote: 6.0.1
Packaged: 2018-06-19 11:46:42 UTC; Marc
Author: Marc Lavielle [aut, cre], Jonathan Chauvin [aut], Duc-Dung Tran [ctb]
Maintainer: Marc Lavielle <Marc.Lavielle@inria.fr>
Repository: CRAN
Date/Publication: 2018-06-21 17:37:58 UTC

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New package RcppMeCab with initial version 0.0.1.1
Package: RcppMeCab
Title: 'rcpp' Wrapper for 'mecab' Library
Version: 0.0.1.1
Authors@R: c(person("Junhewk", "Kim", role = c("aut", "cre"), email = "junhewk.kim@gmail.com"), person("Taku", "Kudo", role = c("aut"), email = "taku@chasen.org"))
Author: Junhewk Kim [aut, cre], Taku Kudo [aut]
Maintainer: Junhewk Kim <junhewk.kim@gmail.com>
Description: R package based on 'Rcpp' for 'MeCab': Yet Another Part-of-Speech and Morphological Analyzer. The purpose of this package is providing a seamless developing and analyzing environment for CJK texts. This package utilizes parallel programming for providing highly efficient text preprocessing 'posParallel()' function. For installation, please refer to README.md file.
Depends: R (>= 3.4.0)
License: GPL
Encoding: UTF-8
LazyData: true
BugReports: https://github.com/junhewk/RcppMeCab/issues
LinkingTo: Rcpp, RcppParallel, BH
Imports: Rcpp, RcppParallel
SystemRequirements: MeCab 0.996 (or mecab-ko 0.9.2) or higher, GNU make
RoxygenNote: 6.0.1
NeedsCompilation: yes
Packaged: 2018-06-14 21:56:05 UTC; jk
Repository: CRAN
Date/Publication: 2018-06-21 17:47:55 UTC

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New package nlmixr with initial version 0.9.1-3
Package: nlmixr
Type: Package
Title: Nonlinear Mixed Effects Models in Population Pharmacokinetics and Pharmacodynamics
Depends: R (>= 3.2)
Imports: Rcpp (>= 0.12.3), brew, lattice, parallel, lbfgs, dparser, methods, ggplot2, memoise, rex, minqa, Matrix, numDeriv, R.utils, n1qn1, PreciseSums, fastGHQuad, crayon, cli, RcppArmadillo (>= 0.5.600.2.0), vpc (>= 1.0.0), RxODE(>= 0.7.2-3), nlme, magrittr
Suggests: knitr, rmarkdown, dplyr, data.table, lbfgsb3, testthat, madness, devtools, expm, matrixcalc, reshape2
Version: 0.9.1-3
Authors@R: c(person("Matthew","Fidler", role = "aut", email = "matthew.fidler@gmail.com"), person("Yuan", "Xiong", role = "aut", email = "yuan.xiong@gmail.com"), person("Rik", "Schoemaker", role = "aut", email = "rik.schoemaker@occams.com"), person("Justin", "Wilkins", role = "aut", email = "justin.wilkins@occams.com"), person("Mirjam","Trame", role = "aut", email = "mirjam.trame@gmail.com"), person("Teun","Post", role = "aut", email = "t.post@lapp.nl"), person("Robert","Leary", role = "ctb"), person("Wenping", "Wang", role = c("aut", "cre"), email = "wwang8198@gmail.com"), person("Hadley","Wickham", role = "ctb"), person("Dirk","Eddelbuettel", role = "cph", email = "edd@debian.org"), person("David","Ardia",role = "cph"), person("Katharine","Mullen",role = "cph") )
Description: Fit and compare nonlinear mixed-effects models in differential equations with flexible dosing information commonly seen in pharmacokinetics and pharmacodynamics (Almquist, Leander, and Jirstrand 2015 <doi:10.1007/s10928-015-9409-1>). Differential equation solving is by compiled C code provided in the 'RxODE' package (Wang, Hallow, and James 2015 <doi:10.1002/psp4.12052>).
License: GPL (>= 2)
NeedsCompilation: yes
LinkingTo: dparser(>= 0.1.8), Rcpp (>= 0.12.3), RcppEigen (>= 0.3.3.3.0), StanHeaders, BH
URL: https://github.com/nlmixrdevelopment/nlmixr
LazyData: true
VignetteBuilder: knitr
RoxygenNote: 6.0.1
Packaged: 2018-06-19 23:02:32 UTC; annie
Maintainer: Wenping Wang <wwang8198@gmail.com>
Author: Matthew Fidler [aut], Yuan Xiong [aut], Rik Schoemaker [aut], Justin Wilkins [aut], Mirjam Trame [aut], Teun Post [aut], Robert Leary [ctb], Wenping Wang [aut, cre], Hadley Wickham [ctb], Dirk Eddelbuettel [cph], David Ardia [cph], Katharine Mullen [cph]
Repository: CRAN
Date/Publication: 2018-06-21 13:59:10 UTC

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Wed, 20 Jun 2018

New package MetaSubtract with initial version 1.41
Package: MetaSubtract
Type: Package
Title: Subtracting Summary Statistics of One or more Cohorts from Meta-GWAS Results
Version: 1.41
Date: 2018-06-19
Author: Ilja M. Nolte
Maintainer: Ilja M. Nolte <i.m.nolte@umcg.nl>
Description: If results from a meta-GWAS are used for validation in one of the cohorts that was included in the meta-analysis, this will yield biased (i.e. too optimistic) results. The validation cohort needs to be independent from the meta-Genome-Wide-Association-Study (meta-GWAS) results. 'MetaSubtract' will subtract the results of the respective cohort from the meta-GWAS results analytically without having to redo the meta-GWAS analysis using the leave-one-out methodology. It can handle different meta-analyses methods and takes into account if single or double genomic control correction was applied to the original meta-analysis. It can also handle different meta-analysis methods. It can be used for whole GWAS, but also for a limited set of genetic markers.
License: GPL (>= 3)
NeedsCompilation: no
Packaged: 2018-06-20 08:32:52 UTC; NolteIM
Repository: CRAN
Date/Publication: 2018-06-20 13:43:02 UTC

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Tue, 19 Jun 2018

New package kidney.epi with initial version 1.0.0
Package: kidney.epi
Title: Kidney Functions: Clinical and Epidemiological
Version: 1.0.0
Authors@R: person("Boris", "Bikbov", email = "boris@bikbov.ru", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-1925-7506"))
Maintainer: Boris Bikbov <boris@bikbov.ru>
Description: Contains kidney care oriented functions. Current version contains only function for calculation of Kidney Donor Risk Index and Kidney Donor Profile Index for kidney transplant donors by Rao et al. (2009) <doi:10.1097/TP.0b013e3181ac620b>.
Depends: R (>= 3.4.0)
License: LGPL (>= 2)
URL: http://kidneyepidemiology.org/r/
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-06-19 13:30:15 UTC; boris
Author: Boris Bikbov [aut, cre] (<https://orcid.org/0000-0002-1925-7506>)
Repository: CRAN
Date/Publication: 2018-06-19 14:08:06 UTC

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New package careless with initial version 1.1.3
Package: careless
Type: Package
Title: Procedures for Computing Indices of Careless Responding
Version: 1.1.3
Date: 2018-06-19
Authors@R: c( person("Richard", "Yentes" , email = "rdyentes@ncsu.edu", role = c("cre", "aut")), person("Francisco", "Wilhelm", email = "franciscowilhelm@gmail.com", role = c("aut")))
Maintainer: Richard Yentes <rdyentes@ncsu.edu>
Description: When taking online surveys, participants sometimes respond to items without regard to their content. These types of responses, referred to as careless or insufficient effort responding, constitute significant problems for data quality, leading to distortions in data analysis and hypothesis testing, such as spurious correlations. The 'R' package 'careless' provides solutions designed to detect such careless / insufficient effort responses by allowing easy calculation of indices proposed in the literature. It currently supports the calculation of longstring, even-odd consistency, psychometric synonyms/antonyms, Mahalanobis distance, and intra-individual response variability (also termed inter-item standard deviation). For a review of these methods, see Curran (2016) <doi:10.1016/j.jesp.2015.07.006>.
License: MIT + file LICENSE
URL: https://github.com/ryentes/careless/
BugReports: https://github.com/ryentes/careless/issues
Imports: psych
Suggests: testthat, knitr
Encoding: UTF-8
LazyData: true
VignetteBuilder: knitr
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-06-19 13:20:33 UTC; Wolf
Author: Richard Yentes [cre, aut], Francisco Wilhelm [aut]
Repository: CRAN
Date/Publication: 2018-06-19 14:08:10 UTC

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New package ubci with initial version 0.0.2
Package: ubci
Version: 0.0.2
Title: Get Cryptocurrency Related Data by Upbit
Description: Get 'UBCI' & Price from 'Upbit'. 'ubci' is the abbreviation of 'UpBit Crypto Index' and is the name of the index provided by 'upbit'. The 'upbit' is one of the cryptocurrency exchange in Korea. The 'ubci' package is a wrapper around the ticker information and 'ubci' API supplied by 'upbit'.
Authors@R: person("Chanyub", "Park", , "mrchypark@gmail.com", c("aut", "cre"))
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
ByteCompile: true
URL: https://github.com/mrchypark/ubci
BugReports: https://github.com/mrchypark/ubci/issues
RoxygenNote: 6.0.1
Imports: httr, lubridate, tibble, dplyr, tidyr, magrittr
Suggests: testthat
Depends: R (>= 3.2)
NeedsCompilation: no
Packaged: 2018-06-19 01:09:38 UTC; patrick
Author: Chanyub Park [aut, cre]
Maintainer: Chanyub Park <mrchypark@gmail.com>
Repository: CRAN
Date/Publication: 2018-06-19 13:48:10 UTC

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New package M2SMF with initial version 1.0
Package: M2SMF
Title: Multi-Modal Similarity Matrix Factorization for Integrative Multi-Omics Data Analysis
Version: 1.0
Authors@R: person("Xiaoyao", "Yin", email = "yinxy1992@sina.com", role = c("aut", "cre"))
Description: A new method to implement clustering from multiple modality data of certain samples, the function M2SMF() jointly factorizes multiple similarity matrices into a shared sub-matrix and several modality private sub-matrices, which is further used for clustering. Along with this method, we also provide function to calculate the similarity matrix and function to evaluate the best cluster number from the original data.
Imports: dplyr, MASS, stats
Depends: R (>= 3.4.0)
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-06-19 12:28:58 UTC; yxy
Author: Xiaoyao Yin [aut, cre]
Maintainer: Xiaoyao Yin <yinxy1992@sina.com>
Repository: CRAN
Date/Publication: 2018-06-19 13:48:17 UTC

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New package adwordsR with initial version 0.3.1
Package: adwordsR
Type: Package
Title: Access the 'Google Adwords' API
Version: 0.3.1
Authors@R: c(person("Sean", "Longthorpe", email = "sean.longthorpe@branded3.com", role = c("aut", "cre", "cph")), person("Johannes", "Burkhardt", role = c("ctb", "cph")))
Maintainer: Sean Longthorpe <sean.longthorpe@branded3.com>
Description: Allows access to selected services that are part of the 'Google Adwords' API <https://developers.google.com/adwords/api/docs/guides/start>. 'Google Adwords' is an online advertising service by 'Google', that delivers Ads to users. This package offers a authentication process using 'OAUTH2'. Currently, there are two methods of data of accessing the API, depending on the type of request. One method uses 'SOAP' requests which require building an 'XML' structure and then sent to the API. These are used for the 'ManagedCustomerService' and the 'TargetingIdeaService'. The second method is by building 'AWQL' queries for the reporting side of the 'Google Adwords' API.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
URL: https://www.branded3.com/
Depends: R (>= 3.4.0)
RoxygenNote: 6.0.1
Date: 2018-06-19
Imports: RCurl, rjson, utils
NeedsCompilation: no
Packaged: 2018-06-19 10:12:45 UTC; Sean.Longthorpe
Author: Sean Longthorpe [aut, cre, cph], Johannes Burkhardt [ctb, cph]
Repository: CRAN
Date/Publication: 2018-06-19 13:48:14 UTC

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New package steemr with initial version 0.0.4
Package: steemr
Version: 0.0.4
Title: A Tool for Processing Steem Data
Author: Peng Zhao <pzhao@pzhao.net>
Maintainer: Peng Zhao <pzhao@pzhao.net>
Depends: R (>= 3.1.0)
Imports: RCurl, XML, rlist, wordcloud, tm, zoo, openair, lattice, VennDiagram
Suggests:
Description: Steem is a blockchain-based social media platform (see <https://en.wikipedia.org/wiki/Steemit>). The Steem social activity data are saved in the Steem blockchain, the SteemDB database, the SteemSQL database, and so on. 'steemr' is an R package that downloads the Steem data from the SteemDB and SteemSQL servers, re-organizes the data in a user-friendly way, and visualizes the data for further analysis.
License: MIT + file LICENSE
URL: https://github.com/pzhaonet/steemr
BugReports: https://github.com/pzhaonet/steemr/issues
RoxygenNote: 6.0.1
NeedsCompilation: no
LazyData: true
Packaged: 2018-06-15 15:41:19 UTC; c7701105
Repository: CRAN
Date/Publication: 2018-06-19 12:27:54 UTC

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New package ROI.plugin.neos with initial version 0.3-0
Package: ROI.plugin.neos
Version: 0.3-0
Title: 'NEOS' Plug-in for the 'R' Optimization Interface
Authors@R: c( person("Ronald", "Hochreiter", role = "aut"), person("Florian", "Schwendinger", role = c("aut", "cre"), email = "FlorianSchwendinger@gmx.at"))
Description: Enhances the 'R' Optimization Infrastructure ('ROI') package with a connection to the 'neos' server. 'ROI' optimization problems can be directly be sent to the 'neos' server and solution obtained in the typical 'ROI' style.
Imports: stats, methods, utils, ROI (>= 0.3-0), xmlrpc2, xml2
Suggests: slam
License: GPL-3
URL: http://R-Forge.R-project.org/projects/roi
NeedsCompilation: no
Packaged: 2018-06-16 13:11:06 UTC; florian
Author: Ronald Hochreiter [aut], Florian Schwendinger [aut, cre]
Maintainer: Florian Schwendinger <FlorianSchwendinger@gmx.at>
Repository: CRAN
Date/Publication: 2018-06-19 12:48:04 UTC

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New package nilde with initial version 1.1-1
Encoding: UTF-8
Package: nilde
Version: 1.1-1
Author: Natalya Pya Arnqvist[aut, cre], Vassilly Voinov [aut], Yevgeniy Voinov [aut]
Maintainer: Natalya Pya Arnqvist <nat.pya@gmail.com>
Title: Nonnegative Integer Solutions of Linear Diophantine Equations with Applications
Date: 2018-06-18
Description: Routines for enumerating all existing nonnegative integer solutions of a linear Diophantine equation. The package provides routines for solving 0-1, bounded and unbounded knapsack problems; 0-1, bounded and unbounded subset sum problems; and a problem of additive partitioning of natural numbers.
Depends: R (>= 2.15.0)
Imports: methods, stats
License: GPL (>= 2)
LazyLoad: yes
NeedsCompilation: no
Packaged: 2018-06-19 10:10:08 UTC; natalya
Repository: CRAN
Date/Publication: 2018-06-19 12:02:58 UTC

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New package ncodeR with initial version 0.1.0
Package: ncodeR
Title: Techniques for Automated Classifiers
Type: Package
Date: 2018-06-18
Author: Cody L Marquart [aut, cre], Brendan Eagan [aut], David Williamson Shaffer [aut]
Authors@R: c(person("Cody L","Marquart", role = c("aut", "cre"), email="cody.marquart@wisc.edu"),person("Brendan","Eagan", role = c("aut"), email="beagan@wisc.edu"),person("David", "Williamson Shaffer", role = c("aut"), email = "dws@education.wisc.edu"))
Maintainer: Cody L Marquart <cody.marquart@wisc.edu>
Version: 0.1.0
Description: A set of techniques that can be used to develop, validate, and implement automated classifiers. A powerful tool for transforming raw data into meaningful information, 'ncodeR' (Shaffer, D. W. (2017) Quantitative Ethnography. ISBN: 0578191687) is designed specifically for working with big data: large document collections, logfiles, and other text data.
LazyData: TRUE
Depends: R (>= 3.0.0)
License: GPL (>= 2)
Imports: R6, rhoR, cli
Suggests: testthat
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-06-19 11:31:46 UTC; clmarquart
Repository: CRAN
Date/Publication: 2018-06-19 12:12:55 UTC

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New package qsort with initial version 0.2.1
Package: qsort
Type: Package
Title: Scoring Q-Sort Data
Version: 0.2.1
Authors@R: c( person("João R", "Daniel", email = "joaordaniel@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "https://orcid.org/0000-0001-6609-2014")), person("David N", "Sousa", email = "davidnsousa@gmail.com", role = "aut"))
Description: Computes scores from Q-sort data, using criteria sorts and derived scales from subsets of items. The 'qsort' package includes descriptions and scoring procedures for four different Q-sets: Attachment Q-set (version 3.0) (Waters, 1995, <doi:10.1111/j.1540-5834.1995.tb00214.x>); California Child Q-set (Block and Block, 1969, <doi:10.1037/0012-1649.21.3.508>); Maternal Behaviour Q-set (version 3.1) (Pederson et al., 1999, <https://ir.lib.uwo.ca/cgi/viewcontent.cgi?article=1000&context=psychologypub>); Preschool Q-set (Baumrind, 1968 revised by Wanda Bronson, <doi:10.1111/j.1540-5834.1995.tb00214.x>).
Imports: cowplot, ggplot2, gridExtra, purrr, stats
Suggests: devtools, knitr, roxygen2
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-06-19 10:28:21 UTC; jdani
Author: João R Daniel [aut, cre] (<https://orcid.org/0000-0001-6609-2014>), David N Sousa [aut]
Maintainer: João R Daniel <joaordaniel@gmail.com>
Repository: CRAN
Date/Publication: 2018-06-19 11:58:00 UTC

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New package rqdatatable with initial version 0.1.0
Package: rqdatatable
Type: Package
Title: 'rquery' for 'data.table'
Version: 0.1.0
Date: 2018-06-14
Authors@R: c( person("John", "Mount", email = "jmount@win-vector.com", role = c("aut", "cre")), person(family = "Win-Vector LLC", role = c("cph")) )
Maintainer: John Mount <jmount@win-vector.com>
Description: Implement the 'rquery' piped query algebra using 'data.table'. This allows for a high-speed in memory implementation of Codd-style data manipulation tools.
URL: https://github.com/WinVector/rqdatatable/, https://winvector.github.io/rqdatatable/
BugReports: https://github.com/WinVector/rqdatatable/issues
License: GPL-3
Encoding: UTF-8
LazyData: true
ByteCompile: true
VignetteBuilder: knitr
Depends: R (>= 3.4.0), rquery (>= 0.5.0)
Imports: wrapr (>= 1.5.0), data.table (>= 1.11.4)
RoxygenNote: 6.0.1
Suggests: knitr, rmarkdown, DBI, RSQLite, parallel, testthat
NeedsCompilation: no
Packaged: 2018-06-18 22:54:36 UTC; johnmount
Author: John Mount [aut, cre], Win-Vector LLC [cph]
Repository: CRAN
Date/Publication: 2018-06-19 09:10:55 UTC

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New package DPtree with initial version 1.0.1
Package: DPtree
Title: Dirichlet-Based Polya Tree
Version: 1.0.1
Authors@R: person("Shaoyang", "Ning", email = "shaoyangning@fas.harvard.edu", role = c("aut", "cre"))
Description: Contains functions to perform copula estimation by the non-parametric Bayesian method, Dirichlet-based Polya Tree. See Ning (2018) <doi:10.1080/00949655.2017.1421194>.
Depends: R (>= 3.3.1)
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: MCMCpack, stats, plyr, MASS, Rdpack
RdMacros: Rdpack
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-06-19 02:29:13 UTC; ning
Author: Shaoyang Ning [aut, cre]
Maintainer: Shaoyang Ning <shaoyangning@fas.harvard.edu>
Repository: CRAN
Date/Publication: 2018-06-19 09:17:55 UTC

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New package RZooRoH with initial version 0.1.0
Package: RZooRoH
Type: Package
Title: Partitioning of Individual Autozygosity into Multiple Homozygous-by-Descent Classes
Version: 0.1.0
Author: Tom Druet, Naveen Kumar Kadri, Amandine Bertrand and Mathieu Gautier
Maintainer: Tom Druet <tom.druet@uliege.be>
Description: Functions to identify Homozygous-by-Descent (HBD) segments associated with runs of homozygosity (ROH) and to estimate individual autozygosity (or inbreeding coefficient). HBD segments and autozygosity are assigned to multiple HBD classes with a model-based approach relying on a mixture of exponential distributions. The rate of the exponential distribution is distinct for each HBD class and defines the expected length of the HBD segments. These HBD classes are therefore related to the age of the segments (longer segments and smaller rates for recent autozygosity / recent common ancestor). The functions allow to estimate the parameters of the model (rates of the exponential distributions, mixing proportions), to estimate global and local autozygosity probabilities and to identify HBD segments with the Viterbi decoding. The method is fully described in Druet and Gautier (2017) <doi:10.1111/mec.14324>.
Depends: R (>= 3.2.0), methods
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: foreach, doParallel, parallel, data.table, RColorBrewer, iterators
RoxygenNote: 6.0.1
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2018-06-12 13:23:22 UTC; tom
Repository: CRAN
Date/Publication: 2018-06-19 08:55:35 UTC

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New package RepoGenerator with initial version 0.0.1
Package: RepoGenerator
Title: Generates a Project and Repo for Easy Initialization of a Workshop
Version: 0.0.1
Authors@R: person(c("Jared", "P."), "Lander", email = "packages@jaredlander.com", role = c("aut", "cre"))
Description: Generates a project and repo for easy initialization of a GitHub repo for R workshops. The repo includes a README with instructions to ensure that all users have the needed packages, an 'RStudio' project with the right directories and the proper data. The repo can then be used for hosting code taught during the workshop.
Depends: R (>= 3.3.0)
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: rstudioapi, git2r, rmarkdown, httr
RoxygenNote: 6.0.1
Suggests: testthat, covr
URL: https://github.com/jaredlander/RepoGenerator
BugReports: https://github.com/jaredlander/RepoGenerator/issues
SystemRequirements: GitHub, 'RStudio'
NeedsCompilation: no
Packaged: 2018-06-17 21:16:21 UTC; jared
Author: Jared P. Lander [aut, cre]
Maintainer: Jared P. Lander <packages@jaredlander.com>
Repository: CRAN
Date/Publication: 2018-06-19 08:10:24 UTC

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New package otuSummary with initial version 0.1.0
Package: otuSummary
Type: Package
Title: Summarizing OTU Table Regarding the Composition, Abundance and Beta Diversity of Abundant and Rare Biospheres
Version: 0.1.0
Date: 2018-6-18
Author: Sizhong Yang
Maintainer: Sizhong Yang <yanglzu@163.com>
Description: Summarizes the taxonomic composition, diversity contribution of the rare and abundant community by using OTU (operational taxonomic unit) table which was generated by analyzing pipeline of 'QIIME' or 'mothur'. The rare biosphere in this package is subset by the relative abundance threshold (for details about rare biosphere please see Lynch and Neufeld (2015) <doi:10.1038/nrmicro3400>).
Depends: R (>= 3.1.0), vegan (>= 2.0-7)
Imports: reshape2 (>= 1.4), fossil (>= 0.3.7), reldist (>= 1.6-6)
URL: https://github.com/camel315/otuSummary
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-06-18 21:55:06 UTC; paul
Repository: CRAN
Date/Publication: 2018-06-19 09:01:09 UTC

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New package groupICA with initial version 0.1.1
Package: groupICA
Title: Independent Component Analysis for Grouped Data
Version: 0.1.1
Author: Niklas Pfister and Sebastian Weichwald
Maintainer: Niklas Pfister <pfister@stat.math.ethz.ch>
Description: Contains an implementation of an independent component analysis (ICA) for grouped data. The main function groupICA() performs a blind source separation, by maximizing an independence across sources and allows to adjust for varying confounding for user-specified groups. Additionally, the package contains the function uwedge() which can be used to approximately jointly diagonalize a list of matrices. For more details see the project website <https://sweichwald.de/groupICA/>.
URL: https://github.com/sweichwald/groupICA-R
BugReports: https://github.com/sweichwald/groupICA-R/issues
Depends: R (>= 3.2.3)
License: AGPL-3
Encoding: UTF-8
LazyData: true
Imports: stats, MASS
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-06-06 11:57:47 UTC; pfisteni
Repository: CRAN
Date/Publication: 2018-06-19 08:55:29 UTC

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New package centralplot with initial version 0.1.0
Package: centralplot
Type: Package
Title: Show the Strength of Relationships Between Centre and Peripheral Items
Version: 0.1.0
Author: Jian Sun
Maintainer: Jian Sun <sunjiansysu@foxmail.com>
Description: The degree of correlation between centre and peripheral items are shown by the length of the line between them. You can self-define the length by inputing the "distance" parameter. For example, you can input (1 - Pearson's correlation coefficient) as "distance" so that the stronger the correlation between centre and peripheral item, the nearer they will be in this plot. Also, If you do a hypothesis test and the null hypothesis is centre and peripheral items are the same, you can input -log(P) as distance. To sum up, the stronger the correlation between centre and peripheral is, the smaller the "distance" parameter should be. Due to its high degree of freedom, it can be applied to many different circumstance.
License: GPL-2
Encoding: UTF-8
LazyData: true
Depends: ggplot2
NeedsCompilation: no
Packaged: 2018-06-18 11:31:52 UTC; jian
Repository: CRAN
Date/Publication: 2018-06-19 08:55:32 UTC

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Mon, 18 Jun 2018

New package NNLM with initial version 0.4.2
Package: NNLM
Type: Package
Title: Fast and Versatile Non-Negative Matrix Factorization
Description: This is a package for Non-Negative Linear Models (NNLM). It implements fast sequential coordinate descent algorithms for non-negative linear regression and non-negative matrix factorization (NMF). It supports mean square error and Kullback-Leibler divergence loss. Many other features are also implemented, including missing value imputation, domain knowledge integration, designable W and H matrices and multiple forms of regularizations.
Version: 0.4.2
Date: 2018-05-17
Authors@R: c(person("Xihui", "Lin", email = "ericxihuilin@gmail.com", role = c("aut", "cre")), person("Paul C Boutros", role = "aut", email = "Paul.Boutros@oicr.on.ca"))
Depends: R (>= 3.0.1)
Imports: Rcpp (>= 0.11.0), stats, utils
LinkingTo: Rcpp, RcppArmadillo, RcppProgress
LazyData: yes
LazyLoad: yes
NeedsCompilation: yes
Suggests: testthat, knitr, rmarkdown, mice, missForest, ISOpureR
VignetteBuilder: knitr
RoxygenNote: 5.0.0
License: BSD_2_clause + file LICENSE
BugReports: https://github.com/linxihui/NNLM/issues
URL: https://github.com/linxihui/NNLM
Packaged: 2018-06-17 01:43:19 UTC; eric
Author: Xihui Lin [aut, cre], Paul C Boutros [aut]
Maintainer: Xihui Lin <ericxihuilin@gmail.com>
Repository: CRAN
Date/Publication: 2018-06-18 18:24:15 UTC

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New package mixdir with initial version 0.1.0
Package: mixdir
Type: Package
Title: Cluster High Dimensional Categorical Datasets
Version: 0.1.0
Authors@R: c(person("Constantin", "Ahlmann-Eltze", email = "artjom31415@googlemail.com", role = c("aut", "cre")), person("Christopher", "Yau", email="c.yau@bham.ac.uk", role="ths"))
Description: Scalable Bayesian clustering of categorical datasets. The package implements a hierarchical Dirichlet (Process) mixture of multinomial distributions. It is thus a probabilistic latent class model (LCM) and can be used to reduce the dimensionality of hierarchical data and cluster individuals into latent classes. It can automatically infer an appropriate number of latent classes or find k classes, as defined by the user. The model is based on a paper by Dunson and Xing (2009) <doi:10.1198/jasa.2009.tm08439>, but implements a scalable variational inference algorithm so that it is applicable to large datasets.
License: GPL-3
Encoding: UTF-8
LazyData: true
Suggests: testthat, tibble, purrr, dplyr, rmutil, pheatmap, mcclust, ggplot2, tidyr, utils
RoxygenNote: 6.0.1
Imports: extraDistr, Rcpp
Depends: R (>= 2.10)
LinkingTo: Rcpp
NeedsCompilation: yes
Packaged: 2018-06-18 10:35:01 UTC; constantin
Author: Constantin Ahlmann-Eltze [aut, cre], Christopher Yau [ths]
Maintainer: Constantin Ahlmann-Eltze <artjom31415@googlemail.com>
Repository: CRAN
Date/Publication: 2018-06-18 16:32:55 UTC

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New package dragonking with initial version 0.1.0
Package: dragonking
Type: Package
Title: Statistical Tools to Identify Dragon Kings
Version: 0.1.0
Authors@R: c(person("Raoul", "Wadhwa", email = "raoulwadhwa@gmail.com", role = c("aut", "cre")), person("Christian", "Kelley", role = "aut"), person("Daniel", "Qin", role = "aut"), person("Osaulenko", "Viacheslav", role = "aut"), person("Judit", "Szente", role = "aut"), person("Peter", "Erdi", role = "aut"))
Description: Statistical tests and test statistics to identify events in a dataset that are dragon kings (DKs). The statistical methods in this package were reviewed in Wheatley & Sornette (2015) <doi:10.2139/ssrn.2645709>.
License: GPL-3
Encoding: UTF-8
URL: https://github.com/rrrlw/dragonking
BugReports: https://github.com/rrrlw/dragonking/issues
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-06-17 23:06:56 UTC; rrrlw
Author: Raoul Wadhwa [aut, cre], Christian Kelley [aut], Daniel Qin [aut], Osaulenko Viacheslav [aut], Judit Szente [aut], Peter Erdi [aut]
Maintainer: Raoul Wadhwa <raoulwadhwa@gmail.com>
Repository: CRAN
Date/Publication: 2018-06-18 16:32:59 UTC

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New package BE with initial version 0.1.0
Package: BE
Version: 0.1.0
Title: Bioequivalence Study Data Analysis
Description: Analyze bioequivalence study data in a industrial strength. Sample size could be determined for various crossover designs, such as 2x2 design, 2x4 design, 4x4 design, Balaam design, Two-sequence dual design, and William design. Reference: Chow SC, Liu JP. Design and Analysis of Bioavailability and Bioequivalence Studies. 3rd ed. (2009, ISBN:978-1-58488-668-6).
Depends: R (>= 3.0.0)
Author: Kyun-Seop Bae [aut]
Maintainer: Kyun-Seop Bae <k@acr.kr>
Copyright: 2018, Kyun-Seop Bae
License: GPL-3
NeedsCompilation: no
LazyLoad: yes
Repository: CRAN
URL: https://cran.r-project.org/package=BE
Packaged: 2018-06-17 18:42:06 UTC; Kyun-SeopBae
Date/Publication: 2018-06-18 16:37:54 UTC

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Sun, 17 Jun 2018

New package spatialwarnings with initial version 1.2
Package: spatialwarnings
Type: Package
Title: Spatial Early Warning Signals of Ecosystem Degradation
Version: 1.2
Author: Alain Danet, Alexandre Genin, Vishwesha Guttal, Sonia Kefi, Sabiha Majumder, Sumithra Sankaran, Florian Schneider
License: MIT + file LICENSE
Maintainer: Alexandre Genin <alexandre.genin@univ-montp2.fr>
Description: Tools to compute and assess significance of early-warnings signals (EWS) of ecosystem degradation on raster data sets. EWS are metrics derived from the observed spatial structure of an ecosystem -- e.g. spatial autocorrelation -- that increase before an ecosystem undergoes a non-linear transition (Kefi et al. (2014) <doi:10.1371/journal.pone.0092097>).
URL: https://github.com/spatial-ews/spatialwarnings
Depends: R (>= 3.3.0)
Imports: Rcpp, ggplot2 (>= 1.0.0), plyr, VGAM, reshape2, tidyr, stats, utils, parallel
Suggests: moments, poweRlaw, testthat, knitr, covr
LinkingTo: Rcpp, RcppArmadillo
LazyData: true
RoxygenNote: 6.0.1
NeedsCompilation: yes
Packaged: 2018-06-17 22:13:58 UTC; alex
Repository: CRAN
Date/Publication: 2018-06-17 22:37:54 UTC

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New package fuser with initial version 1.0.1
Package: fuser
Title: Fused Lasso for High-Dimensional Regression over Groups
Version: 1.0.1
Authors@R: c( person("Frank", "Dondelinger", email = "fdondelinger.work@gmail.com", role = c("aut", "cre")), person("Olivier", "Wilkinson", role = c("aut")) )
Description: Enables high-dimensional penalized regression across heterogeneous subgroups. Fusion penalties are used to share information about the linear parameters across subgroups. The underlying model is described in detail in Dondelinger and Mukherjee (2017) <arXiv:1611.00953>.
Depends: R (>= 3.2.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
Suggests: testthat, ggplot2, knitr, rmarkdown
Imports: Matrix, irlba, Rcpp, glmnet, RSpectra
LinkingTo: Rcpp, RcppEigen
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2018-06-17 19:15:57 UTC; levendis
Author: Frank Dondelinger [aut, cre], Olivier Wilkinson [aut]
Maintainer: Frank Dondelinger <fdondelinger.work@gmail.com>
Repository: CRAN
Date/Publication: 2018-06-17 20:22:54 UTC

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New package multistateutils with initial version 1.1.0
Package: multistateutils
Type: Package
Title: Utility Functions for Parametric Multi-State Models
Version: 1.1.0
Date: 2018-06-05
Author: Stuart Lacy
Maintainer: Stuart Lacy <stuart.lacy@gmail.com>
Description: Provides functions for working with multi-state modelling, such as efficient simulation routines for estimating transition probabilities and length of stay. It is designed as an extension to multi-state modelling capabilities provided with the 'flexsurv' package (see Jackson (2016) <doi:10.18637/jss.v070.i08>).
License: GPL (>= 2)
Imports: Rcpp (>= 0.12.10), data.table, dplyr, magrittr, networkD3, survival, tidyr
Suggests: flexsurv, mstate, microbenchmark, rmarkdown, knitr
URL: https://github.com/stulacy/multistateutils
LinkingTo: Rcpp
RoxygenNote: 6.0.1
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2018-06-15 23:44:15 UTC; stuart
Repository: CRAN
Date/Publication: 2018-06-17 14:12:54 UTC

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New package exuber with initial version 0.1.0
Package: exuber
Type: Package
Title: Econometric Analysis of Explosive Time Series
Version: 0.1.0
Authors@R: c( person("Kostas", "Vasilopoulos", , email = "k.vasilopoulo@gmail.com", c("cre", "aut")), person("Eftymios", "Pavlidis", email = "e.pavlidis@lancaster.ac.uk", role = "aut"), person("Simon", "Spavound", email = "simon.spavound@googlemail.com", role = "aut") )
Description: Testing for and dating periods of explosive dynamics (exuberance) in time series using recursive unit root tests as proposed by Phillips, P. C., Shi, S. and Yu, J. (2015a) <doi:10.1111/iere.12132>. Simulate a variety of periodically-collapsing bubble models. The estimation and simulation utilizes the matrix inversion lemma from the recursive least squares algorithm, which results in a significant speed improvement.
License: GPL-3
URL: https://github.com/kvasilopoulos/exuber
BugReports: https://github.com/kvasilopoulos/exuber/issues
Imports: doParallel, parallel, foreach, Rcpp, rlang, dplyr, ggplot2, purrr
Suggests: knitr, rmarkdown, covr, testthat, withr, gridExtra
LinkingTo: Rcpp
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
NeedsCompilation: yes
Packaged: 2018-06-15 15:43:09 UTC; T460p
Author: Kostas Vasilopoulos [cre, aut], Eftymios Pavlidis [aut], Simon Spavound [aut]
Maintainer: Kostas Vasilopoulos <k.vasilopoulo@gmail.com>
Repository: CRAN
Date/Publication: 2018-06-17 14:07:54 UTC

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New package dragulaR with initial version 0.3.1
Package: dragulaR
Type: Package
Title: Drag and Drop Elements in 'Shiny' using 'Dragula Javascript Library'
Version: 0.3.1
Authors@R: c(person("Nicolas", "Bevacqua", role = c("aut", "cph"), comment = "dragula library in htmlwidgets/lib, https://github.com/bevacqua/dragula"), person("Zygmunt", "Zawadzki", role = c("aut", "cre"), comment = "R interface", email = "zygmunt@zstat.pl"))
Maintainer: Zygmunt Zawadzki <zygmunt@zstat.pl>
Description: Move elements between containers in 'Shiny' without explicitly using 'JavaScript'. It can be used to build custom inputs or to change the positions of user interface elements like plots or tables.
License: GPL-2
LazyData: TRUE
Depends: htmlwidgets, shiny
Imports: shinyjs
RoxygenNote: 6.0.1
Suggests: covr, testthat
BugReports: https://github.com/zzawadz/dragulaR/issues
URL: https://dragular.zstat.pl/
NeedsCompilation: no
Packaged: 2018-06-15 18:16:18 UTC; zzawadz
Author: Nicolas Bevacqua [aut, cph] (dragula library in htmlwidgets/lib, https://github.com/bevacqua/dragula), Zygmunt Zawadzki [aut, cre] (R interface)
Repository: CRAN
Date/Publication: 2018-06-17 14:08:01 UTC

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Sat, 16 Jun 2018

New package RxODE with initial version 0.7.2-4
Package: RxODE
Version: 0.7.2-4
Title: Facilities for Simulating from ODE-Based Models
Authors@R: c( person("Matthew L.","Fidler", role = "aut", email = "matthew.fidler@gmail.com"), person("Melissa", "Hallow", role = "aut", email = "hallowkm@uga.edu"), person("Wenping", "Wang", role = c("aut", "cre"), email = "wwang8198@gmail.com"), person("Zufar", "Mulyukov", role="ctb", email="zufar.mulyukov@novartis.com"), person("Justin", "Wilkins", role = "ctb", email = "justin.wilkins@occams.com"), person("Simon", "Frost", role="ctb"), person("Heng", "Li", role="ctb"), person("Yu", "Feng", role="ctb"), person("Alan", "Hindmarsh",role="ctb"), person("Linda", "Petzold", role="ctb"), person("Ernst", "Hairer", role="ctb"), person("Gerhard", "Wanner", role="ctb"), person("J", "Colinge", role="ctb"), person("Hadley", "Wickham", role="ctb"), person("G", "Grothendieck", role="ctb"), person("Robert", "Gentleman",role="ctb"), person("Ross", "Ihaka",role="ctb"), person("R core team", role="cph"), person("odepack authors", role="cph") )
Maintainer: Wenping Wang <wwang8198@gmail.com>
Depends: R (>= 3.3.0)
Suggests: knitr, nlme, shiny, tcltk, testthat, devtools, covr, rmarkdown, SnakeCharmR, rSymPy, dplyr, tidyr, tibble, curl, ggplot2, gridExtra, microbenchmark, scales, stringi, htmltools
Imports: utils, methods, digest, rex, dparser (>= 0.1.8), brew, memoise, magrittr, Rcpp (>= 0.12.3), inline, Matrix, R.utils, PreciseSums (>= 0.3), mvnfast, cli, crayon
Description: Facilities for running simulations from ordinary differential equation (ODE) models, such as pharmacometrics and other compartmental models. A compilation manager translates the ODE model into C, compiles it, and dynamically loads the object code into R for improved computational efficiency. An event table object facilitates the specification of complex dosing regimens (optional) and sampling schedules. NB: The use of this package requires both C and Fortran compilers, for details on their use with R please see Section 6.3, Appendix A, and Appendix D in the "R Administration and Installation" manual. Also the code is mostly released under GPL. The VODE and LSODA are in the public domain. The information is available in the inst/COPYRIGHTS.
BugReports: https://github.com/nlmixrdevelopment/RxODE/issues
NeedsCompilation: yes
VignetteBuilder: knitr
License: GPL (>= 2)
URL: https://www.r-project.org, https://github.com/nlmixrdevelopment/RxODE
RoxygenNote: 6.0.1
LinkingTo: dparser(>= 0.1.8), Rcpp (>= 0.12.3), RcppArmadillo(>= 0.5.600.2.0), PreciseSums (>= 0.3)
Packaged: 2018-06-16 17:01:38 UTC; WANGWEZ
Author: Matthew L. Fidler [aut], Melissa Hallow [aut], Wenping Wang [aut, cre], Zufar Mulyukov [ctb], Justin Wilkins [ctb], Simon Frost [ctb], Heng Li [ctb], Yu Feng [ctb], Alan Hindmarsh [ctb], Linda Petzold [ctb], Ernst Hairer [ctb], Gerhard Wanner [ctb], J Colinge [ctb], Hadley Wickham [ctb], G Grothendieck [ctb], Robert Gentleman [ctb], Ross Ihaka [ctb], R core team [cph], odepack authors [cph]
Repository: CRAN
Date/Publication: 2018-06-16 19:32:24 UTC

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New package graphicalVAR with initial version 0.2.2
Package: graphicalVAR
Type: Package
Title: Graphical VAR for Experience Sampling Data
Version: 0.2.2
Author: Sacha Epskamp
Maintainer: Sacha Epskamp <mail@sachaepskamp.com>
Description: Estimates within and between time point interactions in experience sampling data, using the Graphical vector autoregression model in combination with regularization. See also Epskamp, Waldorp, Mottus & Borsboom (2018) <doi:10.1080/00273171.2018.1454823>.
License: GPL (>= 2)
LinkingTo: Rcpp, RcppArmadillo
Imports: Rcpp (>= 0.11.3), Matrix, glasso, glmnet, mvtnorm, qgraph (>= 1.3.1), dplyr, methods, igraph
Depends: R (>= 3.1.0)
NeedsCompilation: yes
Packaged: 2018-06-16 13:50:55 UTC; sachaepskamp
Repository: CRAN
Date/Publication: 2018-06-16 19:28:45 UTC

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Fri, 15 Jun 2018

New package SLIDE with initial version 1.0.0
Package: SLIDE
Title: Single Cell Linkage by Distance Estimation is SLIDE
Version: 1.0.0
Authors@R: c(person("Gourab", "Mukherjee", email = "gourab@usc.edu", role = c("aut")), person("Arjun", "Panda", email = "arjunpanda@gwu.edu", role = c("aut","cre")), person("Ann", "Arvin", email = "aarvin@stanford.edu", role = c("aut")), person("Adrish", "Sen", email = "adrishs@stanford.edu", role = c("aut")), person("Nandini", "Sen", email = "nandinis@stanford.edu", role = c("aut")))
Description: This statistical method uses the nearest neighbor algorithm to estimate absolute distances between single cells based on a chosen constellation of surface proteins, with these distances being a measure of the similarity between the two cells being compared. Based on Sen, N., Mukherjee, G., and Arvin, A.M. (2015) <DOI:10.1016/j.ymeth.2015.07.008>.
Depends: R (>= 3.4.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-06-15 14:57:27 UTC; arjun
Author: Gourab Mukherjee [aut], Arjun Panda [aut, cre], Ann Arvin [aut], Adrish Sen [aut], Nandini Sen [aut]
Maintainer: Arjun Panda <arjunpanda@gwu.edu>
Repository: CRAN
Date/Publication: 2018-06-15 15:50:12 UTC

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New package simIReff with initial version 1.0
Package: simIReff
Type: Package
Title: Stochastic Simulation for Information Retrieval Evaluation: Effectiveness Scores
Version: 1.0
Authors@R: c(person("Julián", "Urbano", email = "urbano.julian@gmail.com", role = c("aut", "cre")), person("Thomas", "Nagler", email = "thomas.nagler@tum.de", role = c("ctb")))
Description: Provides tools for the stochastic simulation of effectiveness scores to mitigate data-related limitations of Information Retrieval evaluation research, as described in Urbano and Nagler (2018) <doi:10.1145/3209978.3210043>. These tools include: fitting, selection and plotting distributions to model system effectiveness, transformation towards a prespecified expected value, proxy to fitting of copula models based on these distributions, and simulation of new evaluation data from these distributions and copula models.
BugReports: https://github.com/julian-urbano/simIReff/issues
URL: https://github.com/julian-urbano/simIReff/
Depends: R (>= 3.4)
Imports: stats, graphics, MASS, rvinecopulib (>= 0.2.8.1.0), truncnorm, bde, ks, np, extraDistr
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-06-15 14:53:35 UTC; jurbano
Author: Julián Urbano [aut, cre], Thomas Nagler [ctb]
Maintainer: Julián Urbano <urbano.julian@gmail.com>
Repository: CRAN
Date/Publication: 2018-06-15 15:26:32 UTC

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New package QTL.gCIMapping.GUI with initial version 1.0
Package: QTL.gCIMapping.GUI
Type: Package
Title: QTL Genome-Wide Composite Interval Mapping with Graphical User Interface
Version: 1.0
Date: 2018-6-12
Author: Zhang Ya-Wen, Wen Yang-Jun, Wang Shi-Bo, and Zhang Yuan-Ming
Maintainer: Yuanming Zhang<soyzhang@mail.hzau.edu.cn>
Description: Conduct multiple quantitative trait loci (QTL) mapping under the framework of random-QTL-effect mixed linear model. First, each position on the genome is detected in order to construct a negative logarithm P-value curve against genome position. Then, all the peaks on each effect (additive or dominant) curve are viewed as potential QTL, all the effects of the potential QTL are included in a multi-QTL model, their effects are estimated by empirical Bayes in doubled haploid or by adaptive lasso in F2, and true QTL are identified by likelihood radio test. Wang S-B, Wen Y-J, Ren W-L, Ni Y-L, Zhang J, Feng J-Y, Zhang Y-M (2016) <doi:10.1038/srep29951>.
Encoding: UTF-8
Depends: shiny,MASS,qtl,doParallel,foreach
License: GPL (>= 2)
Imports: Rcpp (>= 0.12.17),methods,stringr,openxlsx,data.table,parcor
LinkingTo: Rcpp
NeedsCompilation: yes
Packaged: 2018-06-13 03:46:03 UTC; 亚雯
Repository: CRAN
Date/Publication: 2018-06-15 15:26:36 UTC

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New package PPQplan with initial version 0.1.0
Package: PPQplan
Type: Package
Title: Process Performance Qualification (PPQ) Plans in Chemistry, Manufacturing and Controls (CMC) Statistical Analysis
Version: 0.1.0
Author: Yalin Zhu
Maintainer: Yalin Zhu <yalin.zhu@merck.com>
Imports: tolerance, ggplot2, plotly
Description: Assessment for statistically-based PPQ sampling plan, including calculating the passing probability, optimizing the baseline and high performance cutoff points, visualizing the PPQ plan and power dynamically. The analytical idea is based on the simulation methods from the textbook "Burdick, R. K., LeBlond, D. J., Pfahler, L. B., Quiroz, J., Sidor, L., Vukovinsky, K., & Zhang, L. (2017). Statistical Methods for CMC Applications. In Statistical Applications for Chemistry, Manufacturing and Controls (CMC) in the Pharmaceutical Industry (pp. 227-250). Springer, Cham."
License: GPL (>= 2)
Copyright: Copyright 2018, Center for Mathematical Sciences, Merck & Co., Inc.
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-06-15 13:50:03 UTC; zhuyal
Repository: CRAN
Date/Publication: 2018-06-15 15:26:39 UTC

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New package Orcs with initial version 1.0.0
Package: Orcs
Type: Package
Title: Omnidirectional R Code Snippets
Version: 1.0.0
Date: 2018-06-15
Authors@R: c( person("Florian", "Detsch", role = c("cre", "aut"), email = "fdetsch@web.de"), person("Tim", "Appelhans", role = "ctb"), person("Baptiste", "Auguie", role = "ctb"), person("OpenStreetMap contributors", role = "cph"))
Maintainer: Florian Detsch <fdetsch@web.de>
Description: I tend to repeat the same code chunks over and over again. At first, this was fine for me and I paid little attention to such redundancies. A little later, when I got tired of manually replacing Linux filepaths with the referring Windows versions, and vice versa, I started to stuff some very frequently used work-steps into functions and, even later, into a proper R package. And that's what this package is - a hodgepodge of various R functions meant to simplify (my) everyday-life coding work without, at the same time, being devoted to a particular scope of application.
License: MIT + file LICENSE
URL: https://github.com/fdetsch/Orcs
BugReports: https://github.com/fdetsch/Orcs/issues
LazyData: TRUE
Depends: R (>= 2.10), methods, raster
Imports: bookdown, devtools, grDevices, grid, knitr, lattice, latticeExtra, plotrix, Rcpp (>= 0.11.3), rgdal, sf, sp, stats
LinkingTo: Rcpp
RoxygenNote: 6.0.1
SystemRequirements: GNU make, 7zip, unix2dos
Suggests: testthat, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2018-06-15 12:38:19 UTC; FlorianD
Author: Florian Detsch [cre, aut], Tim Appelhans [ctb], Baptiste Auguie [ctb], OpenStreetMap contributors [cph]
Repository: CRAN
Date/Publication: 2018-06-15 15:14:35 UTC

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New package MVar with initial version 2.0.2
Package: MVar
Type: Package
Title: Multivariate Analysis
Version: 2.0.2
Date: 2018-06-15
Author: Paulo Cesar Ossani <ossanipc@hotmail.com> Marcelo Angelo Cirillo <macufla@des.ufla.br>
Maintainer: Paulo Cesar Ossani <ossanipc@hotmail.com>
Suggests: MASS
Description: Package for multivariate analysis, having functions that perform simple correspondence analysis (CA) and multiple correspondence analysis (MCA), principal components analysis (PCA), canonical correlation analysis (CCA), factorial analysis (FA), multidimensional scaling (MDS), hierarchical and non-hierarchical cluster analysis, linear regression, multiple factor analysis (MFA) for quantitative, qualitative, frequency (MFACT) and mixed data, projection pursuit (PP), grant tour method and other useful functions for the multivariate analysis.
License: GPL (>= 2)
NeedsCompilation: yes
Packaged: 2018-06-15 11:50:16 UTC; Pc
Repository: CRAN
Date/Publication: 2018-06-15 15:14:39 UTC

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New package CSESA with initial version 1.0.4
Package: CSESA
Type: Package
Title: CRISPR-Based Salmonella Enterica Serotype Analyzer
Version: 1.0.4
Authors@R: c( person("Xia", "Zhang", role = c("aut", "cre"), email = "zhangxia9403@gmail.com"), person("Lang", "Yang", role = "aut", email = "ylang1992@126.com"))
Description: Salmonella enterica is a major cause of bacterial food-borne disease worldwide. Serotype identification is the most commonly used typing method to characterize Salmonella isolates. However, experimental serotyping needs great cost on manpower and resources. Recently, we found that the newly incorporated spacer in the clustered regularly interspaced short palindromic repeat (CRISPR) could serve as an effective marker for typing of Salmonella. It was further revealed by Li et. al (2014) <doi:10.1128/JCM.00696-14> that recognized types based on the combination of two newly incorporated spacer in both CRISPR loci showed high accordance with serotypes. Here, we developed an R package 'CSESA' to predict the serotype based on this finding. Considering it’s time saving and of high accuracy, we recommend to predict the serotypes of unknown Salmonella isolates using 'CSESA' before doing the traditional serotyping.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
Suggests: testthat
Imports: Biostrings
NeedsCompilation: no
Packaged: 2018-06-15 02:59:07 UTC; XiaXia
Author: Xia Zhang [aut, cre], Lang Yang [aut]
Maintainer: Xia Zhang <zhangxia9403@gmail.com>
Repository: CRAN
Date/Publication: 2018-06-15 15:26:43 UTC

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New package autoshiny with initial version 0.0.1
Package: autoshiny
Title: Automatic Transformation of an 'R' Function into a 'shiny' App
Version: 0.0.1
Authors@R: person("Aleksander", "Rutkowski", email = "alek.rutkowski@gmail.com", role = c("aut", "cre"))
Description: Static code compilation of a 'shiny' app given an R function (into 'ui.R' and 'server.R' files or into a 'shiny' app object). See examples at <https://github.com/alekrutkowski/autoshiny>.
URL: https://github.com/alekrutkowski/autoshiny
Depends: R (>= 3.4.0)
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
Imports: shiny, utils
Suggests: roxygen2, magrittr, webshot
NeedsCompilation: no
Packaged: 2018-06-12 15:08:52 UTC; AsiaiAlek
Author: Aleksander Rutkowski [aut, cre]
Maintainer: Aleksander Rutkowski <alek.rutkowski@gmail.com>
Repository: CRAN
Date/Publication: 2018-06-15 15:02:10 UTC

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New package alphastable with initial version 0.1.0
Package: alphastable
Title: Inference for Stable Distribution
Version: 0.1.0
Author: Mahdi Teimouri
Maintainer: Mahdi Teimouri <teimouri@aut.ac.ir>
Description: Developed to perform the tasks given by the following. 1-computing the probability density function and distribution function of a univariate stable distribution; 2- generating realization from univariate stable, truncated stable, multivariate elliptically contoured stable, and bivariate strictly stable distributions; 3- estimating the parameters of univariate symmetric stable, skew stable, Cauchy, multivariate elliptically contoured stable, and multivariate strictly stable distributions; 4- estimating the parameters of the mixture of symmetric stable and mixture of Cauchy distributions.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Depends: R(>= 3.4.0)
Imports: base, methods, mvtnorm, nlme, nnls, stabledist, stats
Suggests: Matrix, fBasics, FMStable, RUnit, Rmpfr, sfsmisc
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-06-15 12:41:53 UTC; NikPardaz
Repository: CRAN
Date/Publication: 2018-06-15 15:14:31 UTC

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New package populationPDXdesign with initial version 1.0.2
Package: populationPDXdesign
Type: Package
Title: Designing Population PDX Studies
Version: 1.0.2
Date: 2018-06-12
Authors@R: c(person("Maria Luisa", "Guerriero", email = "maria.guerriero@astrazeneca.com", role = c("aut", "cre")), person("Natasha", "Karp", email = "natasha.karp@astrazeneca.com", role = c("aut")))
Description: Run simulations to assess the impact of various designs features and the underlying biological behaviour on the outcome of a Patient Derived Xenograft (PDX) population study. This project can either be deployed to a server as a 'shiny' app or installed locally as a package and run the app using the command 'populationPDXdesignApp()'.
License: GPL (>= 3)
Depends: R (>= 3.0.0)
Imports: devtools, ggplot2, plyr, roxygen2, shiny, shinycssloaders
Suggests: testthat
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-06-12 16:50:50 UTC; kpkr710
Author: Maria Luisa Guerriero [aut, cre], Natasha Karp [aut]
Maintainer: Maria Luisa Guerriero <maria.guerriero@astrazeneca.com>
Repository: CRAN
Date/Publication: 2018-06-15 14:52:30 UTC

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New package opensensmapr with initial version 0.4.1
Package: opensensmapr
Type: Package
Title: Client for the Data API of openSenseMap.org
Version: 0.4.1
URL: http://github.com/noerw/opensensmapR
BugReports: http://github.com/noerw/opensensmapR/issues
Imports: dplyr, httr, digest, magrittr
Suggests: maps, maptools, readr, tibble, rgeos, sf, knitr, rmarkdown, lubridate, units, jsonlite, ggplot2, zoo, lintr, testthat, covr
Authors@R: c(person("Norwin", "Roosen", role = c("aut", "cre"), email = "hello@nroo.de"), person("Daniel", "Nuest", role = c("ctb"), email = "daniel.nuest@uni-muenster.de", comment = c(ORCID = "0000-0003-2392-6140")))
Description: Download environmental measurements and sensor station metadata from the API of open data sensor web platform <https://opensensemap.org> for analysis in R. This platform provides real time data of more than 1500 low-cost sensor stations for PM10, PM2.5, temperature, humidity, UV-A intensity and more phenomena. The package aims to be compatible with 'sf' and the 'Tidyverse', and provides several helper functions for data exploration and transformation.
License: GPL (>= 2) | file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-06-11 21:07:07 UTC; kreis
Author: Norwin Roosen [aut, cre], Daniel Nuest [ctb] (<https://orcid.org/0000-0003-2392-6140>)
Maintainer: Norwin Roosen <hello@nroo.de>
Repository: CRAN
Date/Publication: 2018-06-15 14:38:22 UTC

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New package RcppEigenAD with initial version 1.0.0
Package: RcppEigenAD
Type: Package
Title: Compiles 'C++' Code using 'Rcpp', 'Eigen' and 'CppAD' to Produce First and Second Order Partial Derivatives
Version: 1.0.0
Date: 2018-06-14
Author: Damon Berridge <d.m.berridge@swansea.ac.uk> [ctb] Robert Crouchley <r.crouchley@lancaster.ac.uk> [ctb] Daniel Grose <dan.grose@lancaster.ac.uk> [aut,cre,ctb]
Maintainer: Daniel Grose <dan.grose@lancaster.ac.uk>
Description: Compiles 'C++' code using 'Rcpp', 'Eigen' and 'CppAD' to produce first and second order partial derivatives. Also provides an implementation of Faa' di Bruno's formula to combine the partial derivatives of composed functions, (see Hardy, M (2006) <arXiv:math/0601149v1>).
License: GPL (>= 2)
Imports: Rcpp (>= 0.12.12), methods, RcppEigen, functional, memoise, readr, Rdpack
LinkingTo: Rcpp, RcppEigen, BH
SystemRequirements: C++11
RdMacros: Rdpack
NeedsCompilation: yes
Packaged: 2018-06-15 11:36:31 UTC; grosed
Repository: CRAN
Date/Publication: 2018-06-15 13:10:04 UTC

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New package wevid with initial version 0.4.2
Package: wevid
Type: Package
Title: Quantifying Performance of a Binary Classifier Through Weight of Evidence
Version: 0.4.2
Date: 2018-06-15
Authors@R: c(person("Paul", "McKeigue", email="paul.mckeigue@ed.ac.uk", role=c("aut")), person("Marco", "Colombo", email="m.colombo@ed.ac.uk", role=c("ctb", "cre")))
Description: The distributions of the weight of evidence (log Bayes factor) favouring case over noncase status in a test dataset (or test folds generated by cross-validation) can be used to quantify the performance of a diagnostic test (McKeigue P., Quantifying performance of a diagnostic test as the expected information for discrimination: relation to the C-statistic. Statistical Methods for Medical Research 2018, in press). The package can be used with any test dataset on which you have observed case-control status and have computed prior and posterior probabilities of case status using a model learned on a training dataset. To quantify how the predictor will behave as a risk stratifier, the quantiles of the distributions of weight of evidence in cases and controls can be calculated and plotted.
Depends: R (>= 2.10)
License: GPL-3
URL: http://www.homepages.ed.ac.uk/pmckeigu/preprints/classify/wevidtutorial.html
LazyLoad: yes
Imports: ggplot2, pROC, reshape2, zoo
ByteCompile: TRUE
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-06-15 10:37:58 UTC; marco
Author: Paul McKeigue [aut], Marco Colombo [ctb, cre]
Maintainer: Marco Colombo <m.colombo@ed.ac.uk>
Repository: CRAN
Date/Publication: 2018-06-15 11:17:55 UTC

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New package txtq with initial version 0.0.4
Package: txtq
Title: A Small Message Queue for Parallel Processes
Description: This queue is a data structure that lets parallel processes send and receive messages, and it can help coordinate the work of complicated parallel tasks. Processes can push new messages to the queue, pop old messages, and obtain a log of all the messages ever pushed. File locking preserves the integrity of the data even when multiple processes access the queue simultaneously.
Version: 0.0.4
License: MIT + file LICENSE
URL: https://github.com/wlandau/txtq
BugReports: https://github.com/wlandau/txtq/issues
Authors@R: c( person( family = "Landau", given = c("William", "Michael"), email = "will.landau@gmail.com", role = c("aut", "cre") ), person( family = "Eli Lilly and Company", role = "cph" ))
Imports: base64url, filelock, fs, R6
Suggests: parallel, testthat
Encoding: UTF-8
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-06-14 21:13:45 UTC; landau
Author: William Michael Landau [aut, cre], Eli Lilly and Company [cph]
Maintainer: William Michael Landau <will.landau@gmail.com>
Repository: CRAN
Date/Publication: 2018-06-15 11:12:55 UTC

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New package sssc with initial version 1.0.0
Package: sssc
Title: Same Species Sample Contamination Detection
Version: 1.0.0
Authors@R: c(person("Tao", "Jiang", role = c("aut", "cre"), email = "tjiang8@ncsu.edu"))
Description: Imports Variant Calling Format file into R. It can detect whether a sample contains contaminant from the same species. In the first stage of the approach, a change-point detection method is used to identify copy number variations for filtering. Next, features are extracted from the data for a support vector machine model. For log-likelihood calculation, the deviation parameter is estimated by maximum likelihood method. Using a radial basis function kernel support vector machine, the contamination of a sample can be detected.
Depends: R (>= 3.4.0)
Imports: changepoint, e1071, ggplot2, stats, VGAM
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-06-15 04:21:27 UTC; tjiang8
Author: Tao Jiang [aut, cre]
Maintainer: Tao Jiang <tjiang8@ncsu.edu>
Repository: CRAN
Date/Publication: 2018-06-15 11:22:54 UTC

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New package MDFS with initial version 1.0.0
Package: MDFS
Title: MultiDimensional Feature Selection
Version: 1.0.0
Date: 2018-06-15
Authors@R: c( person("Radosław", "Piliszek", email = "r.piliszek@uwb.edu.pl", role = c("aut", "cre")), person("Krzysztof", "Mnich", email = "k.mnich@uwb.edu.pl", role = "aut"), person("Paweł", "Tabaszewski", email = "tabaszewski.pawel@gmail.com", role = "aut"), person("Szymon", "Migacz", email = "szmigacz@gmail.com", role = "aut"), person("Andrzej", "Sułecki", email = "asulecki@gmail.com", role = "aut"), person(c("Witold", "Remigiusz"), "Rudnicki", email = "w.rudnicki@icm.edu.pl", role = "aut"))
URL: https://featureselector.uco.uwb.edu.pl/software/mdfs/
Description: Functions for MultiDimensional Feature Selection (MDFS): calculating multidimensional information gains, scoring variables, finding important variables, plotting selection results. This package includes an optional CUDA implementation that speeds up information gain calculation using NVIDIA GPGPUs.
Depends: R (>= 3.4.0)
License: GPL-3
SystemRequirements: C++11
NeedsCompilation: yes
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
Packaged: 2018-06-15 06:53:04 UTC; r.piliszek
Author: Radosław Piliszek [aut, cre], Krzysztof Mnich [aut], Paweł Tabaszewski [aut], Szymon Migacz [aut], Andrzej Sułecki [aut], Witold Remigiusz Rudnicki [aut]
Maintainer: Radosław Piliszek <r.piliszek@uwb.edu.pl>
Repository: CRAN
Date/Publication: 2018-06-15 11:18:04 UTC

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New package mcen with initial version 1.0
Package: mcen
Type: Package
Title: Multivariate Cluster Elastic Net
Version: 1.0
Date: 2018-06-14
Author: Ben Sherwood [aut, cre], Brad Price [aut]
Depends: R (>= 3.0.0), glmnet, flexclust, Matrix, parallel, faraway, methods, stats
Maintainer: Ben Sherwood <ben.sherwood@ku.edu>
Description: Fits the Multivariate Cluster Elastic Net (MCEN) presented in Price & Sherwood (2018) <arXiv:1707.03530>. The MCEN model simultaneously estimates regression coefficients and a clustering of the responses for a multivariate response model. Currently accommodates the Gaussian and binomial likelihood.
ByteCompile: TRUE
License: MIT + file LICENSE
RoxygenNote: 6.0.1
NeedsCompilation: yes
Packaged: 2018-06-14 19:12:03 UTC; bsherwoo
Repository: CRAN
Date/Publication: 2018-06-15 11:12:59 UTC

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New package IntervalSurgeon with initial version 1.0
Package: IntervalSurgeon
Type: Package
Title: Operating on Integer-Bounded Intervals
Version: 1.0
Date: 2018-06-04
Author: Daniel Greene
Maintainer: Daniel Greene <dg333@cam.ac.uk>
Description: Functions for manipulating integer-bounded intervals including finding overlaps, piling and merging.
License: GPL (>= 2)
Imports: Rcpp (>= 0.12.4)
LinkingTo: Rcpp
Suggests: knitr
VignetteBuilder: knitr
RoxygenNote: 6.0.1
NeedsCompilation: yes
Packaged: 2018-06-07 06:08:28 UTC; dg
Repository: CRAN
Date/Publication: 2018-06-15 11:02:55 UTC

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New package bfw with initial version 0.0.1
Package: bfw
Version: 0.0.1
Date: 2018-06-15
Title: Bayesian Framework for Computational Modelling
Authors@R: person( "Øystein Olav","Skaar", email="bayesianfw@gmail.com", role=c("aut","cre"))
Maintainer: Øystein Olav Skaar <bayesianfw@gmail.com>
URL: https://github.com/oeysan/bfw/
BugReports: https://github.com/oeysan/bfw/issues/
Description: Derived from the work of Kruschke (2015, <ISBN:9780124058880>), the present package aim to provide a framework for conducting Bayesian analysis using Markov chain Monte Carlo (MCMC) sampling utilizing the Just Another Gibbs Sampler ('JAGS', Plummer, 2003, <http://mcmc-jags.sourceforge.net/>). The initial version include several modules for conducting Bayesian equivalents of chi-squared tests, analysis of variance (ANOVA), multiple (hierarchical) regression, softmax regression, and for fitting data (e.g., structural equation modeling).
SystemRequirements: JAGS >=4.3.0 <http://mcmc-jags.sourceforge.net/>, Java JDK >=1.4 <https://www.java.com/en/download/manual.jsp>
Depends: R (>= 3.4.0),
Imports: plyr (>= 1.8.4), methods (>= 3.5.0), MASS (>= 7.3-47), pbapply (>= 1.3-4), ReporteRs (>= 0.8.9), coda (>= 0.19-1), psych (>= 1.7.8), rJava (>= 0.9-9), runjags (>= 2.0.4-2), ggplot2 (>= 2.2.1), scales (>= 0.5.0), truncnorm (>= 1.0-8), robust (>= 0.4-18), lavaan (>= 0.6-1)
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-06-15 10:05:57 UTC; Melkor
Author: Øystein Olav Skaar [aut, cre]
Repository: CRAN
Date/Publication: 2018-06-15 11:17:58 UTC

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New package vip with initial version 0.1.0
Package: vip
Type: Package
Title: Variable Importance Plots
Version: 0.1.0
Authors@R: c( person("Brandon", "Greenwell", email = "greenwell.brandon@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-8120-0084")), person("Brad", "Boehmke", email = "bradleyboehmke@gmail.com", role = c("aut")) )
Description: A general framework for constructing variable importance plots from various types machine learning models in R. Aside from some standard model- based variable importance measures, this package also provides a novel approach based on partial dependence plots (PDPs) and individual conditional expectation (ICE) curves as described in Greenwell et al. (2018) <arXiv:1805.04755>.
License: GPL (>= 2)
URL: https://github.com/koalaverse/vip
BugReports: https://github.com/koalaverse/vip/issues
Encoding: UTF-8
LazyData: true
Imports: dplyr, ggplot2 (>= 0.9.0), gridExtra, magrittr, pdp, plyr, stats, tibble, tidyr, utils
Suggests: C50, caret, earth, gbm, h2o, knitr, party, partykit, ranger, rpart, randomForest, rmarkdown, xgboost, glmnet, testthat
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-06-14 01:39:04 UTC; bgreenwell
Author: Brandon Greenwell [aut, cre] (<https://orcid.org/0000-0002-8120-0084>), Brad Boehmke [aut]
Maintainer: Brandon Greenwell <greenwell.brandon@gmail.com>
Repository: CRAN
Date/Publication: 2018-06-15 09:10:57 UTC

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New package multicastR with initial version 1.0.0
Package: multicastR
Type: Package
Title: A Companion to the Multi-CAST Collection
Version: 1.0.0
Authors@R: person("Nils Norman", "Schiborr", email = "nils-norman.schiborr@uni-bamberg.de", role=c("aut", "cre"))
URL: https://lac.uni-koeln.de/en/multicast/
Description: Provides a basic interface for accessing annotation data from the Multi-CAST collection, a database of spoken natural language texts edited by Geoffrey Haig and Stefan Schnell. The collection draws from a diverse set of languages and has been annotated across multiple levels. Annotation data is downloaded on request from the servers of the Language Archive Cologne. See the Multi-CAST website <https://lac.uni-koeln.de/multicast/> for more information and a list of related publications.
License: CC BY 4.0
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.0.0), data.table (>= 1.10.0)
RoxygenNote: 6.0.1
Suggests: testthat
NeedsCompilation: no
Packaged: 2018-06-13 06:18:01 UTC; Nils
Author: Nils Norman Schiborr [aut, cre]
Maintainer: Nils Norman Schiborr <nils-norman.schiborr@uni-bamberg.de>
Repository: CRAN
Date/Publication: 2018-06-15 08:37:55 UTC

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New package BiocManager with initial version 1.30.1
Package: BiocManager
Title: Access the Bioconductor Project Package Repository
Description: A convenient tool to install and update Bioconductor packages.
Version: 1.30.1
Authors@R: c( person("Martin", "Morgan", email = "martin.morgan@roswellpark.org", role = "aut", comment = c(ORCID = "0000-0002-5874-8148")), person("Marcel", "Ramos", email = "marcel.ramos@roswellpark.org", role = c("ctb", "cre"), comment = c(ORCID = "0000-0002-3242-0582")))
Depends: R (>= 3.5.0)
Imports: utils
Suggests: BiocVersion, remotes, testthat, knitr
BugReports: https://github.com/Bioconductor/BiocManager/issues
VignetteBuilder: knitr
License: Artistic-2.0
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-06-13 15:50:53 UTC; mr148
Author: Martin Morgan [aut] (<https://orcid.org/0000-0002-5874-8148>), Marcel Ramos [ctb, cre] (<https://orcid.org/0000-0002-3242-0582>)
Maintainer: Marcel Ramos <marcel.ramos@roswellpark.org>
Repository: CRAN
Date/Publication: 2018-06-15 08:57:55 UTC

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Thu, 14 Jun 2018

New package lidR with initial version 1.5.1
Package: lidR
Type: Package
Title: Airborne LiDAR Data Manipulation and Visualization for Forestry Applications
Version: 1.5.1
Date: 2018-06-14
Authors@R: c( person("Jean-Romain", "Roussel", email = "jean-romain.roussel.1@ulaval.ca", role = c("aut", "cre", "cph")), person("David", "Auty", email = "", role = c("aut", "ctb"), comment = "Reviews the documentation"), person("Florian", "De Boissieu", email = "", role = ("ctb"), comment = "Fixed bugs and improved catalog features"), person("Andrew", "Sánchez Meador", email = "", role = ("ctb"), comment = "Implemented lassnags"))
Description: Airborne LiDAR (Light Detection and Ranging) interface for data manipulation and visualization. Read/write 'las' and 'laz' files, computation of metrics in area based approach, point filtering, artificial point reduction, classification from geographic data, normalization, individual tree segmentation and other manipulations.
URL: https://github.com/Jean-Romain/lidR
BugReports: https://github.com/Jean-Romain/lidR/issues
License: GPL-3
Depends: R (>= 3.1.0),methods
Imports: data.table, future, gdalUtils, geometry, grDevices, gstat, lazyeval, mapview, mapedit, memoise, RANN, raster, Rcpp, rgeos, rgl, rlas (>= 1.1.10), settings, sp, stats, tools, utils
Suggests: rgdal, testthat, EBImage, hexbin
LazyData: true
RoxygenNote: 6.0.1
LinkingTo: Rcpp
Encoding: UTF-8
ByteCompile: true
biocViews:
Collate: 'RcppExports.R' 'catalog_apply.r' 'catalog_clip.r' 'catalog_index.r' 'catalog_laxindex.r' 'catalog_makecluster.r' 'catalog_query.r' 'catalog_reshape.r' 'catalog_select.r' 'class-lasheader.r' 'class-las.r' 'class-lascatalog.r' 'class-lascluster.r' 'constant.R' 'deprecated.r' 'grid_canopy.r' 'grid_catalog.r' 'grid_density.r' 'grid_hexametrics.r' 'grid_metrics.r' 'grid_metrics3d.r' 'grid_terrain.r' 'grid_tincanopy.r' 'lasaggreagte.r' 'lascheck.r' 'lasclassify.r' 'lasclip.r' 'lascolor.r' 'lasfilter.r' 'lasfilterdecimate.r' 'lasfiltersurfacepoints.r' 'lasground.r' 'lasindentify.r' 'lasmetrics.r' 'lasnormalize.r' 'lasroi.r' 'lassmooth.r' 'lassnags.r' 'lastrees.r' 'lastrees_dalponte.r' 'lastrees_li.r' 'lastrees_li2.r' 'lastrees_silva.r' 'lastrees_watershed.r' 'lasupdateheader.r' 'lidRError.r' 'metrics.r' 'metrics_canopy_roughness.r' 'mutatebyref.r' 'options.r' 'plot.catalog.r' 'plot.las.r' 'plot.lashexametrics.r' 'plot.lasmetrics.r' 'plot.lasmetrics3d.r' 'plot3d.r' 'readLAS.r' 'subcircled.r' 'tree_detection.r' 'tree_metrics.r' 'utils_colors.r' 'utils_geometry.r' 'utils_interpolations.r' 'utils_misc.r' 'utils_projection.r' 'utils_spatial.r' 'utils_typecast.r' 'writeLAS.r' 'zzz.r'
NeedsCompilation: yes
Packaged: 2018-06-14 21:40:31 UTC; jr
Author: Jean-Romain Roussel [aut, cre, cph], David Auty [aut, ctb] (Reviews the documentation), Florian De Boissieu [ctb] (Fixed bugs and improved catalog features), Andrew Sánchez Meador [ctb] (Implemented lassnags)
Maintainer: Jean-Romain Roussel <jean-romain.roussel.1@ulaval.ca>
Repository: CRAN
Date/Publication: 2018-06-14 22:24:14 UTC

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New package MODISTools with initial version 1.0.0
Package: MODISTools
Title: Interface to the 'MODIS Land Products Subsets' Web Services
Version: 1.0.0
Authors@R: person("Hufkens","Koen", email="koen.hufkens@gmail.com", role=c("aut", "cre"), comment = c(ORCID = "0000-0002-5070-8109"))
Description: Programmatic interface to the 'MODIS Land Products Subsets' web services (<https://modis.ornl.gov/data/modis_webservice.html>). Allows for easy downloads of 'MODIS' time series directly to your R workspace or your computer.
URL: https://github.com/khufkens/MODISTools
BugReports: https://github.com/khufkens/MODISTools/issues
Depends: R (>= 3.4)
Imports: httr, utils, tidyr, jsonlite
License: AGPL-3
LazyData: true
ByteCompile: true
RoxygenNote: 6.0.1
Suggests: knitr, rmarkdown, covr, testthat
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-06-14 17:41:59 UTC; khufkens
Author: Hufkens Koen [aut, cre] (<https://orcid.org/0000-0002-5070-8109>)
Maintainer: Hufkens Koen <koen.hufkens@gmail.com>
Repository: CRAN
Date/Publication: 2018-06-14 21:58:16 UTC

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New package mixor with initial version 1.0.4
Package: mixor
Type: Package
Title: Mixed-Effects Ordinal Regression Analysis
Version: 1.0.4
Date: 2018-06-13
Author: Kellie J. Archer, Donald Hedeker, Rachel Nordgren, Robert D. Gibbons
Maintainer: Kellie J. Archer <archer.43@osu.edu>
Description: Provides the function 'mixor' for fitting a mixed-effects ordinal and binary response models and associated methods for printing, summarizing, extracting estimated coefficients and variance-covariance matrix, and estimating contrasts for the fitted models.
License: GPL (>= 2)
Depends: R (>= 2.10), survival
BuildResaveData: best
Biarch: yes
NeedsCompilation: yes
LazyLoad: true
Packaged: 2018-06-14 16:09:02 UTC; kjarcher
Repository: CRAN
Date/Publication: 2018-06-14 21:17:56 UTC

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New package eseis with initial version 0.4.0
Package: eseis
Type: Package
Title: Environmental Seismology Toolbox
Version: 0.4.0
Date: 2018-06-14
Authors@R: c( person("Michael", "Dietze", role = c("cre", "aut", "trl"), email = "mdietze@gfz-potsdam.de"), person("Christoph", "Burow", role = c("ctb")), person("Sophie", "Lagarde", role = c("ctb", "trl")))
Maintainer: Michael Dietze <mdietze@gfz-potsdam.de>
Description: Environmental seismology is a scientific field that studies the seismic signals, emitted by Earth surface processes. This package provides all relevant functions to read/write seismic data files, prepare, analyse and visualise seismic data, and generate reports of the processing history.
License: GPL-3
Depends: R (>= 3.4.0)
LinkingTo: Rcpp (>= 0.12.5)
Imports: sp, multitaper, raster, rgdal, caTools, signal, fftw, matrixStats, methods, IRISSeismic, XML, rmarkdown, Rcpp (>= 0.12.5)
Suggests: plot3D, rgl
SystemRequirements: gipptools dataselect
RoxygenNote: 6.0.1
NeedsCompilation: yes
Packaged: 2018-06-14 21:26:51 UTC; mdietze
Author: Michael Dietze [cre, aut, trl], Christoph Burow [ctb], Sophie Lagarde [ctb, trl]
Repository: CRAN
Date/Publication: 2018-06-14 23:39:08

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New package coxed with initial version 0.1.1
Package: coxed
Type: Package
Title: Duration-Based Quantities of Interest for the Cox Proportional Hazards Model
Version: 0.1.1
Depends: R (>= 2.13.0), rms, survival, mgcv
Authors@R: c( person("Kropko,", "Jonathan", email = "jkropko@virginia.edu", role = c("aut", "cre")), person("Harden,", "Jeffrey J.", email = "jeff.harden@nd.edu", role = c("aut")))
Description: Functions for generating, simulating, and visualizing expected durations and marginal changes in duration from the Cox proportional hazards model.
License: GPL-2
Encoding: UTF-8
URL: https://github.com/jkropko/coxed
LazyData: true
Imports: PermAlgo, dplyr, tidyr, ggplot2, gridExtra, utils
RoxygenNote: 6.0.1
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-06-14 18:38:31 UTC; jk8sd
Author: Kropko, Jonathan [aut, cre], Harden, Jeffrey J. [aut]
Maintainer: "Kropko, Jonathan" <jkropko@virginia.edu>
Repository: CRAN
Date/Publication: 2018-06-14 21:39:48 UTC

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New package jeek with initial version 1.0.0
Package: jeek
Type: Package
Date: 2018-06-15
Title: A Fast and Scalable Joint Estimator for Integrating Additional Knowledge in Learning Multiple Related Sparse Gaussian Graphical Models
Version: 1.0.0
Authors@R: c(person("Beilun", "Wang", role = c("aut", "cre"), email = "bw4mw@virginia.edu"), person("Yanjun", "Qi", role = "aut", email = "yanjun@virginia.edu"))
Author: Beilun Wang [aut, cre], Yanjun Qi [aut]
Maintainer: Beilun Wang <bw4mw@virginia.edu>
Description: Provides a fast and scalable joint estimator for integrating additional knowledge in learning multiple related sparse Gaussian Graphical Models (JEEK). The JEEK algorithm can be used to fast estimate multiple related precision matrices in a large-scale. For instance, it can identify multiple gene networks from multi-context gene expression datasets. By performing data-driven network inference from high-dimensional and heterogeneous data sets, this tool can help users effectively translate aggregated data into knowledge that take the form of graphs among entities. Please run demo(jeekDemo) to learn the basic functions provided by this package. For further details, please read the original paper: Beilun Wang, Arshdeep Sekhon, Yanjun Qi "A Fast and Scalable Joint Estimator for Integrating Additional Knowledge in Learning Multiple Related Sparse Gaussian Graphical Models" (ICML 2018) <arXiv:1806.00548>.
Depends: R (>= 3.0.0), lpSolve, pcaPP, igraph
Suggests: parallel
License: GPL-2
Encoding: UTF-8
URL: https://github.com/QData/jeek
BugReports: https://github.com/QData/jeek
LazyData: true
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-06-13 14:53:50 UTC; beilunwang
Repository: CRAN
Date/Publication: 2018-06-14 19:24:50 UTC

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New package genesysr with initial version 0.9.1
Package: genesysr
Version: 0.9.1
Title: Genesys PGR Client
Description: Access data on plant genetic resources from genebanks around the world published on Genesys (<https://www.genesys-pgr.org>). Your use of data is subject to terms and conditions available at <https://www.genesys-pgr.org/content/legal/terms>.
Authors@R: c(person(family = "Global Crop Diversity Trust", role = c("cph")), person("Matija", "Obreza", email = "matija.obreza@croptrust.org", role = c("aut", "cre")), person("Nora", "Castaneda", email = "nora.castaneda@croptrust.org", role = c("ctb")))
Maintainer: Matija Obreza <matija.obreza@croptrust.org>
Depends: R (>= 3.1.0)
Imports: httr, jsonlite
License: Apache License 2.0
RoxygenNote: 6.0.1
URL: https://gitlab.croptrust.org/genesys-pgr/genesysr
BugReports: https://gitlab.croptrust.org/genesys-pgr/genesysr/issues
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-06-12 19:12:29 UTC; mobreza
Author: Global Crop Diversity Trust [cph], Matija Obreza [aut, cre], Nora Castaneda [ctb]
Repository: CRAN
Date/Publication: 2018-06-14 19:24:54 UTC

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New package varjmcm with initial version 0.1.0
Package: varjmcm
Type: Package
Title: Estimations for the Covariance of Estimated Parameters in Joint Mean-Covariance Models
Version: 0.1.0
Authors@R: c(person("Naimin", "Jing", email = "naimin.jing@temple.edu", role = c("aut", "cre")), person("Hexin", "Bai", role = "aut"), person("Tong", "Wang", role = "aut"), person("Cheng Yong", "Tang", role = "aut"))
Description: The goal of the package is to equip the 'jmcm' package (current version 0.1.8.0) with estimations of the covariance of estimated parameters. Two methods are provided. The first method is to use the inverse of estimated Fisher's information matrix, see M. Pourahmadi (2000) <doi:10.1093/biomet/87.2.425>, M. Maadooliat, M. Pourahmadi and J. Z. Huang (2013) <doi:10.1007/s11222-011-9284-6>, and W. Zhang, C. Leng, C. Tang (2015) <doi:10.1111/rssb.12065>. The second method is bootstrap based, see Liu, R.Y. (1988) <doi:10.1214/aos/1176351062> for reference.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Depends: jmcm
Imports: expm, MASS, stats, Matrix
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-06-12 16:19:38 UTC; jnm
Author: Naimin Jing [aut, cre], Hexin Bai [aut], Tong Wang [aut], Cheng Yong Tang [aut]
Maintainer: Naimin Jing <naimin.jing@temple.edu>
Repository: CRAN
Date/Publication: 2018-06-14 19:00:00 UTC

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New package stockR with initial version 1.0.68
Package: stockR
Title: Identifying Stocks in Genetic Data
Version: 1.0.68
Authors@R: c(person("Scott D.", "Foster", role = c("aut", "cre"), email = "scott.foster@csiro.au"))
Author: Scott D. Foster [aut, cre]
Description: Provides a mixture model for clustering individuals (or sampling groups) into stocks based on their genetic profile. Here, sampling groups are individuals that are sure to come from the same stock (e.g. breeding adults or larvae). The mixture (log-)likelihood is maximised using the EM-algorithm after find good starting values via a K-means clustering of the genetic data. Details can be found in Foster, Feutry, Grewe, Berry, Hui, Davies (in press) Reliably Discriminating Stock Structure with Genetic Markers: Mixture Models with Robust and Fast Computation. Molecular Ecology Resources.
Maintainer: Scott D. Foster <scott.foster@csiro.au>
License: GPL (>= 2)
Imports: stats, gtools, parallel
Suggests: knitr
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2018-06-12 01:02:44 UTC; fos085
Depends: R (>= 2.10)
Repository: CRAN
Date/Publication: 2018-06-14 18:32:57 UTC

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New package nparMD with initial version 0.1.0
Package: nparMD
Type: Package
Title: Nonparametric Analysis of Multivariate Data in Factorial Designs
Version: 0.1.0
Depends: R (>= 3.1.0)
Imports: matrixStats, matrixcalc, MASS, gtools, Formula, methods, stats
Author: Maximilian Kiefel and Arne C. Bathke
Maintainer: Maximilian Kiefel <physik210@hotmail.com>
Description: Analysis of multivariate data with two-way completely randomized factorial design. The analysis is based on fully nonparametric, rank-based methods and uses test statistics based on the Dempster's ANOVA, Wilk's Lambda, Lawley-Hotelling and Bartlett-Nanda-Pillai criteria. The multivariate response is allowed to be ordinal, quantitative, binary or a mixture of the different variable types. The package offers two functions performing the analysis, one for small and the other for large sample sizes. The underlying methodology is largely described in Bathke and Harrar (2016) <doi:10.1007/978-3-319-39065-9_7> and in Munzel and Brunner (2000) <doi:10.1016/S0378-3758(99)00212-8>.
License: GPL-2 | GPL-3
Encoding: UTF-8
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-06-11 13:57:59 UTC; Maxi
Repository: CRAN
Date/Publication: 2018-06-14 18:33:00 UTC

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New package morpheus with initial version 0.2-0
Package: morpheus
Title: Estimate Parameters of Mixtures of Logistic Regressions
Description: Mixture of logistic regressions parameters (H)estimation with (U)spectral methods. The main methods take d-dimensional inputs and a vector of binary outputs, and return parameters according to the GLMs mixture model (General Linear Model). For more details see chapter 3 in the PhD thesis of Mor-Absa Loum: <http://www.theses.fr/s156435>, available here <https://www.math.u-psud.fr/~loum/IMG/pdf/these.compressed-2.pdf>.
Version: 0.2-0
Author: Benjamin Auder <Benjamin.Auder@u-psud.fr> [aut,cre], Mor-Absa Loum <Mor-Absa.Loum@u-psud.fr> [aut]
Maintainer: Benjamin Auder <Benjamin.Auder@u-psud.fr>
Depends: R (>= 3.0.0),
Imports: MASS, jointDiag, methods, pracma
Suggests: devtools, flexmix, parallel, testthat, roxygen2, tensor, nloptr
License: MIT + file LICENSE
RoxygenNote: 5.0.1
Collate: 'utils.R' 'A_NAMESPACE.R' 'computeMu.R' 'multiRun.R' 'optimParams.R' 'plot.R' 'sampleIO.R'
NeedsCompilation: yes
Packaged: 2018-06-12 12:24:17 UTC; auder
Repository: CRAN
Date/Publication: 2018-06-14 18:48:14 UTC

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New package mase with initial version 0.1.1
Package: mase
Type: Package
Title: Model-Assisted Survey Estimators
Version: 0.1.1
Date: 2018-06-06
Authors@R: c(person("Kelly", "McConville", role = c("aut", "cre", "cph"), email = "mcconville@reed.edu"), person("Becky", "Tang", role = "aut"), person("George", "Zhu", role = "aut"), person("Sida", "Li", role = "ctb"), person("Shirley", "Chueng", role = "ctb"), person("Daniell", "Toth", role = c("ctb", "cph"), comment = "Author and copyright holder of treeDesignMatrix helper function") )
Maintainer: Kelly McConville <mcconville@reed.edu>
Description: A set of model-assisted survey estimators and corresponding variance estimators for single stage, unequal probability, without replacement sampling designs. All of the estimators can be written as a generalized regression estimator with the Horvitz-Thompson, ratio, post-stratified, and regression estimators summarized by Sarndal et al. (1992, ISBN:978-0-387-40620-6). Two of the estimators employ a statistical learning model as the assisting model: the elastic net regression estimator, which is an extension of the lasso regression estimator given by McConville et al. (2017) <doi:10.1093/jssam/smw041>, and the regression tree estimator described in McConville and Toth (2017) <arXiv:1712.05708>. The variance estimators which approximate the joint inclusion probabilities can be found in Berger and Tille (2009) <doi:10.1016/S0169-7161(08)00002-3> and the bootstrap variance estimator is presented in Mashreghi et al. (2016) <doi:10.1214/16-SS113>.
License: GPL-2
LazyData: TRUE
Imports: MASS, glmnet, Matrix, foreach, survey, dplyr, magrittr, rpms, boot, stats, Rdpack
Suggests: roxygen2, testthat
Depends: R (>= 3.1)
Collate: 'gregt.R' 'varMase.R' 'GREG.R' 'gregElasticNett.R' 'gregElasticNet.R' 'gregTree.R' 'gregtreet.R' 'htt.R' 'horvitzThompson.R' 'logisticGregElasticNett.R' 'logisticGregt.R' 'postStratt.R' 'postStrat.R' 'ratioEstimatort.R' 'ratioEstimator.R' 'treeDesignMatrix.R'
RoxygenNote: 6.0.1
RdMacros: Rdpack
NeedsCompilation: no
Packaged: 2018-06-11 19:21:21 UTC; kswatmac
Author: Kelly McConville [aut, cre, cph], Becky Tang [aut], George Zhu [aut], Sida Li [ctb], Shirley Chueng [ctb], Daniell Toth [ctb, cph] (Author and copyright holder of treeDesignMatrix helper function)
Repository: CRAN
Date/Publication: 2018-06-14 18:33:03 UTC

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New package liger with initial version 0.1
Package: liger
Type: Package
Title: Lightweight Iterative Geneset Enrichment
Version: 0.1
Authors@R: c(person("Jean", "Fan", role = c("aut", "cre"), email = "jeanfan@fas.harvard.edu", comment = c(ORCID = "0000-0002-0212-5451")), person("Peter", "Kharchenko", role = "aut", email = "Peter_Kharchenko@hms.harvard.edu"))
Description: Gene Set Enrichment Analysis (GSEA) is a computational method that determines whether an a priori defined set of genes shows statistically significant, concordant differences between two biological states. The original algorithm is detailed in Subramanian et al. with 'Java' implementations available through the Broad Institute (Subramanian et al. 2005 <doi:10.1073/pnas.0506580102>). The 'liger' package provides a lightweight R implementation of this enrichment test on a list of values (Fan et al., 2017 <doi:10.5281/zenodo.887386>). Given a list of values, such as p-values or log-fold changes derived from differential expression analysis or other analyses comparing biological states, this package enables you to test a priori defined set of genes for enrichment to enable interpretability of highly significant or high fold-change genes.
License: GPL-3 | file LICENSE
LazyData: TRUE
Depends: R (>= 2.10)
Imports: graphics, stats, Rcpp, matrixStats, parallel
LinkingTo: Rcpp, RcppArmadillo
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
URL: https://github.com/JEFworks/liger
BugReports: https://github.com/JEFworks/liger/issues
RoxygenNote: 6.0.1
NeedsCompilation: yes
Packaged: 2018-06-12 13:38:26 UTC; Jean
Author: Jean Fan [aut, cre] (<https://orcid.org/0000-0002-0212-5451>), Peter Kharchenko [aut]
Maintainer: Jean Fan <jeanfan@fas.harvard.edu>
Repository: CRAN
Date/Publication: 2018-06-14 18:33:07 UTC

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New package IPCAPS with initial version 1.1.5
Package: IPCAPS
Type: Package
Title: Iterative Pruning to Capture Population Structure
Version: 1.1.5
Authors@R: c(person(given = "Kridsadakorn", family = "Chaichoompu", email = "kridsadakorn@biostatgen.org", role = c("aut", "cre")), person(given = "Kristel", family = 'Van Steen', role = "aut"), person(given = "Fentaw", family = "Abegaz", role = "aut"), person(given = "Sissades", family = "Tongsima", role = "aut"), person(given = "Philip", family = "Shaw", role = "aut"), person(given = "Anavaj", family = "Sakuntabhai", role = "aut"), person(given = "Luisa", family = "Pereira", role = "aut"))
Description: An unsupervised clustering algorithm based on iterative pruning is for capturing population structure. This version supports ordinal data which can be applied directly to SNP data to identify fine-level population structure and it is built on the iterative pruning Principal Component Analysis ('ipPCA') algorithm as explained in Intarapanich et al. (2009) <doi:10.1186/1471-2105-10-382>. The 'IPCAPS' involves an iterative process using multiple splits based on multivariate Gaussian mixture modeling of principal components and 'Expectation-Maximization' clustering as explained in Lebret et al. (2015) <doi:10.18637/jss.v067.i06>. In each iteration, rough clusters and outliers are also identified using the function rubikclust() from the R package 'KRIS'.
Depends: R (>= 3.2.4.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
Imports: stats,utils,graphics,grDevices,MASS,Matrix,expm,KRIS,fpc,LPCM,apcluster,Rmixmod
Suggests: testthat
BugReports: https://gitlab.com/kris.ccp/ipcaps/issues
URL: https://gitlab.com/kris.ccp/ipcaps
Collate: 'parallelization.R' 'check.stopping.R' 'clustering.mode.R' 'clustering.R' 'data.R' 'export.groups.R' 'get.node.info.R' 'ipcaps-package.R' 'process.each.node.R' 'output.template.R' 'save.html.R' 'save.eigenplots.html.R' 'save.plots.label.html.R' 'save.plots.cluster.html.R' 'save.plots.R' 'postprocess.R' 'preprocess.R' 'ipcaps.R' 'top.discriminator.R'
NeedsCompilation: no
Packaged: 2018-06-11 13:05:39 UTC; kridsadakorn
Author: Kridsadakorn Chaichoompu [aut, cre], Kristel Van Steen [aut], Fentaw Abegaz [aut], Sissades Tongsima [aut], Philip Shaw [aut], Anavaj Sakuntabhai [aut], Luisa Pereira [aut]
Maintainer: Kridsadakorn Chaichoompu <kridsadakorn@biostatgen.org>
Repository: CRAN
Date/Publication: 2018-06-14 18:01:51 UTC

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New package INDperform with initial version 0.1.0
Type: Package
Package: INDperform
Version: 0.1.0
Title: Evaluation of Indicator Performances for Assessing Ecosystem States
Authors@R: c( person("Saskia A.", "Otto", email = "saskia.a.otto@gmail.com", role = c("aut", "cre")), person("Rene", "Plonus", role = "aut"), person("Steffen", "Funk", role = "aut"), person("Alexander", "Keth", role = "aut") )
Description: An implementation of the 7-step approach suggested by Otto et al. (2018) <doi:10.1016/j.ecolind.2017.05.045> to validate ecological state indicators and to select a suite of complimentary and well performing indicators. This suite can be then used to assess the current state of the system in comparison to a reference period. However, the tools in this package are very generic and can be used to test any type of indicator (e.g. social or economic indicators).
URL: https://github.com/saskiaotto/INDperform
BugReports: https://github.com/SaskiaAOtto/INDperform/issues
Encoding: UTF-8
Depends: R(>= 3.3)
Imports: cowplot (>= 0.7.0), dplyr (>= 0.5.0), grDevices (>= 1.8-17), ggplot2 (>= 2.2.1), htmlwidgets (>= 0.8), jsonlite (>= 1.4), lazyeval (>= 0.2.0), magrittr (>= 1.5), mgcv (>= 1.8-17), nlme (>= 3.1-131), purrr (>= 0.2.2), RColorBrewer (>= 1.1-2), rhandsontable (>= 0.3.4), shiny (>= 1.0.1), stringr (>= 1.2.0), tibble (>= 1.3.0), tidyr (>= 0.6.1), vdiffr (>= 0.1.1), vegan (>= 2.4-3)
Suggests: doParallel (>= 1.0.11), ggdendro (>= 0.1-20), gridExtra (>= 2.2.1), knitr (>= 1.16), parallel (>= 3.3.1), pbapply (>= 1.3-3), testthat (>= 1.0.2), tripack (>= 1.3-8)
License: GPL
LazyData: true
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-06-12 18:19:08 UTC; saskiaotto
Author: Saskia A. Otto [aut, cre], Rene Plonus [aut], Steffen Funk [aut], Alexander Keth [aut]
Maintainer: Saskia A. Otto <saskia.a.otto@gmail.com>
Repository: CRAN
Date/Publication: 2018-06-14 19:00:07 UTC

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New package GFORCE with initial version 0.1.2
Package: GFORCE
Type: Package
Title: Clustering and Inference Procedures for High-Dimensional Latent Variable Models
Version: 0.1.2
Authors@R: person("Carson", "Eisenach", email = "eisenach@princeton.edu", role = c("aut", "cre"))
Description: A complete suite of computationally efficient methods for high dimensional clustering and inference problems in G-Latent Models (a type of Latent Variable Gaussian graphical model). The main feature is the FORCE (First-Order, Certifiable, Efficient) clustering algorithm which is a fast solver for a semi-definite programming (SDP) relaxation of the K-means problem. For certain types of graphical models (G-Latent Models), with high probability the algorithm not only finds the optimal clustering, but produces a certificate of having done so. This certificate, however, is model independent and so can also be used to certify data clustering problems. The 'GFORCE' package also contains implementations of inferential procedures for G-Latent graphical models using n-fold cross validation. Also included are native code implementations of other popular clustering methods such as Lloyd's algorithm with kmeans++ initialization and complete linkage hierarchical clustering. The FORCE method is due to Eisenach and Liu (2017) <arxiv:1806.00530>.
License: GPL-2
LazyData: TRUE
RoxygenNote: 6.0.1
Imports: MASS,lpSolve,stats
Suggests: testthat
NeedsCompilation: yes
Packaged: 2018-06-12 16:17:02 UTC; carson
Author: Carson Eisenach [aut, cre]
Maintainer: Carson Eisenach <eisenach@princeton.edu>
Repository: CRAN
Date/Publication: 2018-06-14 19:00:12 UTC

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New package DiPhiSeq with initial version 0.1.0
Package: DiPhiSeq
Type: Package
Title: Robust Tests for Differential Dispersion and Differential Expression in RNA-Sequencing Data
Version: 0.1.0
Authors@R: c(person("Jun", "Li", email = "jun.li@nd.edu", role = c("aut", "cre")), person("Alicia T.", "Lamere", role = c("aut")))
Description: Implements the algorithm described in Jun Li and Alicia T. Lamere, "DiPhiSeq: Robust comparison of expression levels on RNA-Seq data with large sample sizes" (Unpublished). Detects not only genes that show different average expressions ("differential expression", DE), but also genes that show different diversities of expressions in different groups ("differentially dispersed", DD). DD genes can be important clinical markers. 'DiPhiSeq' uses a redescending penalty on the quasi-likelihood function, and thus has superior robustness against outliers and other noise.
Depends: R (>= 3.1.0)
Imports: stats (>= 3.1.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-06-12 15:15:40 UTC; jun
Author: Jun Li [aut, cre], Alicia T. Lamere [aut]
Maintainer: Jun Li <jun.li@nd.edu>
Repository: CRAN
Date/Publication: 2018-06-14 19:00:17 UTC

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New package corTest with initial version 0.9.6
Package: corTest
Type: Package
Title: Robust Tests for Equal Correlation
Version: 0.9.6
Author: Danyang Yu, Weiliang Qiu
Maintainer: Danyang Yu <danyangyu@hnu.edu.cn>
Description: There are 6 novel robust tests for equal correlation. They are all based on logistic regressions. The difference between 6 methods is the difference of U which are proportion to different types of correlation. The ST1() is based on Pearson correlation. ST2() improved ST1() by using median absolute deviation. ST3() utilized type M correlation and ST4() used Spearman correlation. ST5() and ST6() used two different ways to combine ST3() and ST4(). We highly recommend ST5() according to the passage New Statistical Methods for Constructing Robust Differential Correlation Networks (expected to be public).
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.4.0)
Imports: MASS, graphics, stats
NeedsCompilation: no
Packaged: 2018-06-12 12:38:37 UTC; yudan
Repository: CRAN
Date/Publication: 2018-06-14 18:37:57 UTC

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New package jaccard with initial version 0.1.0
Package: jaccard
Type: Package
Title: Test Similarity Between Binary Data using Jaccard/Tanimoto Coefficients
Version: 0.1.0
Date: 2018-06-06
Author: Neo Christopher Chung <nchchung@gmail.com>, Błażej Miasojedow <bmiasojedow@gmail.com>, Michał Startek <M.Startek@mimuw.edu.pl>, Anna Gambin <aniag@mimuw.edu.pl>
Maintainer: Neo Christopher Chung <nchchung@gmail.com>
Description: Calculate statistical significance of Jaccard/Tanimoto similarity coefficients for binary data.
biocViews:
License: GPL-2
Encoding: UTF-8
LazyData: true
Imports: Rcpp (>= 0.12.6), qvalue, dplyr, magrittr
LinkingTo: Rcpp
NeedsCompilation: yes
SystemRequirements: C++11
RoxygenNote: 6.0.1
Packaged: 2018-06-10 01:52:22 UTC; nc
Repository: CRAN
Date/Publication: 2018-06-14 17:53:00 UTC

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Wed, 13 Jun 2018

New package dextergui with initial version 0.1.3
Package: dextergui
Type: Package
Title: A Graphic User Interface to Dexter
Version: 0.1.3
Author: Jesse Koops, Eva de Schipper, Ivailo Partchev, Timo Bechger, Gunter Maris
Maintainer: jesse koops <jesse.koops@cito.nl>
Description: A graphical user interface for dexter. Offers Classical Test and Item analysis, Item Response analysis and data management for educational and psychological tests.
License: GPL-3
BugReports: https://github.com/jessekps/dexter/issues
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.3), dexter (>= 0.7.0)
Imports: shiny (>= 1.0.5), shinyBS, DT, htmltools, htmlwidgets, shinyjs (>= 1.0), shinyFiles, jsonlite, dplyr, tidyr, tibble, rlang, RCurl, DBI, readxl, writexl, readODS, igraph, ggplot2, ggExtra, ggridges, networkD3, Cairo, RColorBrewer, graphics, grDevices, methods, utils, tools
RoxygenNote: 6.0.1
Suggests: knitr
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-06-13 13:01:52 UTC; jessek
Repository: CRAN
Date/Publication: 2018-06-13 21:37:58 UTC

More information about dextergui at CRAN
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Tue, 12 Jun 2018

New package sensiPhy with initial version 0.8.2
Package: sensiPhy
Title: Sensitivity Analysis for Comparative Methods
Version: 0.8.2
Date: 2018-06-12
Authors@R: c( person("Gustavo","Paterno", email = "paternogbc@gmail.com", role = c("cre","aut")), person("Gijsbert", "Werner", email = "gijsbert.werner@zoo.ox.ac.uk", role = "aut"), person("Caterina", "Penone", email = "caterina.penone@gmail.com", role = "aut"), person("Pablo", "Martinez", email = "pablo_sc82@hotmail.com", role = "ctb"))
Maintainer: Gustavo Paterno <paternogbc@gmail.com>
Description: An implementation of sensitivity analysis for phylogenetic comparative methods. The package is an umbrella of statistical and graphical methods that estimate and report different types of uncertainty in PCM: (i) Species Sampling uncertainty (sample size; influential species and clades). (ii) Phylogenetic uncertainty (different topologies and/or branch lengths). (iii) Data uncertainty (intraspecific variation and measurement error).
Depends: R (>= 3.4.0), ape (>= 3.3), phylolm (>= 2.4), ggplot2 (>= 2.1.0)
Imports: caper (>= 0.5.2), phytools (>= 0.6), geiger (>= 2.0)
License: GPL-2
URL: https://github.com/paternogbc/sensiPhy
BugReports: https://github.com/paternogbc/sensiPhy/issues
LazyData: true
RoxygenNote: 6.0.1
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-06-12 16:19:53 UTC; paterno
Author: Gustavo Paterno [cre, aut], Gijsbert Werner [aut], Caterina Penone [aut], Pablo Martinez [ctb]
Repository: CRAN
Date/Publication: 2018-06-12 20:28:59 UTC

More information about sensiPhy at CRAN
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New package beginr with initial version 0.1.3
Package: beginr
Version: 0.1.3
Date: 2018-06-12
Title: Functions for R Beginners
Author: Peng Zhao
Maintainer: Peng Zhao <pzhao@pzhao.net>
Depends: R (>= 3.1.0)
Imports: cranlogs (>= 2.1.0),
Suggests:
Description: Useful functions for R beginners, including hints for the arguments of the 'plot()' function, self-defined functions for error bars, user-customized pair plots and hist plots, enhanced linear regression figures, etc.. This package could be helpful to R experts as well.
License: MIT + file LICENSE
URL: https://github.com/pzhaonet/beginr
BugReports: https://github.com/pzhaonet/beginr/issues
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-06-12 15:13:39 UTC; c7701105
Repository: CRAN
Date/Publication: 2018-06-12 16:08:09 UTC

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New package ordinalgmifs with initial version 1.0.4
Package: ordinalgmifs
Version: 1.0.4
Date: 2018-06-12
Title: Ordinal Regression for High-Dimensional Data
Author: Kellie J. Archer, Jiayi Hou, Qing Zhou, Kyle Ferber, John G. Layne, Amanda Gentry
Maintainer: Kellie J. Archer <archer.43@osu.edu>
Depends: R (>= 2.10), survival
Description: Provides a function for fitting cumulative link, adjacent category, forward and backward continuation ratio, and stereotype ordinal response models when the number of parameters exceeds the sample size, using the the generalized monotone incremental forward stagewise method.
License: GPL (>= 2)
BuildResaveData: best
SystemRequirements: C++11
NeedsCompilation: yes
BuildVignettes: TRUE
LazyData: true
Packaged: 2018-06-12 14:45:14 UTC; karcher
Repository: CRAN
Date/Publication: 2018-06-12 15:08:16 UTC

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New package spectralAnalysis with initial version 3.12.0
Package: spectralAnalysis
Type: Package
Title: Pre-Process, Visualize and Analyse Process Analytical Data, by Spectral Data Measurements Made During a Chemical Process
Version: 3.12.0
Authors@R: c( person("Robin", "Van Oirbeek", role = c("aut") ), person("Adriaan", "Blommaert", role = c("aut", "cre"), email = "adriaan.blommaert@openanalytics.eu"), person("Nicolas", "Sauwen", role = c("aut"), email = "nicolas.sauwen@openanalytics.eu"), person("Tor", "Maes", role = "ctb" ), person("Jan", "Dijkmans", role = "ctb" ), person("Jef", "Cuypers", role = "ctb" ), person("Tatsiana", "Khamiakova", role = "ctb" ), person("Michel", "Tiel", role = "ctb" ), person("Claudia" , "Beleites" , role = "ctb" ) )
LazyData: true
Maintainer: Adriaan Blommaert <adriaan.blommaert@openanalytics.eu>
URL: http://www.openanalytics.eu
Description: Infrared, near-infrared and Raman spectroscopic data measured during chemical reactions, provide structural fingerprints by which molecules can be identified and quantified. The application of these spectroscopic techniques as inline process analytical tools (PAT), provides the (pharma-)chemical industry with novel tools, allowing to monitor their chemical processes, resulting in a better process understanding through insight in reaction rates, mechanistics, stability, etc. Data can be read into R via the generic spc-format, which is generally supported by spectrometer vendor software. Versatile pre-processing functions are available to perform baseline correction by linking to the 'baseline' package; noise reduction via the 'signal' package; as well as time alignment, normalization, differentiation, integration and interpolation. Implementation based on the S4 object system allows storing a pre-processing pipeline as part of a spectral data object, and easily transferring it to other datasets. Interactive plotting tools are provided based on the 'plotly' package. Non-negative matrix factorization (NMF) has been implemented to perform multivariate analyses on individual spectral datasets or on multiple datasets at once. NMF provides a parts-based representation of the spectral data in terms of spectral signatures of the chemical compounds and their relative proportions. The functionality to read in spc-files was adapted from the 'hyperSpec' package.
License: GPL-3
Imports: baseline, BiocGenerics, data.table, ggplot2, jsonlite, magrittr, methods, nnls, NMF, plotly, plyr, RColorBrewer, signal, stats, viridis, hNMF
RoxygenNote: 6.0.1.9000
Suggests: testthat
Collate: 'internalHelpers.R' 'allGenericFunctions.R' 'objectSpectraInTime.R' 'objectProcessTimes.R' 'objectLinking.R' 'alignmentFunctions.R' 'dataManagementTools.R' 'defaults.R' 'readSPC.R' 'saveSpectraInTime.R' 'spectralAnalysis.R' 'spectralIntegration.R' 'spectralNMF.R' 'spectralPreprocessing.R' 'spectralVisualization.R' 'subsetting.R'
NeedsCompilation: no
Packaged: 2018-06-11 10:37:24 UTC; ablommaert
Author: Robin Van Oirbeek [aut], Adriaan Blommaert [aut, cre], Nicolas Sauwen [aut], Tor Maes [ctb], Jan Dijkmans [ctb], Jef Cuypers [ctb], Tatsiana Khamiakova [ctb], Michel Tiel [ctb], Claudia Beleites [ctb]
Repository: CRAN
Date/Publication: 2018-06-12 14:30:39 UTC

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New package pulsar with initial version 0.3.3
Package: pulsar
Title: Parallel Utilities for Lambda Selection along a Regularization Path
Version: 0.3.3
Encoding: UTF-8
Authors@R: c(person("Zachary", "Kurtz", role = c("aut", "cre"), email="zdkurtz@gmail.com"), person("Christian", "M\u00FCller", role = c("aut", "ctb"), email="cmueller@simonsfoundation.org"))
Description: Model selection for penalized graphical models using the Stability Approach to Regularization Selection ('StARS'), with options for speed-ups including Bounded StARS (B-StARS), batch computing, and other stability metrics (e.g., graphlet stability G-StARS). Christian L. Müller, Richard Bonneau, Zachary Kurtz (2016) <arXiv:1605.07072>.
URL: http://github.com/zdk123/pulsar, http://arxiv.org/abs/1605.07072
BugReports: http://github.com/zdk123/pulsar/issues
Depends: R (>= 3.2.0)
License: GPL (>= 2)
Suggests: batchtools (>= 0.9.10), fs (>= 1.2.2), checkmate (>= 1.8.5), orca, huge, MASS, QUIC, glmnet, network, cluster, testthat, knitr, rmarkdown
Imports: methods, parallel, graphics, stats, utils, tools, Matrix
RoxygenNote: 6.0.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-06-11 14:02:11 UTC; zachary
Author: Zachary Kurtz [aut, cre], Christian Müller [aut, ctb]
Maintainer: Zachary Kurtz <zdkurtz@gmail.com>
Repository: CRAN
Date/Publication: 2018-06-12 14:23:10 UTC

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New package MLZ with initial version 0.1.1
Package: MLZ
Title: Mean Length-Based Estimators of Mortality using TMB
Version: 0.1.1
Authors@R: c(person("Quang", "Huynh", email = "q.huynh@oceans.ubc.ca", role = c("aut", "cre")), person("Todd", "Gedamke", rol = "ctb"), person("Amy", "Then", rol = "ctb"))
Maintainer: Quang Huynh <q.huynh@oceans.ubc.ca>
Description: Estimation functions and diagnostic tools for mean length-based total mortality estimators based on Gedamke and Hoenig (2006) <doi:10.1577/T05-153.1>.
Depends: R (>= 3.4.0)
License: GPL-2
Encoding: UTF-8
LazyData: true
Imports: methods, stats, graphics, grDevices, dplyr (>= 0.5.0), gplots, ggplot2 (>= 2.0.0), reshape2 (>= 1.4.1), parallel, TMB
RoxygenNote: 6.0.1
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
LinkingTo: TMB, RcppEigen
NeedsCompilation: yes
Packaged: 2018-06-11 20:13:46 UTC; qhuynh
Author: Quang Huynh [aut, cre], Todd Gedamke [ctb], Amy Then [ctb]
Repository: CRAN
Date/Publication: 2018-06-12 11:29:34 UTC

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New package freetypeharfbuzz with initial version 0.1.0
Package: freetypeharfbuzz
Title: Deterministic Computation of Text Box Metrics
Version: 0.1.0
Authors@R: c( person("Lionel", "Henry", ,"lionel@rstudio.com", c("aut", "cre")), person("RStudio", role = "cph"), person("David", "Turner", role = "aut", comment = "FreeType library"), person("Robert", "Wilhelm", role = "aut", comment = "FreeType library"), person("Werner", "Wilhelm", role = "aut", comment = "FreeType library"), person("Behdad", "Esfahbod", role = "aut", comment = "Harfbuzz library"), person("Simon", "Hausmann", role = "aut", comment = "Harfbuzz library"), person("Martin", "Hosken", role = "aut", comment = "Harfbuzz library"), person("Jonathan", "Kew", role = "aut", comment = "Harfbuzz library"), person("Lars", "Knoll", role = "aut", comment = "Harfbuzz library"), person("Werner", "Lemberg", role = "aut", comment = "Harfbuzz library"), person("Roozbeh", "Pournader", role = "aut", comment = "Harfbuzz library"), person("Owen", "Taylor", role = "aut", comment = "Harfbuzz library"), person("David", "Turner", role = "aut", comment = "Harfbuzz library"), person("Red Hat", role = "cph", comment = "Harfbuzz library") )
Description: Unlike other tools that dynamically link to the 'Cairo' stack, 'freetypeharfbuzz' is statically linked to specific versions of the 'FreeType' and 'harfbuzz' libraries (2.9 and 1.7.6 respectively). This ensures deterministic computation of text box extents for situations where reproducible results are crucial (for instance unit tests of graphics).
Depends: R (>= 3.2)
Imports: fontquiver
Suggests: testthat
License: GPL-3 | file LICENSE
Encoding: UTF-8
LazyData: true
ByteCompile: true
RoxygenNote: 6.0.1
NeedsCompilation: yes
Packaged: 2018-06-11 15:32:15 UTC; lionel
Author: Lionel Henry [aut, cre], RStudio [cph], David Turner [aut] (FreeType library), Robert Wilhelm [aut] (FreeType library), Werner Wilhelm [aut] (FreeType library), Behdad Esfahbod [aut] (Harfbuzz library), Simon Hausmann [aut] (Harfbuzz library), Martin Hosken [aut] (Harfbuzz library), Jonathan Kew [aut] (Harfbuzz library), Lars Knoll [aut] (Harfbuzz library), Werner Lemberg [aut] (Harfbuzz library), Roozbeh Pournader [aut] (Harfbuzz library), Owen Taylor [aut] (Harfbuzz library), David Turner [aut] (Harfbuzz library), Red Hat [cph] (Harfbuzz library)
Maintainer: Lionel Henry <lionel@rstudio.com>
Repository: CRAN
Date/Publication: 2018-06-12 11:29:31 UTC

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New package swgee with initial version 1.2
Package: swgee
Type: Package
Title: Simulation Extrapolation Inverse Probability Weighted Generalized Estimating Equations
Version: 1.2
Date: 2018-06-09
Imports: stats, graphics, gee, geepack, mvtnorm,
LazyLoad: yes
Author: Juan Xiong <jxiong@szu.edu.cn>, Grace Y. Yi <yyi@uwaterloo.ca>
Maintainer: Juan Xiong <jxiong@szu.edu.cn>
Description: Simulation extrapolation and inverse probability weighted generalized estimating equations method for longitudinal data with missing observations and measurement error in covariates. References: Yi, G. Y. (2008) <doi:10.1093/biostatistics/kxm054>; Cook, J. R. and Stefanski, L. A. (1994) <doi:10.1080/01621459.1994.10476871>; Little, R. J. A. and Rubin, D. B. (2002, ISBN:978-0-471-18386-0).
License: GPL-3
NeedsCompilation: no
Packaged: 2018-06-11 01:56:09 UTC; apple
Repository: CRAN
Date/Publication: 2018-06-12 10:33:35 UTC

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New package smicd with initial version 1.0.0
Package: smicd
Type: Package
Title: Statistical Methods for Interval Censored Data
Version: 1.0.0
Author: Paul Walter
Maintainer: Paul Walter <paul.walter@fu-berlin.de>
Description: Functions that provide statistical methods for interval censored (grouped) data. The package supports the estimation of linear and linear mixed regression models with interval censored dependent variables. Parameter estimates are obtained by a stochastic expectation maximization algorithm. Furthermore, the package enables the direct (without covariates) estimation of statistical indicators from interval censored data via an iterative kernel density algorithm. Survey and Organisation for Economic Co-operation and Development (OECD) weights can be included into the direct estimation (see, Groß, M., U. Rendtel, T. Schmid, S. Schmon, and N. Tzavidis (2017) <doi:10.1111/rssa.12179>).
License: GPL-2
Encoding: UTF-8
LazyData: true
Suggests: knitr, rmarkdown
RoxygenNote: 6.0.1
Imports: ineq, truncnorm, lme4, MuMIn, formula.tools, mvtnorm, spatstat, laeken, weights, mlmRev, Kernelheaping
NeedsCompilation: no
Packaged: 2018-06-11 07:12:11 UTC; paulwalter
Repository: CRAN
Date/Publication: 2018-06-12 10:33:38 UTC

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New package RagGrid with initial version 0.1.1
Package: RagGrid
Type: Package
Title: A Wrapper of the 'JavaScript' Library 'agGrid'
Version: 0.1.1
Authors@R: c( person("Srikkanth", "M",email = "srikkanth18@gmail.com",role = c("aut", "cre")), person("Praveen", "N", email = "npraveen@live.in", role = c("aut", "ctb")) )
Maintainer: Srikkanth M <srikkanth18@gmail.com>
Description: Data objects in 'R' can be rendered as 'HTML' tables using the 'JavaScript' library 'ag-grid' (typically via 'R Markdown' or 'Shiny'). The 'ag-grid' library has been included in this 'R' package. The package name 'RagGrid' is an abbreviation of 'R agGrid'.
URL: https://github.com/no-types/RagGrid/
BugReports: https://github.com/no-types/RagGrid/issues
License: MIT + file LICENSE
Imports: htmltools (>= 0.3.6), htmlwidgets (>= 1.0), crosstalk, knitr
Suggests: jsonlite (>= 0.9.16), rmarkdown, shiny (>= 0.12.1)
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-06-11 02:07:23 UTC; srikkanth
Author: Srikkanth M [aut, cre], Praveen N [aut, ctb]
Repository: CRAN
Date/Publication: 2018-06-12 10:34:04 UTC

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New package pxweb with initial version 0.6.37
Package: pxweb
Type: Package
Title: R Interface to the PX-Web/PC-Axis API
Version: 0.6.37
Encoding: UTF-8
Authors@R: c( person("Mans", "Magnusson", email = "mons.magnusson@gmail.com", role = c("aut", "cre")), person("Love" , "Hansson", role = "aut"), person("Leo", "Lahti", role = "aut"), person("Janne", "Huovari", role = "ctb"), person("Eydun", "Nielsen", role = "ctb"), person("Bo", "Werth", role = "ctb"), person("Thomas", "Runarsson", role = "ctb"), person("Torbjörn", "Lindquist", role = "ctb"), person("Palmar", "Thorsteinsson", role = "ctb"))
Description: Generic interface for the PX-Web/PC-Axis API. The PX-Web/PC-Axis API is used by organizations such as Statistics Sweden and Statistics Finland to disseminate data. The R package can interact with all PX-Web/PC-Axis APIs to fetch information about the data hierarchy, extract metadata and extract and parse statistics to R data.frame format. PX-Web is a solution to disseminate PC-Axis data files in dynamic tables on the web. Since 2013 PX-Web contains an API to disseminate PC-Axis files.
VignetteBuilder: knitr
URL: https://github.com/rOpenGov/pxweb/
BugReports: https://github.com/rOpenGov/pxweb/issues
Depends: methods
Imports: data.table, plyr, stringr, RJSONIO, httr (>= 1.1)
License: BSD_2_clause + file LICENSE
Suggests: ggplot2, knitr, rmarkdown, roxygen2, testthat (>= 0.11)
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-06-11 09:00:38 UTC; mansmagnusson
Author: Mans Magnusson [aut, cre], Love Hansson [aut], Leo Lahti [aut], Janne Huovari [ctb], Eydun Nielsen [ctb], Bo Werth [ctb], Thomas Runarsson [ctb], Torbjörn Lindquist [ctb], Palmar Thorsteinsson [ctb]
Maintainer: Mans Magnusson <mons.magnusson@gmail.com>
Repository: CRAN
Date/Publication: 2018-06-12 10:33:42 UTC

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New package norris with initial version 0.1.0
Package: norris
Title: All of Your Chuck Norris Needs
Version: 0.1.0
Authors@R: person("Chris", "Cardillo", email = "CFCardillo23@gmail.com", role = c("aut", "cre"))
Description: Utility functions for the lovely 'ICNDB' API, <http://www.icndb.com/api/>, which allows users to retrieve Chuck Norris jokes either randomly or by joke number.
Depends: R (>= 3.3.3), httr, jsonlite, stringr, dplyr
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-06-12 00:28:11 UTC; HomeBase
Author: Chris Cardillo [aut, cre]
Maintainer: Chris Cardillo <CFCardillo23@gmail.com>
Repository: CRAN
Date/Publication: 2018-06-12 10:33:46 UTC

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New package netSEM with initial version 0.5.0
Package: netSEM
Type: Package
Title: Network Structural Equation Modeling
Description: The network structural equation modeling conducts a network statistical analysis on a data frame of coincident observations of multiple continuous variables [1]. It builds a pathway model by exploring a pool of domain knowledge guided candidate statistical relationships between each of the variable pairs, selecting the 'best fit' on the basis of a specific criteria such as adjusted r-squared value. This work was funded under U. S. Dept. of Energy, Prime Award No. DE-E-0004946, Award Agreement No. 60220829-51077-T. [1] Bruckman, Laura S., Nicholas R. Wheeler, Junheng Ma, Ethan Wang, Carl K. Wang, Ivan Chou, Jiayang Sun, and Roger H. French. (2013) <doi:10.1109/ACCESS.2013.2267611>.
Version: 0.5.0
Authors@R: c(person("Wei-Heng", "Huang", email="wxh272@case.edu", role=c("aut","cre"), comment = c(ORCID = "0000-0002-6609-4981")), person("Nicholas", "Wheeler", email="nrw16@case.edu", role=c("aut"), comment = c(ORCID = "0000-0003-2248-8919")), person("Addison", "Klinke", email="agk38@case.edu", role=c("aut"), comment = c(ORCID = "0000-0002-6985-7657")), person("Yifan", "Xu", email="yifan.xu@case.edu", role=c("aut"), comment = c(ORCID = "0000-0003-1696-0228")), person("Wenyu", "Du", email="wxd97@case.edu", role=c("aut"), comment = c(ORCID = "0000-0002-8672-9104")), person("Abdulkerim", "Gok", email="axg515@case.edu", role=c("aut"), comment = c(ORCID = "0000-0003-3433-7106")), person("Devin", "Gordon", email="dag109@case.edu", role=c("ctb"), comment = c(ORCID = "0000-0002-5919-0422")), person("Yu", "Wang", email="yxw880@case.edu", role=c("ctb"), comment = c(ORCID = "0000-0003-1353-2578")), person("Jiqi", "Liu", email="jxl1763@case.edu", role=c("ctb"), comment = c(ORCID = "0000-0003-2016-4160")), person("Alan", "Curran", email="ajc269@case.edu", role=c("ctb"), comment = c(ORCID = "0000-0002-4505-8359")), person("Justin", "Fada", email="jxf77@case.edu", role=c("ctb"), comment = c(ORCID = "0000-0002-0029-5051")), person("Xuan", "Ma", email="xxm115@case.edu", role=c("ctb"), comment = c(ORCID = "0000-0003-2361-2846")), person("Jennifer", "Braid", email="jlb269@case.edu", role=c("ctb"), comment = c(ORCID = "0000-0002-0677-7756")), person("Laura", "Bruckman", email="lsh41@case.edu", role=c("aut"), comment = c(ORCID = "0000-0003-1271-1072")), person("Roger", "French", email="rxf131@case.edu", role=c("aut","cph"), comment = c(ORCID = "0000-0002-6162-0532")) )
Depends: R (>= 3.1.0)
Imports: DiagrammeR (>= 0.9.2), DiagrammeRsvg (>= 0.1), htmlwidgets (>= 1.2), knitr (>= 1.20), magrittr (>= 1.5), MASS (>= 7.3-47), rsvg (>= 1.1), svglite (>= 1.2.1), png (>= 0.1-7), segmented (>= 0.5-3.0), gtools (>= 3.5.0)
License: GPL (>= 2)
LazyData: true
Suggests: rmarkdown, testthat
VignetteBuilder: knitr
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-06-10 22:22:21 UTC; setup
Author: Wei-Heng Huang [aut, cre] (<https://orcid.org/0000-0002-6609-4981>), Nicholas Wheeler [aut] (<https://orcid.org/0000-0003-2248-8919>), Addison Klinke [aut] (<https://orcid.org/0000-0002-6985-7657>), Yifan Xu [aut] (<https://orcid.org/0000-0003-1696-0228>), Wenyu Du [aut] (<https://orcid.org/0000-0002-8672-9104>), Abdulkerim Gok [aut] (<https://orcid.org/0000-0003-3433-7106>), Devin Gordon [ctb] (<https://orcid.org/0000-0002-5919-0422>), Yu Wang [ctb] (<https://orcid.org/0000-0003-1353-2578>), Jiqi Liu [ctb] (<https://orcid.org/0000-0003-2016-4160>), Alan Curran [ctb] (<https://orcid.org/0000-0002-4505-8359>), Justin Fada [ctb] (<https://orcid.org/0000-0002-0029-5051>), Xuan Ma [ctb] (<https://orcid.org/0000-0003-2361-2846>), Jennifer Braid [ctb] (<https://orcid.org/0000-0002-0677-7756>), Laura Bruckman [aut] (<https://orcid.org/0000-0003-1271-1072>), Roger French [aut, cph] (<https://orcid.org/0000-0002-6162-0532>)
Maintainer: Wei-Heng Huang <wxh272@case.edu>
Repository: CRAN
Date/Publication: 2018-06-12 10:33:50 UTC

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New package MovieSpider with initial version 1.0
Package: MovieSpider
Type: Package
Title: Using Web Crawler to Obtain Real-Time Movie Data for Further Analysis
Version: 1.0
Date: 2018-06-08
Author: Rongze Zheng,Jingyu Hao
Maintainer: Rongze Zheng <zhengrz@mail2.sysu.edu.cn>
Description: With this package, users can get access to some of the most authoritative movie-rating websites( <https://movie.douban.com> and <https://www.imdb.com> ). Using wed crawler users can obtain real-time movie data. By using different functions, users can obtain data of the top rated movies as well as the recent most popular movies. The obtained data, which can be used for further analysis, includes the names, release time as well as their ratings, etc.
Depends: R (>= 3.1.1)
License: GPL-3
NeedsCompilation: no
Packaged: 2018-06-11 08:56:30 UTC; k
Repository: CRAN
Date/Publication: 2018-06-12 10:34:08 UTC

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New package linpk with initial version 1.0
Package: linpk
Type: Package
Version: 1.0
Date: 2018-06-07
Title: Generate Concentration-Time Profiles from Linear PK Systems
Authors@R: person("Benjamin", "Rich", role=c("aut", "cre"), email="mail@benjaminrich.net")
Description: Generate concentration-time profiles from linear pharmacokinetic (PK) systems, possibly with first-order absorption or zero-order infusion, possibly with one or more peripheral compartments, and possibly under steady-state conditions. Single or multiple doses may be specified. Secondary (derived) PK parameters (e.g. Cmax, Ctrough, AUC, Tmax, half-life, etc.) are computed.
License: GPL-3
Imports: graphics,utils,mvtnorm
Suggests: knitr,shiny
VignetteBuilder: knitr
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-06-07 16:30:43 UTC; brich
Author: Benjamin Rich [aut, cre]
Maintainer: Benjamin Rich <mail@benjaminrich.net>
Repository: CRAN
Date/Publication: 2018-06-12 10:33:53 UTC

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New package CaseBasedReasoning with initial version 0.1
Package: CaseBasedReasoning
Type: Package
Title: Case-Based Reasoning
Version: 0.1
Date: 2018-06-06
Author: Dr. Simon Mueller <simon.mueller@muon-stat.com>, PD Dr. Juergen Dippon <juergen.dippon@mathematik.uni-stuttgart.de>
Maintainer: Dr. Simon Mueller <simon.mueller@muon-stat.com>
Description: Given a large set of problems and their individual solutions case based reasoning seeks to solve a new problem by referring to the solution of that problem which is "most similar" to the new problem. Crucial in case based reasoning is the decision which problem "most closely" matches a given new problem. The basic idea is to define a family of distance functions and to use these distance functions as parameters of local averaging regression estimates of the final result. Then that distance function is chosen for which the resulting estimate is optimal with respect to a certain error measure used in regression estimation. The idea is based on: Dippon J. et al. (2002) <DOI:10.1016/S0167-9473(02)00058-0>.
BugReports: https://github.com/sipemu/case-based-reasoning/issues
License: AGPL
LazyData: TRUE
NeedsCompilation: yes
Imports: R6, ranger, survival, tidyverse, cowplot, dplyr, data.table, magrittr, rms, Rcpp, RcppParallel
Suggests: testthat, knitr, rmarkdown, RcppArmadillo
LinkingTo: Rcpp, RcppArmadillo, RcppParallel
SystemRequirements: C++11
LazyLoad: yes
ByteCompile: yes
VignetteBuilder: knitr
RoxygenNote: 6.0.1
Packaged: 2018-06-10 19:57:26 UTC; info
Repository: CRAN
Date/Publication: 2018-06-12 10:34:11 UTC

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Mon, 11 Jun 2018

New package rlas with initial version 1.2.4
Package: rlas
Type: Package
Title: Read and Write 'las' and 'laz' Binary File Formats Used for Remote Sensing Data
Version: 1.2.4
Date: 2018-05-10
Authors@R: c( person("Jean-Romain", "Roussel", email = "jean-romain.roussel.1@ulaval.ca", role = c("aut", "cre", "cph")), person("Florian", "De Boissieu", email = "", role = c("aut", "ctb"), comment = "Enable the support of .lax file and extra byte attributes"), person("Martin", "Isenburg", email = "", role = "cph", comment = "Is the author of the LASlib and LASzip libraries"), person("David", "Auty", email = "", role = c("ctb"), comment = "Reviewed the documentation"), person("Pierrick", "Marie", email = "", role = ("ctb"), comment = "Helped to compile LASlib code in R"))
Description: Read and write 'las' and 'laz' binary file formats. The LAS file format is a public file format for the interchange of 3-dimensional point cloud data between data users. The LAS specifications are approved by the American Society for Photogrammetry and Remote Sensing <https://www.asprs.org/committee-general/laser-las-file-format-exchange-activities.html>. The LAZ file format is an open and lossless compression scheme for binary LAS format versions 1.0 to 1.3 <https://www.laszip.org/>.
URL: https://github.com/Jean-Romain/rlas
BugReports: https://github.com/Jean-Romain/rlas/issues
License: GPL-3
Depends: R (>= 3.0.0)
Imports: data.table,Rcpp,uuid
LazyData: true
RoxygenNote: 6.0.1
LinkingTo: Rcpp
Suggests: testthat
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2018-06-11 02:31:47 UTC; jr
Author: Jean-Romain Roussel [aut, cre, cph], Florian De Boissieu [aut, ctb] (Enable the support of .lax file and extra byte attributes), Martin Isenburg [cph] (Is the author of the LASlib and LASzip libraries), David Auty [ctb] (Reviewed the documentation), Pierrick Marie [ctb] (Helped to compile LASlib code in R)
Maintainer: Jean-Romain Roussel <jean-romain.roussel.1@ulaval.ca>
Repository: CRAN
Date/Publication: 2018-06-11 09:10:52 UTC

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Sun, 10 Jun 2018

New package dexter with initial version 0.8.0
Package: dexter
Type: Package
Title: Data Management and Analysis of Tests
Version: 0.8.0
Author: Gunter Maris, Timo Bechger, Jesse Koops, Ivailo Partchev
Maintainer: Ivailo Partchev <partchev@gmail.com>
Description: A system for the management, assessment, and psychometric analysis of data from educational and psychological tests. Developed at Cito, The Netherlands, with subsidy from the Dutch Ministry of Education, Culture, and Science.
License: GPL-3
URL: dexterities.netlify.com
BugReports: https://github.com/jessekps/dexter/issues
Encoding: UTF-8
LazyLoad: yes
LazyData: yes
Depends: R (>= 3.3), RSQLite (>= 2.0)
Imports: DBI, tidyr (>= 0.8.0), tibble, colorspace, shiny, shinyBS, shinydashboard, DT, fastmatch, purrr (>= 0.2.3), rlang (>= 0.2.0), dplyr (>= 0.7.4), dbplyr (>= 1.2.0), rprintf, RColorBrewer, graphics, grDevices, methods, utils
RoxygenNote: 6.0.1
Suggests: knitr, rmarkdown, latticeExtra, testthat, calibrate, ggplot2, Cairo
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2018-06-08 20:37:34 UTC; ivailo
Repository: CRAN
Date/Publication: 2018-06-10 22:41:15 UTC

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New package erhcv with initial version 0.1.1
Package: erhcv
Type: Package
Title: Equi-Rank Hierarchical Clustering Validation
Version: 0.1.1
License: GPL (>= 2)
Author: Simon-Pierre Gadoury <spgadou@me.com>
Maintainer: Simon-Pierre Gadoury <spgadou@me.com>
Description: Assesses the statistical significance of clusters for a given dataset through bootstrapping and hypothesis testing of a given matrix of empirical Spearman's rho, based on the technique of S. Gaiser et al. (2010) <doi:10.1016/j.jmva.2010.07.008>.
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
Depends: R (>= 3.5.0)
Suggests: HAC, knitr, rmarkdown
Imports: igraph, stringr, stringi, utils, Rdpack
RdMacros: Rdpack
Collate: 'VerifyTree.R' 'ClusterNodeSelection.R' 'EliminateCluster.R' 'GetLeaves.R' 'GetPairs.R' 'hclust2tree.R' 'tree2plot.R'
NeedsCompilation: no
Packaged: 2018-06-08 11:06:14 UTC; Simon-Pierre
Repository: CRAN
Date/Publication: 2018-06-10 17:05:38 UTC

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New package trade with initial version 0.5.3
Package: trade
Type: Package
Title: Tools for Trade Practitioners
Version: 0.5.3
Author: Charles Taragin
Maintainer: Charles Taragin <charles.taragin@usdoj.gov>
Depends: antitrust
Imports: methods, stats
Suggests: shiny,bookdown,knitr, rhandsontable
VignetteBuilder: knitr
Description: A collection of tools for trade practitioners, including the ability to calibrate different consumer demand systems and simulate the effects of tariffs and quotas under different competitive regimes.
License: Unlimited
LazyLoad: yes
RoxygenNote: 6.0.1
Collate: 'QuotaClasses.R' 'TariffClasses.R' 'TariffCournot-methods.R' 'summary-methods.R' 'ps-methods.R' 'bertrand_quota.R' 'bertrand_tariff.R' 'cournot_tariff.R' 'initialize-methods.R' 'trade_shiny.R'
NeedsCompilation: no
Packaged: 2018-06-07 19:17:23 UTC; TaragIC
Repository: CRAN
Date/Publication: 2018-06-10 16:42:59 UTC

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New package mvMISE with initial version 1.0
Package: mvMISE
Title: A General Framework of Multivariate Mixed-Effects Selection Models
Version: 1.0
Date: 2018-06-04
Author: Jiebiao Wang and Lin S. Chen
Maintainer: Jiebiao Wang <randel.wang@gmail.com>
Description: Offers a general framework of multivariate mixed-effects models for the joint analysis of multiple correlated outcomes with clustered data structures and potential missingness proposed by Wang et al. (2018) <doi:10.1093/biostatistics/kxy022>. The missingness of outcome values may depend on the values themselves (missing not at random and non-ignorable), or may depend on only the covariates (missing at random and ignorable), or both. This package provides functions for two models: 1) mvMISE_b() allows correlated outcome-specific random intercepts with a factor-analytic structure, and 2) mvMISE_e() allows the correlated outcome-specific error terms with a graphical lasso penalty on the error precision matrix. Both functions are motivated by the multivariate data analysis on data with clustered structures from labelling-based quantitative proteomic studies. These models and functions can also be applied to univariate and multivariate analyses of clustered data with balanced or unbalanced design and no missingness.
License: GPL
Depends: lme4, MASS
URL: https://github.com/randel/mvMISE
BugReports: https://github.com/randel/mvMISE/issues
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-06-04 17:54:46 UTC; rande
Repository: CRAN
Date/Publication: 2018-06-10 16:47:54 UTC

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New package FILEST with initial version 1.0.3
Package: FILEST
Type: Package
Title: Fine-Level Structure Simulator
Version: 1.0.3
Authors@R: c(person(given = "Kridsadakorn", family = "Chaichoompu", email = "kridsadakorn@biostatgen.org", role = c("aut", "cre")),person(given = "Kristel", family = 'Van Steen', role = "aut"),person(given = "Fentaw", family = "Abegaz", role = "aut"))
Description: A population genetic simulator, which is able to generate synthetic datasets for single-nucleotide polymorphisms (SNP) for multiple populations. The genetic distances among populations can be set according to the Fixation Index (Fst) as explained in Balding and Nichols (1995) <doi:10.1007/BF01441146>. This tool is able to simulate outlying individuals and missing SNPs can be specified. For Genome-wide association study (GWAS), disease status can be set in desired level according risk ratio.
Depends: R (>= 3.2.4.0)
License: GPL-2 | GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
Imports: KRIS (>= 1.1.1),rARPACK,grDevices,stats,utils
Suggests: testthat
BugReports: https://gitlab.com/kris.ccp/filest/issues
URL: https://gitlab.com/kris.ccp/filest
NeedsCompilation: no
Packaged: 2018-06-07 08:40:28 UTC; kridsadakorn
Author: Kridsadakorn Chaichoompu [aut, cre], Kristel Van Steen [aut], Fentaw Abegaz [aut]
Maintainer: Kridsadakorn Chaichoompu <kridsadakorn@biostatgen.org>
Repository: CRAN
Date/Publication: 2018-06-10 16:12:58 UTC

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New package ratematrix with initial version 1.0
Package: ratematrix
Title: Bayesian Estimation of the Evolutionary Rate Matrix
Version: 1.0
Authors@R: c( person("Daniel", "Caetano", email = "caetanods1@gmail.com", role = c("aut", "cre")), person("Luke", "Harmon", email = "lukeh@uidaho.edu", role = "aut") )
Description: Estimates the evolutionary rate matrix (R) using Markov chain Monte Carlo (MCMC) as described in Caetano and Harmon (2017) <doi:10.1111/2041-210X.12826>. The package has functions to run MCMC chains, plot results, evaluate convergence, and summarize posterior distributions.
URL: https://github.com/Caetanods/ratematrix
License: GPL (>= 2.0)
Encoding: UTF-8
LazyData: true
Imports: ape, geiger, coda, corpcor, MASS, phylolm, readr, mvMORPH, Rcpp, ellipse
Suggests: microbenchmark, knitr, rmarkdown, phytools
VignetteBuilder: knitr
LinkingTo: Rcpp, RcppArmadillo
RoxygenNote: 6.0.1
NeedsCompilation: yes
Packaged: 2018-06-06 18:02:46 UTC; daniel
Author: Daniel Caetano [aut, cre], Luke Harmon [aut]
Maintainer: Daniel Caetano <caetanods1@gmail.com>
Depends: R (>= 2.10)
Repository: CRAN
Date/Publication: 2018-06-10 15:27:53 UTC

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New package PQLseq with initial version 1.0
Package: PQLseq
Type: Package
Title: Efficient Mixed Model Analysis of Count Data in Large-Scale Genomic Sequencing Studies
Version: 1.0
Date: 2018-06-02
Author: Shiquan Sun, Jiaqiang Zhu, Xiang Zhou
Maintainer: Shiquan Sun <shiquans@umich.edu>
Description: An efficient tool designed for differential analysis of large-scale RNA sequencing (RNAseq) data and Bisulfite sequencing (BSseq) data in the presence of individual relatedness and population structure. 'PQLseq' first fits a Generalized Linear Mixed Model (GLMM) with adjusted covariates, predictor of interest and random effects to account for population structure and individual relatedness, and then performs Wald tests for each gene in RNAseq or site in BSseq.
License: GPL (>= 2)
Imports: Rcpp (>= 0.12.14),foreach,doParallel,parallel,Matrix
LinkingTo: Rcpp,RcppArmadillo
NeedsCompilation: yes
Packaged: 2018-06-06 17:49:47 UTC; jiaqiang
Depends: R (>= 2.10)
Repository: CRAN
Date/Publication: 2018-06-10 15:22:54 UTC

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New package inplace with initial version 0.1.0
Package: inplace
Version: 0.1.0
Date: 2018-06-06
Title: In-place Operators for R
Description: It provides in-place operators for R that are equivalent to '+=', '-=', '*=', '/=' in C++. Those can be applied on integer|double vectors|matrices. You have also access to sweep operations (in-place).
Authors@R: person("Florian", "Privé", email = "florian.prive.21@gmail.com", role = c("aut", "cre"))
License: GPL-3
Language: en-US
Encoding: UTF-8
LazyData: true
ByteCompile: true
RoxygenNote: 6.0.1
LinkingTo: Rcpp
Imports: Rcpp
Suggests: spelling, data.table, testthat, covr
URL: https://github.com/privefl/inplace
BugReports: https://github.com/privefl/inplace/issues
NeedsCompilation: yes
Packaged: 2018-06-06 15:30:14 UTC; Florian
Author: Florian Privé [aut, cre]
Maintainer: Florian Privé <florian.prive.21@gmail.com>
Repository: CRAN
Date/Publication: 2018-06-10 15:13:01 UTC

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New package CMLS with initial version 1.0-0
Package: CMLS
Type: Package
Title: Constrained Multivariate Least Squares
Version: 1.0-0
Date: 2018-06-06
Author: Nathaniel E. Helwig <helwig@umn.edu>
Maintainer: Nathaniel E. Helwig <helwig@umn.edu>
Depends: quadprog, parallel
Description: Solves multivariate least squares (MLS) problems subject to constraints on the coefficients, e.g., non-negativity, orthogonality, equality, inequality, monotonicity, unimodality, smoothness, etc. Includes flexible functions for solving MLS problems subject to user-specified equality and/or inequality constraints, as well as a wrapper function that implements 24 common constraint options. Also does k-fold or generalized cross-validation to tune constraint options for MLS problems. See ten Berge (1993, ISBN:9789066950832) for an overview of MLS problems, and see Goldfarb and Idnani (1983) <doi:10.1007/BF02591962> for a discussion of the underlying quadratic programming algorithm.
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2018-06-06 17:19:23 UTC; Nate
Repository: CRAN
Date/Publication: 2018-06-10 15:17:57 UTC

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New package BHTSpack with initial version 0.1
Package: BHTSpack
Type: Package
Title: Bayesian Multi-Plate High-Throughput Screening of Compounds
Version: 0.1
Authors@R: c(person(c("Ivo", "D."), "Shterev", role = c("aut", "cre"), email = "i.shterev@duke.edu"), person(c("David", "B."), "Dunson", role = "aut"), person("Cliburn", "Chan", role = "aut"), person(c("Gregory", "D."), "Sempowski", role = "aut"))
Description: Can be used for joint identification of candidate compound hits from multiple assays, in drug discovery. This package implements the framework of I. D. Shterev, D. B. Dunson, C. Chan and G. D. Sempowski. "Bayesian Multi-Plate High-Throughput Screening of Compounds", Scientific Reports (to appear). This project was funded by the Division of Allergy, Immunology, and Transplantation, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Department of Health and Human Services, under contract No. HHSN272201400054C entitled "Adjuvant Discovery For Vaccines Against West Nile Virus and Influenza", awarded to Duke University and lead by Drs. Herman Staats and Soman Abraham.
Depends: R (>= 3.2.3), R2HTML (>= 2.3.2), xtable (>= 1.8-2)
VignetteBuilder: knitr
Suggests: knitr
License: GPL-3
LazyLoad: yes
NeedsCompilation: yes
Packaged: 2018-06-05 15:57:04 UTC; is33
Author: Ivo D. Shterev [aut, cre], David B. Dunson [aut], Cliburn Chan [aut], Gregory D. Sempowski [aut]
Maintainer: Ivo D. Shterev <i.shterev@duke.edu>
Repository: CRAN
Date/Publication: 2018-06-10 15:13:05 UTC

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New package xmlrpc2 with initial version 1.0
Package: xmlrpc2
Type: Package
Title: Implementation of the Remote Procedure Call Protocol ('XML-RPC')
Version: 1.0
Author: Florian Schwendinger [aut, cre]
Maintainer: Florian Schwendinger <FlorianSchwendinger@gmx.at>
Description: The 'XML-RPC' is a remote procedure call protocol based on 'XML'. The 'xmlrpc2' package is inspired by the 'XMLRPC' package but uses the 'curl' and 'xml2' packages instead 'RCurl' and 'XML'.
License: GPL-3
Imports: curl, xml2, base64enc
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-06-06 12:40:12 UTC; florian
Repository: CRAN
Date/Publication: 2018-06-10 14:57:58 UTC

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New package tuts with initial version 0.1.0
Package: tuts
Type: Package
Title: Time Uncertain Time Series Analysis
Version: 0.1.0
Date: 2018-05-09
Authors@R: c( person("Peter", "Franke", email = "peter.franke@ucdconnect.ie", role = c("aut","cre")), person("Andrew", "Parnell", role = c("aut")))
Description: Models of time-uncertain time series addressing frequency and non-frequency behavior of continuous and discrete (counting) data.
License: GPL (>= 2)
Depends: R (>= 3.4.0), rjags
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
Imports: coda, doParallel, foreach, lomb, mcmcplots, parallel, stats, truncnorm
NeedsCompilation: no
Packaged: 2018-06-09 22:18:24 UTC; Peter Max
Author: Peter Franke [aut, cre], Andrew Parnell [aut]
Maintainer: Peter Franke <peter.franke@ucdconnect.ie>
Repository: CRAN
Date/Publication: 2018-06-10 14:27:55 UTC

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New package StatCharrms with initial version 0.90.91
Package: StatCharrms
Version: 0.90.91
Date: 2018-6-05
Title: Statistical Analysis of Chemistry, Histopathology, and Reproduction Endpoints Including Repeated Measures and Multi-Generation Studies
Authors@R: c(person("Joe", "Swintek", role = c("aut", "cre"), email = "swintek.joe@epa.gov"), person("Kevin", "Flynn", role = "ctb", email = "Flynn.Kevin@epa.gov"), person("Jon", "Haselman", role = "ctb", email = "Haselman.Jon@epa.gov") )
Depends: R (>= 3.1.0)
Imports: RGtk2, R2HTML, gWidgets, gWidgetsRGtk2, multcomp, nlme, lattice, cairoDevice, car, clinfun, survival, coxme, methods, RSCABS
SystemRequirements: GTK+ (>= 2.8.0)
ByteCompile: no
LazyLoad: yes
LazyData: yes
Description: A front end for the statistical analyses involved in the tier II endocrine disruptor screening program. The analyses available to this package are: Rao-Scott adjusted Cochran-Armitage test for trend By Slices (RSCABS), a Standard Cochran-Armitage test for trend By Slices (SCABS), mixed effects Cox proportional model, Jonckheere-Terpstra step down trend test Dunn test, one way ANOVA, weighted ANOVA, mixed effects ANOVA, repeated measures ANOVA, and Dunnett test.
License: CC0
URL: https://CRAN.R-project.org/package=StatCharrms
Author: Joe Swintek [aut, cre], Kevin Flynn [ctb], Jon Haselman [ctb]
Maintainer: Joe Swintek <swintek.joe@epa.gov>
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-06-06 13:56:37 UTC; jswintek
Repository: CRAN
Date/Publication: 2018-06-10 14:58:01 UTC

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New package pseudorank with initial version 0.1.0
Package: pseudorank
Title: Pseudo-Ranks
Version: 0.1.0
Date: 2018-06-08
Authors@R: c(person("Martin Happ", role = c("aut", "cre"), email = "martin.happ@aon.at", comment = c(ORCID = "0000-0003-0009-2665")), person("Georg Zimmermann", role = "aut"), person("Arne C. Bathke", role = "aut"), person("Edgar Brunner", role = "aut"))
Maintainer: Martin Happ <martin.happ@aon.at>
Description: Efficient calculation of pseudo-ranks. In case of equal sample sizes, pseudo-ranks and mid-ranks are equal. When used for inference mid-ranks may lead to paradoxical results. Pseudo-ranks are in general not affected by such a problem. For details, see Brunner, E., Bathke A. C. and Konietschke, F: Rank- and Pseudo-Rank Procedures in Factorial Designs - Using R and SAS, Springer Verlag, to appear.
License: GPL-3
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.4.0)
Imports: Rcpp (>= 0.12.16)
LinkingTo: Rcpp
RoxygenNote: 6.0.1
NeedsCompilation: yes
Packaged: 2018-06-10 06:48:39 UTC; Martin
Author: Martin Happ [aut, cre] (<https://orcid.org/0000-0003-0009-2665>), Georg Zimmermann [aut], Arne C. Bathke [aut], Edgar Brunner [aut]
Repository: CRAN
Date/Publication: 2018-06-10 14:32:56 UTC

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New package mdsstat with initial version 0.1.0
Package: mdsstat
Type: Package
Title: Statistical Trending for Medical Devices Surveillance
Version: 0.1.0
Authors@R: person("Gary", "Chung", email="gchung05@gmail.com", role=c("aut", "cre"))
Maintainer: Gary Chung <gchung05@gmail.com>
Description: A collection of common statistical algorithms used in active surveillance of medical device events. Context includes post-market surveillance, pharmacovigilance, signal detection and trending, and regulatory reporting. Primary inputs are device-event time series. Outputs include trending results with the ability to run multiple algorithms at once. This package works well with the 'mds' package, but does not require it.
License: GPL-3
Encoding: UTF-8
LazyData: true
Depends: R (>= 2.10)
Imports: utils, stats, graphics, mds, lubridate
Suggests: testthat, knitr, rmarkdown
RoxygenNote: 6.0.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-06-06 11:50:54 UTC; Gary
Author: Gary Chung [aut, cre]
Repository: CRAN
Date/Publication: 2018-06-10 14:27:59 UTC

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New package GLMMadaptive with initial version 0.1-3
Package: GLMMadaptive
Title: Generalized Linear Mixed Models using Adaptive Gaussian Quadrature
Version: 0.1-3
Date: 2018-06-06
Author: Dimitris Rizopoulos <d.rizopoulos@erasmusmc.nl>
Maintainer: Dimitris Rizopoulos <d.rizopoulos@erasmusmc.nl>
Description: Fits generalized linear mixed models for a single grouping factor under maximum likelihood approximating the integrals over the random effects with an adaptive Gaussian quadrature rule; Jose C. Pinheiro and Douglas M. Bates (1995) <doi:10.1080/10618600.1995.10474663>.
Imports: MASS, nlme, parallel
Suggests: lattice
Encoding: UTF-8
LazyLoad: yes
LazyData: yes
License: GPL (>= 3)
URL: https://github.com/drizopoulos/GLMMadaptive
NeedsCompilation: no
Packaged: 2018-06-06 12:46:46 UTC; drizo
Repository: CRAN
Date/Publication: 2018-06-10 14:58:05 UTC

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New package AROC with initial version 1.0
Package: AROC
Type: Package
Title: Covariate-Adjusted Receiver Operating Characteristic Curve Inference
Version: 1.0
Date: 2018-05-30
Authors@R: c( person(given = "Maria Xose", family = "Rodriguez-Alvarez", email = "mxrodriguez@bcamath.org", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-1329-9238")), person(given = "Vanda", family = "Inacio de Carvalho", email = "Vanda.Inacio@ed.ac.uk", role = c("aut"), comment = c(ORCID = "0000-0001-8084-1616")))
Imports: stats, grDevices, graphics, splines, np, Matrix, Hmisc, MASS, moments
Description: Estimates the covariate-adjusted Receiver Operating Characteristic (AROC) curve and pooled (unadjusted) ROC curve by different methods. Inacio de Carvalho, V., and Rodriguez-Alvarez, M. X. (2018) <arXiv:1806.00473>.
License: GPL
NeedsCompilation: no
Packaged: 2018-06-06 13:15:24 UTC; mrodriguez
Author: Maria Xose Rodriguez-Alvarez [aut, cre] (<https://orcid.org/0000-0002-1329-9238>), Vanda Inacio de Carvalho [aut] (<https://orcid.org/0000-0001-8084-1616>)
Maintainer: Maria Xose Rodriguez-Alvarez <mxrodriguez@bcamath.org>
Repository: CRAN
Date/Publication: 2018-06-10 14:58:08 UTC

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Sat, 09 Jun 2018

New package tiler with initial version 0.2.0
Package: tiler
Version: 0.2.0
Title: Create Geographic and Non-Geographic Map Tiles
Description: Creates geographic map tiles from geospatial map files or non-geographic map tiles from simple image files. This package provides a tile generator function for creating map tile sets for use with packages such as 'leaflet'. In addition to generating map tiles based on a common raster layer source, it also handles the non-geographic edge case, producing map tiles from arbitrary images. These map tiles, which have a non-geographic, simple coordinate reference system (CRS), can also be used with 'leaflet' when applying the simple CRS option. Map tiles can be created from an input file with any of the following extensions: tif, grd and nc for spatial maps and png, jpg and bmp for basic images. This package requires 'Python' and the 'gdal' library for 'Python'. 'Windows' users are recommended to install 'OSGeo4W' (<https://trac.osgeo.org/osgeo4w/>) as an easy way to obtain the required 'gdal' support for 'Python'.
Authors@R: c(person("Matthew", "Leonawicz", email = "mfleonawicz@alaska.edu", role = c("aut", "cre")), person("Scenarios Network for Alaska and Arctic Planning", role = c("cph", "fnd")) )
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
ByteCompile: true
URL: https://github.com/leonawicz/tiler
BugReports: https://github.com/leonawicz/tiler/issues
SystemRequirements: Python (>= 2.7), python-gdal library (For Windows, gdal installed via OSGeo4W <https://trac.osgeo.org/osgeo4w/> recommended) clipboard
Suggests: testthat, knitr, rmarkdown, lintr, covr, jpeg, bmp
Imports: sp, rgdal, raster, png
VignetteBuilder: knitr
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-06-09 16:56:42 UTC; Matt
Author: Matthew Leonawicz [aut, cre], Scenarios Network for Alaska and Arctic Planning [cph, fnd]
Maintainer: Matthew Leonawicz <mfleonawicz@alaska.edu>
Repository: CRAN
Date/Publication: 2018-06-09 19:48:52 UTC

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New package Libra with initial version 1.6
Package: Libra
Type: Package
Title: Linearized Bregman Algorithms for Generalized Linear Models
Version: 1.6
Date: 2018-6-9
Author: Feng Ruan, Jiechao Xiong and Yuan Yao
Maintainer: Jiechao Xiong <xiongjiechao@pku.edu.cn>
Depends: R (>= 3.0), nnls
Suggests: lars, MASS, igraph
SystemRequirements: GNU Scientific Library (GSL)
Description: Efficient procedures for fitting the regularization path for linear, binomial, multinomial, Ising and Potts models with lasso, group lasso or column lasso(only for multinomial) penalty. The package uses Linearized Bregman Algorithm to solve the regularization path through iterations. Bregman Inverse Scale Space Differential Inclusion solver is also provided for linear model with lasso penalty.
License: GPL-2
URL: http://arxiv.org/abs/1406.7728
Packaged: 2018-06-09 12:44:00 UTC; jcxiong
NeedsCompilation: yes
Repository: CRAN
Date/Publication: 2018-06-09 19:48:57 UTC
RoxygenNote: 5.0.1

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New package bioacoustics with initial version 0.1.2
Package: bioacoustics
Type: Package
Title: Analyse Audio Recordings and Automatically Extract Animal Vocalizations
Version: 0.1.2
Authors@R: c(person("Jean", "Marchal", email = "jean.marchal@wavx.ca", role = c("aut","cre")), person("Francois", "Fabianek", email = "francois.fabianek@wavx.ca", role = "aut"), person("Christopher", "Scott", role = "aut"), person("Chris", "Corben", role = c("ctb", "cph"), email = "chris@hoarybat.com", comment = "Read ZC files, original C code"), person("Peter", "Wilson", role = c("ctb", "cph"), email = "peter@peterwilson.id.au", comment = "Read ZC files, original R code"), person(family = "Wildlife Acoustics, Inc.", role = c("ctb", "cph"), comment = "Read WAC files, original C code"), person(family = "WavX Inc.", role = "cph"))
Maintainer: Jean Marchal <jean.marchal@wavx.ca>
Description: Contains all the necessary tools to process audio recordings of various formats (e.g., WAV, WAC, MP3, ZC), filter noisy files, display audio signals, detect and extract automatically acoustic features for further analysis such as classification.
License: GPL-3
Encoding: UTF-8
LazyData: true
SystemRequirements: C++11, cmake
Depends: R (>= 3.3.0)
LinkingTo: Rcpp
Imports: htmltools, graphics, grDevices, methods, moments, Rcpp (>= 0.12.13), stringr, tools, tuneR (>= 1.3.0)
Suggests: knitr, rmarkdown
URL: https://github.com/wavx/bioacoustics/
BugReports: https://github.com/wavx/bioacoustics/issues/
NeedsCompilation: yes
RoxygenNote: 6.0.1
VignetteBuilder: knitr
Biarch: TRUE
Packaged: 2018-06-09 02:02:51 UTC; JEMAR270
Author: Jean Marchal [aut, cre], Francois Fabianek [aut], Christopher Scott [aut], Chris Corben [ctb, cph] (Read ZC files, original C code), Peter Wilson [ctb, cph] (Read ZC files, original R code), Wildlife Acoustics, Inc. [ctb, cph] (Read WAC files, original C code), WavX Inc. [cph]
Repository: CRAN
Date/Publication: 2018-06-09 06:22:12 UTC

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Thu, 07 Jun 2018

New package MPV with initial version 1.53
Package: MPV
Title: Data Sets from Montgomery, Peck and Vining
Version: 1.53
Author: W.J. Braun
Description: Most of this package consists of data sets from the textbook Introduction to Linear Regression Analysis (3rd ed), by Montgomery, Peck and Vining. Some additional data sets and functions are included.
Maintainer: W.J. Braun <john.braun@ubc.ca>
LazyLoad: true
LazyData: true
Depends: R (>= 2.0.1)
ZipData: no
License: Unlimited
NeedsCompilation: no
Packaged: 2018-06-07 16:40:54 UTC; braun
Repository: CRAN
Date/Publication: 2018-06-07 19:20:01 UTC

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Wed, 06 Jun 2018

New package plotlyGeoAssets with initial version 0.0.1
Package: plotlyGeoAssets
Title: Render 'Plotly' Maps without an Internet Connection
Version: 0.0.1
Authors@R: person("Carson", "Sievert", role = c("aut", "cre"), email = "cpsievert1@gmail.com", comment = c(ORCID = "0000-0002-4958-2844"))
Description: Includes 'JavaScript' files that allow 'plotly' maps to render without an internet connection.
Depends: R (>= 2.10)
Enhances: plotly
Suggests: testthat, htmltools
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
URL: https://github.com/cpsievert/plotlyGeoAssets
BugReports: https://github.com/cpsievert/plotlyGeoAssets/issues
NeedsCompilation: no
Packaged: 2018-05-31 21:18:58 UTC; cpsievert
Author: Carson Sievert [aut, cre] (<https://orcid.org/0000-0002-4958-2844>)
Maintainer: Carson Sievert <cpsievert1@gmail.com>
Repository: CRAN
Date/Publication: 2018-06-06 12:53:07 UTC

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New package sambia with initial version 0.1.0
Package: sambia
Type: Package
Title: A Collection of Techniques Correcting for Sample Selection Bias
Version: 0.1.0
Author: Norbert Krautenbacher, Kevin Strauss, Maximilian Mandl, Christiane Fuchs
Maintainer: Norbert Krautenbacher <norbert.krautenbacher@tum.de>
Description: A collection of various techniques correcting statistical models for sample selection bias is provided. In particular, the resampling-based methods "stochastic inverse-probability oversampling" and "parametric inverse-probability bagging" are placed at the disposal which generate synthetic observations for correcting classifiers for biased samples resulting from stratified random sampling. For further information, see the article Krautenbacher, Theis, and Fuchs (2017) <doi:10.1155/2017/7847531>. The methods may be used for further purposes where weighting and generation of new observations is needed.
License: GPL-3
LazyData: TRUE
RoxygenNote: 6.0.1.9000
NeedsCompilation: no
Packaged: 2018-06-04 14:15:39 UTC; norbertkrautenbacher
Imports: stats, mvtnorm, dplyr, smotefamily, e1071, ranger, pROC, FNN
Repository: CRAN
Date/Publication: 2018-06-06 11:27:57 UTC

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New package rtrek with initial version 0.1.0
Package: rtrek
Version: 0.1.0
Title: Datasets and Functions Relating to Star Trek
Description: Provides datasets related to the Star Trek fictional universe and functions for working with the data. The package also provides access to real world datasets based on the televised series and other related licensed media productions. It interfaces with Wikipedia (<https://www.wikipedia.org/>), the Star Trek API (STAPI) (<http://stapi.co/>), Memory Alpha (<http://memory-alpha.wikia.com/wiki/Portal:Main>), and Memory Beta (<http://memory-beta.wikia.com/wiki/Main_Page>) to retrieve data, metadata and other information relating to Star Trek. It also contains local datasets covering a variety of topics such as Star Trek universe species data, geopolitical data, and summary datasets resulting from text mining analyses of Star Trek novels. The package also provides functions for working with data from other Star Trek-related R data packages containing larger datasets not stored in 'rtrek'.
Authors@R: person("Matthew", "Leonawicz", email = "mfleonawicz@alaska.edu", role = c("aut", "cre"))
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
ByteCompile: true
URL: https://github.com/leonawicz/rtrek
BugReports: https://github.com/leonawicz/rtrek/issues
Depends: R (>= 3.4.0)
Suggests: testthat, knitr, rmarkdown, covr, leaflet, lintr, ggplot2, showtext, sysfonts, trekfont
Imports: magrittr, dplyr, jsonlite, purrr
VignetteBuilder: knitr
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-06-05 20:49:17 UTC; Matt
Author: Matthew Leonawicz [aut, cre]
Maintainer: Matthew Leonawicz <mfleonawicz@alaska.edu>
Repository: CRAN
Date/Publication: 2018-06-06 11:28:00 UTC

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New package rppo with initial version 1.0
Package: rppo
Title: Access the Global Plant Phenology Data Portal
URL: https://github.com/ropensci/rppo
BugReports: https://github.com/ropensci/rppo/issues
Version: 1.0
Authors@R: c( person("John","Deck", email = "jdeck88@gmail.com", role = c("aut", "cre")), person("Brian","Stucky",email = "stuckyb@flmnh.ufl.edu", role = "aut"), person("Ramona","Walls", email = "rwalls@cyverse.org", role = "aut"), person("Kjell", "Bolmgren", email = "Kjell.Bolmgren@slu.se", role = "aut"), person("Ellen", "Denny", email = "ellen@usanpn.org", role = "aut"), person("Robert","Guralnick", email = "rguralnick@flmnh.ufl.edu", role = "aut") )
Maintainer: John Deck <jdeck88@gmail.com>
Description: An R interface to the Global Plant Phenology Data Portal, which is accessible online at <https://www.plantphenology.org/>.
Depends: R (>= 3.4.0)
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1.9000
Imports: jsonlite, readr, plyr, httr
Suggests: testthat, knitr, rmarkdown, covr
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-06-05 23:44:09 UTC; jdeck
Author: John Deck [aut, cre], Brian Stucky [aut], Ramona Walls [aut], Kjell Bolmgren [aut], Ellen Denny [aut], Robert Guralnick [aut]
Repository: CRAN
Date/Publication: 2018-06-06 11:45:23 UTC

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New package RColetum with initial version 0.1.0
Package: RColetum
Type: Package
Title: Access your Coletum's Data from API
Version: 0.1.0
Authors@R: c( person("André", "Smaniotto", , "smaniotto@geosapiens.com.br", c("aut", "cre")), person("GeoSapiens", role = c("cph", "fnd")) )
Maintainer: André Smaniotto <smaniotto@geosapiens.com.br>
Description: Get your data (forms, structures, answers) from Coletum <https://coletum.com> to handle and analyse.
License: LGPL-3
URL: https://github.com/geo-sapiens/RColetum
BugReports: https://github.com/geo-sapiens/RColetum/issues
Encoding: UTF-8
LazyData: true
Imports: httr, jsonlite, dplyr, stats
RoxygenNote: 6.0.1
Suggests: testthat
NeedsCompilation: no
Packaged: 2018-06-05 17:39:34 UTC; andre
Author: André Smaniotto [aut, cre], GeoSapiens [cph, fnd]
Repository: CRAN
Date/Publication: 2018-06-06 11:17:59 UTC

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New package PxWebApiData with initial version 0.1.0
Package: PxWebApiData
Type: Package
Title: PX-Web Data by API
Version: 0.1.0
Date: 2018-06-04
Author: Øyvind Langsrud and Jan Bruusgaard
Maintainer: Øyvind Langsrud <oyl@ssb.no>
Depends: R (>= 3.0.0), httr, rjstat, jsonlite
Description: Function to read PX-Web data into R via API. The example code reads data from the three national statistical institutes, Statistics Norway, Statistics Sweden and Statistics Finland.
License: Apache License 2.0 | file LICENSE
Encoding: UTF-8
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-06-04 10:38:49 UTC; oyl
Repository: CRAN
Date/Publication: 2018-06-06 11:59:05 UTC

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New package kendallRandomWalks with initial version 0.9.2
Package: kendallRandomWalks
Title: Simulate and Visualize Kendall Random Walks and Related Distributions
Version: 0.9.2
Authors@R: person("Mateusz", "Staniak", email = "mateusz.staniak@math.uni.wroc.pl", role = c("aut", "cre"))
Description: Kendall random walks are a continuous-space Markov chains generated by the Kendall generalized convolution. This package provides tools for simulating these random walks and studying distributions related to them. For more information about Kendall random walks see Jasiulis-Gołdyn (2014) <arXiv:1412.0220>.
Depends: R (>= 3.3)
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: ggplot2, dplyr, tidyr, EnvStats, tibble, nleqslv
RoxygenNote: 6.0.1
Suggests: knitr, rmarkdown, testthat, covr
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-06-05 18:33:35 UTC; mtst
Author: Mateusz Staniak [aut, cre]
Maintainer: Mateusz Staniak <mateusz.staniak@math.uni.wroc.pl>
Repository: CRAN
Date/Publication: 2018-06-06 11:17:55 UTC

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New package ursa with initial version 3.8.8
Package: ursa
Type: Package
Title: Non-Interactive Spatial Tools for Raster Processing and Visualization
Version: 3.8.8
Author: Nikita Platonov
Maintainer: Nikita Platonov <platonov@sevin.ru>
Description: S3 classes and methods for manipulation with georeferenced raster data: reading/writing, processing, multi-panel visualization.
License: GPL (>= 2)
URL: https://github.com/nplatonov/ursa
BugReports: https://github.com/nplatonov/ursa/issues
Depends: R (>= 3.0.0)
Imports: utils, graphics, grDevices, stats, rgdal, png, jpeg
Suggests: proj4, sf (>= 0.6-1), raster, ncdf4, locfit, knitr, tcltk, sp, methods, fasterize, IRdisplay, caTools, ggmap
NeedsCompilation: yes
ByteCompile: no
Packaged: 2018-06-05 06:52:21 UTC; pl
Repository: CRAN
Date/Publication: 2018-06-06 10:36:01 UTC

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New package rERR with initial version 0.1
Package: rERR
Title: Excess Relative Risk Models
Version: 0.1
Author: Francesc Badia Roca (ISGlobal) <francesc.badia@isglobal.org>, David Moriña Soler (Catalan Institute of Oncology (ICO)-IDIBELL) <david.morina@uab.cat>
Description: Fits a linear excess relative risk model by maximum likelihood, possibly including several variables and allowing for lagged exposures. Allow time dependent covariates.
Depends: R (>= 3.5.0)
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
Imports: survival, stats4, plyr, dplyr, reshape2, numDeriv, ggplot2
Maintainer: Francesc Badia Roca <francesc.badia@isglobal.org>
Date: 2018-06-05
Suggests: testthat, knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2018-06-05 05:46:10 UTC; fbadia
Repository: CRAN
Date/Publication: 2018-06-06 10:30:02 UTC

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New package reclin with initial version 0.1.0
Package: reclin
Type: Package
Title: Record Linkage Toolkit
Version: 0.1.0
Date: 2018-06-04
Author: Jan van der Laan
Maintainer: Jan van der Laan <r@eoos.dds.nl>
Description: Functions to assist in performing probabilistic record linkage and deduplication: generating pairs, comparing records, em-algorithm for estimating m- and u-probabilities, forcing one-to-one matching. Can also be used for pre- and post-processing for machine learning methods for record linkage.
Depends: stats, lvec, ldat, R (>= 3.4.0)
Imports: dplyr, stringdist, utils, methods, lpSolve, Rcpp
Suggests: testthat, knitr, rmarkdown
LinkingTo: Rcpp
SystemRequirements: C++11
License: GPL-3
LazyLoad: yes
RoxygenNote: 6.0.1
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2018-06-05 06:51:45 UTC; dlan
Repository: CRAN
Date/Publication: 2018-06-06 10:36:11 UTC

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New package gustave with initial version 0.3.0
Package: gustave
Type: Package
Title: A User-Oriented Statistical Toolkit for Analytical Variance Estimation
Depends: R(>= 3.3.0)
Imports: Matrix, methods, stats, MASS
Suggests: testthat, sampling, vardpoor
Version: 0.3.0
Authors@R: person("Martin", "Chevalier", role = c("aut", "cre", "cph"), email = "martin.chevalier@insee.fr")
Author: Martin Chevalier [aut, cre, cph]
Maintainer: Martin Chevalier <martin.chevalier@insee.fr>
URL: https://github.com/martinchevalier/gustave
BugReports: https://github.com/martinchevalier/gustave/issues
Description: Provides a toolkit for analytical variance estimation in survey sampling. Apart from the implementation of standard variance estimators, its main feature is to help the sampling expert produce easy-to-use variance estimation "wrappers", where systematic operations (linearization, domain estimation) are handled in a consistent and transparent way for the end user.
License: GPL-3
Collate: 'data.R' 'utils.R' 'define_variance_wrapper.R' 'variance_function.R' 'define_linearization_wrapper.R' 'linearization_wrapper_standard.R'
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-06-05 10:13:41 UTC; gc004y
Repository: CRAN
Date/Publication: 2018-06-06 10:57:54 UTC

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New package BICORN with initial version 0.1.0
Package: BICORN
Title: Integrative Inference of De Novo Cis-Regulatory Modules
Version: 0.1.0
Authors@R: c(person("Xi", "Chen", email = "xichen86@vt.edu", role = c("aut", "cre")), person("Jianhua", "Xuan", email = "xuan@vt.edu", role = "aut"))
Description: Prior transcription factor binding knowledge and target gene expression data are integrated in a Bayesian framework for functional cis-regulatory module inference. Using Gibbs sampling, we iteratively estimate transcription factor associations for each gene, regulation strength for each binding event and the hidden activity for each transcription factor.
Depends: R (>= 3.4)
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
Suggests: knitr, rmarkdown
Imports: stats
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-06-04 19:37:06 UTC; xichen
Author: Xi Chen [aut, cre], Jianhua Xuan [aut]
Maintainer: Xi Chen <xichen86@vt.edu>
Repository: CRAN
Date/Publication: 2018-06-06 10:30:06 UTC

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New package AssetCorr with initial version 1.0.0
Package: AssetCorr
Type: Package
Title: Estimating Asset Correlations from Default Data
Version: 1.0.0
Date: 2018-06-04
Author: Maximilian Nagl [aut,cre], Yevhen Havrylenko [aut], Marius Pfeuffer [aut], Kevin Jakob [aut], Matthias Fischer [aut], Daniel Roesch [aut]
Maintainer: Maximilian Nagl <maximilian.nagl@ur.de>
Description: Functions for the estimation of intra- and inter-cohort correlations in the Vasicek credit portfolio model. For intra-cohort correlations, the package covers the two method of moments estimators of Gordy (2000) <doi:10.1016/S0378-4266(99)00054-0>, the method of moments estimator of Lucas (1995) <doi:10.3905/jfi.1995.408124> and a Binomial approximation extension of this approach. Moreover, the maximum likelihood estimators of Gordy and Heitfield (2010) <http://elsa.berkeley.edu/~mcfadden/e242_f03/heitfield.pdf> and Duellmann and Gehde-Trapp (2004) <http://hdl.handle.net/10419/19729> are implemented. For inter-cohort correlations, the method of moments estimator of Bluhm and Overbeck (2003) <doi:10.1007/978-3-642-59365-9_2>/Bams et al. (2016) <https://ssrn.com/abstract=2676595> is provided and the maximum likelihood estimators comprise the approaches of Gordy and Heitfield (2010)/Kalkbrener and Onwunta (2010) <ISBN: 978-1906348250> and Pfeuffer et al. (2018). Bootstrap and Jackknife procedures for bias correction are included as well as the method of moments estimator of Frei and Wunsch (2018) <doi:10.21314/JCR.2017.231> for auto-correlated time series.
VignetteBuilder: knitr
License: GPL-3
Imports: VineCopula, mvtnorm, bootstrap, stats4, boot, numDeriv, mvQuad, ggplot2, methods, Rdpack, knitr,grid
RdMacros: Rdpack
NeedsCompilation: no
Packaged: 2018-06-05 04:58:03 UTC; maximiliannagl
Repository: CRAN
Date/Publication: 2018-06-06 10:30:09 UTC

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New package pds3 with initial version 0.5.0
Package: pds3
Version: 0.5.0
Title: Manipulate PDS3 ODL Files
Description: Reads Planetary Data Systems v3 (PDS3 - <https://pds.jpl.nasa.gov/>) Object Description Language (ODL) formatted files, typically used in NASA missions for storing metadata about observations.
Authors@R: person("Micah", "Waldstein", , "micah@waldste.in", c("aut", "cre"))
License: GPL-3
Encoding: UTF-8
LazyData: true
ByteCompile: true
Depends: R (>= 3.5.0)
Suggests: testthat, covr, lintr, knitr, curl, rmarkdown
Imports: rly
RoxygenNote: 6.0.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-06-04 15:13:44 UTC; micah
Author: Micah Waldstein [aut, cre]
Maintainer: Micah Waldstein <micah@waldste.in>
Repository: CRAN
Date/Publication: 2018-06-06 09:02:55 UTC

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New package CREAM with initial version 1.1.1
Package: CREAM
Type: Package
Title: Clustering of Genomic Regions Analysis Method
Version: 1.1.1
Date: 2018-05-30
Authors@R: c( person("Seyed Ali", "Madani Tonekaboni", , email = "ali.madanitonekaboni@mail.utoronto.ca", role = c("aut")), person("Victor", "Kofia", , email = "victor.kofia@uhnresearch.ca", role = c("aut")), person("Mathieu", "Lupien", , email = "mlupien@uhnres.utoronto.ca", role = c("aut")), person("Benjamin", "Haibe-Kains", , email = "benjamin.haibe.kains@utoronto.ca", role = c("aut", "cre")) )
Description: Provides a new method for identification of clusters of genomic regions within chromosomes. Primarily, it is used for calling clusters of cis-regulatory elements (COREs). 'CREAM' uses genome-wide maps of genomic regions in the tissue or cell type of interest, such as those generated from chromatin-based assays including DNaseI, ATAC or ChIP-Seq. 'CREAM' considers proximity of the elements within chromosomes of a given sample to identify COREs in the following steps: 1) It identifies window size or the maximum allowed distance between the elements within each CORE, 2) It identifies number of elements which should be clustered as a CORE, 3) It calls COREs, 4) It filters the COREs with lowest order which does not pass the threshold considered in the approach.
License: GPL (>= 3)
Imports: stats, utils
Depends: R (>= 3.3)
URL: https://github.com/bhklab/CREAM
Suggests: testthat
RoxygenNote: 6.0.1
LazyData: true
biocViews: PeakDetection, FunctionalPrediction, BiomedicalInformatics, Clustering
BugReports: https://github.com/bhklab/CREAM/issues
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2018-06-04 13:45:12 UTC; root
Author: Seyed Ali Madani Tonekaboni [aut], Victor Kofia [aut], Mathieu Lupien [aut], Benjamin Haibe-Kains [aut, cre]
Maintainer: Benjamin Haibe-Kains <benjamin.haibe.kains@utoronto.ca>
Repository: CRAN
Date/Publication: 2018-06-06 09:07:56 UTC

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New package cloudml with initial version 0.5.0
Package: cloudml
Title: Interface to the Google Cloud Machine Learning Platform
Version: 0.5.0
Authors@R: c( person("Javier", "Luraschi", email = "javier@rstudio.com", role = c("aut", "cre")), person("JJ", "Allaire", role = c("aut")), person("Kevin", "Ushey", role = c("aut")), person(family = "RStudio", role = c("cph")) )
Description: Interface to the Google Cloud Machine Learning Platform <https://cloud.google.com/ml-engine>, which provides cloud tools for training machine learning models.
Depends: R (>= 3.3.0), tfruns (>= 1.3)
Imports: jsonlite, packrat, processx, rprojroot, rstudioapi, tools, utils, withr, yaml, config
Suggests: tensorflow (>= 1.4.2), keras (>= 2.1.2), knitr, testthat
License: Apache License 2.0
SystemRequirements: Python (>= 2.7.0)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-06-04 15:46:21 UTC; javierluraschi
Author: Javier Luraschi [aut, cre], JJ Allaire [aut], Kevin Ushey [aut], RStudio [cph]
Maintainer: Javier Luraschi <javier@rstudio.com>
Repository: CRAN
Date/Publication: 2018-06-06 09:02:58 UTC

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New package AGHmatrix with initial version 0.0.4
Package: AGHmatrix
Title: Relationship Matrices for Diploid and Autopolyploid Species
Version: 0.0.4
Date: 2018-05-31
Description: Computation of A (pedigree), G (genomic-base), and H (A corrected by G) relationship matrices for diploid and autopolyploid species considering additive and non-additive effects as in Amadeu et al (2016) <doi:10.3835/plantgenome2016.01.0009>.
Authors@R: c(person("Rodrigo","Amadeu", role = c("aut","cre"), email = "rramadeu@ufl.edu"), person("Catherine", "Cellon", role = "ctb"), person("Leticia", "Lara", role = "ctb"), person("Marcio", "Resende", role = "ctb"), person("Ivone", "Oliveira", role = "ctb"), person("Luis", "Ferrao", role = "ctb"), person("Patricio", "Munoz", role = "ctb"), person("Augusto", "Garcia", role = "ctb"))
Author: Rodrigo Amadeu [aut, cre], Catherine Cellon [ctb], Leticia Lara [ctb], Marcio Resende [ctb], Ivone Oliveira [ctb], Luis Ferrao [ctb], Patricio Munoz [ctb], Augusto Garcia [ctb]
Imports: Matrix (>= 1.2-7.1)
Suggests: knitr, MASS, rmarkdown
VignetteBuilder: knitr
Encoding: UTF-8
License: GPL-3
URL: http://github.com/prmunoz/AGHmatrix
Maintainer: Rodrigo Amadeu <rramadeu@ufl.edu>
RoxygenNote: 6.0.1
NeedsCompilation: yes
Packaged: 2018-06-04 15:33:26 UTC; rramadeu
Repository: CRAN
Date/Publication: 2018-06-06 09:03:01 UTC

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New package tiler with initial version 0.1.6
Package: tiler
Version: 0.1.6
Title: Create Geographic and Non-Geographic Map Tiles
Description: Creates geographic map tiles from geospatial map files or non-geographic map tiles from simple image files. This package provides a tile generator function for creating map tile sets for use with packages such as 'leaflet'. In addition to generating map tiles based on a common raster layer source, it also handles the non-geographic edge case, producing map tiles from arbitrary images. These map tiles, which have a non-geographic, simple coordinate reference system (CRS), can also be used with 'leaflet' when applying the simple CRS option. Map tiles can be created from a input file with any of the following extensions: tif, grd and nc for spatial maps and png, jpg and bmp for basic images. This package requires 'Python' and the 'gdal' library for 'Python'. 'Windows' users are recommended to install 'OSGeo4W' (<https://trac.osgeo.org/osgeo4w/>) as an easy way to obtain the required 'gdal' support for 'Python'.
Authors@R: c(person("Matthew", "Leonawicz", email = "mfleonawicz@alaska.edu", role = c("aut", "cre")), person("Scenarios Network for Alaska and Arctic Planning", role = c("cph", "fnd")) )
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
ByteCompile: true
URL: https://github.com/leonawicz/tiler
BugReports: https://github.com/leonawicz/tiler/issues
SystemRequirements: Python (>= 2.7), python-gdal library (For Windows, gdal installed via OSGeo4W <https://trac.osgeo.org/osgeo4w/> recommended) clipboard
Suggests: testthat, knitr, rmarkdown, lintr, covr
Imports: sp, rgdal, raster
VignetteBuilder: knitr
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-06-04 13:59:46 UTC; Matt
Author: Matthew Leonawicz [aut, cre], Scenarios Network for Alaska and Arctic Planning [cph, fnd]
Maintainer: Matthew Leonawicz <mfleonawicz@alaska.edu>
Repository: CRAN
Date/Publication: 2018-06-06 08:52:57 UTC

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New package iptmnetr with initial version 0.1.2
Package: iptmnetr
Type: Package
Title: Interface to the 'iPTMnet' API
Version: 0.1.2
Author: Sachin Gavali
Maintainer: Sachin Gavali <saching@udel.edu>
Description: Provides an R interface to the 'iPTMnet' database REST API, which can be used to retrieve Post Translational Modification (PTM) data in systems biology context. This package handles all the aspects of communicating with the API, which involve sending the request, checking the error codes and parsing the response in a format that is ready to integrate into existing workflows.
License: MIT + file LICENSE
URL: https://research.bioinformatics.udel.edu/iptmnet/, https://github.com/udel-cbcb/iptmnetr
Encoding: UTF-8
LazyData: true
Suggests: testthat
Imports: httr, jsonlite
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-06-04 14:35:52 UTC; Lenovo
Repository: CRAN
Date/Publication: 2018-06-06 08:57:58 UTC

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New package bjscrapeR with initial version 0.1.0
Package: bjscrapeR
Type: Package
Title: An API Wrapper for the Bureau of Justice Statistics (BJS)
Version: 0.1.0
Authors@R: person("Dylan", "McDowell", email = "dylan.mcdowell226@gmail.com", role = c("aut", "cre"))
Description: Drawing heavy influence from 'blscrapeR', this package scrapes crime data from <https://www.bjs.gov/>. Specifically, it scrapes data from the National Crime Victimization Survey which tracks personal and household crime in the USA. The idea is to utilize the 'tidyverse' methodology to create an efficient work flow when dealing with crime statistics.
Depends: R (>= 3.4.0)
Imports: readr, dplyr, glue, tibble
License: MIT + file LICENSE
URL: https://github.com/dylanjm/bjscrapeR
BugReports: https://github.com/dylanjm/bjscrapeR/issues
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1.9000
NeedsCompilation: no
Packaged: 2018-06-04 14:01:29 UTC; DJM
Author: Dylan McDowell [aut, cre]
Maintainer: Dylan McDowell <dylan.mcdowell226@gmail.com>
Repository: CRAN
Date/Publication: 2018-06-06 08:53:01 UTC

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Tue, 05 Jun 2018

New package powerCompRisk with initial version 1.0.1
Package: powerCompRisk
Type: Package
Title: Power Analysis Tool for Joint Testing Hazards with Competing Risks Data
Version: 1.0.1
Date: 2018-06-15
Author: Qing Yang[aut], Wing K. Fung[aut], Eric Kawaguchi[ctb], Gang Li[aut, cre]
Maintainer: Eric Kawaguchi <erickawaguchi@ucla.edu>
Depends: R (>= 3.1.0), mvtnorm, stats
Description: A power analysis tool for jointly testing the cause-1 cause-specific hazard and the any-cause hazard with competing risks data.
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-06-05 20:44:11 UTC; erickawaguchi
Repository: CRAN
Date/Publication: 2018-06-05 21:24:38 UTC

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New package frailtySurv with initial version 1.3.3
Title: General Semiparametric Shared Frailty Model
Priority: optional
Type: Package
Package: frailtySurv
Version: 1.3.3
Date: 2018-06-01
Authors@R: c(person("Vinnie Monaco", role = c("aut", "cre"), email = "contact@vmonaco.com"), person("Malka Gorfine", role = "aut", email = "gorfinem@post.tau.ac.il"), person("Li Hsu", role = "aut", email = "lih@fredhutch.org"))
Maintainer: Vinnie Monaco <contact@vmonaco.com>
Description: Simulates and fits semiparametric shared frailty models under a wide range of frailty distributions using a consistent and asymptotically-normal estimator. Currently supports: gamma, power variance function, log-normal, and inverse Gaussian frailty models.
License: LGPL-2
URL: https://github.com/vmonaco/frailtySurv/
BugReports: https://github.com/vmonaco/frailtySurv/issues
Depends: R (>= 3.0.0), survival
Imports: stats, nleqslv, reshape2, ggplot2, numDeriv
Suggests: knitr, parallel, gridExtra
NeedsCompilation: yes
LinkingTo: Rcpp
LazyData: Yes
LazyLoad: Yes
ByteCompile: Yes
Repository: CRAN
RoxygenNote: 5.0.1
Packaged: 2018-06-05 16:22:38 UTC; vinnie
Author: Vinnie Monaco [aut, cre], Malka Gorfine [aut], Li Hsu [aut]
Date/Publication: 2018-06-05 17:25:15 UTC

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New package randomizeR with initial version 1.4.1
Package: randomizeR
Title: Randomization for Clinical Trials
Version: 1.4.1
Date: 2018-06-01
Authors@R: c( person(given="David", family="Schindler", email="dschindler@ukaachen.de", role="aut"), person(given="Diane", family="Uschner", email="duschner@ukaachen.de", role=c("aut","cre")), person(given="Martin", family="Manolov", email="martin.manolov@rwth-aachen.de", role="ctb"), person(given="Thi Mui", family="Pham", email="thi.mui.pham@rwth-aachen.de", role="ctb"), person(given="Ralf-Dieter", family="Hilgers", email="rhilgers@ukaachen.de", role=c("aut","ths")), person(given="Nicole", family="Heussen", email="nheussen@ukaachen.de", role=c("aut","ths")) )
Description: This tool enables the user to choose a randomization procedure based on sound scientific criteria. It comprises the generation of randomization sequences as well the assessment of randomization procedures based on carefully selected criteria. Furthermore, 'randomizeR' provides a function for the comparison of randomization procedures.
Depends: R (>= 3.3.0), methods, ggplot2, plotrix
License: GPL (>= 3)
LazyData: true
Collate: 'getDesign.R' 'randPar.R' 'abcdPar.R' 'randSeq.R' 'abcdSeq.R' 'getExpectation.R' 'normEndp.R' 'endpoint.R' 'util.R' 'getStat.R' 'power.R' 'imbalance.R' 'corGuess.R' 'doublyF.R' 'testDec.R' 'doublyT.R' 'chronBias.R' 'selBias.R' 'bias.R' 'issue.R' 'assess.R' 'bbcdPar.R' 'bbcdSeq.R' 'ebcPar.R' 'bsdPar.R' 'bsdSeq.R' 'chenPar.R' 'chenSeq.R' 'chronBiasStepT.R' 'combinedBias.R' 'compare.R' 'crPar.R' 'crSeq.R' 'createParam.R' 'derFunc.R' 'desFunc.R' 'getDesFunc.R' 'derringerLs.R' 'derringerRs.R' 'derringerTs.R' 'desScores.R' 'desirability.R' 'ebcSeq.R' 'evaluate.R' 'gbcdPar.R' 'gbcdSeq.R' 'hadaPar.R' 'hadaSeq.R' 'mpPar.R' 'mpSeq.R' 'pbrPar.R' 'pbrSeq.R' 'probUnDes.R' 'rtbdSeq.R' 'rpbrSeq.R' 'randomBlockSeq.R' 'randomizeROverview.R' 'randomizeRPackage.R' 'rarPar.R' 'rarSeq.R' 'rpbrPar.R' 'tbdPar.R' 'rtbdPar.R' 'saveAssess.R' 'saveRand.R' 'tbdSeq.R' 'udPar.R' 'udSeq.R'
Suggests: testthat, knitr
VignetteBuilder: knitr
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-06-04 16:21:11 UTC; martin
Author: David Schindler [aut], Diane Uschner [aut, cre], Martin Manolov [ctb], Thi Mui Pham [ctb], Ralf-Dieter Hilgers [aut, ths], Nicole Heussen [aut, ths]
Maintainer: Diane Uschner <duschner@ukaachen.de>
Repository: CRAN
Date/Publication: 2018-06-05 14:32:04 UTC

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New package FIAR with initial version 0.6
Package: FIAR
Type: Package
Title: Functional Integration Analysis in R
Version: 0.6
Author: Bjorn Roelstraete
Maintainer: Bjorn Roelstraete <Bjornroelstraete@gmail.com>
Description: Contains Dynamic Causal Models (DCM), Autoregressive Structural Equation Models (ARSEM), and multivariate partial and conditional Granger causality tests for analysing fMRI connectivity data.
Depends: lavaan, Matrix, np
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
NeedsCompilation: yes
Packaged: 2018-06-05 09:44:52 UTC; Bjorn
Repository: CRAN
Date/Publication: 2018-06-05 11:48:21 UTC

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Mon, 04 Jun 2018

New package gdm with initial version 1.3.10
Package: gdm
Type: Package
Title: Generalized Dissimilarity Modeling
Version: 1.3.10
Date: 2018-06-04
Author: Glenn Manion, Matthew Lisk, Simon Ferrier, Diego Nieto-Lugilde, Karel Mokany, Matthew C. Fitzpatrick
Maintainer: Matthew C. Fitzpatrick <mfitzpatrick@umces.edu>
Description: A toolkit with functions to fit, plot, and summarize Generalized Dissimilarity Models (Ferrier et al. 2007, <doi:10.1111/j.1472-4642.2007.00341.x>).
License: GPL-2
Depends: R (>= 2.15.2), raster, foreach, doParallel, parallel
LinkingTo: Rcpp
Imports: Rcpp (>= 0.10.4), reshape2, vegan
Suggests: R.rsp
VignetteBuilder: R.rsp
NeedsCompilation: yes
Packaged: 2018-06-04 18:34:03 UTC; mlisk
Repository: CRAN
Date/Publication: 2018-06-04 21:54:27 UTC

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New package rwc with initial version 1.11
Package: rwc
Type: Package
Title: Random Walk Covariance Models
Version: 1.11
Date: 2018-06-04
Author: Ephraim M. Hanks
Depends: R (>= 2.10), raster, Matrix, mvtnorm, MASS
Maintainer: Ephraim M. Hanks <hanks@psu.edu>
Description: Code to facilitate simulation and inference when connectivity is defined by underlying random walks. Methods for spatially-correlated pairwise distance data are especially considered. This provides core code to conduct analyses similar to that in Hanks and Hooten (2013) <doi:10.1080/01621459.2012.724647>.
License: GPL-2
NeedsCompilation: no
Packaged: 2018-06-04 17:32:33 UTC; ephraim
Repository: CRAN
Date/Publication: 2018-06-04 18:23:43 UTC

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New package ssh with initial version 0.2
Package: ssh
Type: Package
Title: Secure Shell (SSH) Client for R
Version: 0.2
Author: Jeroen Ooms
Maintainer: Jeroen Ooms <jeroen@berkeley.edu>
Description: Connect to a remote server over SSH to transfer files via SCP, setup a secure tunnel, or run a command or script on the host while streaming stdout and stderr directly to the client.
License: MIT + file LICENSE
Encoding: UTF-8
SystemRequirements: libssh (the original, not libssh2)
RoxygenNote: 6.0.1.9000
Imports: getPass
Suggests: knitr, rmarkdown, spelling, sys, testthat, mongolite
Language: en-GB
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2018-05-26 22:40:40 UTC; jeroen
Repository: CRAN
Date/Publication: 2018-06-04 17:43:04 UTC

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New package GREP2 with initial version 0.99.9
Package: GREP2
Type: Package
Title: GEO RNA-Seq Experiments Processing Pipeline
Version: 0.99.9
Authors@R: c(person("Naim Al", "Mahi", role = c("cre", "aut"), email = "mahina@mail.uc.edu"), person("Mario", "Medvedovic", role = c("aut", "ctb")))
Maintainer: Naim Al Mahi <mahina@mail.uc.edu>
Description: An R based pipeline to download and process Gene Expression Omnibus (GEO) RNA-seq data. For a given GEO series accession ID, this pipeline generates metadata, both gene and transcript level counts, and quality control (QC) report.
Depends: R (>= 3.4.0)
Imports: XML, rentrez, RCurl, GEOquery, Biobase, parallel, tximport, EnsDb.Hsapiens.v86, EnsDb.Rnorvegicus.v79, EnsDb.Mmusculus.v79, AnnotationDbi, org.Hs.eg.db, org.Mm.eg.db, org.Rn.eg.db, GenomicFeatures, utils
Suggests: knitr, rmarkdown
SystemRequirements: SRAtoolkit, Salmon, Java, FastQC, MultiQC
URL: https://github.com/uc-bd2k/GREP2
BugReports: https://github.com/uc-bd2k/GREP2/issues
License: GPL-3
VignetteBuilder: knitr
LazyData: true
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-06-03 00:36:25 UTC; naim
Author: Naim Al Mahi [cre, aut], Mario Medvedovic [aut, ctb]
Repository: CRAN
Date/Publication: 2018-06-04 17:44:00 UTC

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New package rcane with initial version 1.0
Package: rcane
Type: Package
Title: Different Numeric Optimizations to Estimate Parameter Coefficients
Version: 1.0
Date: 2018-06-01
Author: Akshay Suresh, Siddhesh Acharekar, Hsiangwei Chao, Shiva Yogi Biradar
Maintainer: Akshay Suresh<suresh.aks@husky.neu.edu>
Description: There are different numeric optimizations which are used in order to estimate coefficients in models such as linear regression and neural networks. This package covers parameter estimation in linear regression using different methods such as batch gradient descent, stochastic gradient descent, minibatch gradient descent and coordinate descent. Kiwiel, Krzysztof C (2001) <doi:10.1007/PL00011414> Yu Nesterov (2004) <ISBN:1-4020-7553-7> Ferguson, Thomas S (1982) <doi:10.1080/01621459.1982.10477894> Zeiler, Matthew D (2012) <arXiv:1212.5701> Wright, Stephen J (2015) <arXiv:1502.04759>.
License: MIT + file LICENSE
RoxygenNote: 6.0.1.9000
Suggests: testthat, knitr, rmarkdown, stats
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-06-01 16:16:00 UTC; sures
Repository: CRAN
Date/Publication: 2018-06-04 09:03:22 UTC

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New package AdaSampling with initial version 1.0
Package: AdaSampling
Type: Package
Title: Adaptive Sampling for Positive Unlabeled and Label Noise Learning
Version: 1.0
Author: Pengyi Yang & Dinuka Perera
Maintainer: Pengyi Yang <yangpy7@gmail.com>
Description: Implements the adaptive sampling procedure, a framework for both positive unlabeled learning and learning with class label noise. Yang, P., Ormerod, J., Liu, W., Ma, C., Zomaya, A., Yang, J. (2018) <doi:10.1109/TCYB.2018.2816984>.
License: GPL-3
Encoding: UTF-8
Depends: R (>= 3.4.0)
LazyData: true
Imports: caret (>= 6.0-78) , class (>= 7.3-14), e1071 (>= 1.6-8), stats, MASS
BugReports: https://github.com/PengyiYang/AdaSampling/issues
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
URL: https://github.com/PengyiYang/AdaSampling/
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-06-01 22:01:42 UTC; pengyiyang
Repository: CRAN
Date/Publication: 2018-06-04 09:19:52 UTC

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New package wISAM with initial version 0.2.8
Package: wISAM
Type: Package
Title: Weighted Inbred Strain Association Mapping
Version: 0.2.8
Author: Robert W. Cort <rcorty@gmail.com>
Maintainer: Robert W. Cort <rcorty@gmail.com>
Description: In the course of a genome-wide association study, the situation often arises that some phenotypes are known with greater precision than others. It could be that some individuals are known to harbor more micro-environmental variance than others. In the case of inbred strains of model organisms, it could be the case that more organisms were observed from some strains than others, so the strains with more organisms have better-estimated means. Package 'wISAM' handles this situation by allowing for weighting of each observation according to residual variance. Specifically, the 'weight' parameter to the function conduct_scan() takes the precision of each observation (one over the variance).
License: GPL-3
Encoding: UTF-8
Depends: R (>= 3.0.0)
LazyData: true
Suggests: testthat
RoxygenNote: 6.0.1
Imports: methods, MASS
NeedsCompilation: no
Packaged: 2018-05-31 17:18:15 UTC; rcorty
Repository: CRAN
Date/Publication: 2018-06-04 08:12:54 UTC

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New package spacesRGB with initial version 1.0-4
Package: spacesRGB
Type: Package
Title: Standard and User-Defined RGB Color Spaces, with Conversion Between RGB and CIE XYZ
Version: 1.0-4
Encoding: UTF-8
Date: 2018-05-31
Author: Glenn Davis [aut,cre]
Maintainer: Glenn Davis <gdavis@gluonics.com>
Description: Standard RGB spaces included are sRGB, 'Adobe' RGB, and 'ProPhoto' RGB. User-defined RGB spaces are also possible.
License: GPL (>= 3)
LazyLoad: yes
LazyData: yes
Depends: R (>= 2.13.0)
Suggests: microbenchmark
Repository: CRAN
NeedsCompilation: no
Packaged: 2018-06-01 00:56:07 UTC; Glenn
Date/Publication: 2018-06-04 08:47:57 UTC

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New package readabs with initial version 0.2.1
Package: readabs
Type: Package
Title: Read 'Excel' Files from the Australian Bureau of Statistics into Tidy Data Sets
Version: 0.2.1
Authors@R: c( person("Zoe", "Meers", role = c("aut", "cre"), email = "zoe.meers@sydney.edu.au"), person("Jaron", "Lee", role = c("aut"), email = "jaron.lee@sydney.edu.au"))
Maintainer: Zoe Meers <zoe.meers@sydney.edu.au>
Description: Reads files from the Australian Bureau of Statistics <https://www.abs.gov.au/> into clean, tidy data sets.
Date: 2018-05-30
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: readxl, dplyr, tidyr, sjmisc, rsdmx, readr, stringr
URL: https://github.com/zmeers/readabs
BugReports: https://github.com/zmeers/readabs/issues
RoxygenNote: 6.0.1
VignetteBuilder: knitr
Suggests: knitr, rmarkdown, testthat
NeedsCompilation: no
Packaged: 2018-05-31 23:59:33 UTC; zmeers
Author: Zoe Meers [aut, cre], Jaron Lee [aut]
Repository: CRAN
Date/Publication: 2018-06-04 08:37:55 UTC

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New package nnTensor with initial version 0.99.1
Package: nnTensor
Type: Package
Title: Non-Negative Tensor Decomposition
Version: 0.99.1
Date: 2018-06-01
Author: Koki Tsuyuzaki, Manabu Ishii, Itoshi Nikaido
Maintainer: Koki Tsuyuzaki <k.t.the-answer@hotmail.co.jp>
Suggests: testthat
Depends: R (>= 3.4.0), fields, rTensor, plot3D, tagcloud
Imports: methods
Description: Some functions for performing non-negative matrix factorization, non-negative CANDECOMP/PARAFAC (CP) decomposition, non-negative Tucker decomposition, and generating toy model data. See Andrzej Cichock et al (2009) <doi:10.1002/9780470747278> and the reference section of GitHub README.md <https://github.com/rikenbit/nnTensor>, for details of the methods.
License: Artistic-2.0
URL: https://github.com/rikenbit/nnTensor
NeedsCompilation: no
Packaged: 2018-06-01 00:42:22 UTC; tsuyusakikouki
Repository: CRAN
Date/Publication: 2018-06-04 08:48:01 UTC

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New package CVglasso with initial version 1.0
Package: CVglasso
Type: Package
Title: Lasso Penalized Precision Matrix Estimation
Version: 1.0
Date: 2018-05-31
Authors@R: person("Matt", "Galloway", email = "gall0441@umn.edu", role = c("aut", "cre"))
Description: Estimates a lasso penalized precision matrix via the blockwise coordinate descent (BCD). This package is a simple wrapper around the popular 'glasso' package that extends and enhances its capabilities. These enhancements include built-in cross validation and visualizations. See Friedman et al (2008) <doi:10.1093/biostatistics/kxm045> for details regarding the estimation method.
URL: https://github.com/MGallow/CVglasso
BugReports: https://github.com/MGallow/CVglasso/issues
License: GPL (>= 2)
ByteCompile: TRUE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
Imports: stats, parallel, foreach, ggplot2, dplyr, glasso
Depends: doParallel
Suggests: testthat
NeedsCompilation: no
Packaged: 2018-05-31 23:30:18 UTC; Matt
Author: Matt Galloway [aut, cre]
Maintainer: Matt Galloway <gall0441@umn.edu>
Repository: CRAN
Date/Publication: 2018-06-04 08:42:55 UTC

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Sat, 02 Jun 2018

New package plsRcox with initial version 1.7.3
Package: plsRcox
Version: 1.7.3
Date: 2018-05-31
Depends: R (>= 2.4.0)
Imports: survival, plsRglm, lars, pls, kernlab, mixOmics, risksetROC, survcomp, survAUC, rms
Enhances:
Suggests: survivalROC, plsdof
Title: Partial Least Squares Regression for Cox Models and Related Techniques
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: Provides Partial least squares Regression and various regular, sparse or kernel, techniques for fitting Cox models in high dimensional settings.
License: GPL-3
Encoding: latin1
URL: http://www-irma.u-strasbg.fr/~fbertran/
Classification/MSC: 62N01, 62N02, 62N03, 62N99
NeedsCompilation: no
Packaged: 2018-06-02 09:33:35 UTC; fbertran
Repository: CRAN
Date/Publication: 2018-06-02 22:10:14 UTC

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New package plsRbeta with initial version 0.2.1
Package: plsRbeta
Version: 0.2.1
Date: 2018-05-31
Depends: R (>= 2.4.0)
Imports: mvtnorm, boot, Formula, plsdof, MASS, plsRglm, betareg, methods
Enhances:
Suggests: pls
Title: Partial Least Squares Regression for Beta Regression Models
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: Provides Partial least squares Regression for (weighted) beta regression models and k-fold cross-validation of such models using various criteria. It allows for missing data in the explanatory variables. Bootstrap confidence intervals constructions are also available.
License: GPL-3
Encoding: latin1
URL: http://www-irma.u-strasbg.fr/~fbertran/
Classification/MSC: 62J12, 62J99
NeedsCompilation: no
Packaged: 2018-06-02 09:10:22 UTC; fbertran
Repository: CRAN
Date/Publication: 2018-06-02 22:10:19 UTC

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New package bib2df with initial version 1.0.1
Package: bib2df
Type: Package
Title: Parse a BibTeX File to a data.frame
Version: 1.0.1
Authors@R: c(person("Philipp", "Ottolinger", email = "philipp@ottolinger.de", role = c("aut", "cre")), person("Thomas", "Leeper", email = "thosjleeper@gmail.com", role = "ctb"), person("Maëlle", "Salmon", email = "maelle.salmon@yahoo.se", role = "ctb"), person("Paul", "Egeler", email = "paulegeler@gmail.com", role = "ctb"))
Description: Parse a BibTeX file to a data.frame to make it accessible for further analysis and visualization.
URL: https://github.com/ropensci/bib2df
BugReports: http://github.com/ropensci/bib2df/issues
License: GPL-3
LazyData: TRUE
Imports: dplyr, stringr, humaniformat, httr
Suggests: testthat, knitr, rmarkdown, ggplot2, tidyr
RoxygenNote: 6.0.1
VignetteBuilder: knitr
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2018-06-02 09:38:06 UTC; philipp
Author: Philipp Ottolinger [aut, cre], Thomas Leeper [ctb], Maëlle Salmon [ctb], Paul Egeler [ctb]
Maintainer: Philipp Ottolinger <philipp@ottolinger.de>
Repository: CRAN
Date/Publication: 2018-06-02 21:33:50 UTC

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New package sparseSVM with initial version 1.1-6
Package: sparseSVM
Type: Package
Title: Solution Paths of Sparse High-Dimensional Support Vector Machine with Lasso or Elastic-Net Regularization
Version: 1.1-6
Date: 2018-06-01
Author: Congrui Yi and Yaohui Zeng
Maintainer: Congrui Yi <eric.ycr@gmail.com>
Description: Fast algorithm for fitting solution paths of sparse SVM models with lasso or elastic-net regularization.
License: GPL-3
NeedsCompilation: yes
Imports: parallel
Packaged: 2018-06-02 06:32:28 UTC; cyi
Repository: CRAN
Date/Publication: 2018-06-02 12:27:22 UTC

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New package plsRglm with initial version 1.2.1
Package: plsRglm
Version: 1.2.1
Date: 2018-05-30
Depends: R (>= 2.4.0)
Imports: mvtnorm, boot, bipartite, car
Enhances: pls
Suggests: MASS, plsdof, R.rsp, chemometrics, plsdepot
Title: Partial Least Squares Regression for Generalized Linear Models
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: Provides (weighted) Partial least squares Regression for generalized linear models and repeated k-fold cross-validation of such models using various criteria. It allows for missing data in the explanatory variables. Bootstrap confidence intervals constructions are also available.
License: GPL-3
Encoding: latin1
URL: http://www-irma.u-strasbg.fr/~fbertran/
VignetteBuilder: R.rsp
Classification/MSC: 62J12, 62J99
NeedsCompilation: no
Packaged: 2018-06-01 22:05:31 UTC; fbertran
Repository: CRAN
Date/Publication: 2018-06-02 06:53:03 UTC

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Thu, 31 May 2018

New package OpenRepGrid with initial version 0.1.12
Package: OpenRepGrid
License: GPL (>= 2)
Title: Tools to Analyze Repertory Grid Data
LazyData: yes
Type: Package
LazyLoad: yes
Authors@R: person("Mark", "Heckmann", email = "heckmann.mark@gmail.com", role = c("aut", "cre"))
Description: Analyze repertory grids, a qualitative-quantitative data collection technique devised by George A. Kelly in the 1950s. Today, grids are used across various domains ranging from clinical psychology to marketing. The package contains functions to quantitatively analyze and visualize repertory grid data (see e.g. Bell, 2005, <doi:10.1002/0470013370.ch9>; Fransella, Bell, & Bannister, 2004, ISBN: 978-0-470-09080-0).
Version: 0.1.12
Date: 2018-05-31
Encoding: UTF-8
URL: http://openrepgrid.org, https://github.com/markheckmann/OpenRepGrid
Imports: methods, graphics, grid, utils, stats, grDevices, plyr, stringr, abind, rgl, colorspace, GPArotation, psych, XML, tcltk, pvclust, openxlsx
Collate: 'bertin.r' 'calc.r' 'data-openrepgrid.r' 'dev-functions.r' 'distance.R' 'double-entry.R' 'export.r' 'gmMain.r' 'import.r' 'measures.r' 'onair.r' 'openrepgrid.r' 'repgrid.r' 'repgrid-basicops.r' 'repgrid-constructs.r' 'repgrid-elements.r' 'repgrid-output.r' 'repgrid-plots.r' 'repgrid-ratings.r' 'rgl-3d.r' 'settings.r' 'utils-import.r' 'utils.r' 'zzz.r'
RoxygenNote: 6.0.1
NeedsCompilation: no
Author: Mark Heckmann [aut, cre]
Maintainer: Mark Heckmann <heckmann.mark@gmail.com>
Packaged: 2018-05-31 22:06:52 UTC; heckm
Repository: CRAN
Date/Publication: 2018-05-31 22:52:29 UTC

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New package sampler with initial version 0.2.0
Package: sampler
Type: Package
Title: Sample Design, Drawing & Data Analysis Using Data Frames
Version: 0.2.0
Author: Michael Baldassaro
Maintainer: Michael Baldassaro <mbaldassaro@gmail.com>
Description: Determine sample sizes, draw samples, and conduct data analysis using data frames. It specifically enables you to determine simple random sample sizes, stratified sample sizes, and complex stratified sample sizes using a secondary variable such as population; draw simple random samples and stratified random samples from sampling data frames; determine which observations are missing from a random sample, missing by strata, duplicated within a dataset; and perform data analysis, including proportions, margins of error and upper and lower bounds for simple, stratified and cluster sample designs.
License: MIT + file LICENSE
URL: https://github.com/mbaldassaro/sampler
BugReports: https://github.com/mbaldassaro/sampler/issues
Encoding: UTF-8
LazyData: true
Imports: dplyr, tidyr, splitstackshape, reshape
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-05-30 20:41:19 UTC; mbaldassaro
Repository: CRAN
Date/Publication: 2018-05-31 20:37:59 UTC

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New package palasso with initial version 0.0.1
Package: palasso
Version: 0.0.1
Title: Paired Lasso Regression
Description: Implements sparse regression with paired covariates (Rauschenberger et al. 2018).
Depends: R (>= 3.0.0)
Imports: glmnet, stats, Matrix, survival
Suggests: knitr, testthat, edgeR, pROC
Authors@R: person("Armin","Rauschenberger",email="a.rauschenberger@vumc.nl",role=c("aut","cre"))
VignetteBuilder: knitr
License: GPL-3
LazyData: true
RoxygenNote: 6.0.1
URL: https://github.com/rauschenberger/palasso
BugReports: https://github.com/rauschenberger/palasso/issues
NeedsCompilation: no
Packaged: 2018-05-22 11:34:23 UTC; a.rauschenbe
Author: Armin Rauschenberger [aut, cre]
Maintainer: Armin Rauschenberger <a.rauschenberger@vumc.nl>
Repository: CRAN
Date/Publication: 2018-05-31 20:38:11 UTC

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New package optrdd with initial version 1.0.1
Package: optrdd
Title: Optimized Regression Discontinuity Designs
Version: 1.0.1
Authors@R: c( person("Guido", "Imbens", email = "imbens@stanford.edu", role = c("aut")), person("Stefan", "Wager", email = "swager@stanford.edu", role = c("aut", "cre")))
Description: Optimized inference in regression discontinuity designs, as proposed by Imbens and Wager (2017) <arXiv:1705.01677>.
Depends: R (>= 3.2.0)
Imports: quadprog, splines, Matrix, CVXR
Suggests: Rmosek, RColorBrewer, testthat
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-05-31 07:23:57 UTC; swager
Author: Guido Imbens [aut], Stefan Wager [aut, cre]
Maintainer: Stefan Wager <swager@stanford.edu>
Repository: CRAN
Date/Publication: 2018-05-31 20:38:15 UTC

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New package MM4LMM with initial version 1.0.5
Package: MM4LMM
Type: Package
Title: Inference of Linear Mixed Models Through MM Algorithm
Version: 1.0.5
Date: 2018-05-31
Author: Fabien Laporte, Tristan Mary-Huard
Maintainer: Fabien Laporte <fabien.laporte@inra.fr>
Description: The main function MMEst() performs (Restricted) Maximum Likelihood in a variance component mixed models using a Min-Max (MM) algorithm (Hunter, D. R., & Lange, K. (2004) <doi:10.1198/0003130042836>).
License: GPL (>= 2)
Imports: Rcpp (>= 0.12.13), Matrix, parallel, stats
LinkingTo: Rcpp, RcppEigen
NeedsCompilation: yes
Packaged: 2018-05-31 10:24:29 UTC; fabien
Depends: R (>= 2.10)
Repository: CRAN
Date/Publication: 2018-05-31 20:38:35 UTC

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New package mdendro with initial version 1.0.0
Package: mdendro
Version: 1.0.0
Date: 2018-05-29
Title: Variable-Group Methods for Agglomerative Hierarchical Clustering
Authors@R: c(person("Alberto", "Fernandez", role = c("aut", "cre"), email = "alberto.fernandez@urv.cat", comment = c(ORCID = "0000-0002-1241-1646")), person("Sergio", "Gomez", role = "aut", email = "sergio.gomez@urv.cat", comment = c(ORCID = "0000-0003-1820-0062")))
Description: A collection of methods for agglomerative hierarchical clustering strategies on a matrix of distances, implemented using the variable-group approach introduced in Fernandez and Gomez (2008) <doi:10.1007/s00357-008-9004-x>. Descriptive measures to analyze the resulting hierarchical trees are also provided. In addition to the usual clustering methods, two parameterized methods are provided to explore an infinite family of hierarchical clustering strategies. When there are ties in proximity values, the hierarchical trees obtained are unique and independent of the order of the elements in the input matrix.
Depends: R (>= 3.5.0)
Imports: rJava (>= 0.9.8)
SystemRequirements: Java (>= 6)
License: LGPL-2.1
Encoding: UTF-8
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-05-30 13:12:40 UTC; Alberto
Author: Alberto Fernandez [aut, cre] (<https://orcid.org/0000-0002-1241-1646>), Sergio Gomez [aut] (<https://orcid.org/0000-0003-1820-0062>)
Maintainer: Alberto Fernandez <alberto.fernandez@urv.cat>
Repository: CRAN
Date/Publication: 2018-05-31 20:38:22 UTC

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New package gestalt with initial version 0.1.1
Package: gestalt
Title: Tools for Making and Combining Functions
Version: 0.1.1
Authors@R: person("Eugene", "Ha", , "eha@posteo.de", c("aut", "cre"))
Description: Provides a suite of function-building tools centered around a (forward) composition operator, %>>>%, which extends the semantics of the 'magrittr' %>% operator and supports 'tidyverse' quasiquotation. It enables you to construct composite functions that can be inspected and transformed as list-like objects. In conjunction with %>>>%, a compact function constructor, fn(), and a function that performs partial application, partial(), are also provided. Both support quasiquotation.
License: MIT + file LICENSE
URL: https://github.com/egnha/gestalt
BugReports: https://github.com/egnha/gestalt/issues
Depends: R (>= 3.1.0)
Imports: rlang (>= 0.2.0), utils
Suggests: magrittr (>= 1.5), dplyr (>= 0.7.5), testthat (>= 2.0.0), knitr, rmarkdown
Collate: 'gestalt.R' 'utils.R' 'compose.R' 'constant.R' 'partial.R' 'fn.R'
RoxygenNote: 6.0.1.9000
VignetteBuilder: knitr
Encoding: UTF-8
ByteCompile: true
NeedsCompilation: no
Packaged: 2018-05-30 21:05:29 UTC; eha
Author: Eugene Ha [aut, cre]
Maintainer: Eugene Ha <eha@posteo.de>
Repository: CRAN
Date/Publication: 2018-05-31 20:38:25 UTC

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New package EmissV with initial version 0.664.5
Package: EmissV
Title: Vehicular Emissions by Top-Down Methods
Version: 0.664.5
Authors@R: c( person(given = "Daniel", family = "Schuch", role = c("aut", "cre"), email = "schuch@usp.br", comment = c(ORCID = "0000-0001-5977-4519")), person(given = "Sergio", family = "Ibarra-Espinosa", role = c("aut"), email = "sergio.ibarra@usp.br", comment = c(ORCID = "0000-0002-3162-1905")) )
Maintainer: Daniel Schuch <schuch@usp.br>
Description: Creates emissions for use in air quality models. Vehicular emissions are estimated by a top-down approach, total emissions are calculated using the statistical description of the fleet of vehicles, the emission is spatially distributed according to satellite images or openstreetmap <https://www.openstreetmap.org> data and then distributed temporarily (Vara-Vela et al., 2016, <doi:10.5194/acp-16-777-2016>).
Depends: R (>= 3.4)
Imports: ncdf4, raster, units, methods, sp, spatstat, maptools, rgeos, rgdal
Suggests: osmar
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
URL: https://github.com/atmoschem/EmissV
BugReports: https://github.com/atmoschem/EmissV/issues/
NeedsCompilation: no
Packaged: 2018-05-31 05:35:40 UTC; Schuch
Author: Daniel Schuch [aut, cre] (<https://orcid.org/0000-0001-5977-4519>), Sergio Ibarra-Espinosa [aut] (<https://orcid.org/0000-0002-3162-1905>)
Repository: CRAN
Date/Publication: 2018-05-31 20:38:39 UTC

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New package conflicted with initial version 0.1.0
Package: conflicted
Title: An Alternative Conflict Resolution Strategy
Version: 0.1.0
Authors@R: c( person("Hadley", "Wickham", , "hadley@rstudio.com", role = c("aut", "cre")), person("RStudio", role = "cph") )
Description: R's default conflict management system gives the most recently loaded package precedence. This can make it hard to detect conflicts, particularly when they arise because a package update creates ambiguity that did not previously exist. 'conflicted' takes a different approach, making every conflict an error and forcing you to choose which function to use.
License: GPL-3
URL: https://github.com/r-lib/conflicted
BugReports: https://github.com/r-lib/conflicted/issues
Depends: R (>= 3.1)
Imports: rlang
Suggests: covr, crayon, testthat
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-05-30 14:26:26 UTC; hadley
Author: Hadley Wickham [aut, cre], RStudio [cph]
Maintainer: Hadley Wickham <hadley@rstudio.com>
Repository: CRAN
Date/Publication: 2018-05-31 20:38:29 UTC

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New package clusterlab with initial version 0.0.0.9
Package: clusterlab
Title: Flexible Gaussian Cluster Simulator
Version: 0.0.0.9
Date: 2018-05-29
Author: Christopher R John
Maintainer: Christopher R John <chris.r.john86@gmail.com>
Depends: R (>= 3.4.0)
Description: Clustering is a central task in big data analyses and clusters are often Gaussian or near Gaussian. However, a flexible Gaussian cluster simulation tool with precise control over the size, variance, and spacing of the clusters in NXN dimensional space does not exist. This is why we created 'clusterlab'. The algorithm first creates X points equally spaced on the circumference of a circle in 2D space. These form the centers of each cluster to be simulated. Additional samples are added by adding Gaussian noise to each cluster center and concatenating the new sample co-ordinates. Then if the feature space is greater than 2D, the generated points are considered principal component scores and projected into N dimensional space using linear combinations using fixed eigenvectors. The algorithm is highly customizable and well suited to testing class discovery tools across a range of fields.
License: AGPL-3
Encoding: UTF-8
LazyData: true
Imports: ggplot2
Suggests: knitr
VignetteBuilder: knitr
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-05-31 06:18:36 UTC; christopher
Repository: CRAN
Date/Publication: 2018-05-31 20:38:32 UTC

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New package CBT with initial version 1.0
Package: CBT
Type: Package
Title: Confidence Bound Target Algorithm
Version: 1.0
Date: 2018-05-16
Author: Hock Peng Chan and Shouri Hu
Maintainer: Shouri Hu <e0054325@u.nus.edu>
Description: The Confidence Bound Target (CBT) algorithm is designed for infinite arms bandit problem. It is shown that CBT algorithm achieves the regret lower bound for general reward distributions. Reference: Hock Peng Chan and Shouri Hu (2018) <arXiv:1805.11793>.
License: GPL-2
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-05-31 09:44:57 UTC; e0054325
Repository: CRAN
Date/Publication: 2018-05-31 20:38:43 UTC

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Wed, 30 May 2018

New package PVR with initial version 0.3
Package: PVR
Type: Package
Title: Phylogenetic Eigenvectors Regression and Phylogentic Signal-Representation Curve
Version: 0.3
Date: 2018-05-29
Author: Thiago Santos
Maintainer: Thiago Santos <thiago.santos@ufvjm.edu.br>
Description: Estimates (and controls for) phylogenetic signal through phylogenetic eigenvectors regression (PVR) and phylogenetic signal-representation (PSR) curve, along with some plot utilities.
License: GPL (>= 2)
Imports: splancs, ape, methods, graphics, stats, utils, MASS
NeedsCompilation: no
Packaged: 2018-05-30 20:02:35 UTC; Thiago
Repository: CRAN
Date/Publication: 2018-05-30 22:29:01 UTC

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New package reReg with initial version 1.1.4
Package: reReg
Title: Recurrent Event Regression
Version: 1.1.4
Authors@R: person("Sy Han (Steven)", "Chiou", email = "schiou@utdallas.edu", role = c("aut", "cre"))
Description: A collection of regression models for recurrent event process and failure time. Available methods include these from Xu et al. (2017) <doi:10.1080/01621459.2016.1173557>, Lin et al. (2000) <doi:10.1111/1467-9868.00259>, Wang et al. (2001) <doi:10.1198/016214501753209031>, Ghosh and Lin (2003) <doi:10.1111/j.0006-341X.2003.00102.x>, and Huang and Wang (2004) <doi:10.1198/016214504000001033>.
Depends: R (>= 3.4.0)
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
Imports: BB (>= 2014.10.1), nleqslv (>= 3.3.1), SQUAREM (>= 2017.10.1), survival (>= 2.41.3), plyr (>= 1.8.4), ggplot2 (>= 2.2.1), purrr (>= 0.2.4), dplyr (>= 0.7.4), tidyr (>= 0.8.0), MASS (>= 7.3.49), methods
RoxygenNote: 6.0.1
NeedsCompilation: yes
Packaged: 2018-05-30 14:34:15 UTC; schiou
Author: Sy Han (Steven) Chiou [aut, cre]
Maintainer: Sy Han (Steven) Chiou <schiou@utdallas.edu>
Repository: CRAN
Date/Publication: 2018-05-30 17:51:38 UTC

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New package DDoutlier with initial version 0.1.0
Package: DDoutlier
Type: Package
Title: Distance & Density-Based Outlier Detection
Version: 0.1.0
Author: Jacob H. Madsen <jacob.madsen1@mail.com>
Maintainer: Jacob H. Madsen <jacob.madsen1@mail.com>
Description: Outlier detection in multidimensional domains. Implementation of notable distance and density-based outlier algorithms. Allows users to identify local outliers by comparing observations to their nearest neighbors, reverse nearest neighbors, shared neighbors or natural neighbors. For distance-based approaches, see Knorr, M., & Ng, R. T. (1997) <doi:10.1145/782010.782021>, Angiulli, F., & Pizzuti, C. (2002) <doi:10.1007/3-540-45681-3_2>, Hautamaki, V., & Ismo, K. (2004) <doi:10.1109/ICPR.2004.1334558> and Zhang, K., Hutter, M. & Jin, H. (2009) <doi:10.1007/978-3-642-01307-2_84>. For density-based approaches, see Tang, J., Chen, Z., Fu, A. W. C., & Cheung, D. W. (2002) <doi:10.1007/3-540-47887-6_53>, Jin, W., Tung, A. K. H., Han, J., & Wang, W. (2006) <doi:10.1007/11731139_68>, Schubert, E., Zimek, A. & Kriegel, H-P. (2014) <doi:10.1137/1.9781611973440.63>, Latecki, L., Lazarevic, A. & Prokrajac, D. (2007) <doi:10.1007/978-3-540-73499-4_6>, Papadimitriou, S., Gibbons, P. B., & Faloutsos, C. (2003) <doi:10.1109/ICDE.2003.1260802>, Breunig, M. M., Kriegel, H.-P., Ng, R. T., & Sander, J. (2000) <doi:10.1145/342009.335388>, Kriegel, H.-P., Kröger, P., Schubert, E., & Zimek, A. (2009) <doi:10.1145/1645953.1646195>, Zhu, Q., Feng, Ji. & Huang, J. (2016) <doi:10.1016/j.patrec.2016.05.007>, Huang, J., Zhu, Q., Yang, L. & Feng, J. (2015) <doi:10.1016/j.knosys.2015.10.014>, Tang, B. & Haibo, He. (2017) <doi:10.1016/j.neucom.2017.02.039> and Gao, J., Hu, W., Zhang, X. & Wu, Ou. (2011) <doi:10.1007/978-3-642-20847-8_23>.
License: MIT + file LICENSE
URL: https://github.com/jhmadsen/DDoutlier
Encoding: UTF-8
LazyData: true
Imports: dbscan, proxy, pracma
NeedsCompilation: no
Packaged: 2018-05-29 21:18:22 UTC; Jacob
Repository: CRAN
Date/Publication: 2018-05-30 13:24:41 UTC

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New package swissMrP with initial version 0.62
Package: swissMrP
Type: Package
Title: Multilevel Regression with Post-Stratification (MrP) for Switzerland
Version: 0.62
Date: 2018-05-25
Author: Lucas Leemann
Maintainer: Lucas Leemann <lleemann@gmail.com>
Depends: R (>= 3.4.0), arm, lme4, maptools, blme, sp, utils
Description: Provides a number of useful functions to employ MrP for small area prediction in Switzerland. Based on a hierarchical model and survey data one can derive cantonal preference measures. The package allows to automatize the prediction and post-stratification steps. It further provides adequate print, summary, map, and plot functions for objects of its class.
License: GPL-2
LazyData: true
LazyLoad: true
NeedsCompilation: no
Packaged: 2018-05-30 09:31:51 UTC; lleemann
Repository: CRAN
Date/Publication: 2018-05-30 12:35:42 UTC

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New package SimEUCartelLaw with initial version 1.0.1
Package: SimEUCartelLaw
Type: Package
Title: Simulation of Legal Exemption System for European Cartel Law
Version: 1.0.1
Date: 2018-05-30
Authors@R: person("Martin","Becker", role = c("aut","cre"), email = "martin.becker@mx.uni-saarland.de", comment=c(ORCID="0000-0003-2336-9751"))
Description: Monte Carlo simulations of a game-theoretic model for the legal exemption system of the European cartel law are implemented in order to estimate the (mean) deterrent effect of this system. The input and output parameters of the simulated cartel opportunities can be visualized by three-dimensional projections.
Depends: R (>= 3.2.0)
Suggests: knitr, rmarkdown
Imports: plot3Drgl, plot3D, rgl, stats
License: GPL (>= 2)
LazyLoad: yes
NeedsCompilation: yes
RoxygenNote: 6.0.1
Packaged: 2018-05-30 11:36:27 UTC; mabe003
Author: Martin Becker [aut, cre] (<https://orcid.org/0000-0003-2336-9751>)
Maintainer: Martin Becker <martin.becker@mx.uni-saarland.de>
Repository: CRAN
Date/Publication: 2018-05-30 12:35:45 UTC

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New package Semblance with initial version 0.1.0
Package: Semblance
Type: Package
Title: Pair-Wise Semblance Using a Rank-Based Kernel
Version: 0.1.0
Author: Divyansh Agarwal <divyansh@upenn.edu> Nancy R. Zhang <nzh@wharton.upenn.edu>
Maintainer: Divyansh Agarwal <divyansh@upenn.edu>
Description: We present a rank-based Mercer kernel to compute a pair-wise similarity metric, corresponding to informative representation of data. We tailor the development of a kernel to encode our prior knowledge about the data distribution over a probability space. The philosophical concept behind our construction is that objects whose feature values fall on the extreme of that feature’s probability mass distribution are more similar to each other, than objects whose feature values lie closer to the mean. Semblance emphasizes features whose values lie far away from the mean of their probability distribution. The kernel relies on properties empirically determined from the data and does not assume an underlying distribution. The use of feature ranks on a probability space ensures that Semblance is computational efficacious, robust to outliers, and statistically stable, thus making it widely applicable algorithm for pattern analysis.
License: GPL-2
Encoding: UTF-8
LazyData: true
Imports: fields (>= 9.6)
Suggests: kernlab
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-05-30 11:29:59 UTC; divyanshagarwal
Repository: CRAN
Date/Publication: 2018-05-30 12:35:49 UTC

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New package scico with initial version 1.0.0
Package: scico
Title: Colour Palettes Based on the Scientific Colour-Maps
Version: 1.0.0
Date: 2018-05-30
Authors@R: c( person("Thomas Lin", "Pedersen", email = "thomasp85@gmail.com", role = c("aut", "cre")), person("Fabio", "Crameri", role = c("aut")))
Maintainer: Thomas Lin Pedersen <thomasp85@gmail.com>
Description: Colour choice in information visualisation is important in order to avoid being mislead by inherent bias in the used colour palette. The 'scico' package provides access to the perceptually uniform and colour-blindness friendly palettes developed by Fabio Crameri and released under the "Scientific Colour-Maps" moniker. The package contains 17 different palettes and includes both diverging and sequential types.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Depends: R (>= 2.10)
Imports: grDevices
Suggests: ggplot2
URL: https://github.com/thomasp85/scico
BugReports: https://github.com/thomasp85/scico/issues
RoxygenNote: 6.0.1.9000
NeedsCompilation: no
Packaged: 2018-05-30 12:26:04 UTC; thomas
Author: Thomas Lin Pedersen [aut, cre], Fabio Crameri [aut]
Repository: CRAN
Date/Publication: 2018-05-30 12:43:06 UTC

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New package dextergui with initial version 0.1.1
Package: dextergui
Type: Package
Title: A Graphic User Interface to Dexter
Version: 0.1.1
Author: Jesse Koops, Eva de Schipper, Ivailo Partchev, Timo Bechger, Gunter Maris
Maintainer: jesse koops <jesse.koops@cito.nl>
Description: Shiny Dexter provides a graphic user interface to most of the main functionality in dexter. Its main purpose is to make the first steps in R for the practising psychometrician much easier but it can be used as a standalone tool for the main psychometric tasks of a typical educational testing institute such as Data management, Classical test analysis and IRT.
License: GPL-3
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.3), dexter (>= 0.7.0)
Imports: shiny (>= 1.0.5), shinyBS, DT, htmltools, htmlwidgets, sparkline, graphics, methods, utils, dplyr, tidyr, tibble, readxl, shinyjs, shinyFiles, jsonlite, igraph, ggplot2, ggExtra, ggridges, networkD3, rlang, RCurl, DBI, grDevices, Cairo, RColorBrewer, writexl, tools
RoxygenNote: 6.0.1
Suggests: knitr
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-05-28 10:52:48 UTC; jessek
Repository: CRAN
Date/Publication: 2018-05-30 12:01:29 UTC

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New package overlapptest with initial version 1.0
Package: overlapptest
Type: Package
Title: Test Overlapping of Polygons Against Random Rotation
Version: 1.0
Date: 2018-05-30
Author: Marcelino de la Cruz Rot
Depends: R (>= 2.10), spatstat
Suggests: maptools
Maintainer: Marcelino de la Cruz <marcelino.delacruz@urjc.es>
Description: Tests the observed overlapping polygon area in a collection of polygons against a null model of random rotation, as explained in De la Cruz et al. (2017) <doi:10.13140/RG.2.2.12825.72801>.
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2018-05-30 08:17:40 UTC; marcelino
Repository: CRAN
Date/Publication: 2018-05-30 09:28:06 UTC

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New package ggdistribute with initial version 1.0.1
Package: ggdistribute
Title: A 'ggplot2' Extension for Plotting Unimodal Distributions
Version: 1.0.1
Date: 2018-5-19
Authors@R: c( person("Joseph M.", "Burling", email = "josephburling@gmail.com", role = c("aut", "cre")))
Description: The 'ggdistribute' package is an extension for plotting posterior or other types of unimodal distributions that require overlaying information about a distribution's intervals. It makes use of the 'ggproto' system to extend 'ggplot2', providing additional "geoms", "stats", and "positions." The extensions integrate with existing 'ggplot2' layer elements.
License: GPL-3
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.5.0)
Imports: data.table, ggplot2, tibble, magrittr, grDevices
Suggests: knitr, testthat, rmarkdown, viridisLite, extrafont
VignetteBuilder: knitr
RoxygenNote: 6.0.1.9000
NeedsCompilation: no
Packaged: 2018-05-30 09:13:22 UTC; josep
Author: Joseph M. Burling [aut, cre]
Maintainer: Joseph M. Burling <josephburling@gmail.com>
Repository: CRAN
Date/Publication: 2018-05-30 09:28:09 UTC

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New package wdm with initial version 0.1.0
Package: wdm
Title: Weighted Dependence Measures
Version: 0.1.0
Authors@R: person("Thomas", "Nagler", email = "mail@tnagler.com", role = c("aut", "cre"))
Description: Provides efficient implementations of weighted dependence measures and related asymptotic tests for independence. Implemented measures are the Pearson correlation, Spearman's rho, Kendall's tau, Blomqvist's beta, and Hoeffding's D; see, e.g., Nelsen (2006) <doi:10.1007/0-387-28678-0> and Hollander et al. (2015, ISBN:9780470387375).
Depends: R (>= 3.2.0)
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
LinkingTo: Rcpp
Imports: Rcpp
RoxygenNote: 6.0.1
URL: https://github.com/tnagler/wdm-r
BugReports: https://github.com/tnagler/wdm-r/issues
Suggests: testthat, Hmisc, copula, covr
NeedsCompilation: yes
Packaged: 2018-05-29 10:56:45 UTC; n5
Author: Thomas Nagler [aut, cre]
Maintainer: Thomas Nagler <mail@tnagler.com>
Repository: CRAN
Date/Publication: 2018-05-30 08:12:56 UTC

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New package Spbsampling with initial version 1.0.0
Package: Spbsampling
Title: Spatially Balanced Samples
Version: 1.0.0
Author: Francesco Pantalone, Roberto Benedetti, Federica Piersimoni
Maintainer: Francesco Pantalone <pantalone.fra@gmail.com>
Description: Provides functions to draw spatially balanced samples. It contains fast implementations (C++ via 'Rcpp') of the included sampling methods. In particular, the algorithms to draw spatially balanced samples are pwd() and swd(). These methods use a probability distribution, proportional to the within sample distance. See Benedetti R and Piersimoni F (2017) <doi:10.1002/bimj.201600194> for details. Moreover, there is a function hpwd(), which is a heuristic method to achieve approximated samples obtained by pwd() in a faster way. See Benedetti R and Piersimoni F (2017) <arXiv:1710.09116> for details. Finally, there are two functions, stprod() and stsum(), useful to standardize distance matrices in order to achieve fixed sample size using, respectively, the functions pwd() and swd().
Depends: R (>= 3.1)
License: GPL-3
Encoding: UTF-8
LazyData: true
LinkingTo: Rcpp
Imports: Rcpp, Rdpack
RdMacros: Rdpack
RoxygenNote: 6.0.1
NeedsCompilation: yes
Packaged: 2018-05-29 10:49:53 UTC; francesco
Repository: CRAN
Date/Publication: 2018-05-30 08:07:56 UTC

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New package shinyhelper with initial version 0.1.1
Package: shinyhelper
Type: Package
Title: Easily Add Markdown Help Files to 'shiny' Inputs and Outputs
Version: 0.1.1
Authors@R: person("Chris", "Thom", email = "christopher.w.thom@outlook.com", role=c("aut","cre"))
Description: Creates a lightweight way to add markdown helpfiles to 'shiny' apps, using modal dialog boxes, with no need to observe each help button separately.
License: GPL-3
Imports: shiny, shinyjs
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-05-29 20:48:14 UTC; chris
Author: Chris Thom [aut, cre]
Maintainer: Chris Thom <christopher.w.thom@outlook.com>
Repository: CRAN
Date/Publication: 2018-05-30 08:43:26 UTC

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New package lacm with initial version 0.0.3
Package: lacm
Version: 0.0.3
Priority: optional
Title: Latent Autoregressive Count Models
Authors@R: c(person(given = "Xanthi", family = "Pedeli", role = c("aut", "cre"), email = "xanthi9@gmail.com"), person(given = "Cristiano", family = "Varin", role = c("aut"), email = "cristiano.varin@unive.it"))
Description: Perform pairwise likelihood inference in latent autoregressive count models. See Pedeli and Varin (2018) <arXiv:1805.10865> for details.
Maintainer: Xanthi Pedeli <xanthi9@gmail.com>
Depends: R (>= 3.4.0)
Imports: stats, graphics, numDeriv, statmod
License: GPL (>= 2)
NeedsCompilation: yes
Author: Xanthi Pedeli [aut, cre], Cristiano Varin [aut]
Packaged: 2018-05-29 12:17:51 UTC; cristianovarin
Repository: CRAN
Date/Publication: 2018-05-30 08:18:04 UTC

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New package heatwaveR with initial version 0.2.7
Package: heatwaveR
Version: 0.2.7
Date: 2018-05-28
Title: Detect Heatwaves and Cold-Spells
Description: The different methods of defining and detecting extreme events, known as heatwaves or cold-spells in both air and water temperature data are encompassed within this package. These detection algorithms may be used on non-temperature data as well however, this is not catered for explicitly here as no use of this technique in the literature currently exists.
Type: Package
Authors@R: c(person("Robert W.", "Schlegel", role = c("aut", "cre", "ctb"), email = "robwschlegel@gmail.com", comment = c(ORCID = "0000-0002-0705-1287")), person("Albertus J.", "Smit", role = c("aut", "ctb"), comment = c(ORCID = "0000-0002-3799-6126")))
Maintainer: Robert W. Schlegel <robwschlegel@gmail.com>
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
ByteCompile: true
RoxygenNote: 6.0.1
Depends: R (>= 3.00), data.table, ggplot2
Suggests: tidyverse, testthat, knitr, rmarkdown
Imports: tibble, lubridate, dplyr, stats, utils, zoo, grid, RcppRoll, Rcpp (>= 0.12.16)
LinkingTo: Rcpp, RcppArmadillo
NeedsCompilation: yes
VignetteBuilder: knitr
URL: https://robwschlegel.github.io/heatwaveR/index.html
Packaged: 2018-05-29 11:51:45 UTC; rws
Author: Robert W. Schlegel [aut, cre, ctb] (<https://orcid.org/0000-0002-0705-1287>), Albertus J. Smit [aut, ctb] (<https://orcid.org/0000-0002-3799-6126>)
Repository: CRAN
Date/Publication: 2018-05-30 08:13:00 UTC

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New package glmmboot with initial version 0.1.2
Package: glmmboot
Type: Package
Title: Bootstrap Resampling for Mixed Effects and Plain Models
Version: 0.1.2
Authors@R: person("Colman", "Humphrey", email = "humphrc@tcd.ie", role = c("aut", "cre"))
Description: Performs bootstrap resampling for most models that update() works for. There are two main functions: BootGlmm() performs block resampling if random effects are present, and case resampling if not; BootCI() converts output from bootstrap model runs into confidence intervals and p-values. By default, BootGlmm() calls BootCI(). Package motivated by Humphrey and Swingley (2018) <arXiv:1805.08670>.
License: AGPL-3 | file LICENSE
URL: https://github.com/ColmanHumphrey/glmmboot
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.1)
Imports: methods, stats
Suggests: glmmTMB (>= 0.2.1), testthat (>= 0.11.0), pbapply (>= 1.3.0), parallel (>= 3.0.0), knitr, rmarkdown
RoxygenNote: 6.0.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-05-23 01:55:38 UTC; colmanhumphrey
Author: Colman Humphrey [aut, cre]
Maintainer: Colman Humphrey <humphrc@tcd.ie>
Repository: CRAN
Date/Publication: 2018-05-30 08:05:48 UTC

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New package epubr with initial version 0.4.0
Package: epubr
Version: 0.4.0
Title: Read EPUB File Metadata and Text
Description: Provides functions supporting the reading and parsing of internal e-book content from EPUB files. E-book formatting is non-standard enough across all literature that no function can curate parsed e-book content across an arbitrary collection of e-books, in completely general form, resulting in a singular, consistently formatted output containing all the same variables. EPUB file parsing functionality in this package is intended for relatively general application to arbitrary e-books. However, poorly formatted e-books or e-books with highly uncommon formatting may not work with this package. Text is read 'as is'. Additional text cleaning should be performed by the user at their discretion, such as with functions from packages like 'tm' or 'qdap'.
Authors@R: person("Matthew", "Leonawicz", email = "mfleonawicz@alaska.edu", role = c("aut", "cre"))
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
ByteCompile: true
URL: https://github.com/leonawicz/epubr
BugReports: https://github.com/leonawicz/epubr/issues
Depends: R (>= 3.5.0)
Suggests: testthat, knitr, rmarkdown, lintr, covr, readr
Imports: xml2, xslt, magrittr, dplyr, purrr, tidyr
VignetteBuilder: knitr
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-05-29 18:50:18 UTC; Matt
Author: Matthew Leonawicz [aut, cre]
Maintainer: Matthew Leonawicz <mfleonawicz@alaska.edu>
Repository: CRAN
Date/Publication: 2018-05-30 08:36:46 UTC

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New package easyCODA with initial version 0.23
Package: easyCODA
Type: Package
Depends: R (>= 2.10), ca (>= 0.6)
Title: Compositional Data Analysis in Practice
Version: 0.23
Date: 2018-05-07
Author: Michael Greenacre
Maintainer: Michael Greenacre <michael.greenacre@upf.edu>
Description: Univariate and multivariate methods for compositional data analysis, based on logratios.
License: GPL
Repository: CRAN
Repository/R-Forge/Project: easycoda
Repository/R-Forge/Revision: 10
Repository/R-Forge/DateTimeStamp: 2018-05-07 13:51:46
Date/Publication: 2018-05-30 08:36:50 UTC
NeedsCompilation: no
Packaged: 2018-05-07 14:15:10 UTC; rforge

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New package comperank with initial version 0.1.0
Package: comperank
Title: Ranking Methods for Competition Results
Version: 0.1.0
Authors@R: person("Evgeni", "Chasnovski", email = "evgeni.chasnovski@gmail.com", role = c("aut", "cre"))
Description: Compute ranking and rating based on competition results. Methods of different nature are implemented: with fixed Head-to-Head structure, with variable Head-to-Head structure and with iterative nature. All algorithms are taken from the book 'Who’s #1?: The science of rating and ranking' by Amy N. Langville and Carl D. Meyer (2012, ISBN:978-0-691-15422-0).
License: MIT + file LICENSE
URL: https://github.com/echasnovski/comperank
BugReports: https://github.com/echasnovski/comperank/issues
Depends: comperes (>= 0.1.0), R (>= 3.4.0)
Imports: dplyr (>= 0.6.0), Rcpp, rlang (>= 0.2.0), tibble
Suggests: covr, knitr, rmarkdown, testthat
LinkingTo: Rcpp
VignetteBuilder: knitr
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
NeedsCompilation: yes
Packaged: 2018-05-29 18:01:51 UTC; evgeni
Author: Evgeni Chasnovski [aut, cre]
Maintainer: Evgeni Chasnovski <evgeni.chasnovski@gmail.com>
Repository: CRAN
Date/Publication: 2018-05-30 08:27:55 UTC

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Tue, 29 May 2018

New package RchivalTag with initial version 0.0.7
Package: RchivalTag
Type: Package
Title: Analyzing Archival Tagging Data
Version: 0.0.7
Date: 2018-05-25
Author: Robert Bauer
Maintainer: Robert Bauer <r.bauer@profish-technology.de>
Description: A set of functions to generate, access and analyze standard data products from archival tagging data.
Depends: R (>= 3.0.1)
Imports: plyr, maptools, graphics, stats, raster, rgeos, ncdf4, maps, mapdata, grDevices, oceanmap, sp, methods, PBSmapping
License: GPL (>= 3)
LazyLoad: yes
Packaged: 2018-05-29 20:13:18 UTC; robert
Repository: CRAN
Date/Publication: 2018-05-29 21:17:56 UTC
NeedsCompilation: no

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New package spotGUI with initial version 0.1.1
Package: spotGUI
Type: Package
Title: Graphical User Interface for the Package 'SPOT'
Version: 0.1.1
Authors@R: c( person("Frederik","Rehbach", role = c("aut", "cre"), email = "frederik.rehbach@th-koeln.de"), person("Martin", "Zaefferer", role = "aut"), person("Thomas", "Bartz-Beielstein", role = "ctb"), person("Andreas","Fischbach", role = "ctb"), person("Lorenzo","Gentile", role = "ctb"))
Author: Frederik Rehbach [aut, cre], Martin Zaefferer [aut], Thomas Bartz-Beielstein [ctb], Andreas Fischbach [ctb], Lorenzo Gentile [ctb]
Maintainer: Frederik Rehbach <frederik.rehbach@th-koeln.de>
Description: A graphical user interface for the Sequential Parameter Optimization Toolbox (package 'SPOT'). It includes a quick, graphical setup for spot, interactive 3D plots, export possibilities and more.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.1.0),
Imports: shinyBS, shiny, shinydashboard, SPOT (>= 2.0.3), gridExtra, shinyjs, rhandsontable, XML, rclipboard, plotly, tools, httpuv, methods
Suggests: roxygen2, testthat, shinytest, devtools
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-05-29 08:51:38 UTC; rehbach
Repository: CRAN
Date/Publication: 2018-05-29 10:23:58 UTC

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New package rtsplot with initial version 0.1.0
Package: rtsplot
Type: Package
Title: Time Series Plot
Version: 0.1.0
Authors@R: c( person("Irina", "Kapler", role = c("cre"), email = "irkapler@gmail.com"), person(family = "RTSVizTeam", role = c("aut", "cph"), email = "rtsvizteam@gmail.com") )
Description: A fast and elegant time series visualization package. In addition to the standard R plot types, this package supports candle sticks, open-high-low-close, and volume plots. Useful for visualizing any time series data, e.g., stock prices and technical indicators.
License: MIT + file LICENSE
Imports: xts, quantmod, TTR, zoo, RColorBrewer
URL: https://bitbucket.org/rtsvizteam/rtsplot
BugReports: https://bitbucket.org/rtsvizteam/rtsplot/issues
LazyLoad: yes
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-05-29 01:38:13 UTC; pcadmin
Author: Irina Kapler [cre], RTSVizTeam [aut, cph]
Maintainer: Irina Kapler <irkapler@gmail.com>
Repository: CRAN
Date/Publication: 2018-05-29 10:06:17 UTC

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New package ggfocus with initial version 0.8
Package: ggfocus
Type: Package
Title: Focus on Specific Factor Levels in your ggplot()
Version: 0.8
Author: Victor Freguglia
Maintainer: Victor Freguglia <victorfreguglia@gmail.com>
BugReports: https://github.com/Freguglia/ggfocus/issues
URL: https://github.com/Freguglia/ggfocus
Description: A 'ggplot2' extension that provides tools for automatically focusing specific factor levels.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
Imports: magrittr, dplyr, rlang, RColorBrewer, ggplot2
NeedsCompilation: no
Packaged: 2018-05-29 02:35:33 UTC; victor
Repository: CRAN
Date/Publication: 2018-05-29 10:15:08 UTC

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New package c3 with initial version 0.2.0
Package: c3
Type: Package
Title: 'C3.js' Chart Library
Description: Create interactive charts with the 'C3.js' <http://c3js.org/> charting library. All plot types in 'C3.js' are available and include line, bar, scatter, and mixed geometry plots. Plot annotations, labels and axis are highly adjustable. Interactive web based charts can be embedded in R Markdown documents or Shiny web applications.
Version: 0.2.0
Authors@R: c( person("Matt", "Johnson", email = "mrjoh3@gmail.com", role = c("aut", "cre")) )
Maintainer: Matt Johnson <mrjoh3@gmail.com>
Depends: R (>= 3.2.2)
Imports: jsonlite, data.table, lazyeval, htmlwidgets, dplyr, viridis
URL: https://github.com/mrjoh3/c3
BugReports: https://github.com/mrjoh3/c3/issues
License: GPL (>= 3)
LazyData: TRUE
Encoding: UTF-8
RoxygenNote: 6.0.1
Suggests: testthat, RColorBrewer, knitr, rmarkdown, webshot, purrr
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-05-29 08:41:54 UTC; johnsom
Author: Matt Johnson [aut, cre]
Repository: CRAN
Date/Publication: 2018-05-29 10:20:57 UTC

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New package vinereg with initial version 0.2.0
Package: vinereg
Type: Package
Title: D-Vine Quantile Regression
Version: 0.2.0
Author: Thomas Nagler, Daniel Kraus
Maintainer: Thomas Nagler <mail@tnagler.com>
Description: Implements D-vine quantile regression models with parametric or nonparametric pair-copulas. See Kraus and Czado (2017) <doi:10.1016/j.csda.2016.12.009> and Schallhorn et al. (2017) <arXiv:1705.08310>.
License: GPL-3
LazyData: TRUE
Imports: cctools, rvinecopulib (>= 0.2.8), doParallel, parallel, foreach, kde1d (>= 0.2.0),
RoxygenNote: 6.0.1
NeedsCompilation: no
Suggests: knitr, rmarkdown, ggplot2, PivotalR, quantreg, tidyr, dplyr, purrr, scales, mgcv, testthat, covr
VignetteBuilder: knitr
Packaged: 2018-05-28 15:33:41 UTC; n5
Repository: CRAN
Date/Publication: 2018-05-29 09:23:18 UTC

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New package r2d3 with initial version 0.2.0
Package: r2d3
Type: Package
Title: Interface to 'D3' Visualizations
Version: 0.2.0
Authors@R: c( person("Javier", "Luraschi", email = "javier@rstudio.com", role = c("aut", "cre")), person("JJ", "Allaire", role = c("aut")), person("Mike", "Bostock", role = c("ctb", "cph"), comment = "d3.js library, http://d3js.org"), person(family = "RStudio", role = c("cph")) )
Maintainer: Javier Luraschi <javier@rstudio.com>
Description: Suite of tools for using 'D3', a library for producing dynamic, interactive data visualizations. Supports translating objects into 'D3' friendly data structures, rendering 'D3' scripts, publishing 'D3' visualizations, incorporating 'D3' in R Markdown, creating interactive 'D3' applications with Shiny, and distributing 'D3' based 'htmlwidgets' in R packages.
License: BSD_3_clause + file LICENSE
Encoding: UTF-8
LazyData: TRUE
Depends: R (>= 3.1.2)
Imports: htmlwidgets (>= 1.2), htmltools, jsonlite, rstudioapi
Suggests: knitr, rmarkdown, shiny, shinytest, testthat, webshot
RoxygenNote: 6.0.1
URL: https://github.com/rstudio/r2d3
BugReports: https://github.com/rstudio/r2d3/issues
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-05-28 15:25:25 UTC; javierluraschi
Author: Javier Luraschi [aut, cre], JJ Allaire [aut], Mike Bostock [ctb, cph] (d3.js library, http://d3js.org), RStudio [cph]
Repository: CRAN
Date/Publication: 2018-05-29 09:23:22 UTC

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New package GrimR with initial version 0.5
Package: GrimR
Type: Package
Title: Calculate Optical Parameters from Spindle Stage Measurements
Version: 0.5
Date: 2018-05-28
Authors@R: person("Florian","Dufey",email="GrimR@gmx.de",role=c("aut","cre"))
Author: Florian Dufey [aut, cre]
Maintainer: Florian Dufey <GrimR@gmx.de>
Description: Calculates optical parameters of crystals like the optical axes, the axis angle 2V, and the direction of the principal axes of the indicatrix from extinction angles measured on a spindle stage mounted on a polarisation microscope stage. Details of the method can be found in Dufey (2017) <arXiv:1703.00070>.
License: GPL-3
RoxygenNote: 6.0.1
LazyData: true
Depends: car, stats4
NeedsCompilation: no
Packaged: 2018-05-28 14:44:01 UTC; dufeyf
Repository: CRAN
Date/Publication: 2018-05-29 09:23:26 UTC

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New package atlas with initial version 0.5.0
Package: atlas
Type: Package
Title: Stanford 'ATLAS' Search Engine API
Version: 0.5.0
Author: Vladimir Polony
Maintainer: Vladimir Polony <podalv@gmail.com>
Description: Stanford 'ATLAS' (Advanced Temporal Search Engine) is a powerful tool that allows constructing cohorts of patients extremely quickly and efficiently. This package is designed to interface directly with an instance of 'ATLAS' search engine and facilitates API queries and data dumps. Prerequisite is a good knowledge of the temporal language to be able to efficiently construct a query. More information available at <https://shahlab.stanford.edu/start>.
License: GPL-3
URL: https://shahlab.stanford.edu/start
Imports: httr, testthat
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1.9000
NeedsCompilation: no
Packaged: 2018-05-28 14:44:14 UTC; podalv
Repository: CRAN
Date/Publication: 2018-05-29 09:09:57 UTC

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New package NFWdist with initial version 0.1.0
Package: NFWdist
Type: Package
Title: The Standard Distribution Functions for the 3D NFW Profile
Version: 0.1.0
Author: Aaron Robotham
Maintainer: Aaron Robotham <aaron.robotham@uwa.edu.au>
Description: Density, distribution function, quantile function and random generation for the 3D Navarro, Frenk & White (NFW) profile. For details see Robotham & Howlett (2018) <arXiv:1805.09550>.
License: GPL-3
LazyData: true
Depends: R (>= 3.00)
Suggests: knitr, gsl, lamW
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-05-28 01:17:56 UTC; aaron
Repository: CRAN
Date/Publication: 2018-05-29 08:31:03 UTC

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New package metaBLUE with initial version 1.0.0
Package: metaBLUE
Title: BLUE for Combining Location and Scale Information in a Meta-Analysis
Version: 1.0.0
Authors@R: c( person("Xin", "Yang", email = "xyang.krystal@gmail.com", role = c("cre","aut")), person("Alan", "Hutson", email = "Alan.Hutson@roswellpark.org", role = "aut"), person("Dongliang", "Wang", email = "WangD@upstate.edu", role = "aut"))
Description: The sample mean and standard deviation are two commonly used statistics in meta-analyses, but some trials use other summary statistics such as the median and quartiles to report the results. Therefore, researchers need to transform those information back to the sample mean and standard deviation. This package implemented sample mean estimators by Luo et al. (2016) <arXiv:1505.05687>, sample standard deviation estimators by Wan et al. (2014) <arXiv:1407.8038>, and the best linear unbiased estimators (BLUEs) of location and scale parameters by Yang et al. (2018, submitted) based on sample quantiles derived summaries in a meta-analysis.
Depends: R (>= 3.3)
Imports: stats, Matrix
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-05-27 22:53:23 UTC; HP-PC
Author: Xin Yang [cre, aut], Alan Hutson [aut], Dongliang Wang [aut]
Maintainer: Xin Yang <xyang.krystal@gmail.com>
Repository: CRAN
Date/Publication: 2018-05-29 08:30:49 UTC

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New package imagerExtra with initial version 1.0
Package: imagerExtra
Type: Package
Title: Extra Image Processing Library Based on 'imager'
Version: 1.0
Date: 2018-05-24
Authors@R: c( person("Shota", "Ochi", email = "shotaochi1990@gmail.com", role = c("aut", "cre")), person("Guoshen", "Yu", email = "yu@cmap.polytechnique.fr", role = c("ctb", "cph")), person("Guillermo", "Sapiro", email = "guille@umn.edu", role = c("ctb", "cph")), person("Catalina", "Sbert", email = "catalina.sbert@uib.es", role = c("ctb", "cph")), person("Image Processing On Line", role = "cph"))
Maintainer: Shota Ochi <shotaochi1990@gmail.com>
Description: Providing several advanced functions for image processing based on the package 'imager'.
License: GPL (>= 3)
Depends: imager (>= 0.40.2)
Imports: Rcpp (>= 0.12.14), dtt, magrittr
Suggests: testthat (>= 2.0.0), knitr, rmarkdown
URL: https://github.com/ShotaOchi/imagerExtra
BugReports: https://github.com/ShotaOchi/imagerExtra/issues
LinkingTo: Rcpp
RoxygenNote: 6.0.1
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2018-05-27 23:40:24 UTC; shota
Author: Shota Ochi [aut, cre], Guoshen Yu [ctb, cph], Guillermo Sapiro [ctb, cph], Catalina Sbert [ctb, cph], Image Processing On Line [cph]
Repository: CRAN
Date/Publication: 2018-05-29 08:30:56 UTC

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New package hdbinseg with initial version 1.0.1
Package: hdbinseg
Type: Package
Title: Change-Point Analysis of High-Dimensional Time Series via Binary Segmentation
Version: 1.0.1
Date: 2018-05-18
Authors@R: c( person('Haeran', 'Cho', email='haeran.cho@bristol.ac.uk', role=c('aut', 'cre')), person('Piotr', 'Fryzlewicz', email='p.fryzlewicz@lse.ac.uk', role='aut'))
Description: Binary segmentation methods for detecting and estimating multiple change-points in the mean or second-order structure of high-dimensional time series as described in Cho and Fryzlewicz (2014) <doi:10.1111/rssb.12079> and Cho (2016) <doi:10.1214/16-EJS1155>.
Depends: R (>= 3.4.0)
License: GPL (>= 3)
LazyData: TRUE
Suggests: RcppArmadillo
Imports: Rcpp (>= 0.12.10), foreach, iterators, doParallel
LinkingTo: Rcpp, RcppArmadillo
RoxygenNote: 6.0.1
NeedsCompilation: yes
Packaged: 2018-05-28 12:02:41 UTC; mahrc
Author: Haeran Cho [aut, cre], Piotr Fryzlewicz [aut]
Maintainer: Haeran Cho <haeran.cho@bristol.ac.uk>
Repository: CRAN
Date/Publication: 2018-05-29 08:59:41 UTC

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New package glmmEP with initial version 1.0-1
Package: glmmEP
Version: 1.0-1
Date: 2018-05-28
Title: Generalized Linear Mixed Model Analysis via Expectation Propagation
Authors@R: c(person("Matt P.", "Wand", role = c("aut", "cre"), email = "matt.wand@uts.edu.au"), person("James F.C.", "Yu", role = "aut", email = "james.yu@student.uts.edu.au"))
Maintainer: Matt P. Wand <matt.wand@uts.edu.au>
Depends: stats
Imports: lme4, matrixcalc
Suggests: mlmRev
Description: Approximate frequentist inference for generalized linear mixed model analysis with expectation propagation used to circumvent the need for multivariate integration. In this version, the random effects can be any reasonable dimension. However, only probit mixed models with one level of nesting are supported. The methodology is described in Hall, Johnstone, Ormerod, Wand and Yu (2018) <arXiv:1805.08423v1>.
License: GPL (>= 2)
NeedsCompilation: yes
Packaged: 2018-05-28 03:39:42 UTC; mwand
Author: Matt P. Wand [aut, cre], James F.C. Yu [aut]
Repository: CRAN
Date/Publication: 2018-05-29 08:30:59 UTC

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New package Equalden.HD with initial version 1.0
Package: Equalden.HD
Title: Testing the Equality of a High Dimensional Set of Densities
Version: 1.0
Authors@R: c( person("Marta", "Cousido Rocha", email = "martacousido@uvigo.es", role = c("aut", "cre")), person("José Carlos", "Soage González", email = "jsoage@uvigo.es", role = "ctr"), person("Jacobo", "de Uña Álvarez", email = "jacobo@uvigo.es", role = c("aut", "ths")), person("Jeffrey", "D. Hart", email = "hart@stat.tamu.edu", role = "aut"), person("Ivan", "Kojadinovic", email = "ivan.kojadinovic@univ-pau.fr", role = "cph"), person("A.", "Patton", email = "andrew.patton@duke.edu", role = "cph"), person("C.", "Parmeter", email = "c.parmeter@miami.edu", role = "cph"), person("J.", "Racine", email = "racinej@mcmaster.ca", role = "cph"))
Maintainer: Marta Cousido Rocha <martacousido@uvigo.es>
Description: The equality of a large number k of densities is tested by measuring the L2 distance between the corresponding kernel density estimators and the one based on the pooled sample. The test even works for sample sizes as small as 2.
Depends: R (>= 3.4.0)
ByteCompile: true
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
NeedsCompilation: yes
Packaged: 2018-05-28 13:48:26 UTC; JoseCarlos
Author: Marta Cousido Rocha [aut, cre], José Carlos Soage González [ctr], Jacobo de Uña Álvarez [aut, ths], Jeffrey D. Hart [aut], Ivan Kojadinovic [cph], A. Patton [cph], C. Parmeter [cph], J. Racine [cph]
Repository: CRAN
Date/Publication: 2018-05-29 08:50:23 UTC

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New package DTWBI with initial version 1.0
Package: DTWBI
Type: Package
Title: Imputation of Time Series Based on Dynamic Time Warping
Version: 1.0
Date: 2018-05-02
Author: DEZECACHE Camille, PHAN Thi Thu Hong, POISSON-CAILLAULT Emilie
Maintainer: POISSON-CAILLAULT Emilie <emilie.poisson@univ-littoral.fr>
Description: Functions to impute large gaps within time series based on Dynamic Time Warping methods. It contains all required functions to create large missing consecutive values within time series and to fill them, according to the paper Phan et al. (2017), <DOI:10.1016/j.patrec.2017.08.019>. Performance criteria are added to compare similarity between two signals (query and reference).
Depends: R (>= 3.0.0)
Imports: dtw, rlist, stats, e1071, entropy, lsa
License: GPL (>= 2)
RoxygenNote: 6.0.1
URL: http://mawenzi.univ-littoral.fr/DTWBI/
NeedsCompilation: no
Packaged: 2018-05-28 07:23:12 UTC; poisson
Repository: CRAN
Date/Publication: 2018-05-29 08:38:29 UTC

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Mon, 28 May 2018

New package aftgee with initial version 1.1-2
Package: aftgee
Type: Package
Title: Accelerated Failure Time Model with Generalized Estimating Equations
Version: 1.1-2
Date: 2018-05-28
Author: Sy Han (Steven) Chiou, Sangwook Kang, Jun Yan
Maintainer: Sy Han (Steven) Chiou <schiou@utdallas.edu>
Description: A collection of methods for both the rank-based estimates and least square estimates to the Accelerated Failure Time (AFT) model. For rank-based estimation, it provides approaches that include the computationally efficient Gehan's weight and the general's weight such as the logrank weight. Details of the rank-based estimation can be found in Chiou et al. (2014) <doi:10.1007/s11222-013-9388-2> and Chiou et al. (2015) <doi:10.1002/sim.6415>. For the least-square estimation, the estimating equation is solved with Generalized Estimating Equations (GEE). Moreover, in multivariate cases, the dependence working correlation structure can be specified in GEE's setting. Details on the least-squares estimation can be found in Chiou et al. (2014) <doi:10.1007/s10985-014-9292-x>.
License: GPL (>= 3)
Imports: MASS, BB, survival, geepack, parallel, methods
Suggests: copula
LazyLoad: yes
Packaged: 2018-05-28 18:13:33 UTC; schiou
NeedsCompilation: yes
Repository: CRAN
Date/Publication: 2018-05-28 22:58:57 UTC

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