Tue, 29 Aug 2017

Package RcppHMM updated to version 1.2 with previous version 1.0.1 dated 2017-02-07

Title: Rcpp Hidden Markov Model
Description: Collection of functions to evaluate sequences, decode hidden states and estimate parameters from a single or multiple sequences of a discrete time Hidden Markov Model. The observed values can be modeled by a multinomial distribution for categorical/labeled emissions, a mixture of Gaussians for continuous data and also a mixture of Poissons for discrete values. It includes functions for random initialization, simulation, backward or forward sequence evaluation, Viterbi or forward-backward decoding and parameter estimation using an Expectation-Maximization approach.
Author: Roberto A. Cardenas-Ovando, Julieta Noguez and Claudia Rangel-Escareno
Maintainer: Roberto A. Cardenas-Ovando <robalecarova@gmail.com>

Diff between RcppHMM versions 1.0.1 dated 2017-02-07 and 1.2 dated 2017-08-29

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Package HGNChelper updated to version 0.3.6 with previous version 0.3.5 dated 2017-06-13

Title: Handy Functions for Working with HGNC Gene Symbols and Affymetrix Probeset Identifiers
Description: Contains functions for identifying and correcting HGNC gene symbols which have been converted to date format by Excel, for reversibly converting between HGNC symbols and valid R names, identifying invalid HGNC symbols and correcting synonyms and outdated symbols which can be mapped to an official symbol.
Author: Levi Waldron and Markus Riester
Maintainer: Levi Waldron <lwaldron.research@gmail.com>

Diff between HGNChelper versions 0.3.5 dated 2017-06-13 and 0.3.6 dated 2017-08-29

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Package statquotes updated to version 0.2.2 with previous version 0.2 dated 2016-09-06

Title: Quotes on Statistics, Data Visualization and Science
Description: Generates a random quotation from a data base of quotes on topics in statistics, data visualization and science.
Author: Michael Friendly [aut, cre], Phil Chalmers [ctb], Matthew Sigal [ctb]
Maintainer: Michael Friendly <friendly@yorku.ca>

Diff between statquotes versions 0.2 dated 2016-09-06 and 0.2.2 dated 2017-08-29

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New package splashr with initial version 0.4.0
Package: splashr
Type: Package
Title: Tools to Work with the 'Splash' 'JavaScript' Rendering and Scraping Service
Version: 0.4.0
Date: 2017-08-26
Encoding: UTF-8
Authors@R: c( person("Bob", "Rudis", email = "bob@rud.is", role = c("aut", "cre")) )
Maintainer: Bob Rudis <bob@rud.is>
Description: 'Splash' <https://github.com/scrapinghub/splash> is a 'JavaScript' rendering service. It is a lightweight web browser with an 'HTTP' API, implemented in 'Python' using 'Twisted' and 'QT' and provides some of the core functionality of the 'RSelenium' or 'seleniumPipes' R packages in a lightweight footprint. Some of 'Splash' features include the ability to process multiple web pages in parallel; retrieving 'HTML' results and/or take screen shots; disabling images or use 'Adblock Plus' rules to make rendering faster; executing custom 'JavaScript' in page context; getting detailed rendering info in 'HAR' format.
URL: http://github.com/hrbrmstr/splashr
BugReports: https://github.com/hrbrmstr/splashr/issues
License: AGPL
Suggests: testthat, tibble, jpeg, png, covr, knitr, rmarkdown
Depends: R (>= 3.2.0)
Imports: xml2, curl, httr, clipr, purrr, stats, utils, docker, magick, scales, formatR, openssl, stringi, jsonlite, HARtools, lubridate
RoxygenNote: 6.0.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2017-08-28 17:09:46 UTC; bob
Author: Bob Rudis [aut, cre]
Repository: CRAN
Date/Publication: 2017-08-29 21:41:48 UTC

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Package sensitivitymult updated to version 1.0.2 with previous version 1.0.1 dated 2017-05-16

Title: Sensitivity Analysis for Observational Studies with Multiple Outcomes
Description: Sensitivity analysis for multiple outcomes in observational studies. For instance, all linear combinations of several outcomes may be explored using Scheffe projections in the comparison() function; see Rosenbaum (2016, Annals of Applied Statistics) <doi:10.1214/16-AOAS942>. Alternatively, attention may focus on a few principal components in the principal() function. The package includes parallel methods for individual outcomes, including tests in the senm() function and confidence intervals in the senmCI() function.
Author: Paul R. Rosenbaum
Maintainer: Paul R. Rosenbaum <rosenbaum@wharton.upenn.edu>

Diff between sensitivitymult versions 1.0.1 dated 2017-05-16 and 1.0.2 dated 2017-08-29

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Package mbir updated to version 1.1 with previous version 1.0 dated 2017-08-14

Title: Magnitude-Based Inferences
Description: Allows practitioners and researchers a wholesale approach for deriving magnitude-based inferences from raw data. A major goal of 'mbir' is to programmatically detect appropriate statistical tests to run in lieu of relying on practitioners to determine correct stepwise procedures independently.
Author: Kyle Peterson [aut, cre]
Maintainer: Kyle Peterson <petersonkdon@gmail.com>

Diff between mbir versions 1.0 dated 2017-08-14 and 1.1 dated 2017-08-29

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New package billboarder with initial version 0.0.3
Package: billboarder
Title: Create Interactive Chart with the JavaScript 'Billboard' Library
Version: 0.0.3
Authors@R: c( person("Victor", "Perrier", email = "victor.perrier@dreamrs.fr", role = c("aut", "cre")), person("Fanny", "Meyer", email = "fanny.meyer@dreamrs.fr", role = c("aut")), person("NAVER Corp", role = c("cph"), comment = "billboard library"))
Description: Provides an 'htmlwidgets' interface to 'billboard.js', a re-usable easy interface JavaScript chart library, based on D3 v4+. Chart types include line charts, scatterplots, bar charts, pie/donut charts and gauge charts. All charts are interactive, and a proxy method is implemented to smoothly update a chart without rendering it again in 'shiny' apps.
URL: https://github.com/dreamRs/billboarder
BugReports: https://github.com/dreamRs/billboarder/issues
Depends: R (>= 3.3.2)
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
Imports: htmlwidgets, magrittr, jsonlite
Suggests: RColorBrewer, ggplot2, shiny, testthat, knitr, rmarkdown, prettydoc
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2017-08-28 18:32:50 UTC; Victor
Author: Victor Perrier [aut, cre], Fanny Meyer [aut], NAVER Corp [cph] (billboard library)
Maintainer: Victor Perrier <victor.perrier@dreamrs.fr>
Repository: CRAN
Date/Publication: 2017-08-29 21:43:50 UTC

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Package BETS updated to version 0.3.2 with previous version 0.3.1 dated 2017-08-03

Title: Brazilian Economic Time Series
Description: It provides access to and information about the most important Brazilian economic time series - from the Getulio Vargas Foundation <http://portal.fgv.br/en>, the Central Bank of Brazil <http://www.bcb.gov.br> and the Brazilian Institute of Geography and Statistics <http://www.ibge.gov.br>. It also presents tools for managing, analysing (e.g. generating dynamic reports with a complete analysis of a series) and exporting these time series.
Author: Pedro Costa Ferreira [aut, cre], Talitha Speranza [aut], Jonatha Azevedo [aut], Fernando Teixeira [aut], Daiane Marcolino [aut]
Maintainer: Pedro Costa Ferreira <pedro.guilherme@fgv.br>

Diff between BETS versions 0.3.1 dated 2017-08-03 and 0.3.2 dated 2017-08-29

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Package Rsampletrees updated to version 1.0.1 with previous version 1.0 dated 2017-04-18

Title: MCMC Sampling of Gene Genealogies Conditional on Genetic Data
Description: Sample ancestral trees conditional on phased or unphased SNP genotype data. The actual tree sampling is done using a C++ program that is launched within R. The package also contains functions for specifying the tree-sampling settings (pre-processing) and for storing and manipulating the sampled trees (post-processing). More information about 'sampletrees' can be found at <http://stat.sfu.ca/statgen/research/sampletrees.html>.
Author: Kelly Burkett, Brad McNeney, Jinko Graham, Jean-Francois Lefebvre
Maintainer: Jean-Francois Lefebvre <jflefebvre27@gmail.com>

Diff between Rsampletrees versions 1.0 dated 2017-04-18 and 1.0.1 dated 2017-08-29

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Package mapmisc updated to version 1.6.3 with previous version 1.6.2 dated 2017-08-14

Title: Utilities for Producing Maps
Description: A minimal, light-weight set of tools for producing nice looking maps in R, with support for map projections.
Author: Patrick Brown <patrick.brown@utoronto.ca>
Maintainer: Patrick Brown <patrick.brown@utoronto.ca>

Diff between mapmisc versions 1.6.2 dated 2017-08-14 and 1.6.3 dated 2017-08-29

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Package enveomics.R updated to version 1.1.6 with previous version 1.1.5 dated 2017-04-04

Title: Various Utilities for Microbial Genomics and Metagenomics
Description: A collection of functions for microbial ecology and other applications of genomics and metagenomics. Companion package for the Enveomics Collection (Rodriguez-R, L.M. and Konstantinidis, K.T., 2016 <DOI:10.7287/peerj.preprints.1900v1>).
Author: Luis M. Rodriguez-R [aut, cre]
Maintainer: Luis M. Rodriguez-R <lmrodriguezr@gmail.com>

Diff between enveomics.R versions 1.1.5 dated 2017-04-04 and 1.1.6 dated 2017-08-29

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Package poweRlaw updated to version 0.70.1 with previous version 0.70.0 dated 2016-12-22

Title: Analysis of Heavy Tailed Distributions
Description: An implementation of maximum likelihood estimators for a variety of heavy tailed distributions, including both the discrete and continuous power law distributions. Additionally, a goodness-of-fit based approach is used to estimate the lower cut-off for the scaling region.
Author: Colin Gillespie [aut, cre]
Maintainer: Colin Gillespie <csgillespie@gmail.com>

Diff between poweRlaw versions 0.70.0 dated 2016-12-22 and 0.70.1 dated 2017-08-29

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Package uptasticsearch updated to version 0.1.0 with previous version 0.0.2 dated 2017-07-18

Title: Get Data Frame Representations of 'Elasticsearch' Results
Description: 'Elasticsearch' is an open-source, distributed, document-based datastore (<https://www.elastic.co/products/elasticsearch>). It provides an 'HTTP' 'API' for querying the database and extracting datasets, but that 'API' was not designed for common data science workflows like pulling large batches of records and normalizing those documents into a data frame that can be used as a training dataset for statistical models. 'uptasticsearch' provides an interface for 'Elasticsearch' that is explicitly designed to make these data science workflows easy and fun.
Author: James Lamb [aut, cre], Nick Paras [aut], Austin Dickey [aut], Michael Frasco [ctb], Weiwen Gu [ctb], Uptake Technologies Inc. [cph]
Maintainer: James Lamb <james.lamb@uptake.com>

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Package benchmarkmeData updated to version 0.5.1 with previous version 0.4.0 dated 2017-01-04

Title: Data Set for the 'benchmarkme' Package
Description: Crowd sourced benchmarks from running the 'benchmarkme' package.
Author: Colin Gillespie [aut, cre]
Maintainer: Colin Gillespie <csgillespie@gmail.com>

Diff between benchmarkmeData versions 0.4.0 dated 2017-01-04 and 0.5.1 dated 2017-08-29

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Package texPreview updated to version 1.1.0 with previous version 1.0.0 dated 2017-04-03

Title: Compile and Preview Snippets of 'LaTeX' in 'RStudio'
Description: Compile and preview snippets of 'LaTeX'. Can be used directly from the R console, from 'RStudio', in Shiny apps and R Markdown documents. Must have 'pdflatex' or 'xelatex' or 'lualatex' in 'PATH'.
Author: Jonathan Sidi [aut, cre], Daniel Polhamus [aut]
Maintainer: Jonathan Sidi <yonis@metrumrg.com>

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Package RcppArmadillo updated to version 0.7.960.1.2 with previous version 0.7.960.1.1 dated 2017-08-20

Title: 'Rcpp' Integration for the 'Armadillo' Templated Linear Algebra Library
Description: 'Armadillo' is a templated C++ linear algebra library (by Conrad Sanderson) that aims towards a good balance between speed and ease of use. Integer, floating point and complex numbers are supported, as well as a subset of trigonometric and statistics functions. Various matrix decompositions are provided through optional integration with LAPACK and ATLAS libraries. The 'RcppArmadillo' package includes the header files from the templated 'Armadillo' library. Thus users do not need to install 'Armadillo' itself in order to use 'RcppArmadillo'. From release 7.800.0 on, 'Armadillo' is licensed under Apache License 2; previous releases were under licensed as MPL 2.0 from version 3.800.0 onwards and LGPL-3 prior to that; 'RcppArmadillo' (the 'Rcpp' bindings/bridge to Armadillo) is licensed under the GNU GPL version 2 or later, as is the rest of 'Rcpp'. Note that Armadillo requires a fairly recent compiler; for the g++ family at least version 4.6.* is required.
Author: Dirk Eddelbuettel, Romain Francois, Doug Bates and Binxiang Ni
Maintainer: Dirk Eddelbuettel <edd@debian.org>

Diff between RcppArmadillo versions 0.7.960.1.1 dated 2017-08-20 and 0.7.960.1.2 dated 2017-08-29

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Package ipft updated to version 0.7.1 with previous version 0.6 dated 2017-05-10

Title: Indoor Positioning Fingerprinting Toolset
Description: Algorithms and utility functions for indoor positioning using fingerprinting techniques. These functions are designed for manipulation of RSSI (Received Signal Strength Intensity) data sets, estimation of positions,comparison of the performance of different models, and graphical visualization of data. Machine learning algorithms and methods such as k-nearest neighbors or probabilistic fingerprinting are implemented in this package to perform analysis and estimations over RSSI data sets.
Author: Emilio Sansano [aut, cre], Raúl Montoliu [ctb]
Maintainer: Emilio Sansano <esansano@uji.es>

Diff between ipft versions 0.6 dated 2017-05-10 and 0.7.1 dated 2017-08-29

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New package ebmc with initial version 1.0.0
Package: ebmc
Type: Package
Title: Ensemble-Based Methods for Class Imbalance Problem
Version: 1.0.0
Author: Hsiang Hao, Chen
Maintainer: "Hsiang Hao, Chen" <kbman1101@gmail.com>
Description: Four ensemble-based methods (SMOTEBoost, RUSBoost, UnderBagging, and SMOTEBagging) for class imbalance problem are implemented for binary classification. Such methods adopt ensemble methods and data re-sampling techniques to improve model performance in presence of class imbalance problem. One special feature offers the possibility to choose multiple supervised learning algorithms to build weak learners within ensemble models. References: Nitesh V. Chawla, Aleksandar Lazarevic, Lawrence O. Hall, and Kevin W. Bowyer (2003) <doi:10.1007/978-3-540-39804-2_12>, Chris Seiffert, Taghi M. Khoshgoftaar, Jason Van Hulse, and Amri Napolitano (2010) <doi:10.1109/TSMCA.2009.2029559>, R. Barandela, J. S. Sanchez, R. M. Valdovinos (2003) <doi:10.1007/s10044-003-0192-z>, Shuo Wang and Xin Yao (2009) <doi:10.1109/CIDM.2009.4938667>, Yoav Freund and Robert E. Schapire (1997) <doi:10.1006/jcss.1997.1504>.
Depends: methods
Imports: e1071, rpart, C50, randomForest, DMwR, pROC
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2017-08-29 14:47:59 UTC; user
Repository: CRAN
Date/Publication: 2017-08-29 15:44:12 UTC

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Package difNLR updated to version 1.1.1 with previous version 1.1.0 dated 2017-08-22

Title: Detection of Differential Item Functioning (DIF) and Differential Distractor Functioning (DDF) by Non-Linear Regression Models
Description: Detection of DIF among dichotomously scored items and DDF among unscored items with non-linear regression procedures based on generalized logistic regression models.
Author: Adela Drabinova [aut, cre], Patricia Martinkova [aut], Karel Zvara [aut]
Maintainer: Adela Drabinova <adela.drabinova@gmail.com>

Diff between difNLR versions 1.1.0 dated 2017-08-22 and 1.1.1 dated 2017-08-29

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Package ctmm updated to version 0.4.0 with previous version 0.3.6 dated 2017-04-24

Title: Continuous-Time Movement Modeling
Description: Functions for identifying, fitting, and applying continuous-space, continuous-time stochastic movement models to animal tracking data. The package is described in Calabrese & Fleming (2016) <doi:10.1111/2041-210X.12559> and its methods are based on those introduced in Fleming et al (2014) <doi:10.1086/675504>, Fleming et al (2014) <doi:10.1111/2041-210X.12176>, Fleming et al (2015) <doi:10.1890/14-2010.1>, Fleming et al (2016) <doi:10.1890/15-1607>, Péron et al (2016) <doi:10.1186/s40462-016-0084-7>, Fleming & Calabrese (2016) <doi:10.1111/2041-210X.12673>, Péron et al (2017) <doi:10.1002/ecm.1260>, and Fleming et al (2017) <doi:10.1016/j.ecoinf.2017.04.008>.
Author: Christen H. Fleming [aut, cre], Justin M. Calabrese [aut], Xianghui Dong [ctb], Kevin Winner [ctb], Guillaume Péron [ctb], Bart Kranstauber [ctb], Eliezer Gurarie [ctb], Kamran Safi [ctb], Paul C. Cross [dtc], Thomas Mueller [dtc]
Maintainer: Christen H. Fleming <flemingc@si.edu>

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New package WordR with initial version 0.2.1
Package: WordR
Type: Package
Title: Rendering Word Documents with R Inline Code
Version: 0.2.1
Author: Tomas Hovorka
Maintainer: Tomas Hovorka <tomashovorka@seznam.cz>
Description: Serves for rendering MS Word documents with R inline code and inserting tables and plots.
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: dplyr, ReporteRs, officer
RoxygenNote: 6.0.1
Suggests: knitr, rmarkdown, ggplot2, testthat
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2017-08-24 10:58:57 UTC; tomas_hovorka
Repository: CRAN
Date/Publication: 2017-08-29 13:07:26 UTC

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Package sfdct updated to version 0.0.4 with previous version 0.0.3 dated 2017-05-02

Title: Constrained Triangulation for Simple Features
Description: Build a constrained 'Delaunay' triangulation from simple features objects, applying constraints based on input line segments, and triangle properties including maximum area, minimum internal angle.
Author: Michael D. Sumner [aut, cre]
Maintainer: Michael D. Sumner <mdsumner@gmail.com>

Diff between sfdct versions 0.0.3 dated 2017-05-02 and 0.0.4 dated 2017-08-29

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Package uGMAR updated to version 1.0.1 with previous version 1.0.0 dated 2017-08-28

Title: Estimate Univariate Gaussian or Student's t Mixture Autoregressive Model
Description: Maximum likelihood estimation of univariate Gaussian Mixture Autoregressive (GMAR) and Student's t Mixture Autoregressive (StMAR) models, quantile residual tests, graphical diagnostics, forecast and simulate from GMAR and StMAR processes. Also general linear constraints and restricting autoregressive parameters to be the same for all regimes are supported. Leena Kalliovirta, Mika Meitz, Pentti Saikkonen (2015) <doi:10.1111/jtsa.12108>, Leena Kalliovirta (2012) <doi:10.1111/j.1368-423X.2011.00364.x>.
Author: Savi Virolainen [aut, cre]
Maintainer: Savi Virolainen <savi.virolainen@helsinki.fi>

Diff between uGMAR versions 1.0.0 dated 2017-08-28 and 1.0.1 dated 2017-08-29

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New package sptemExp with initial version 0.1.0
Package: sptemExp
Type: Package
Title: Constrained Spatiotemporal Mixed Models for Exposure Estimation
Version: 0.1.0
Author: Lianfa Li,
Maintainer: Lianfa Li <lspatial@gmail.com>
Description: The approach of constrained spatiotemporal mixed models is to make reliable estimation of air pollutant concentrations at high spatiotemporal resolution (Li, L., Lurmann, F., Habre, R., Urman, R., Rappaport, E., Ritz, B., Chen, J., Gilliland, F., Wu, J., (2017) <doi:10.1021/acs.est.7b01864>). This package is an extensive tool for this modeling approach with support of block Kriging (Goovaerts, P. (1997) <http://www.gbv.de/dms/goettingen/229148123.pdf>) and uses the PM2.5 modeling as examples. It provides the following functionality: (1) Extraction of covariates from the satellite images such as GeoTiff and NC4 raster; (2) Generation of temporal basis functions to simulate the seasonal trends in the study regions; (3) Generation of the regional monthly or yearly means of air pollutant concentration; (4) Generation of Thiessen polygons and spatial effect modeling; (5) Ensemble modeling for spatiotemporal mixed models, supporting multi-core parallel computing; (6) Integrated predictions with or without weights of the model's performance, supporting multi-core parallel computing; (7) Constrained optimization to interpolate the missing values; (8) Generation of the grid surfaces of air pollutant concentration estimates at high resolution; (9) Block Kriging for regional mean estimation at multiple scales.
Depends: R (>= 2.14)
Imports: Rcpp (>= 0.12.12), methods, rgdal, raster,deldir, SpatioTemporal,plyr,sp,limSolve, R2BayesX,BayesX,BayesXsrc,ncdf4, bcv, rgeos, splines, parallel, foreach,doParallel,automap
LinkingTo: Rcpp, RcppEigen
SystemRequirements: C++11
License: GPL
Encoding: UTF-8
LazyData: true
NeedsCompilation: yes
RoxygenNote: 6.0.1
Packaged: 2017-08-28 21:01:20 UTC; lpola
Repository: CRAN
Date/Publication: 2017-08-29 12:45:00 UTC

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Package sgPLS updated to version 1.7 with previous version 1.4 dated 2015-11-25

Title: Sparse Group Partial Least Square Methods
Description: Regularized version of partial least square approaches providing sparse, group, and sparse group versions of partial least square regression models (Liquet, B., Lafaye de Micheaux, P., Hejblum B., Thiebaut, R. (2016) <doi:10.1093/bioinformatics/btv535>). Version of PLS Discriminant analysis is also provided.
Author: Benoit Liquet and Pierre Lafaye de Micheaux and Camilo Broc
Maintainer: Benoit Liquet <b.liquet@uq.edu.au>

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Package replyr updated to version 0.5.3 with previous version 0.5.2 dated 2017-08-01

Title: Diligent Use of Big Data with R
Description: Methods to diligently use 'dplyr' remote data sources ('SQL' databases, 'Spark' 2.0.0 and above). Adds convenience functions to make such tasks more like working with an in-memory R 'data.frame'.
Author: John Mount [aut, cre], Nina Zumel [aut], Win-Vector LLC [cph]
Maintainer: John Mount <jmount@win-vector.com>

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New package qgam with initial version 1.1.1
Package: qgam
Type: Package
Title: Smooth Additive Quantile Regression Models
Version: 1.1.1
Date: 2017-8-29
Author: Matteo Fasiolo, Simon N. Wood, Yannig Goude, Raphael Nedellec.
Maintainer: Matteo Fasiolo <matteo.fasiolo@gmail.com>
Description: Smooth additive quantile regression models, fitted using the methods of Fasiolo et al. (2017) <arXiv:1707.03307>. Differently from 'quantreg', the smoothing parameters are estimated automatically by marginal loss minimization, while the regression coefficients are estimated using either PIRLS or Newton algorithm. The learning rate is determined so that the Bayesian credible intervals of the estimated effects have approximately the correct coverage. The main function is qgam() which is similar to gam() in 'mgcv', but fits non-parametric quantile regression models.
License: GPL (>= 2)
Depends: mgcv (>= 1.8.18)
Imports: shiny, plyr, doParallel, parallel, grDevices
Suggests: knitr, MASS, RhpcBLASctl
VignetteBuilder: knitr
RoxygenNote: 6.0.1
NeedsCompilation: yes
Packaged: 2017-08-29 10:49:44 UTC; teo
Repository: CRAN
Date/Publication: 2017-08-29 12:15:16 UTC

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New package MTE with initial version 1.0.0
Package: MTE
Type: Package
Title: Maximum Tangent Likelihood and Other Robust Estimation for High-Dimensional Regression
Version: 1.0.0
Author: Shaobo Li and Yichen Qin
Maintainer: Shaobo Li <lis6@mail.uc.edu>
Description: Provides several robust estimators for linear regression and variable selection. They are Maximum tangent likelihood estimator (Qin, et al. (2017) <arXiv:1708.05439>), least absolute deviance estimator, and Huber loss. The penalized version of each of these estimator incorporates L1 penalty function, i.e., LASSO and Adaptive Lasso. They are able to produce consistent estimates for both fixed and high-dimensional settings.
Depends: R (>= 3.1.0)
License: GPL-3
LazyData: TRUE
RoxygenNote: 6.0.1
Imports: stats, quantreg, parcor
NeedsCompilation: no
Packaged: 2017-08-29 03:28:23 UTC; shaoboli
Repository: CRAN
Date/Publication: 2017-08-29 12:18:35 UTC

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Package mmap updated to version 0.6-14 with previous version 0.6-12 dated 2013-08-28

Title: Map Pages of Memory
Description: R interface to POSIX mmap and Window's MapViewOfFile.
Author: Jeffrey A. Ryan
Maintainer: Jeffrey A. Ryan <jeff.a.ryan@gmail.com>

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Package mgcv updated to version 1.8-19 with previous version 1.8-18 dated 2017-07-28

Title: Mixed GAM Computation Vehicle with Automatic Smoothness Estimation
Description: Generalized additive (mixed) models, some of their extensions and other generalized ridge regression with multiple smoothing parameter estimation by (Restricted) Marginal Likelihood, Generalized Cross Validation and similar. Includes a gam() function, a wide variety of smoothers, JAGS support and distributions beyond the exponential family.
Author: Simon Wood <simon.wood@r-project.org>
Maintainer: Simon Wood <simon.wood@r-project.org>

Diff between mgcv versions 1.8-18 dated 2017-07-28 and 1.8-19 dated 2017-08-29

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New package mcompanion with initial version 0.4-5
Package: mcompanion
Type: Package
Title: Objects and Methods for Multi-Companion Matrices
Version: 0.4-5
Date: 2017-08-28
Author: Georgi N. Boshnakov
Maintainer: Georgi N. Boshnakov <georgi.boshnakov@manchester.ac.uk>
Imports: methods, Matrix, gbutils, MASS, Rdpack
Suggests: testthat
RdMacros: Rdpack
Description: Provides a class for multi-companion matrices with methods for arithmetic and factorization. A method for generation of multi-companion matrices with prespecified spectral properties is provided, as well as some utilities for periodically correlated and multivariate time series models. See Boshnakov (2002) <doi:10.1016/j.laa.2007.02.010> and Boshnakov & Iqelan (2009) <doi:10.1111/j.1467-9892.2009.00617.x>.
License: GPL (>= 2)
Collate: matutils.R mc.R mc01zero.R mc02gen.R auto_sim.R classMC.R auto_classMF.R classmcSpec.R spaces.R classJordan.R jd.R jdecomp.R classSMC.R smc.R make_chains.R
NeedsCompilation: no
Packaged: 2017-08-28 18:56:06 UTC; mcbssgb2
Repository: CRAN
Date/Publication: 2017-08-29 12:30:35 UTC

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Package LowWAFOMSobol updated to version 1.1.1 with previous version 1.0 dated 2017-07-13

Title: Low WAFOM Sobol Sequence
Description: Implementation of Low Walsh Figure of Merit (WAFOM) sequence based on Sobol sequence.
Author: Shinsuke Mori [aut], Ryuichi Ohori [aut], Makoto Matsumoto [aut], Mutsuo Saito [cre]
Maintainer: Mutsuo Saito <sai10@hiroshima-u.ac.jp>

Diff between LowWAFOMSobol versions 1.0 dated 2017-07-13 and 1.1.1 dated 2017-08-29

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New package ggconf with initial version 0.1
Package: ggconf
Type: Package
Title: Simpler Appearance Modification of 'ggplot2'
Version: 0.1
Authors@R: c(person('Yasutaka', 'Tanaka', , 'tnk.yasutaka@gmail.com', c('aut', 'cre')))
Description: A flexible interface for ggplot2::theme(), potentially saving 50% of your typing.
License: GPL-3
Depends: R (>= 3.3.0)
Imports: tibble (>= 1.0.0), ggplot2 (>= 2.2.0), rly (>= 1.3.0)
Suggests: tidyverse, knitr, testthat, futile.logger (>= 1.4.3), hexbin, dplyr
URL: https://github.com/caprice-j/ggconf
BugReports: https://github.com/caprice-j/ggconf/issues
Encoding: UTF-8
LazyData: true
RoxygenNote: 5.0.1
VignetteBuilder: knitr
Collate: 'ggconf.R' 'prefix_match.R' 'approx_match.R' 'compiler.R'
NeedsCompilation: no
Packaged: 2017-08-28 21:30:54 UTC; PCUser
Author: Yasutaka Tanaka [aut, cre]
Maintainer: Yasutaka Tanaka <tnk.yasutaka@gmail.com>
Repository: CRAN
Date/Publication: 2017-08-29 12:27:47 UTC

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New package FPV with initial version 0.5
Package: FPV
Type: Package
Title: Testing Hypotheses via Fuzzy P-Value in Fuzzy Environment
Version: 0.5
Date: 2017-08-21
Author: Abbas Parchami (Department of Statistics, Faculty of Mathematics and Computer, Shahid Bahonar University of Kerman, Kerman, Iran)
Maintainer: Abbas Parchami <parchami@uk.ac.ir>
Description: The main goal of this package is drawing the membership function of the fuzzy p-value which is defined as a fuzzy set on the unit interval for three following problems: (1) testing crisp hypotheses based on fuzzy data, see Filzmoser and Viertl (2004) <doi:10.1007/s001840300269>, (2) testing fuzzy hypotheses based on crisp data, see Parchami et al. (2010) <doi:10.1007/s00362-008-0133-4>, and (3) testing fuzzy hypotheses based on fuzzy data, see Parchami et al. (2012) <doi:10.1007/s00362-010-0353-2>. In all cases, the fuzziness of data or / and the fuzziness of the boundary of null fuzzy hypothesis transported via the p-value function and causes to produce the fuzzy p-value. If the p-value is fuzzy, it is more appropriate to consider a fuzzy significance level for the problem. Therefore, the comparison of the fuzzy p-value and the fuzzy significance level is evaluated by a fuzzy ranking method in this package.
License: LGPL (>= 3)
Imports: FuzzyNumbers, FuzzyNumbers.Ext.2
NeedsCompilation: no
Packaged: 2017-08-27 13:25:08 UTC; parchami
Repository: CRAN
Date/Publication: 2017-08-29 12:57:59 UTC

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Package datapack updated to version 1.3.1 with previous version 1.3.0 dated 2017-08-03

Title: A Flexible Container to Transport and Manipulate Data and Associated Resources
Description: Provides a flexible container to transport and manipulate complex sets of data. These data may consist of multiple data files and associated meta data and ancillary files. Individual data objects have associated system level meta data, and data files are linked together using the OAI-ORE standard resource map which describes the relationships between the files. The OAI-ORE standard is described at <https://www.openarchives.org/ore>. Data packages can be serialized and transported as structured files that have been created following the BagIt specification. The BagIt specification is described at <https://tools.ietf.org/html/draft-kunze-bagit-08>.
Author: Matthew B. Jones [aut, cre], Peter Slaughter [aut], Regents of the University of California [cph]
Maintainer: Matthew B. Jones <jones@nceas.ucsb.edu>

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Package LabourMarketAreas updated to version 3.1 with previous version 3.0 dated 2017-05-15

Title: Identification, Tuning, Visualisation and Analysis of Labour Market Areas
Description: Produces Labour Market Areas from commuting flows available at elementary territorial units. It provides tools for automatic tuning based on spatial contiguity. It also allows for statistical analyses and visualisation of the new functional geography.
Author: Daniela Ichim, Luisa Franconi, Michele D'Alo', Guido van den Heuvel
Maintainer: Luisa Franconi <franconi@istat.it>

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Package Anthropometry updated to version 1.9 with previous version 1.8 dated 2017-04-26

Title: Statistical Methods for Anthropometric Data
Description: Statistical methodologies especially developed to analyze anthropometric data. These methods are aimed at providing effective solutions to some commons problems related to Ergonomics and Anthropometry. They are based on clustering, the statistical concept of data depth, statistical shape analysis and archetypal analysis.
Author: Guillermo Vinue, Irene Epifanio, Amelia Simo, M. Victoria Ibanez, Juan Domingo, Guillermo Ayala
Maintainer: Guillermo Vinue <Guillermo.Vinue@uv.es>

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Package wooldridge updated to version 1.1.0 with previous version 1.0.1 dated 2017-07-11

Title: 105 Data Sets from "Introductory Econometrics: A Modern Approach" by Jeffrey M. Wooldridge
Description: Economics students new to both econometrics and R may find the simultaneous introduction to both challenging. In particular, the process of loading and preparing data before building one's first model can present challenges. The `wooldridge` data package aims to lighten the task by loading any data set from the text into the current working environment with a single command. The package contains documentation for each set and all data has been compressed to 62.73% of its original size. Just install the package, load it, and use the `data()` function to call the data set you need to work with. In addition, a wooldridge-vignette illustrates solutions to examples from each chapter of the text, offering a relevant introduction to econometric modelling with R. The vignette also includes an Appendix to helpful resources about using R for econometrics. Note: Data sets are from the 5th edition (Wooldridge 2013, ISBN-13:978-1-111-53104-1), and are compatible with others.
Author: Justin M. Shea
Maintainer: Justin M. Shea <jshea@roosevelt.edu>

Diff between wooldridge versions 1.0.1 dated 2017-07-11 and 1.1.0 dated 2017-08-29

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Package PeriodicTable updated to version 0.1.2 with previous version 0.1.1 dated 2017-01-24

Title: Periodic Table of the Elements
Description: Provides a dataset containing properties for chemical elements. Helper functions are also provided to access some atomic properties.
Author: Julien Idé
Maintainer: Julien Idé <julien.ide.fr@gmail.com>

Diff between PeriodicTable versions 0.1.1 dated 2017-01-24 and 0.1.2 dated 2017-08-29

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Package WVPlots updated to version 0.2.6 with previous version 0.2.5 dated 2017-07-04

Title: Common Plots for Analysis
Description: Select data analysis plots, under a standardized calling interface implemented on top of 'ggplot2' and 'plotly'. Plots of interest include: 'ROC', gain curve, scatter plot with marginal distributions, conditioned scatter plot with marginal densities. box and stem with matching theoretical distribution, and density with matching theoretical distribution.
Author: John Mount [aut, cre], Nina Zumel [aut], Win-Vector LLC [cph]
Maintainer: John Mount <jmount@win-vector.com>

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