Fri, 23 Aug 2019

Package rmumps updated to version 5.2.1-4 with previous version 5.1.2-6 dated 2019-04-25

Title: Wrapper for MUMPS Library
Description: Some basic features of MUMPS (Multifrontal Massively Parallel sparse direct Solver) are wrapped in a class whose methods can be used for sequentially solving a sparse linear system (symmetric or not) with one or many right hand sides (dense or sparse). There is a possibility to do separately symbolic analysis, LU (or LDL^t) factorization and system solving. Third part ordering libraries are included and can be used: PORD, METIS, SCOTCH. MUMPS method was first described in Amestoy et al. (2001) <doi:10.1137/S0895479899358194> and Amestoy et al. (2006) <doi:10.1016/j.parco.2005.07.004>.
Author: Serguei Sokol [aut, cre], Emmanuel Agullo [ctb], Patrick Amestoy [ctb], Maurice Bremond [ctb], Alfredo Buttari [ctb], Philippe Combes [ctb], Marie Durand [ctb], Aurelia Fevre [ctb], Abdou Guermouche [ctb], Guillaume Joslin [ctb], Jacko Koster [ctb], Jean-Yves L'Excellent [ctb], Stephane Pralet [ctb], Chiara Puglisi [ctb], Francois-Henry Rouet [ctb], Wissam Sid-Lakhdar [ctb], Tzvetomila Slavova [ctb], Bora Ucar [ctb], Clement Weisbecker [ctb], Juergen Schulze [ctb], George Karypis [ctb], Douglas C. Schmidt [ctb], Isamu Hasegawa [ctb], Alexander Chemeris [ctb], Makoto Matsumoto [ctb], Takuji Nishimura [ctb], Francois Pellegrini [ctb], David Goudin [ctb], Pascal Henon [ctb], Pierre Ramet [ctb], Sebastien Fourestier [ctb], Jun-Ho Her [ctb], Cedric Chevalier [ctb], Timothy A. Davis [ctb], Iain S. Duff [ctb], John K. Reid [ctb], Richard Stallman [ctb], Samuel Thibault [ctb]
Maintainer: Serguei Sokol <sokol@insa-toulouse.fr>

Diff between rmumps versions 5.1.2-6 dated 2019-04-25 and 5.2.1-4 dated 2019-08-23

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New package expectreg with initial version 0.50
Package: expectreg
Version: 0.50
Date: 2019-08-22
Title: Expectile and Quantile Regression
Authors@R: c(person("Fabian", "Otto-Sobotka", role = "cre", email = "fabian.otto-sobotka@uni-oldenburg.de"), person("Elmar", "Spiegel", role = "aut", email = "espiege@uni-goettingen.de"), person("Sabine", "Schnabel", role = "aut", email = "sabine.schnabel@wur.nl"), person("Linda", "Schulze Waltrup", role = "aut", email = "lschulze_waltrup@stat.uni-muenchen.de"), person("Paul", "Eilers", role = "ctb", email = "p.eilers@erasmusmc.nl"), person("Thomas", "Kneib", role = "ths", email = "tkneib@uni-goettingen.de"), person("Goeran", "Kauermann", role = "ctb", email = "goeran.kauermann@stat.uni-muenchen.de"))
Author: Fabian Otto-Sobotka [cre], Elmar Spiegel [aut], Sabine Schnabel [aut], Linda Schulze Waltrup [aut], Paul Eilers [ctb], Thomas Kneib [ths], Goeran Kauermann [ctb]
Maintainer: Fabian Otto-Sobotka <fabian.otto-sobotka@uni-oldenburg.de>
Depends: R (>= 3.5.0), stats, parallel, mboost (>= 2.1.0), BayesX (>= 0.2-4), Matrix
Imports: Rcpp (>= 0.11.2), splines, quadprog, colorspace (>= 0.97), fields
Suggests: SemiPar
LinkingTo: Rcpp, RcppEigen
Description: Expectile and quantile regression of models with nonlinear effects e.g. spatial, random, ridge using least asymmetric weighed squares / absolutes as well as boosting; also supplies expectiles for common distributions.
License: GPL-2
LazyData: yes
NeedsCompilation: yes
Encoding: UTF-8
Packaged: 2019-08-23 09:19:52 UTC; fabiansobotka
Repository: CRAN
Date/Publication: 2019-08-23 22:30:03 UTC

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Package EIAdata updated to version 0.0.5 with previous version 0.0.3 dated 2015-03-10

Title: R Wrapper for the Energy Information Administration (EIA) API
Description: An R wrapper to allow the user to query categories and Series IDs, and import data, from the EIA's API <https://www.eia.gov/opendata/>.
Author: Matthew Brigida and others (see GitHub)
Maintainer: Matthew Brigida <mdbrigida@gmail.com>

Diff between EIAdata versions 0.0.3 dated 2015-03-10 and 0.0.5 dated 2019-08-23

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Package economiccomplexity updated to version 0.2 with previous version 0.1.2 dated 2019-07-11

Title: Methods Used in the Economic Complexity Literature
Description: A wrapper of different indices and networks commonly used in Economic Complexity to explore bipartite relations such as countries and their exported products. These methods are also useful for different kind of relations such as countries and their spoken languages. The functions within this package correspond to code implementations of the equations described in Hausmann, et al. (2005) <doi:10.3386/w11905>, Hausmann, et al. (2014) <doi:10.7551/mitpress/9647.001.0001>, and Mariani, et al. (2015) <doi:10.1140/epjb/e2015-60298-7>.
Author: Mauricio Vargas [aut, cre, cph] (<https://orcid.org/0000-0003-1017-7574>), Carlo Bottai [ctb] (improved the eigenvalues calculation), Diego Kozlowski [ctb] (provided initial RCA and proximity functions he used for his thesis), Mark Padgham [rev] (compared PRODY equations from different articles), Nico Pintar [rev] (suggested improvements to special cases in eigenvalues calculation), The World Bank [dtc], Open Trade Statistics [dtc]
Maintainer: Mauricio Vargas <mvargas@dcc.uchile.cl>

Diff between economiccomplexity versions 0.1.2 dated 2019-07-11 and 0.2 dated 2019-08-23

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Package covr updated to version 3.3.1 with previous version 3.3.0 dated 2019-08-06

Title: Test Coverage for Packages
Description: Track and report code coverage for your package and (optionally) upload the results to a coverage service like 'Codecov' <http://codecov.io> or 'Coveralls' <http://coveralls.io>. Code coverage is a measure of the amount of code being exercised by a set of tests. It is an indirect measure of test quality and completeness. This package is compatible with any testing methodology or framework and tracks coverage of both R code and compiled C/C++/FORTRAN code.
Author: Jim Hester [aut, cre], Willem Ligtenberg [ctb], Kirill Müller [ctb], Henrik Bengtsson [ctb], Steve Peak [ctb], Kirill Sevastyanenko [ctb], Jon Clayden [ctb], Robert Flight [ctb], Eric Brown [ctb], Brodie Gaslam [ctb], Will Beasley [ctb], Robert Krzyzanowski [ctb], Markus Wamser [ctb], Karl Forner [ctb], Gergely Daróczi [ctb], Jouni Helske [ctb], Kun Ren [ctb], Jeroen Ooms [ctb], Ken Williams [ctb], Chris Campbell [ctb], David Hugh-Jones [ctb], Qin Wang [ctb], Ivan Sagalaev [ctb, cph] (highlight.js library), Mark Otto [ctb] (Bootstrap library), Jacob Thornton [ctb] (Bootstrap library), Bootstrap contributors [ctb] (Bootstrap library), Twitter, Inc [cph] (Bootstrap library)
Maintainer: Jim Hester <james.f.hester@gmail.com>

Diff between covr versions 3.3.0 dated 2019-08-06 and 3.3.1 dated 2019-08-23

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Package tinytest updated to version 1.0.0 with previous version 0.9.6 dated 2019-06-28

Title: Lightweight and Feature Complete Unit Testing Framework
Description: Provides a lightweight (zero-dependency) and easy to use unit testing framework. Main features: install tests with the package. Test results are treated as data that can be stored and manipulated. Test files are R scripts interspersed with test commands, that can be programmed over. Fully automated build-install-test sequence for packages. Skip tests when not run locally (e.g. on CRAN). Flexible and configurable output printing. Compare computed output with output stored with the package. Run tests in parallel. Extensible by other packages. Report side effects.
Author: Mark van der Loo [aut, cre]
Maintainer: Mark van der Loo <mark.vanderloo@gmail.com>

Diff between tinytest versions 0.9.6 dated 2019-06-28 and 1.0.0 dated 2019-08-23

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Package RcmdrPlugin.NMBU updated to version 1.8.10 with previous version 1.8.9 dated 2018-08-24

Title: R Commander Plug-in for University Level Applied Statistics
Description: An R Commander "plug-in" extending functionality of linear models and providing an interface to Partial Least Squares Regression and Linear and Quadratic Discriminant analysis. Several statistical summaries are extended, predictions are offered for additional types of analyses, and extra plots, tests and mixed models are available.
Author: Kristian Hovde Liland [aut, cre], Solve Sæbø [aut]
Maintainer: Kristian Hovde Liland <kristian.liland@nmbu.no>

Diff between RcmdrPlugin.NMBU versions 1.8.9 dated 2018-08-24 and 1.8.10 dated 2019-08-23

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Package hpa (with last version 1.0.0) was removed from CRAN

Previous versions (as known to CRANberries) which should be available via the Archive link are:

2019-08-23 1.0.0

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Package sigora updated to version 3.0.5 with previous version 3.0.1 dated 2018-09-28

Title: Signature Overrepresentation Analysis
Description: Pathway Analysis is the process of statistically linking observations on the molecular level to biological processes or pathways on the systems(i.e. organism, organ, tissue, cell) level. Traditionally, pathway analysis methods regard pathways as collections of single genes and treat all genes in a pathway as equally informative. This can lead to identification of spurious pathways as statistically significant, since components are often shared amongst pathways. SIGORA seeks to avoid this pitfall by focusing on genes or gene-pairs that are (as a combination) specific to a single pathway. In relying on such pathway gene-pair signatures (Pathway-GPS), SIGORA inherently uses the status of other genes in the experimental context to identify the most relevant pathways. The current version allows for pathway analysis of human and mouse datasets and contains pre-computed Pathway-GPS data for pathways in the KEGG and Reactome pathway repositories as well as mechanisms for extracting GPS for user supplied repositories.
Author: Amir B.K. Foroushani, Fiona S.L. Brinkman, David J. Lynn
Maintainer: Amir Foroushani <sigora.dev@gmail.com>

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Package pricesensitivitymeter updated to version 1.1.1 with previous version 1.0.1 dated 2019-04-29

Title: Van Westendorp Price Sensitivity Meter Analysis
Description: An implementation of the van Westendorp Price Sensitivity Meter in R, which is a survey-based approach to analyze consumer price preferences and sensitivity (van Westendorp 1976, isbn:9789283100386).
Author: Max Alletsee [aut, cre]
Maintainer: Max Alletsee <max.alletsee@gmail.com>

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Package GGIR updated to version 1.10-1 with previous version 1.9-2 dated 2019-07-03

Title: Raw Accelerometer Data Analysis
Description: A tool to process and analyse data collected with wearable raw acceleration sensors as described in van Hees and colleagues (2014) <doi: 10.1152/japplphysiol.00421.2014> and (2015) <doi: 10.1371/journal.pone.0142533>. The package has been developed and tested for binary data from 'GENEActiv' <https://www.activinsights.com/> and GENEA devices (not for sale), .csv-export data from 'Actigraph' <http://actigraphcorp.com> devices, and .cwa and .wav-format data from 'Axivity' <https://axivity.com/product/ax3>. These devices are currently widely used in research on human daily physical activity.
Author: Vincent T van Hees [aut, cre], Zhou Fang [ctb], Jing Hua Zhao [ctb], Joe Heywood [ctb], Evgeny Mirkes [ctb], Severine Sabia [ctb], Joan Capdevila Pujol [ctb], Jairo H Migueles [ctb]
Maintainer: Vincent T van Hees <vincentvanhees@gmail.com>

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Package UCSCXenaShiny updated to version 0.3.0 with previous version 0.2.0 dated 2019-07-10

Title: A Shiny App for UCSC Xena Database
Description: Provides a web app for downloading, analyzing and visualizing datasets from UCSC Xena (<http://xena.ucsc.edu/>), which is a collection of UCSC-hosted public databases such as TCGA, ICGC, TARGET, GTEx, CCLE, and others.
Author: Shixiang Wang [aut] (<https://orcid.org/0000-0001-9855-7357>), Yi Xiong [aut] (<https://orcid.org/0000-0002-4370-9824>), Longfei Zhao [aut] (<https://orcid.org/0000-0002-6277-0137>), Kai Gu [aut, cre] (<https://orcid.org/0000-0002-0177-0774>), Yin Li [aut], Fei Zhao [aut]
Maintainer: Kai Gu <gukai1212@163.com>

Diff between UCSCXenaShiny versions 0.2.0 dated 2019-07-10 and 0.3.0 dated 2019-08-23

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New package SimBIID with initial version 0.1.0
Package: SimBIID
Title: Simulation-Based Inference Methods for Infectious Disease Models
Version: 0.1.0
Authors@R: c(person("Trevelyan J.", "McKinley", email = "t.mckinley@exeter.ac.uk", role = c("aut", "cre")), person("Stefan", "Widgren", role = "aut", email = "stefan.widgren@gmail.com", comment = "Author of 'R/mparse.R'"), person("Pavol", "Bauer", role = "cph", comment = 'R/mparse.R'), person("Robin", "Eriksson", role = "cph", comment = 'R/mparse.R'), person("Stefan", "Engblom", role = "cph", comment = 'R/mparse.R'))
Description: Provides some code to run simulations of state-space models, and then use these in the Approximate Bayesian Computation Sequential Monte Carlo (ABC-SMC) algorithm of Toni et al. (2009) <doi:10.1098/rsif.2008.0172> and a bootstrap particle filter based particle Markov chain Monte Carlo (PMCMC) algorithm (Andrieu et al., 2010 <doi:10.1111/j.1467-9868.2009.00736.x>). Also provides functions to plot and summarise the outputs.
License: GPL (>= 3)
Depends: R (>= 3.5)
Imports: stats, dplyr, purrr, tibble, ggplot2, tidyr, mvtnorm, grDevices, RColorBrewer, Rcpp, RcppXPtrUtils, coda
Suggests: parallel, GGally, testthat
LinkingTo: Rcpp, RcppArmadillo
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: yes
Packaged: 2019-08-23 14:40:30 UTC; tj
Author: Trevelyan J. McKinley [aut, cre], Stefan Widgren [aut] (Author of 'R/mparse.R'), Pavol Bauer [cph] (R/mparse.R), Robin Eriksson [cph] (R/mparse.R), Stefan Engblom [cph] (R/mparse.R)
Maintainer: Trevelyan J. McKinley <t.mckinley@exeter.ac.uk>
Repository: CRAN
Date/Publication: 2019-08-23 15:30:11 UTC

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New package sicegar with initial version 0.2.3
Package: sicegar
Type: Package
Title: Analysis of Single-Cell Viral Growth Curves
Version: 0.2.3
Authors@R: c( person( given = "M. Umut", family = "Caglar", role = c("aut"), email = "umut.caglar@gmail.com" ), person( given = "Claus O.", family = "Wilke", role = c("aut", "cre"), email = "wilke@austin.utexas.edu", comment = c(ORCID = "0000-0002-7470-9261") ) )
Description: Aims to quantify time intensity data by using sigmoidal and double sigmoidal curves. It fits straight lines, sigmoidal, and double sigmoidal curves on to time vs intensity data. Then all the fits are used to make decision on which model (sigmoidal, double sigmoidal, no signal or ambiguous) best describes the data. No signal means the intensity does not reach a high enough point or does not change at all over time. Sigmoidal means intensity starts from a small number than climbs to a maximum. Double sigmoidal means intensity starts from a small number, climbs to a maximum then starts to decay. After the decision between those four options, the algorithm gives the sigmoidal (or double sigmoidal) associated parameter values that quantifies the time intensity curve. The origin of the package name came from "SIngle CEll Growth Analysis in R".
URL: https://github.com/wilkelab/sicegar
Imports: dplyr, minpack.lm, fBasics, ggplot2, stats
License: GPL-2 | GPL-3
LazyData: true
Suggests: covr, cowplot, testthat, vdiffr, knitr
VignetteBuilder: knitr
BugReports: https://github.com/wilkelab/sicegar/issues
Collate: 'categorize.R' 'mainFunctions.R' 'multipleFitFunction.R' 'sigmoidalFitFunctions.R' 'doublesigmoidalFitFunctions.R' 'normalizationFunction.R' 'sicegar.R' 'dataInputCheck.R' 'parameterCalculation.R' 'figureGeneration.R'
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-08-22 21:34:42 UTC; clauswilke
Author: M. Umut Caglar [aut], Claus O. Wilke [aut, cre] (<https://orcid.org/0000-0002-7470-9261>)
Maintainer: Claus O. Wilke <wilke@austin.utexas.edu>
Repository: CRAN
Date/Publication: 2019-08-23 15:30:02 UTC

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Package RecordLinkage updated to version 0.4-11.2 with previous version 0.4-11.1 dated 2019-05-28

Title: Record Linkage in R
Description: Provides functions for linking and de-duplicating data sets. Methods based on a stochastic approach are implemented as well as classification algorithms from the machine learning domain.
Author: Andreas Borg <andreas.borg.public@posteo.de>, Murat Sariyar <murat.sariyar@charite.de>
Maintainer: ORPHANED

Diff between RecordLinkage versions 0.4-11.1 dated 2019-05-28 and 0.4-11.2 dated 2019-08-23

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New package PML with initial version 1.0
Package: PML
Type: Package
Title: Penalized Multi-Band Learning for Circadian Rhythm Analysis Using Actigraphy
Version: 1.0
Date: 2019-08-16
Authors@R: c(person(given = "Xinyue", family = "Li", email = "xinyue.li@yale.edu", role = c("aut", "cre")), person(given="Michael", family="Kane", email = "michael.kane@yale.edu", role = c("aut")))
Maintainer: Xinyue Li <xinyue.li@yale.edu>
Description: Penalized Multi-Band Learning algorithm can be effectively implemented for circadian rhythm analysis and daily activity pattern characterization using actigraphy (continuously measured objective physical activity data). Functions for interactive visualization of actigraph data are also included. Method reference: Li, X., Kane, M., Zhang, Y., Sun, W., Song, Y., Dong, S., Lin, Q., Zhu, Q., Jiang, F., Zhao, H. (2019) A Novel Penalized Multi-band Learning Approach Characterizes the Consolidation of Sleep-Wake Circadian Rhythms During Early Childhood Development.
Depends: R (>= 3.4.0)
License: GPL (>= 2)
Imports: trelliscopejs,tidyr,rbokeh,dplyr,
Encoding: UTF-8
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
RoxygenNote: 6.1.1
URL: https://github.com/xinyue-L/PML
BugReports: https://github.com/xinyue-L/PML/issues
NeedsCompilation: no
Packaged: 2019-08-23 13:26:37 UTC; xinyueli
Author: Xinyue Li [aut, cre], Michael Kane [aut]
Repository: CRAN
Date/Publication: 2019-08-23 15:10:05 UTC

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New package PetfindeR with initial version 2.0.0
Package: PetfindeR
Type: Package
Title: 'Petfinder' API Wrapper
Version: 2.0.0
Author: Aaron Schlegel
Maintainer: Aaron Schlegel <aaron@aaronschlegel.me>
Description: Wrapper of the 'Petfinder API' <https://www.petfinder.com/developers/v2/docs/> that implements methods for interacting with and extracting data from the 'Petfinder' database. The 'Petfinder REST API' allows access to the 'Petfinder' database, one of the largest online databases of adoptable animals and animal welfare organizations across North America.
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
License: MIT + file LICENSE
URL: https://github.com/aschleg/PetfindeR
VignetteBuilder: knitr
Imports: R6, httr, jsonlite
Suggests: testthat, knitr, rmarkdown, dplyr
NeedsCompilation: no
Packaged: 2019-08-23 15:16:35 UTC; aaronschlegel
Repository: CRAN
Date/Publication: 2019-08-23 15:30:15 UTC

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New package nlmixr with initial version 1.1.1-1
Package: nlmixr
Type: Package
Title: Nonlinear Mixed Effects Models in Population Pharmacokinetics and Pharmacodynamics
Depends: R (>= 3.5)
Imports: Rcpp (>= 0.12.3), brew, lattice, parallel, lbfgs, dparser, methods, ggplot2, memoise, rex, minqa, Matrix, R.utils, n1qn1, fastGHQuad, crayon, cli, RcppArmadillo (>= 0.5.600.2.0), vpc (>= 1.0.0), RxODE(>= 0.9.1-0), nlme, magrittr, tidyr, sys, generics, huxtable, digest, flextable, stringr, yaml
Suggests: knitr, rmarkdown, dplyr, data.table, lbfgsb3c, testthat, madness, devtools, expm, matrixcalc, reshape2, nloptr, ucminf, Rvmmin, broom.mixed, dotwhisker, officer, pkgdown, gridExtra, xpose, drake (>= 7.5.2)
Version: 1.1.1-1
Authors@R: c(person("Matthew","Fidler", role = "aut", email = "matthew.fidler@gmail.com", comment=c(ORCID="0000-0001-8538-6691")), person("Yuan", "Xiong", role = "aut", email = "yuan.xiong@gmail.com"), person("Rik", "Schoemaker", role = "aut", email = "rik.schoemaker@occams.com", comment=c(ORCID="0000-0002-7538-3005")), person("Justin", "Wilkins", role = "aut", email = "justin.wilkins@occams.com", comment=c(ORCID="0000-0002-7099-9396")), person("Mirjam","Trame", role = "aut", email = "mirjam.trame@gmail.com"), person("Richard", "Hooijmaijers", email = "richardhooijmaijers@gmail.com", role = "aut"), 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("Johannes", "Pfeifer",role="ctb"), person("Robert B.", "Schnabel",role="ctb"), person("Elizabeth", "Eskow", role="ctb"), person("Emmanuelle", "Comets", role="ctb", email="emmanuelle.comets@inserm.fr"), person("Audrey", "Lavenu", role="ctb"), person("Marc", "Lavielle", role="ctb"), person("David","Ardia",role = "cph"), person("Bill", "Denney", role=c("ctb"), email="wdenney@humanpredictions.com", comment=c(ORCID="0000-0002-5759-428X")), 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), RxODE(>= 0.9.1-3), RcppEigen (>= 0.3.3.3.0), lbfgsb3c, Rcpp, BH, StanHeaders(>= 2.18.0)
URL: https://github.com/nlmixrdevelopment/nlmixr
LazyData: true
VignetteBuilder: knitr
RoxygenNote: 6.1.1
Biarch: true
Packaged: 2019-08-23 14:03:50 UTC; annie
Maintainer: Wenping Wang <wwang8198@gmail.com>
Author: Matthew Fidler [aut] (<https://orcid.org/0000-0001-8538-6691>), Yuan Xiong [aut], Rik Schoemaker [aut] (<https://orcid.org/0000-0002-7538-3005>), Justin Wilkins [aut] (<https://orcid.org/0000-0002-7099-9396>), Mirjam Trame [aut], Richard Hooijmaijers [aut], Teun Post [aut], Robert Leary [ctb], Wenping Wang [aut, cre], Hadley Wickham [ctb], Dirk Eddelbuettel [cph], Johannes Pfeifer [ctb], Robert B. Schnabel [ctb], Elizabeth Eskow [ctb], Emmanuelle Comets [ctb], Audrey Lavenu [ctb], Marc Lavielle [ctb], David Ardia [cph], Bill Denney [ctb] (<https://orcid.org/0000-0002-5759-428X>), Katharine Mullen [cph]
Repository: CRAN
Date/Publication: 2019-08-23 15:20:03 UTC

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New package fdm2id with initial version 0.8.7
Package: fdm2id
Title: Data Mining and R Programming for Beginners
Version: 0.8.7
Authors@R: person("Alexandre", "Blansché", email = "alexandre.blansche@univ-lorraine.fr", role = c("aut", "cre"))
Description: Contains functions to simplify the use of data mining methods (classification, regression, clustering, etc.), for students and beginners in R programming. Various R packages are used and wrappers are built around the main functions, to standardize the use of data mining methods (input/output): it brings a certain loss of flexibility, but also a gain of simplicity. The package name came from the French "Fouille de Données en Master 2 Informatique Décisionnelle".
Depends: R (>= 3.6.0), arules, FactoMineR, mclust, nnet, pls
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Imports: car, caret, class, cluster, e1071, flexclust, fpc, glmnet, graphics, grDevices, ibr, irr, kohonen, leaps, MASS, mda, meanShiftR, methods, NMF, questionr, randomForest, ROCR, rpart, Rtsne, stats, utils, xgboost
Suggests: datasets, fds
NeedsCompilation: no
Packaged: 2019-08-22 15:43:32 UTC; blansche
Author: Alexandre Blansché [aut, cre]
Maintainer: Alexandre Blansché <alexandre.blansche@univ-lorraine.fr>
Repository: CRAN
Date/Publication: 2019-08-23 15:20:08 UTC

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Package dsr updated to version 0.2.2 with previous version 0.2.1 dated 2019-01-09

Title: Compute Directly Standardized Rates, Ratios and Differences
Description: A set of functions to compute and compare directly standardized rates, rate differences and ratios. A variety of user defined options for analysis (e.g confidence intervals) and formatting are included.
Author: Matthew Kumar <mattkumar@gmail.com>
Maintainer: Matthew Kumar <mattkumar@gmail.com>

Diff between dsr versions 0.2.1 dated 2019-01-09 and 0.2.2 dated 2019-08-23

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New package dfadjust with initial version 1.0.0
Package: dfadjust
Title: Degrees of Freedom Adjustment for Robust Standard Errors
Version: 1.0.0
Authors@R: person(given = "Michal", family = "Kolesár", role = c("aut", "cre"), email = "kolesarmi@googlemail.com", comment = c(ORCID = "0000-0002-2482-7796"))
Description: Computes small-sample degrees of freedom adjustment for heteroskedasticity robust standard errors, and for clustered standard errors in linear regression. See Imbens and Kolesár (1994) <doi:10.1162/REST_a_00552> for a discussion of these adjustments.
Depends: R (>= 3.5.0)
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Suggests: testthat (>= 2.1.0), sandwich, knitr, rmarkdown, spelling, formatR
RoxygenNote: 6.1.1
URL: https://github.com/kolesarm/Robust-Small-Sample-Standard-Errors
BugReports: https://github.com/kolesarm/Robust-Small-Sample-Standard-Errors/issues
Language: en-US
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-08-22 16:58:17 UTC; kolesarm
Author: Michal Kolesár [aut, cre] (<https://orcid.org/0000-0002-2482-7796>)
Maintainer: Michal Kolesár <kolesarmi@googlemail.com>
Repository: CRAN
Date/Publication: 2019-08-23 15:30:05 UTC

More information about dfadjust at CRAN
Permanent link

Package gmailr updated to version 1.0.0 with previous version 0.7.1 dated 2016-04-11

Title: Access the 'Gmail' 'RESTful' API
Description: An interface to the 'Gmail' 'RESTful' API. Allows access to your 'Gmail' messages, threads, drafts and labels.
Author: Jim Hester
Maintainer: Jim Hester <james.f.hester@gmail.com>

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More information about gmailr at CRAN
Permanent link

Package validate updated to version 0.9.1 with previous version 0.2.6 dated 2018-08-01

Title: Data Validation Infrastructure
Description: Declare data validation rules and data quality indicators; confront data with them and analyze or visualize the results. The package supports rules that are per-field, in-record, cross-record or cross-dataset. Rules can be automatically analyzed for rule type and connectivity. See also Van der Loo and De Jonge (2018) <doi:10.1002/9781118897126>, chapter 6.
Author: Mark van der Loo [cre, aut] (<https://orcid.org/0000-0002-9807-4686>), Edwin de Jonge [aut], Paul Hsieh [ctb]
Maintainer: Mark van der Loo <mark.vanderloo@gmail.com>

Diff between validate versions 0.2.6 dated 2018-08-01 and 0.9.1 dated 2019-08-23

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Package oceanis updated to version 1.0.0 with previous version 0.8.6 dated 2019-07-05

Title: Cartography for Statistical Analysis
Description: Creating maps for statistical analysis such as proportional circles, chroropleth, typology and flows. Some functions use 'shiny' or 'leaflet' technologies for dynamism and interactivity. The great features are : - Create maps in a web environment where the parameters are modifiable on the fly ('shiny' and 'leaflet' technology). - Create interactive maps through zoom and pop-up ('leaflet' technology). - Create frozen maps with the possibility to add labels.
Author: Sébastien CALVET - PSAR-AT - DR Provence-Alpes-Cote d'Azur - INSEE [cre, aut], Sophie AUDRIC - PSAR-AT - DR Provence-Alpes-Cote d'Azur - INSEE [aut], SED - DR Hauts-de-France - INSEE [ctb], PSAR-SL - DR Auvergne-Rhone-Alpes - INSEE [ctb], PSAR-EEP - DR Occitanie - INSEE [ctb], SED - DR Pays-de-la-Loire - INSEE [ctb]
Maintainer: Sébastien CALVET <sebastien.calvet@insee.fr>

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Package komaletter updated to version 0.3.1 with previous version 0.3.0 dated 2018-10-12

Title: Simple yet Flexible Letters via the 'KOMA-Script LaTeX Bundle'
Description: An R Markdown template for writing beautiful yet versatile letters, using the 'KOMA-Script' letter class 'scrlttr2' and an adaptation of the 'pandoc-letter' template. 'scrlttr2' provides layouts for many different window envelope types and the possibility to define your own.
Author: Robert Nuske [aut, cre] (<https://orcid.org/0000-0001-9773-2061>), Dirk Eddelbuettel [aut], Aaron Wolen [aut]
Maintainer: Robert Nuske <robert.nuske@mailbox.org>

Diff between komaletter versions 0.3.0 dated 2018-10-12 and 0.3.1 dated 2019-08-23

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Package TAM updated to version 3.3-10 with previous version 3.2-24 dated 2019-07-04

Title: Test Analysis Modules
Description: Includes marginal maximum likelihood estimation and joint maximum likelihood estimation for unidimensional and multidimensional item response models. The package functionality covers the Rasch model, 2PL model, 3PL model, generalized partial credit model, multi-faceted Rasch model, nominal item response model, structured latent class model, mixture distribution IRT models, and located latent class models. Latent regression models and plausible value imputation are also supported. For details see Adams, Wilson and Wang, 1997 <doi:10.1177/0146621697211001>, Adams, Wilson and Wu, 1997 <doi:10.3102/10769986022001047>, Formann, 1982 <doi:10.1002/bimj.4710240209>, Formann, 1992 <doi:10.1080/01621459.1992.10475229>.
Author: Alexander Robitzsch [aut, cre], Thomas Kiefer [aut], Margaret Wu [aut]
Maintainer: Alexander Robitzsch <robitzsch@ipn.uni-kiel.de>

Diff between TAM versions 3.2-24 dated 2019-07-04 and 3.3-10 dated 2019-08-23

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Package portfolioBacktest updated to version 0.2.0 with previous version 0.1.1 dated 2019-07-05

Title: Automated Backtesting of Portfolios over Multiple Datasets
Description: Automated backtesting of multiple portfolios over multiple datasets of stock prices in a rolling-window fashion. Intended for researchers and practitioners to backtest a set of different portfolios, as well as by a course instructor to assess the students in their portfolio design in a fully automated and convenient manner, with results conveniently formatted in tables and plots. Each portfolio design is easily defined as a function that takes as input a window of the stock prices and outputs the portfolio weights. Multiple portfolios can be easily specified as a list of functions or as files in a folder. Multiple datasets can be conveniently extracted randomly from different markets, different time periods, and different subsets of the stock universe. The results can be later assessed and ranked with tables based on a number of performance criteria (e.g., expected return, volatility, Sharpe ratio, drawdown, turnover rate, return on investment, computational time, etc.), as well as plotted in a number of ways with nice barplots and boxplots.
Author: Daniel P. Palomar [cre, aut], Rui Zhou [aut]
Maintainer: Daniel P. Palomar <daniel.p.palomar@gmail.com>

Diff between portfolioBacktest versions 0.1.1 dated 2019-07-05 and 0.2.0 dated 2019-08-23

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Package miceadds updated to version 3.5-14 with previous version 3.4-17 dated 2019-06-19

Title: Some Additional Multiple Imputation Functions, Especially for 'mice'
Description: Contains functions for multiple imputation which complements existing functionality in R. In particular, several imputation methods for the mice package (van Buuren & Groothuis-Oudshoorn, 2011, <doi:10.18637/jss.v045.i03>) are included. Main features of the miceadds package include plausible value imputation (Mislevy, 1991, <doi:10.1007/BF02294457>), multilevel imputation for variables at any level or with any number of hierarchical and non-hierarchical levels (Grund, Luedtke & Robitzsch, 2018, <doi:10.1177/1094428117703686>; van Buuren, 2018, Ch.7, <doi:10.1201/9780429492259>), imputation using partial least squares (PLS) for high dimensional predictors (Robitzsch, Pham & Yanagida, 2016), nested multiple imputation (Rubin, 2003, <doi:10.1111/1467-9574.00217>) and substantive model compatible imputation (Bartlett et al., 2015, <doi:10.1177/0962280214521348>).
Author: Alexander Robitzsch [aut, cre], Simon Grund [aut], Thorsten Henke [ctb]
Maintainer: Alexander Robitzsch <robitzsch@ipn.uni-kiel.de>

Diff between miceadds versions 3.4-17 dated 2019-06-19 and 3.5-14 dated 2019-08-23

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Package gamair updated to version 1.0-2 with previous version 1.0-0 dated 2016-10-07

Title: Data for 'GAMs: An Introduction with R'
Description: Data sets and scripts used in the book 'Generalized Additive Models: An Introduction with R', Wood (2006,2017) CRC.
Author: Simon Wood <simon.wood@r-project.org>
Maintainer: Simon Wood <simon.wood@r-project.org>

Diff between gamair versions 1.0-0 dated 2016-10-07 and 1.0-2 dated 2019-08-23

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Package ctsem updated to version 3.0.1 with previous version 3.0.0 dated 2019-07-31

Title: Continuous Time Structural Equation Modelling
Description: Hierarchical continuous time state space modelling, for linear and nonlinear systems measured by continuous variables, with limited support for binary data. The subject specific dynamic system is modelled as a stochastic differential equation (SDE), measurement models are typically multivariate normal factor models. Using the original ctsem formulation based on OpenMx, described in the JSS paper "Continuous Time Structural Equation Modeling with R Package ctsem", with updated version as CRAN vignette <https://cran.r-project.org/web/packages/ctsem/vignettes/ctsem.pdf> , linear mixed effects SDE's estimated via maximum likelihood and optimization are possible. Using the Stan based formulation, described in <https://github.com/cdriveraus/ctsem/raw/master/vignettes/hierarchicalmanual.pdf> , nonlinearity (state dependent parameters) and random effects on all parameters are possible, using either optimization (with optional importance sampling) or Stan's Hamiltonian Monte Carlo sampling. Priors may be used. For the conceptual overview of the hierarchical Bayesian linear SDE approach, see <https://www.researchgate.net/publication/324093594_Hierarchical_Bayesian_Continuous_Time_Dynamic_Modeling>. Exogenous inputs may also be included, for an overview of such possibilities see <https://www.researchgate.net/publication/328221807_Understanding_the_Time_Course_of_Interventions_with_Continuous_Time_Dynamic_Models> . Stan based functions are not available on 32 bit Windows systems at present.
Author: Charles Driver [aut, cre, cph], Manuel Voelkle [aut, cph], Han Oud [aut, cph], Trustees of Columbia University [cph]
Maintainer: Charles Driver <driver@mpib-berlin.mpg.de>

Diff between ctsem versions 3.0.0 dated 2019-07-31 and 3.0.1 dated 2019-08-23

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Package bcrm updated to version 0.5.4 with previous version 0.5.3 dated 2019-06-04

Title: Bayesian Continual Reassessment Method for Phase I Dose-Escalation Trials
Description: Implements a wide variety of one- and two-parameter Bayesian CRM designs. The program can run interactively, allowing the user to enter outcomes after each cohort has been recruited, or via simulation to assess operating characteristics. See Sweeting et al. (2013): <doi:10.18637/jss.v054.i13>.
Author: Michael Sweeting [aut], Graham Wheeler [aut, cre]
Maintainer: Graham Wheeler <graham.wheeler@ucl.ac.uk>

Diff between bcrm versions 0.5.3 dated 2019-06-04 and 0.5.4 dated 2019-08-23

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New package wyz.code.rdoc with initial version 1.1.6
Package: wyz.code.rdoc
Type: Package
Title: Wizardry Code Offensive Programming R Documentation
Version: 1.1.6
Author: Fabien Gelineau <neonira@gmail.com>
Maintainer: Fabien Gelineau <neonira@gmail.com>
Description: Allows to generate automatically R documentation files from offensive programming test cases. It populates most of the section of the documentation content from the offensive programming instrumentation. This reduces greatly the package producer effort and time to get to a fully documented manual page for any instrumented function. Following documentation sections are now automatically filled from instrumentation data: title, description, usage, arguments, value, author, examples. Sections references, notes and keyword are instrumented to industrialize their production. Produced manual pages are ready for completion (e.g note section if needed), language and phrasal adjustments. Main task for the package producer is now review, no more content production. Refer to chapter 9 of Offensive Programming Book, Fabien GELINEAU (2019, ISBN:979-10-699-4075-8), to learn about details and get value from this package.
Encoding: UTF-8
LazyData: true
License: GPL-3
Depends: R (>= 3.5)
Imports: methods, data.table (>= 1.11.8), tidyr, lubridate (>= 1.7.4), wyz.code.offensiveProgramming (>= 1.1.7)
Suggests: testthat, knitr, rmarkdown, DT (>= 0.5)
RoxygenNote: 6.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-08-22 07:42:02 UTC; fgelineau
Repository: CRAN
Date/Publication: 2019-08-23 11:20:02 UTC

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Package ICtest updated to version 0.3-2 with previous version 0.3-1 dated 2018-05-22

Title: Estimating and Testing the Number of Interesting Components in Linear Dimension Reduction
Description: For different linear dimension reduction methods like principal components analysis (PCA), independent components analysis (ICA) and supervised linear dimension reduction tests and estimates for the number of interesting components (ICs) are provided.
Author: Klaus Nordhausen, Hannu Oja, David E. Tyler, Joni Virta
Maintainer: Klaus Nordhausen <klaus.nordhausen@tuwien.ac.at>

Diff between ICtest versions 0.3-1 dated 2018-05-22 and 0.3-2 dated 2019-08-23

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New package nph with initial version 1.9
Package: nph
Title: Planning and Analysing Survival Studies under Non-Proportional Hazards
Version: 1.9
Authors@R: c( person("Robin", "Ristl", email = "robin.ristl@meduniwien.ac.at", role = c("aut", "cre")), person("Nicolas", "Ballarini", email = "nicolas.ballarini@meduniwien.ac.at", role = c("ctb")))
Description: Piecewise constant hazard functions are used to flexibly model survival distributions with non-proportional hazards and to simulate data from the specified distributions. Also, a function to calculate weighted log-rank tests for the comparison of two hazard functions is included. Finally, a function to calculate a test using the maximum of a set of test statistics from weighted log-rank tests is provided. This test utilizes the asymptotic multivariate normal joint distribution of the separate test statistics. The correlation is estimated from the data.
Date: 2019-08-21
Maintainer: Robin Ristl <robin.ristl@meduniwien.ac.at>
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
NeedsCompilation: no
Depends: R (>= 3.3.0)
Imports: stats, graphics, mvtnorm, ggplot2
Suggests: knitr, shiny, shinycssloaders, formatR, styler, rmarkdown
VignetteBuilder: knitr
Packaged: 2019-08-22 07:26:05 UTC; Robin
Author: Robin Ristl [aut, cre], Nicolas Ballarini [ctb]
Repository: CRAN
Date/Publication: 2019-08-23 10:50:02 UTC

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New package mod with initial version 0.1.3
Package: mod
Type: Package
Title: Lightweight and Self-Contained Modules for Code Organization
Version: 0.1.3
Authors@R: c( person("Siqi", "Zhang", email = "iqis.gnahz@gmail.com", role = c("aut", "cre")), person() )
Description: Creates modules inline or from a file. Modules can contain any R object and be nested. Each module have their own scope and package "search path" that does not interfere with one another or the user's working environment.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
URL: https://github.com/iqis/mod
BugReports: https://github.com/iqis/mod/issues
Suggests: testthat (>= 2.1.0), covr
NeedsCompilation: no
Packaged: 2019-08-22 02:33:34 UTC; Siqi
Author: Siqi Zhang [aut, cre]
Maintainer: Siqi Zhang <iqis.gnahz@gmail.com>
Repository: CRAN
Date/Publication: 2019-08-23 10:40:02 UTC

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New package iSTATS with initial version 0.1.0
Package: iSTATS
Type: Package
Title: A Graphical Interface to Perform STOCSY Analyses on NMR Data
Version: 0.1.0
Date: 2019-08-19
Author: Luiz Henrique Keng Queiroz Junior[aut,cre], Vitor Mendes de Oliveira [aut]
Maintainer: Luiz Henrique Keng Queiroz Junior <keng@ufg.br>
Description: Launches a 'shiny' based application for Nuclear Magnetic Resonance (NMR) data importation and Statistical TOtal Correlation SpectroscopY (STOCSY) analyses in a full interactive approach. The theoretical background and applications of STOCSY method could be found at Cloarec, O., Dumas, M. E., Craig, A., Barton, R. H., Trygg, J., Hudson, J., Blancher, C., Gauguier, D., Lindon, J. C., Holmes, E. & Nicholson, J. (2005) <doi:10.1021/ac048630x>.
Depends: R(>= 3.0)
Imports: Cairo(>= 1.5), ggplot2(>= 3.0.0), gtools(>= 3.8.1), shiny(>= 1.0.2), shinyBS(>= 0.61), shinyWidgets(>= 0.4.3)
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-08-22 05:48:41 UTC; keng
Repository: CRAN
Date/Publication: 2019-08-23 10:50:05 UTC

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New package hpa with initial version 1.0.0
Package: hpa
Type: Package
Title: Distributions Hermite Polynomial Approximation
Version: 1.0.0
Date: 2019-08-20
Author: Potanin Bogdan
Maintainer: Potanin Bogdan <bogdanpotanin@gmail.com>
Description: Multivariate conditional and marginal densities, moments, cumulative distribution functions as well as binary choice and sample selection models based on hermite polynomial approximation which was proposed and described by A. Gallant and D. W. Nychka (1987) <doi:10.2307/1913241>.
License: GPL-3
Imports: Rcpp (>= 1.0.1)
LinkingTo: Rcpp, RcppArmadillo
RoxygenNote: 6.1.1
Encoding: UTF-8
Suggests: ggplot2, mvtnorm, titanic, sampleSelection
NeedsCompilation: yes
Packaged: 2019-08-21 15:10:39 UTC; Bogdan
Repository: CRAN
Date/Publication: 2019-08-23 09:10:02 UTC

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Package hms updated to version 0.5.1 with previous version 0.5.0 dated 2019-07-09

Title: Pretty Time of Day
Description: Implements an S3 class for storing and formatting time-of-day values, based on the 'difftime' class.
Author: Kirill Müller [aut, cre], The R Consortium [fnd], RStudio [fnd]
Maintainer: Kirill Müller <krlmlr+r@mailbox.org>

Diff between hms versions 0.5.0 dated 2019-07-09 and 0.5.1 dated 2019-08-23

 DESCRIPTION                    |    8 ++++----
 MD5                            |   10 +++++-----
 NEWS.md                        |    5 +++++
 R/cast.R                       |    7 +++++--
 build/hms.pdf                  |binary
 tests/testthat/test-coercion.R |    3 +++
 6 files changed, 22 insertions(+), 11 deletions(-)

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New package Rwordseg with initial version 0.3-2
Package: Rwordseg
License: LGPL
Title: Chinese Word Segmentation
Type: Package
LazyLoad: yes
Author: Jian Li
Maintainer: Jian Li <rweibo@sina.com>
Description: Provides interfaces and useful tools for Chinese word segmentation. Implements a segmentation algorithm based on Hidden Markov Model (HMM) in native R codes. Methods for HHMM-Based Chinese lexical analyzer are as described in : Hua-Ping Zhang et al., (2003) <doi:10.3115/1119250.1119280>.
Version: 0.3-2
Date: 2019-08-21
Depends: R (>= 3.0.0), utils, stats, tmcn, HMM
Suggests: jiebaR, coreNLP
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2019-08-21 13:08:48 UTC; jli
Repository: CRAN
Date/Publication: 2019-08-23 09:00:06 UTC

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New package hchinamap with initial version 0.1.0
Package: hchinamap
Type: Package
Title: Mapping China and Its Provinces
Version: 0.1.0
Authors@R: person("Zhenxing", "Cheng", email = "czxjnu@163.com", role = c("aut", "cre"))
Description: By binding R functions and the 'Highmaps' <https://www.highcharts.com.cn/products/highmaps> chart library, 'hchinamap' package provides a simple way to map China and its provinces. The map of China drawn by this package contains complete Chinese territory, especially the Nine-dotted line, South Tibet, Hong Kong, Macao and Taiwan.
License: MIT + file LICENSE
Encoding: UTF-8
Date: 2019-08-18
URL: https://github.com/czxa/hchinamap
BugReports: https://github.com/czxa/hchinamap/issues
LazyData: true
RoxygenNote: 6.1.1
Depends: R (>= 3.0.0)
Suggests: knitr, rmarkdown, magrittr, dplyr, shiny, colourpicker
VignetteBuilder: knitr
Imports: htmlwidgets
NeedsCompilation: no
Packaged: 2019-08-21 05:41:33 UTC; czxa
Author: Zhenxing Cheng [aut, cre]
Maintainer: Zhenxing Cheng <czxjnu@163.com>
Repository: CRAN
Date/Publication: 2019-08-23 08:50:02 UTC

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Package gllvm updated to version 1.1.6 with previous version 1.1.3 dated 2019-04-16

Title: Generalized Linear Latent Variable Models
Description: Analysis of multivariate data using generalized linear latent variable models (gllvm). Estimation is performed using either Laplace approximation method or variational approximation method implemented via TMB (Kristensen et al., (2016), <doi:10.18637/jss.v070.i05>). For details see Niku et al. (2019) <doi:10.1371/journal.pone.0216129>.
Author: Jenni Niku, Wesley Brooks, Riki Herliansyah, Francis K.C. Hui, Sara Taskinen, David I. Warton
Maintainer: Jenni Niku <jenni.m.e.niku@jyu.fi>

Diff between gllvm versions 1.1.3 dated 2019-04-16 and 1.1.6 dated 2019-08-23

 DESCRIPTION             |   14 +
 MD5                     |   59 +++++--
 NAMESPACE               |   14 +
 R/TMBtrait.R            |   59 +++++--
 R/confint.gllvm.R       |    4 
 R/getLV.gllvm.R         |only
 R/gllvm.R               |   28 ++-
 R/gllvm.TMB.R           |   81 +++++++---
 R/gllvm.auxiliary.R     |  356 +++++++++++++++++++++++++++++-------------------
 R/ordiplot.gllvm.R      |   46 ++++--
 R/plot.gllvm.R          |   29 ++-
 R/predict.gllvm.R       |   22 ++
 R/predictLVs.gllvm.R    |only
 R/residuals.gllvm.R     |   22 ++
 R/simulate.gllvm.R      |only
 R/summary.gllvm.R       |    3 
 build                   |only
 data                    |only
 inst                    |only
 man/getLV.gllvm.Rd      |only
 man/gllvm.Rd            |   11 +
 man/ordiplot.gllvm.Rd   |    9 +
 man/plot.gllvm.Rd       |    9 -
 man/predict.gllvm.Rd    |    5 
 man/predictLVs.gllvm.Rd |only
 man/sim_bacteria.Rd     |only
 man/simulate.gllvm.Rd   |only
 src/gllvm.cpp           |   30 +++-
 tests                   |only
 vignettes               |only
 30 files changed, 544 insertions(+), 257 deletions(-)

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Package GLDEX updated to version 2.0.0.6 with previous version 2.0.0.5 dated 2016-12-26

Title: Fitting Single and Mixture of Generalised Lambda Distributions (RS and FMKL) using Various Methods
Description: The fitting algorithms considered in this package have two major objectives. One is to provide a smoothing device to fit distributions to data using the weight and unweighted discretised approach based on the bin width of the histogram. The other is to provide a definitive fit to the data set using the maximum likelihood and quantile matching estimation. Other methods such as moment matching, starship method, L moment matching are also provided. Diagnostics on goodness of fit can be done via qqplots, KS-resample tests and comparing mean, variance, skewness and kurtosis of the data with the fitted distribution.
Author: Steve Su, with contributions from: Diethelm Wuertz, Martin Maechler and Rmetrics core team members for low discrepancy algorithm, Juha Karvanen for L moments codes, Robert King for gld C codes and starship codes, Benjamin Dean for corrections and input in ks.gof code and R core team for histsu function.
Maintainer: Steve Su <allegro.su@gmail.com>

Diff between GLDEX versions 2.0.0.5 dated 2016-12-26 and 2.0.0.6 dated 2019-08-23

 DESCRIPTION                  |    8 ++++----
 MD5                          |    6 +++---
 man/fun.diag.ks.g.Rd         |    4 ++--
 man/fun.diag.ks.g.bimodal.Rd |    2 +-
 4 files changed, 10 insertions(+), 10 deletions(-)

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New package completejourney with initial version 1.0.0
Package: completejourney
Title: Retail Shopping Data
Version: 1.0.0
Authors@R: c( person("Brad", "Boehmke", email = "bradleyboehmke@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-3611-8516")), person(c("Steven", "M."), "Mortimer", email = "reportmort@gmail.com", role = "aut") )
Description: Retail shopping transactions for 2,469 households over one year. Originates from the 84.51° Complete Journey 2.0 source files <https://www.8451.com/area51> which also includes useful metadata on products, coupons, campaigns, and promotions.
License: CC0
LazyData: true
Depends: R (>= 2.10)
Imports: dplyr, tibble, progress, stringr, zeallot
Suggests: lubridate, knitr, rmarkdown, testthat
URL: https://github.com/bradleyboehmke/completejourney
BugReports: https://github.com/bradleyboehmke/completejourney/issues
RoxygenNote: 6.1.1
Encoding: UTF-8
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-08-21 14:10:09 UTC; b294776
Author: Brad Boehmke [aut, cre] (<https://orcid.org/0000-0002-3611-8516>), Steven M. Mortimer [aut]
Maintainer: Brad Boehmke <bradleyboehmke@gmail.com>
Repository: CRAN
Date/Publication: 2019-08-23 09:00:02 UTC

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Package epiR updated to version 1.0-4 with previous version 1.0-2 dated 2019-05-22

Title: Tools for the Analysis of Epidemiological Data
Description: Tools for the analysis of epidemiological data. Contains functions for directly and indirectly adjusting measures of disease frequency, quantifying measures of association on the basis of single or multiple strata of count data presented in a contingency table, and computing confidence intervals around incidence risk and incidence rate estimates. Miscellaneous functions for use in meta-analysis, diagnostic test interpretation, and sample size calculations.
Author: Mark Stevenson <mark.stevenson1@unimelb.edu.au> with contributions from Telmo Nunes, Cord Heuer, Jonathon Marshall, Javier Sanchez, Ron Thornton, Jeno Reiczigel, Jim Robison-Cox, Paola Sebastiani, Peter Solymos, Kazuki Yoshida, Geoff Jones, Sarah Pirikahu, Simon Firestone, Ryan Kyle, Johann Popp, Mathew Jay and Charles Reynard.
Maintainer: Mark Stevenson <mark.stevenson1@unimelb.edu.au>

Diff between epiR versions 1.0-2 dated 2019-05-22 and 1.0-4 dated 2019-08-23

 epiR-1.0-2/epiR/R/NEW_epi.2by2_v01.R   |only
 epiR-1.0-2/epiR/R/NEW_epi.2by2_v02.R   |only
 epiR-1.0-4/epiR/DESCRIPTION            |   10 ++---
 epiR-1.0-4/epiR/MD5                    |   12 ++----
 epiR-1.0-4/epiR/R/epi.cp.R             |    4 +-
 epiR-1.0-4/epiR/R/epi.tests.R          |   35 +++++++++++++++++++
 epiR-1.0-4/epiR/man/epi.interaction.Rd |    4 +-
 epiR-1.0-4/epiR/man/epi.tests.Rd       |   58 +++++++++++++++++++++++++++++----
 8 files changed, 100 insertions(+), 23 deletions(-)

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