Sat, 06 Oct 2018

New package tls with initial version 0.1.0
Package: tls
Title: Tools of Total Least Squares in Error-in-Variables Models
Version: 0.1.0
Date: 2018-09-28
Authors@R: c( person(given = "Yan", family = "Li", email = "yan.4.li@uconn.edu", role = c("aut", "cre")), person(given = "Kun", family = "Chen", role = "aut"), person(given = "Jun", family = "Yan", role = "aut"))
Description: Functions for point and interval estimation in error-in-variables models via total least squares or generalized total least squares method. See Golub and Van Loan (1980) <doi:10.1137/0717073>, Gleser (1981) <https://www.jstor.org/stable/2240867>, Ivan Markovsky and Huffel (2007) <doi:10.1016/j.sigpro.2007.04.004> for more information.
Depends: R (>= 3.2.3)
Imports: stats, utils
License: GPL (>= 3)
URL: https://github.com/LiYanStat/tls
BugReports: https://github.com/LiYanStat/tls/issues
Repository: CRAN
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-09-28 23:29:10 UTC; YLi
Author: Yan Li [aut, cre], Kun Chen [aut], Jun Yan [aut]
Maintainer: Yan Li <yan.4.li@uconn.edu>
Date/Publication: 2018-10-06 23:00:03 UTC

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New package lamme with initial version 0.0.1
Package: lamme
Title: Log-Analytic Methods for Multiplicative Effects
Version: 0.0.1
Authors@R: person("Qimin", "Liu", email = "qliu6@nd.edu", role = c("aut", "cre"))
Description: Log-analytic methods intended for testing multiplicative effects.
Depends: R (>= 3.4.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0.9000
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-09-29 05:13:02 UTC; qliu6
Author: Qimin Liu [aut, cre]
Maintainer: Qimin Liu <qliu6@nd.edu>
Repository: CRAN
Date/Publication: 2018-10-06 23:00:06 UTC

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New package CoRpower with initial version 1.0.0
Package: CoRpower
Title: Power Calculations for Assessing Correlates of Risk in Clinical Efficacy Trials
Version: 1.0.0
BugReports: https://github.com/mjuraska/CoRpower/issues
Authors@R: c(person("Peter", "Gilbert", email = "pgilbert@scharp.org", role = "aut"), person("Stephanie", "Wu", email = "swu18@uw.edu", role = "aut"), person("Michal", "Juraska", email = "mjuraska@fredhutch.org", role = c("aut", "cre")), person("Yunda", "Huang", email = "yunda@scharp.org", role = "aut"))
Description: Calculates power for assessment of intermediate biomarker responses as correlates of risk in the active treatment group in clinical efficacy trials, as described in Gilbert, Janes, and Huang, Power/Sample Size Calculations for Assessing Correlates of Risk in Clinical Efficacy Trials (2016, Statistics in Medicine). The methods differ from past approaches by accounting for the level of clinical treatment efficacy overall and in biomarker response subgroups, which enables the correlates of risk results to be interpreted in terms of potential correlates of efficacy/protection. The methods also account for inter-individual variability of the observed biomarker response that is not biologically relevant (e.g., due to technical measurement error of the laboratory assay used to measure the biomarker response), which is important because power to detect a specified correlate of risk effect size is heavily affected by the biomarker's measurement error. The methods can be used for a general binary clinical endpoint model with a univariate dichotomous, trichotomous, or continuous biomarker response measured in active treatment recipients at a fixed timepoint after randomization, with either case-cohort Bernoulli sampling or case-control without-replacement sampling of the biomarker (a baseline biomarker is handled as a trivial special case). In a specified two-group trial design, the computeN() function can initially be used for calculating additional requisite design parameters pertaining to the target population of active treatment recipients observed to be at risk at the biomarker sampling timepoint. Subsequently, the power calculation employs an inverse probability weighted logistic regression model fitted by the tps() function in the 'osDesign' package. Power results as well as the relationship between the correlate of risk effect size and treatment efficacy can be visualized using various plotting functions.
URL: https://github.com/mjuraska/CoRpower
Depends: R (>= 3.5.0)
License: GPL-2
Encoding: UTF-8
Imports: survival, osDesign
RoxygenNote: 6.1.0
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
LazyData: true
NeedsCompilation: no
Packaged: 2018-09-28 21:34:45 UTC; mjuraska
Author: Peter Gilbert [aut], Stephanie Wu [aut], Michal Juraska [aut, cre], Yunda Huang [aut]
Maintainer: Michal Juraska <mjuraska@fredhutch.org>
Repository: CRAN
Date/Publication: 2018-10-06 23:00:09 UTC

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Package bazar updated to version 1.0.10 with previous version 1.0.9 dated 2018-07-31

Title: Miscellaneous Basic Functions
Description: A collection of miscellaneous functions for copying objects to the clipboard ('Copy'); manipulating strings ('concat', 'mgsub', 'trim', 'verlan'); loading or showing packages ('library_with_dep', 'require_with_dep', 'sessionPackages'); creating or testing for named lists ('nlist', 'as.nlist', 'is.nlist'), formulas ('is.formula'), empty objects ('as.empty', 'is.empty'), whole numbers ('as.wholenumber', 'is.wholenumber'); testing for equality ('almost.equal', 'almost.zero') and computing uniqueness ('almost.unique'); getting modified versions of usual functions ('rle2', 'sumNA'); making a pause or a stop ('pause', 'stopif'); converting into a function ('as.fun'); providing a C like ternary operator ('condition %?% true %:% false'); finding packages and functions ('get_all_pkgs', 'get_all_funs'); and others ('erase', '%nin%', 'unwhich', 'top', 'bot', 'normalize').
Author: Paul Poncet [aut, cre]
Maintainer: Paul Poncet <paulponcet@yahoo.fr>

Diff between bazar versions 1.0.9 dated 2018-07-31 and 1.0.10 dated 2018-10-06

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Package SSDforR updated to version 1.4.21 with previous version 1.4.20 dated 2018-09-25

Title: Functions to Analyze Single System Data
Description: Functions to visually and statistically analyze single system data.
Author: Charles Auerbach [aut, cre], Wendy Zeitlin [aut]
Maintainer: Charles Auerbach <auerbach@yu.edu>

Diff between SSDforR versions 1.4.20 dated 2018-09-25 and 1.4.21 dated 2018-10-06

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New package QDComparison with initial version 1.0
Package: QDComparison
Type: Package
Title: Modern Nonparametric Tools for Two-Sample Quantile and Distribution Comparisons
Version: 1.0
Date: 2018-09-25
Author: David Jungreis, Subhadeep Mukhopadhyay
Maintainer: David Jungreis <dbjungreis@gmail.com>
Description: Allows practitioners to determine (i) if two univariate distributions (which can be continuous, discrete, or even mixed) are equal, (ii) how two distributions differ (shape differences, e.g., location, scale, etc.), and (iii) where two distributions differ (at which quantiles), all using nonparametric LP statistics. The primary reference is Jungreis, D. and Mukhopadhyay, S. (2018, Technical Report).
License: GPL-2
NeedsCompilation: no
Packaged: 2018-09-28 17:18:00 UTC; Dave
Repository: CRAN
Date/Publication: 2018-10-06 21:20:11 UTC

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New package PredictionR with initial version 1.0-11
Package: PredictionR
Title: Prediction for Future Data from any Continuous Distribution
Version: 1.0-11
Authors@R: c(person("H. ", "M. Barakat", role = c("aut"), email = "hbarakat2@hotmail.com"), person("O. ", "M. Khaled", role = c("aut"), email = "osam87@yahoo.com"), person("Hadeer ", "A. Ghonem", role = c("aut", "cre"), email = "hadeer_ghonem15@yahoo.com"))
Author: H. M. Barakat [aut], O. M. Khaled [aut], Hadeer A. Ghonem [aut, cre]
Maintainer: Hadeer A. Ghonem <hadeer_ghonem15@yahoo.com>
Description: Functions to get prediction intervals and prediction points of future observations from any continuous distribution.
License: GPL (>= 2)
LazyData: TRUE
Imports: stats, fitdistrplus
Suggests: actuar
NeedsCompilation: no
Packaged: 2018-09-28 15:25:40 UTC; USER
Repository: CRAN
Date/Publication: 2018-10-06 21:30:14 UTC

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New package outcomerate with initial version 1.0.1
Package: outcomerate
Version: 1.0.1
Title: AAPOR Survey Outcome Rates
Description: Standardized survey outcome rate functions, including the response rate, contact rate, cooperation rate, and refusal rate. These outcome rates allow survey researchers to measure the quality of survey data using definitions published by the American Association of Public Opinion Research (AAPOR). For details on these standards, see AAPOR (2016) <https://www.aapor.org/Standards-Ethics/Standard-Definitions-(1).aspx>.
Authors@R: c( person(given = "Rafael", family = "Pilliard Hellwig", email = "rafael.taph@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-3092-3493")), person(given = "Carl", family = "Ganz", role = "rev"), person(given = "Neal", family = "Richardson", role = "rev") )
License: CC0
Encoding: UTF-8
LazyData: true
ByteCompile: true
RoxygenNote: 6.1.0
Depends: R (>= 2.10)
Suggests: dplyr, forcats, ggplot2, knitr, testthat, tidyr, covr, rmarkdown, spelling, stringr
Imports: Rdpack (>= 0.7), stats
RdMacros: Rdpack
Language: en-US
URL: https://github.com/ropensci/outcomerate
BugReports: https://github.com/ropensci/outcomerate/issues
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-09-27 21:13:18 UTC; rtaph
Author: Rafael Pilliard Hellwig [aut, cre] (<https://orcid.org/0000-0002-3092-3493>), Carl Ganz [rev], Neal Richardson [rev]
Maintainer: Rafael Pilliard Hellwig <rafael.taph@gmail.com>
Repository: CRAN
Date/Publication: 2018-10-06 21:20:03 UTC

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New package mlflow with initial version 0.7.0
Package: mlflow
Type: Package
Title: Interface to 'MLflow'
Version: 0.7.0
Authors@R: c( person("Matei", "Zaharia", email = "matei@databricks.com", role = c("aut", "cre")), person("Javier", "Luraschi", email = "javier@rstudio.com", role = c("aut")), person("Kevin", "Kuo", role = c("aut"), email = "kevin.kuo@rstudio.com", comment = c(ORCID = "0000-0001-7803-7901")), person(family = "RStudio", role = c("cph")) )
Maintainer: Matei Zaharia <matei@databricks.com>
Description: R interface to 'MLflow', open source platform for the complete machine learning life cycle, see <https://mlflow.org/>. This package supports installing 'MLflow', tracking experiments, creating and running projects, and saving and serving models.
License: Apache License 2.0
URL: https://github.com/mlflow/mlflow
BugReports: https://github.com/mlflow/mlflow/issues
SystemRequirements: MLflow (https://www.mlflow.org/)
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.1.2)
Imports: aws.s3, forge, fs, git2r, httpuv, httr, jsonlite, openssl, processx, reticulate, packrat, purrr, swagger, withr, xml2, yaml, pryr, rlang (>= 0.2.0)
RoxygenNote: 6.1.0
Suggests: covr, keras, lintr, testthat
NeedsCompilation: no
Packaged: 2018-09-28 19:17:25 UTC; tomas
Author: Matei Zaharia [aut, cre], Javier Luraschi [aut], Kevin Kuo [aut] (<https://orcid.org/0000-0001-7803-7901>), RStudio [cph]
Repository: CRAN
Date/Publication: 2018-10-06 21:30:03 UTC

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New package metamedian with initial version 0.1.0
Package: metamedian
Type: Package
Title: Meta-Analysis of Medians
Version: 0.1.0
Authors@R: c(person("Sean", "McGrath", role = c("aut", "cre"), email = "sean.mcgrath@mail.mcgill.ca"), person("XiaoFei", "Zhao", role = c("aut"), email = "xiaofei.zhao@mail.mcgill.ca"), person("Russell", "Steele", role = c("aut"), email = "russell.steele@mcgill.ca"), person("Andrea", "Benedetti", role = c("aut"), email = "andrea.benedetti@mcgill.ca"))
Author: Sean McGrath [aut, cre], XiaoFei Zhao [aut], Russell Steele [aut], Andrea Benedetti [aut]
Maintainer: Sean McGrath <sean.mcgrath@mail.mcgill.ca>
Description: Implements several methods to meta-analyze one-group or two-group studies that report the median of the outcome. These methods estimate the pooled median in the one-group context and the pooled raw difference of medians across groups in the two-group context.
Imports: stats, metafor, Hmisc
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2018-09-28 18:13:28 UTC; Sean
Repository: CRAN
Date/Publication: 2018-10-06 21:30:07 UTC

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Package installr updated to version 0.21.0 with previous version 0.20.0 dated 2018-05-02

Title: Using R to Install Stuff (Such As: R, 'Rtools', 'RStudio', 'Git', and More!)
Description: R is great for installing software. Through the 'installr' package you can automate the updating of R (on Windows, using updateR()) and install new software. Software installation is initiated through a GUI (just run installr()), or through functions such as: install.Rtools(), install.pandoc(), install.git(), and many more. The updateR() command performs the following: finding the latest R version, downloading it, running the installer, deleting the installation file, copy and updating old packages to the new R installation.
Author: Tal Galili [aut, cre, cph] (http://www.r-statistics.com), Barry Rowlingson [ctb], Boris Hejblum [ctb], Dason [ctb], Felix Schonbrodt [ctb], G. Grothendieck [ctb], GERGELY DAROCZI [ctb], Heuristic Andrew [ctb], James [ctb] (http://stackoverflow.com/users/269476/james), Thomas Leeper [ctb] (http://thomasleeper.com/), VitoshKa [ctb], Yihui Xie [ctb] (http://yihui.name), Michael Friendly [ctb] (http://datavis.ca/), Kornelius Rohmeyer [ctb] (http://algorithm-forge.com/techblog/), Dieter Menne [ctb], Tyler Hunt [ctb] (https://github.com/JackStat), Takekatsu Hiramura [ctb] (https://github.com/hiratake55), Berry Boessenkool [ctb] (https://github.com/BerryBoessenkool), Jonathan Godfrey [ctb] (https://github.com/ajrgodfrey), Tom Allard [ctb], ChingChuan Chen [ctb], Jonathan Hill [ctb], Chan-Yub Park [ctb] (https://github.com/mrchypark)
Maintainer: Tal Galili <tal.galili@gmail.com>

Diff between installr versions 0.20.0 dated 2018-05-02 and 0.21.0 dated 2018-10-06

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Package coalitions updated to version 0.6.5 with previous version 0.6.4 dated 2018-08-27

Title: Coalition Probabilities in Multi-Party Democracies
Description: An implementation of a MCMC method to calculate probabilities for a coalition majority based on survey results, see Bender and Bauer (2018) <doi:10.21105/joss.00606>.
Author: Andreas Bender [aut, cre] (<https://orcid.org/0000-0001-5628-8611>), Alexander Bauer [aut] (<https://orcid.org/0000-0003-3495-5131>)
Maintainer: Andreas Bender <andreas.bender@stat.uni-muenchen.de>

Diff between coalitions versions 0.6.4 dated 2018-08-27 and 0.6.5 dated 2018-10-06

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 21 files changed, 277 insertions(+), 220 deletions(-)

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New package airportr with initial version 0.1.2
Package: airportr
Type: Package
Title: Convenience Tools for Working with Airport Data
Version: 0.1.2
Author: Dmitry Shkolnik
Maintainer: Dmitry Shkolnik <shkolnikd@gmail.com>
Description: Retrieves open source airport data and provides tools to look up information, translate names into codes and vice-verse, as well as some basic calculation functions for measuring distances.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: dplyr
Depends: R(>= 2.10.0)
URL: https://github.com/dshkol/airportr
BugReports: https://github.com/dshkol/airportr/issues
RoxygenNote: 6.0.1
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-09-27 15:37:44 UTC; dshkol
Repository: CRAN
Date/Publication: 2018-10-06 21:20:07 UTC

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Package sdPrior updated to version 1.0-0 with previous version 0.6 dated 2018-07-07

Title: Scale-Dependent Hyperpriors in Structured Additive Distributional Regression
Description: Utility functions for scale-dependent and alternative hyperpriors. The distribution parameters may capture location, scale, shape, etc. and every parameter may depend on complex additive terms (fixed, random, smooth, spatial, etc.) similar to a generalized additive model. Hyperpriors for all effects can be elicitated within the package. Including complex tensor product interaction terms and variable selection priors. The basic model is explained in in Klein and Kneib (2016) <doi:10.1214/15-BA983>.
Author: Nadja Klein [aut, cre]
Maintainer: Nadja Klein <nadja.klein@hu-berlin.de>

Diff between sdPrior versions 0.6 dated 2018-07-07 and 1.0-0 dated 2018-10-06

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New package radiant.multivariate with initial version 0.9.7
Package: radiant.multivariate
Type: Package
Title: Multivariate Menu for Radiant: Business Analytics using R and Shiny
Version: 0.9.7
Date: 2018-10-5
Authors@R: person("Vincent", "Nijs", , "radiant@rady.ucsd.edu", c("aut", "cre"))
Description: The Radiant Multivariate menu includes interfaces for perceptual mapping, factor analysis, cluster analysis, and conjoint analysis. The application extends the functionality in radiant.data.
Depends: R (>= 3.4.0), radiant.data (>= 0.9.7)
Imports: radiant.model (>= 0.9.7), shiny (>= 1.1.0), dplyr (>= 0.7.5), rlang (>= 0.2.0), ggplot2 (>= 2.2.1), gridExtra (>= 2.0.0), scales (>= 0.4.0), magrittr (>= 1.5), psych (>= 1.8.4), GPArotation (>= 2014.11-1), car (>= 2.1.1), MASS (>= 7.3), import (>= 1.1.0), Gmedian (>= 1.2.3), ggrepel (>= 0.8)
Suggests: testthat (>= 2.0.0), pkgdown (>= 1.1.0)
URL: https://github.com/radiant-rstats/radiant.multivariate, https://radiant-rstats.github.io/radiant.multivariate, https://radiant-rstats.github.io/docs
BugReports: https://github.com/radiant-rstats/radiant.multivariate/issues
License: AGPL-3 | file LICENSE
LazyData: true
Encoding: UTF-8
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2018-10-06 16:59:48 UTC; vnijs
Author: Vincent Nijs [aut, cre]
Maintainer: Vincent Nijs <radiant@rady.ucsd.edu>
Repository: CRAN
Date/Publication: 2018-10-06 21:00:07 UTC

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Package piggyback updated to version 0.0.8 with previous version 0.0.7 dated 2018-09-30

Title: Managing Larger Data on a GitHub Repository
Description: Because larger (> 50 MB) data files cannot easily be committed to git, a different approach is required to manage data associated with an analysis in a GitHub repository. This package provides a simple work-around by allowing larger (up to 2 GB) data files to piggyback on a repository as assets attached to individual GitHub releases. These files are not handled by git in any way, but instead are uploaded, downloaded, or edited directly by calls through the GitHub API. These data files can be versioned manually by creating different releases. This approach works equally well with public or private repositories. Data can be uploaded and downloaded programmatically from scripts. No authentication is required to download data from public repositories.
Author: Carl Boettiger [aut, cre, cph] (<https://orcid.org/0000-0002-1642-628X>), Mark Padgham [ctb] (<https://orcid.org/0000-0003-2172-5265>)
Maintainer: Carl Boettiger <cboettig@gmail.com>

Diff between piggyback versions 0.0.7 dated 2018-09-30 and 0.0.8 dated 2018-10-06

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Package Opt5PL updated to version 0.1.1 with previous version 0.1.0 dated 2018-09-30

Title: Optimal Designs for the 5-Parameter Logistic Model
Description: Obtain and evaluate various optimal designs for the 3, 4, and 5-parameter logistic models. The optimal designs are obtained based on the numerical algorithm in Hyun, Wong, Yang (2018) <doi:10.18637/jss.v083.i05>.
Author: Seung Won Hyun, Weng Kee Wong, and Yarong Yang
Maintainer: Seung Won Hyun <yellowatom09@gmail.com>

Diff between Opt5PL versions 0.1.0 dated 2018-09-30 and 0.1.1 dated 2018-10-06

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Package mcbiopi updated to version 1.1.6 with previous version 1.1.5 dated 2018-09-15

Title: Matrix Computation Based Identification of Prime Implicants
Description: Computes the prime implicants or a minimal disjunctive normal form for a logic expression presented by a truth table or a logic tree. Has been particularly developed for logic expressions resulting from a logic regression analysis, i.e. logic expressions typically consisting of up to 16 literals, where the prime implicants are typically composed of a maximum of 4 or 5 literals.
Author: Holger Schwender
Maintainer: Holger Schwender <holger.schw@gmx.de>

Diff between mcbiopi versions 1.1.5 dated 2018-09-15 and 1.1.6 dated 2018-10-06

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Package umx updated to version 2.8.5 with previous version 2.8.0 dated 2018-06-19

Title: Structural Equation and Twin Modeling in R
Description: Quickly create, run, and report structural equation and twin models. See '?umx' for help, and file.show(system.file("NEWS", package="umx")) for NEWS.
Author: Timothy C Bates [aut, cre] (<https://orcid.org/0000-0002-1153-9007>)
Maintainer: Timothy C Bates <timothy.c.bates@gmail.com>

Diff between umx versions 2.8.0 dated 2018-06-19 and 2.8.5 dated 2018-10-06

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More information about umx at CRAN
Permanent link

Package eixport updated to version 0.3.6 with previous version 0.3.0 dated 2018-03-01

Title: Export Emissions to Atmospheric Models
Description: Emissions are the mass of pollutants released into the atmosphere. Air quality models need emissions data, with spatial and temporal distribution, to represent air pollutant concentrations. This package, eixport, creates inputs for the air quality models 'WRF-Chem' Grell et al (2005) <doi:10.1016/j.atmosenv.2005.04.027>, 'BRAMS-SPM' Freitas et al (2005) <doi:10.1016/j.atmosenv.2005.07.017> and 'RLINE' Snyder et al (2013) <doi:10.1016/j.atmosenv.2013.05.074>. See the eixport website (<https://atmoschem.github.io/eixport/>) for more information, documentations and examples. More details in Ibarra-Espinosa et al (2018) <doi.org/10.21105/joss.00607>.
Author: Sergio Ibarra-Espinosa [aut, cre] (<https://orcid.org/0000-0002-3162-1905>), Daniel Schuch [aut] (<https://orcid.org/0000-0001-5977-4519>), Edmilson Freitas [ctb] (<https://orcid.org/0000-0001-8783-2747>)
Maintainer: Sergio Ibarra-Espinosa <sergio.ibarra@usp.br>

Diff between eixport versions 0.3.0 dated 2018-03-01 and 0.3.6 dated 2018-10-06

 DESCRIPTION                              |   29 ++--
 MD5                                      |   83 ++++++++----
 NAMESPACE                                |    6 
 NEWS.md                                  |   36 +++++
 R/Lights.R                               |    6 
 R/eixport.R                              |    2 
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 R/to_munich.R                            |only
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Permanent link

New package radiant.model with initial version 0.9.7
Package: radiant.model
Type: Package
Title: Model Menu for Radiant: Business Analytics using R and Shiny
Version: 0.9.7
Date: 2018-10-5
Authors@R: person("Vincent", "Nijs", , "radiant@rady.ucsd.edu", c("aut", "cre"))
Description: The Radiant Model menu includes interfaces for linear and logistic regression, naive Bayes, neural networks, classification and regression trees, model evaluation, collaborative filtering, decision analysis, and simulation. The application extends the functionality in radiant.data.
Depends: R (>= 3.4.0), radiant.data (>= 0.9.7)
Imports: radiant.basics (>= 0.9.7), shiny (>= 1.1.0), nnet (>= 7.3.12), NeuralNetTools (>= 1.5.1), sandwich (>= 2.3.4), car (>= 2.1.3), ggplot2 (>= 2.2.1), gridExtra (>= 2.0.0), data.tree (>= 0.7.4), stringr (>= 1.1.0), lubridate (>= 1.7.2), tidyr (>= 0.8.0), dplyr (>= 0.7.6), rlang (>= 0.2.2), magrittr (>= 1.5), DiagrammeR (>= 1.0.0), import (>= 1.1.0), psych (>= 1.8.4), e1071 (>= 1.6.8), rpart (>= 4.1.11), yaml
Suggests: testthat (>= 2.0.0), pkgdown (>= 1.1.0)
URL: https://github.com/radiant-rstats/radiant.model, https://radiant-rstats.github.io/radiant.model, https://radiant-rstats.github.io/docs
BugReports: https://github.com/radiant-rstats/radiant.model/issues
License: AGPL-3 | file LICENSE
LazyData: true
Encoding: UTF-8
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2018-10-06 15:25:47 UTC; vnijs
Author: Vincent Nijs [aut, cre]
Maintainer: Vincent Nijs <radiant@rady.ucsd.edu>
Repository: CRAN
Date/Publication: 2018-10-06 16:00:03 UTC

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Package pdSpecEst updated to version 1.2.3 with previous version 1.2.2 dated 2018-07-10

Title: An Analysis Toolbox for Hermitian Positive Definite Matrices
Description: An implementation of data analysis tools for samples of symmetric or Hermitian positive definite matrices, such as collections of covariance matrices or spectral density matrices. The tools in this package can be used to perform: (i) intrinsic wavelet transforms for curves (1D) or surfaces (2D) of Hermitian positive definite matrices with applications to dimension reduction, denoising and clustering in the space of Hermitian positive definite matrices; and (ii) exploratory data analysis and inference for samples of positive definite matrices by means of intrinsic data depth functions and rank-based hypothesis tests in the space of Hermitian positive definite matrices.
Author: Joris Chau [aut, cre]
Maintainer: Joris Chau <joris.chau@openanalytics.eu>

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Package RcppCCTZ updated to version 0.2.4 with previous version 0.2.3 dated 2017-06-20

Title: 'Rcpp' Bindings for the 'CCTZ' Library
Description: 'Rcpp' Access to the 'CCTZ' timezone library is provided. 'CCTZ' is a C++ library for translating between absolute and civil times using the rules of a time zone. The 'CCTZ' source code, released under the Apache 2.0 License, is included in this package. See <https://github.com/google/cctz> for more details.
Author: Dirk Eddelbuettel
Maintainer: Dirk Eddelbuettel <edd@debian.org>

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Package CutpointsOEHR updated to version 0.1.1 with previous version 0.1.0 dated 2018-09-20

Title: Optimal Equal-HR Method to Find Two Cutpoints for U-Shaped Relationships in Cox Model
Description: Use optimal equal-HR method to determine two optimal cutpoints of a continuous predictor that has a U-shaped relationship with survival outcomes based on Cox regression model. The optimal equal-HR method estimates two optimal cut-points that have approximately the same log hazard value based on Cox regression model and divides individuals into different groups according to their HR values.
Author: Yimin Chen, Zhang Jinxin
Maintainer: Yimin Chen <chenyimin0226@126.com>

Diff between CutpointsOEHR versions 0.1.0 dated 2018-09-20 and 0.1.1 dated 2018-10-06

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Package gamlss.dist updated to version 5.1-0 with previous version 5.0-6 dated 2018-06-06

Title: Distributions for Generalized Additive Models for Location Scale and Shape
Description: A set of distributions which can be used for modelling the response variables in Generalized Additive Models for Location Scale and Shape, Rigby and Stasinopoulos (2005), <doi:10.1111/j.1467-9876.2005.00510.x>. The distributions can be continuous, discrete or mixed distributions. Extra distributions can be created, by transforming, any continuous distribution defined on the real line, to a distribution defined on ranges 0 to infinity or 0 to 1, by using a ''log'' or a ''logit' transformation respectively.
Author: Mikis Stasinopoulos [aut, cre, cph], Robert Rigby [aut], Calliope Akantziliotou [ctb], Vlasios Voudouris [ctb], Gillian Heller [ctb], Fernanda De Bastiani [ctb], Raydonal Ospina [ctb], Nicoletta Motpan [ctb], Fiona McElduff [ctb], Majid Djennad [ctb], Marco Enea [ctb], Alexios Ghalanos [ctb], Christos Argyropoulos [ctb], Almond Stocker [ctb], Jens Lichter [ctb], Stanislaus Stadlmann [ctb]
Maintainer: Mikis Stasinopoulos <d.stasinopoulos@londonmet.ac.uk>

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Package gamlss.data updated to version 5.1-0 with previous version 5.0-1 dated 2018-04-30

Title: GAMLSS Data
Description: Data used as examples to demonstrate GAMLSS models.
Author: Mikis Stasinopoulos <d.stasinopoulos@londonmet.ac.uk>, Bob Rigby, Fernanda De Bastiani
Maintainer: Mikis Stasinopoulos <d.stasinopoulos@londonmet.ac.uk>

Diff between gamlss.data versions 5.0-1 dated 2018-04-30 and 5.1-0 dated 2018-10-06

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Package provenance updated to version 2.2 with previous version 2.1 dated 2018-08-03

Title: Statistical Toolbox for Sedimentary Provenance Analysis
Description: Bundles a number of established statistical methods to facilitate the visual interpretation of large datasets in sedimentary geology. Includes functionality for adaptive kernel density estimation, principal component analysis, correspondence analysis, multidimensional scaling, generalised procrustes analysis and individual differences scaling using a variety of dissimilarity measures. Univariate provenance proxies, such as single-grain ages or (isotopic) compositions are compared with the Kolmogorov-Smirnov, Kuiper or Sircombe-Hazelton L2 distances. Categorical provenance proxies such as chemical compositions are compared with the Aitchison and Bray-Curtis distances, and point-counting data with the chi-square distance. Also included are tools to plot compositional and point-counting data on ternary diagrams, to calculate the sample size required for specified levels of statistical precision, and to assess the effects of hydraulic sorting on detrital compositions. Includes an intuitive query-based user interface for users who are not proficient in R.
Author: Pieter Vermeesch [aut, cre]
Maintainer: Pieter Vermeesch <p.vermeesch@ucl.ac.uk>

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Package gamlss updated to version 5.1-2 with previous version 5.1-0 dated 2018-06-08

Title: Generalised Additive Models for Location Scale and Shape
Description: Functions for fitting the Generalized Additive Models for Location Scale and Shape introduced by Rigby and Stasinopoulos (2005), <doi:10.1111/j.1467-9876.2005.00510.x>. The models use a distributional regression approach where all the parameters of the conditional distribution of the response variable are modelled using explanatory variables.
Author: Mikis Stasinopoulos [aut, cre, cph], Bob Rigby [aut], Vlasios Voudouris [ctb], Calliope Akantziliotou [ctb], Marco Enea [ctb], Daniil Kiose [ctb]
Maintainer: Mikis Stasinopoulos <d.stasinopoulos@londonmet.ac.uk>

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Package treemapify updated to version 2.5.1 with previous version 2.5.0 dated 2018-04-30

Title: Draw Treemaps in 'ggplot2'
Description: Provides 'ggplot2' geoms for drawing treemaps.
Author: David Wilkins <david@wilkox.org>
Maintainer: David Wilkins <david@wilkox.org>

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Permanent link

Package stacomirtools updated to version 0.5.3 with previous version 0.5.2 dated 2017-06-24

Title: 'ODBC' Connection Class for Package stacomiR
Description: S4 class wrappers for the 'ODBC' connection, also provides some utilities to paste small datasets to clipboard, rename columns. It is used by the package 'stacomiR' for connections to the database. Development versions of 'stacomiR' are available in R-forge.
Author: Cedric Briand [aut, cre]
Maintainer: Cedric Briand <cedric.briand00@gmail.com>

Diff between stacomirtools versions 0.5.2 dated 2017-06-24 and 0.5.3 dated 2018-10-06

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More information about stacomirtools at CRAN
Permanent link

Package googledrive updated to version 0.1.2 with previous version 0.1.1 dated 2017-08-28

Title: An Interface to Google Drive
Description: Manage Google Drive files from R.
Author: Lucy D'Agostino McGowan [aut], Jennifer Bryan [aut, cre] (<https://orcid.org/0000-0002-6983-2759>), RStudio [cph, fnd]
Maintainer: Jennifer Bryan <jenny@rstudio.com>

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More information about googledrive at CRAN
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Package cvar updated to version 0.3-0 with previous version 0.2-0 dated 2018-08-19

Title: Compute Expected Shortfall and Value at Risk for Continuous Distributions
Description: Compute expected shortfall (ES) and Value at Risk (VaR) from a quantile function, distribution function, random number generator or probability density function. ES is also known as Conditional Value at Risk (CVaR). Virtually any continuous distribution can be specified. The functions are vectorized over the arguments. The computations are done directly from the definitions, see e.g. Acerbi and Tasche (2002) <doi:10.1111/1468-0300.00091>. Some support for GARCH models is provided, as well.
Author: Georgi N. Boshnakov [aut, cre]
Maintainer: Georgi N. Boshnakov <georgi.boshnakov@manchester.ac.uk>

Diff between cvar versions 0.2-0 dated 2018-08-19 and 0.3-0 dated 2018-10-06

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Permanent link

New package VICmodel with initial version 0.1.1
Package: VICmodel
Type: Package
Title: The Variable Infiltration Capacity (VIC) Model
Version: 0.1.1
Authors@R: c(person("Ruida", "Zhong", email = "zrd2017@163.com", role = c("aut", "cre")), person("Xiaohong", "Chen", email = "eescxh@mail.sysu.edu.cn", role = c("aut", "ctb")), person("Zhaoli", "Wang", email = "wangzhl@scut.edu.cn", role = c("aut", "ctb")), person("Chengguang", "Lai", email = "laichg@scut.edu.cn", role = c("aut", "ctb")), person("Joseph J", "Hamman", role = c("ctb"), comment = "Contributor and maintainer of VIC source code"), person("Keith", "Cherkauer", role = c("ctb")) )
Description: The Variable Infiltration Capacity (VIC) model is a macroscale hydrologic model that solves full water and energy balances, originally developed by Xu Liang at the University of Washington (UW). The version of VIC source code used is of 5.0.1 on <https://github.com/UW-Hydro/VIC/>, see Hamman et al. (2018). Development and maintenance of the current official version of the VIC model at present is led by the UW Hydro (Computational Hydrology group) in the Department of Civil and Environmental Engineering at UW. VIC is a research model and in its various forms it has been applied to most of the major river basins around the world, as well as globally. If you make use of this model, please acknowledge the appropriate references listed in the help page of this package or on the references page <http://vic.readthedocs.io/en/master/Documentation/References/> of the VIC official documentation website. These should include Liang et al. (1994) plus any references relevant to the features you are using Reference: Liang, X., D. P. Lettenmaier, E. F. Wood, and S. J. Burges (1994), A simple hydrologically based model of land surface water and energy fluxes for general circulation models, J. Geophys. Res., 99(D7), 14415-14428, <doi:10.1029/94JD00483>. Hamman et al. (2018) about VIC 5.0.1 also can be considered: Hamman, J. J., Nijssen, B., Bohn, T. J., Gergel, D. R., and Mao, Y. (2018), The Variable Infiltration Capacity model version 5 (VIC-5): infrastructure improvements for new applications and reproducibility, Geosci. Model Dev., 11, 3481-3496, <doi:10.5194/gmd-11-3481-2018>.
License: GPL-3
Copyright: file inst/COPYRIGHTS
URL: https://github.com/Sibada/VICmodel
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.0.0)
Imports: stats, utils, Rcpp (>= 0.12.0), foreach
Suggests: doParallel
LinkingTo: Rcpp
RoxygenNote: 5.0.1
NeedsCompilation: yes
Packaged: 2018-10-06 03:00:18 UTC; vicerTi
Author: Ruida Zhong [aut, cre], Xiaohong Chen [aut, ctb], Zhaoli Wang [aut, ctb], Chengguang Lai [aut, ctb], Joseph J Hamman [ctb] (Contributor and maintainer of VIC source code), Keith Cherkauer [ctb]
Maintainer: Ruida Zhong <zrd2017@163.com>
Repository: CRAN
Date/Publication: 2018-10-06 06:50:20 UTC

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New package radiant.design with initial version 0.9.7
Package: radiant.design
Type: Package
Title: Design Menu for Radiant: Business Analytics using R and Shiny
Version: 0.9.7
Date: 2018-10-5
Authors@R: person("Vincent", "Nijs", , "radiant@rady.ucsd.edu", c("aut", "cre"))
Description: The Radiant Design menu includes interfaces for design of experiments, sampling, and sample size calculation. The application extends the functionality in radiant.data.
Depends: R (>= 3.4.0), radiant.data (>= 0.9.7), mvtnorm
Imports: dplyr (>= 0.7.6), shiny (>= 1.1.0), AlgDesign (>= 1.1.7.3), import (>= 1.1.0), polycor
Suggests: testthat (>= 2.0.0), pkgdown (>= 1.1.0)
URL: https://github.com/radiant-rstats/radiant.design, https://radiant-rstats.github.io/radiant.design, https://radiant-rstats.github.io/docs
BugReports: https://github.com/radiant-rstats/radiant.design/issues
License: AGPL-3 | file LICENSE
LazyData: true
Encoding: UTF-8
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2018-10-06 03:42:51 UTC; vnijs
Author: Vincent Nijs [aut, cre]
Maintainer: Vincent Nijs <radiant@rady.ucsd.edu>
Repository: CRAN
Date/Publication: 2018-10-06 06:50:04 UTC

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New package radiant.basics with initial version 0.9.7
Package: radiant.basics
Type: Package
Title: Basics Menu for Radiant: Business Analytics using R and Shiny
Version: 0.9.7
Date: 2018-10-5
Authors@R: person("Vincent", "Nijs", , "radiant@rady.ucsd.edu", c("aut", "cre"))
Description: The Radiant Basics menu includes interfaces for probability calculation, central limit theorem simulation, comparing means and proportions, goodness-of-fit testing, cross-tabs, and correlation. The application extends the functionality in radiant.data.
Depends: R (>= 3.4.0), radiant.data (>= 0.9.7)
Imports: ggplot2 (>= 2.2.1), gridExtra (>= 2.0.0), scales (>= 0.4.0), dplyr (>= 0.7.6), tidyr (>= 0.8.0), magrittr (>= 1.5), shiny (>= 1.1.0), psych (>= 1.8.3.3), import (>= 1.1.0)
Suggests: testthat (>= 2.0.0), pkgdown (>= 1.1.0)
URL: https://github.com/radiant-rstats/radiant.basics, https://radiant-rstats.github.io/radiant.basics, https://radiant-rstats.github.io/docs
BugReports: https://github.com/radiant-rstats/radiant.basics/issues
License: AGPL-3 | file LICENSE
LazyData: true
Encoding: UTF-8
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2018-10-06 03:47:04 UTC; vnijs
Author: Vincent Nijs [aut, cre]
Maintainer: Vincent Nijs <radiant@rady.ucsd.edu>
Repository: CRAN
Date/Publication: 2018-10-06 06:50:09 UTC

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Package spmoran updated to version 0.1.6 with previous version 0.1.5 dated 2018-08-09

Title: Moran's Eigenvector-Based Spatial Regression Models
Description: Functions for estimating Moran's eigenvector-based spatial regression models. For details see Murakami (2018) <arXiv:1703.04467>.
Author: Daisuke Murakami
Maintainer: Daisuke Murakami <dmuraka@ism.ac.jp>

Diff between spmoran versions 0.1.5 dated 2018-08-09 and 0.1.6 dated 2018-10-06

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Package GUIDE updated to version 1.2.7 with previous version 1.2.3.1 dated 2016-09-13

Title: GUI for DErivatives in R
Description: A nice GUI for financial DErivatives in R.
Author: S Subramanian <ssubramanian@sssihl.edu.in>
Maintainer: S Subramanian <ssubramanian@sssihl.edu.in>

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More information about GUIDE at CRAN
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