Mon, 19 Nov 2018

Package meteoForecast updated to version 0.53 with previous version 0.52 dated 2018-04-04

Title: Numerical Weather Predictions
Description: Access to several Numerical Weather Prediction services both in raster format and as a time series for a location. Currently it works with GFS, MeteoGalicia, NAM, and RAP.
Author: Oscar Perpinan Lamigueiro [cre, aut], Marcelo Pinho Almeida [ctb]
Maintainer: Oscar Perpinan Lamigueiro <oscar.perpinan@gmail.com>

Diff between meteoForecast versions 0.52 dated 2018-04-04 and 0.53 dated 2018-11-19

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Package gcite updated to version 0.9.3 with previous version 0.9.2 dated 2018-02-02

Title: Google Citation Parser
Description: Scrapes Google Citation pages and creates data frames of citations over time.
Author: John Muschelli [aut, cre] (<https://orcid.org/0000-0001-6469-1750>)
Maintainer: John Muschelli <muschellij2@gmail.com>

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Package RBesT updated to version 1.3-7 with previous version 1.3-6 dated 2018-11-15

Title: R Bayesian Evidence Synthesis Tools
Description: Tool-set to support Bayesian evidence synthesis. This includes meta-analysis, (robust) prior derivation from historical data, operating characteristics and analysis (1 and 2 sample cases).
Author: Novartis Pharma AG [cph], Sebastian Weber [aut, cre], Beat Neuenschwander [ctb], Heinz Schmidli [ctb], Baldur Magnusson [ctb], Yue Li [ctb], Satrajit Roychoudhury [ctb], Trustees of Columbia University [cph] (src/init.cpp, tools/make_cc.R, R/stanmodels.R, src/Makevars, src/Makevars.win)
Maintainer: Sebastian Weber <sebastian.weber@novartis.com>

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Package polyRAD updated to version 1.0 with previous version 0.5-0 dated 2018-08-02

Title: Genotype Calling with Uncertainty from Sequencing Data in Polyploids and Diploids
Description: Read depth data from genotyping-by-sequencing (GBS) or restriction site-associated DNA sequencing (RAD-seq) are imported and used to make Bayesian probability estimates of genotypes in polyploids or diploids. The genotype probabilities, or genotypes sampled from those probabilties, can then be exported for downstream analysis. 'polyRAD' is described by Clark et al. (2018) <doi:10.1101/380899>.
Author: Lindsay V. Clark [aut, cre] (<https://orcid.org/0000-0002-3881-9252>), U.S. National Science Foundation [fnd]
Maintainer: Lindsay V. Clark <lvclark@illinois.edu>

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New package LindleyPowerSeries with initial version 0.1.0
Package: LindleyPowerSeries
Type: Package
Title: Lindley Power Series Distribution
Version: 0.1.0
Author: Saralees Nadarajah & Yuancheng Si, Peihao Wang
Maintainer: Yuancheng Si <yuancheng.si@manchester.ac.uk>
Description: Computes the probability density function, the cumulative distribution function, the hazard rate function, the quantile function and random generation for Lindley Power Series distributions, see Nadarajah and Si (2018) <doi:10.1007/s13171-018-0150-x>.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
Imports: stats, lamW(>= 1.3.0)
NeedsCompilation: no
Packaged: 2018-11-19 19:36:41 UTC; Lenovo
Repository: CRAN
Date/Publication: 2018-11-19 23:20:11 UTC

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Package epibasix updated to version 1.5 with previous version 1.3 dated 2012-11-15

Title: Elementary Epidemiological Functions for Epidemiology and Biostatistics
Description: Contains elementary tools for analysis of common epidemiological problems, ranging from sample size estimation, through 2x2 contingency table analysis and basic measures of agreement (kappa, sensitivity/specificity). Appropriate print and summary statements are also written to facilitate interpretation wherever possible. Source code is commented throughout to facilitate modification. The target audience includes advanced undergraduate and graduate students in epidemiology or biostatistics courses, and clinical researchers.
Author: Michael A Rotondi <mrotondi@yorku.ca>
Maintainer: Michael A Rotondi <mrotondi@yorku.ca>

Diff between epibasix versions 1.3 dated 2012-11-15 and 1.5 dated 2018-11-19

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Package spaMM updated to version 2.5.11 with previous version 2.5.0 dated 2018-09-28

Title: Mixed-Effect Models, Particularly Spatial Models
Description: Inference based on mixed-effect models, including generalized linear mixed models with spatial correlations and models with non-Gaussian random effects (e.g., Beta). Variation in residual variance (heteroscedasticity) can itself be represented by a generalized linear mixed model. Various approximations of likelihood or restricted likelihood are implemented, in particular h-likelihood (Lee and Nelder 2001 <doi:10.1093/biomet/88.4.987>) and Laplace approximation.
Author: François Rousset [aut, cre, cph] (<https://orcid.org/0000-0003-4670-0371>), Jean-Baptiste Ferdy [aut, cph], Alexandre Courtiol [aut] (<https://orcid.org/0000-0003-0637-2959>), GSL authors [ctb] (src/gsl_bessel.*)
Maintainer: François Rousset <francois.rousset@umontpellier.fr>

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Package GSODR updated to version 1.3.0 with previous version 1.2.3 dated 2018-10-11

Title: Global Surface Summary of the Day ('GSOD') Weather Data Client
Description: Provides automated downloading, parsing, cleaning, unit conversion and formatting of Global Surface Summary of the Day ('GSOD') weather data from the from the USA National Centers for Environmental Information ('NCEI') for use in R. Units are converted from from United States Customary System ('USCS') units to International System of Units ('SI'). Stations may be individually checked for number of missing days defined by the user, where stations with too many missing observations are omitted. Only stations with valid reported latitude and longitude values are permitted in the final data. Additional useful elements, saturation vapour pressure ('es'), actual vapour pressure ('ea') and relative humidity are calculated from the original data and included in the final data set. The resulting data include station identification information, state, country, latitude, longitude, elevation, weather observations and associated flags. Additional data are included with this R package: a list of elevation values for stations between -60 and 60 degrees latitude derived from the Shuttle Radar Topography Measuring Mission ('SRTM'). For information on the 'GSOD' data from 'NCEI', please see the 'GSOD' 'readme.txt' file available from, <http://www1.ncdc.noaa.gov/pub/data/gsod/readme.txt>.
Author: Adam Sparks [aut, cre] (<https://orcid.org/0000-0002-0061-8359>), Tomislav Hengl [aut] (<https://orcid.org/0000-0002-9921-5129>), Andrew Nelson [aut] (<https://orcid.org/0000-0002-7249-3778>), Hugh Parsonage [cph, ctb] (<https://orcid.org/0000-0003-4055-0835>), Bob Rudis [cph, ctb] (<https://orcid.org/0000-0001-5670-2640>), Gwenael Giboire [ctb] (Several bug reports in early versions and testing feedback), Łukasz Pawlik [ctb] (Reported bug in windspeed conversion calculation), Ross Darnell [ctb] (Reported bug in 'Windows OS' versions causing 'GSOD' data untarring to fail)
Maintainer: Adam Sparks <adamhsparks@gmail.com>

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Package rscopus updated to version 0.6.3 with previous version 0.6.1 dated 2018-10-22

Title: Scopus Database 'API' Interface
Description: Uses Elsevier 'Scopus' API <https://dev.elsevier.com/sc_apis.html> to download information about authors and their citations.
Author: John Muschelli [aut, cre]
Maintainer: John Muschelli <muschellij2@gmail.com>

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Package mscstts updated to version 0.4.0 with previous version 0.3.0 dated 2018-08-16

Title: R Client for the Microsoft Cognitive Services 'Text-to-Speech' REST API
Description: R Client for the Microsoft Cognitive Services 'Text-to-Speech' REST API, including voice synthesis. A valid account must be registered at the Microsoft Cognitive Services website <https://www.microsoft.com/cognitive-services/> in order to obtain a (free) API key. Without an API key, this package will not work properly.
Author: John Muschelli [aut, cre] (<https://orcid.org/0000-0001-6469-1750>)
Maintainer: John Muschelli <muschellij2@gmail.com>

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Package fslr updated to version 2.22.0 with previous version 2.17.3 dated 2018-02-02

Title: Wrapper Functions for 'FSL' ('FMRIB' Software Library) from Functional MRI of the Brain ('FMRIB')
Description: Wrapper functions that interface with 'FSL' <http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/>, a powerful and commonly-used 'neuroimaging' software, using system commands. The goal is to be able to interface with 'FSL' completely in R, where you pass R objects of class 'nifti', implemented by package 'oro.nifti', and the function executes an 'FSL' command and returns an R object of class 'nifti' if desired.
Author: John Muschelli [aut, cre] (<https://orcid.org/0000-0001-6469-1750>)
Maintainer: John Muschelli <muschellij2@gmail.com>

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Package tseries updated to version 0.10-46 with previous version 0.10-45 dated 2018-06-04

Title: Time Series Analysis and Computational Finance
Description: Time series analysis and computational finance.
Author: Adrian Trapletti [aut], Kurt Hornik [aut, cre], Blake LeBaron [ctb] (BDS test code)
Maintainer: Kurt Hornik <Kurt.Hornik@R-project.org>

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Package scrm updated to version 1.7.3-1 with previous version 1.7.2-4 dated 2018-06-30

Title: Simulating the Evolution of Biological Sequences
Description: A coalescent simulator that allows the rapid simulation of biological sequences under neutral models of evolution. Different to other coalescent based simulations, it has an optional approximation parameter that allows for high accuracy while maintaining a linear run time cost for long sequences. It is optimized for simulating massive data sets as produced by Next- Generation Sequencing technologies for up to several thousand sequences.
Author: Paul Staab [aut, cre, cph], Zhu Sha [aut, cph], Dirk Metzler [aut, cph, ths], Gerton Lunter [aut, cph, ths]
Maintainer: Paul Staab <develop@paulstaab.de>

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Package ggsolvencyii updated to version 0.1.1 with previous version 0.1.0 dated 2018-10-28

Title: A 'ggplot2'-Plot of Composition of Solvency II SCR: SF and IM
Description: An implementation of 'ggplot2'-methods to present the composition of Solvency II Solvency Capital Requirement (SCR) as a series of concentric circle-parts. Solvency II (Solvency 2) is European insurance legislation, coming in force by the delegated acts of October 10, 2014. <https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=OJ%3AL%3A2015%3A012%3ATOC>. Additional files, defining the structure of the Standard Formula (SF) method of the SCR-calculation are provided. The structure files can be adopted for localization or for insurance companies who use Internal Models (IM). Options are available for combining smaller components, horizontal and vertical scaling, rotation, and plotting only some circle-parts. With outlines and connectors several SCR-compositions can be compared, for example in ORSA-scenarios (Own Risk and Solvency Assessment).
Author: Marco van Zanden [aut, cre]
Maintainer: Marco van Zanden <git@vanzanden.nl>

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New package spreadr with initial version 0.1.0
Package: spreadr
Type: Package
Title: Simulating Spreading Activation in a Network
Version: 0.1.0
Authors@R: c( person("Cynthia","Siew", email = "cynsiewsq@gmail.com", role = c("aut", "cre")), person(c("Dirk","U."), "Wulff", role = "ctb", email = "dirk.wulff@gmail.com") )
Description: The notion of spreading activation is a prevalent metaphor in the cognitive sciences. This package provides the tools for cognitive scientists and psychologists to conduct computer simulations that implement spreading activation in a network representation. The algorithmic method implemented in 'spreadr' subroutines follows the approach described in Vitevitch, Ercal, and Adagarla (2011, Frontiers), who viewed activation as a fixed cognitive resource that could spread among nodes that were connected to each other via edges or connections (i.e., a network). See Vitevitch, M. S., Ercal, G., & Adagarla, B. (2011). Simulating retrieval from a highly clustered network: Implications for spoken word recognition. Frontiers in Psychology, 2, 369. <doi:10.3389/fpsyg.2011.00369>.
License: GPL-3
Encoding: UTF-8
LazyData: true
Depends: Rcpp (>= 0.12.5)
RoxygenNote: 6.1.0
Imports: igraph, extrafont, ggplot2
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
LinkingTo: Rcpp
NeedsCompilation: yes
Packaged: 2018-11-13 17:45:18 UTC; csqsiew
Author: Cynthia Siew [aut, cre], Dirk U. Wulff [ctb]
Maintainer: Cynthia Siew <cynsiewsq@gmail.com>
Repository: CRAN
Date/Publication: 2018-11-19 19:20:03 UTC

More information about spreadr at CRAN
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New package R.temis with initial version 0.1.0
Package: R.temis
Type: Package
Title: Integrated Text Mining Solution
Version: 0.1.0
Authors@R: c(person("Milan", "Bouchet-Valat", email="nalimilan@club.fr", role=c("aut", "cre")), person("Gilles", "Bastin", email="gilles.bastin@sciencespo-grenoble.fr", role="aut"), person("Antoine", "Chollet", email="antoine.chollet@eleve.ensai.fr", role="aut"))
Imports: stats, utils, graphics, testthat, wordcloud, igraph, stringi, crayon, SnowballC, tm.plugin.factiva, tm.plugin.lexisnexis, tm.plugin.europresse, tm.plugin.alceste
Depends: tm (>= 0.6), NLP, slam, FactoMineR, explor
Description: An integrated solution to perform a series of text mining tasks such as importing and cleaning a corpus, and analyses like terms and documents counts, lexical summary, terms co-occurrences and documents similarity measures, graphs of terms, correspondence analysis and hierarchical clustering. Corpora can be imported from spreadsheet-like files, directories of raw text files, as well as from 'Dow Jones Factiva', 'LexisNexis', 'Europresse' and 'Alceste' files.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2018-11-13 08:51:43 UTC; milan
Author: Milan Bouchet-Valat [aut, cre], Gilles Bastin [aut], Antoine Chollet [aut]
Maintainer: Milan Bouchet-Valat <nalimilan@club.fr>
Repository: CRAN
Date/Publication: 2018-11-19 19:10:03 UTC

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Package quanteda updated to version 1.3.14 with previous version 1.3.13 dated 2018-11-01

Title: Quantitative Analysis of Textual Data
Description: A fast, flexible, and comprehensive framework for quantitative text analysis in R. Provides functionality for corpus management, creating and manipulating tokens and ngrams, exploring keywords in context, forming and manipulating sparse matrices of documents by features and feature co-occurrences, analyzing keywords, computing feature similarities and distances, applying content dictionaries, applying supervised and unsupervised machine learning, visually representing text and text analyses, and more.
Author: Kenneth Benoit [cre, aut, cph] (<https://orcid.org/0000-0002-0797-564X>), Kohei Watanabe [aut] (<https://orcid.org/0000-0001-6519-5265>), Haiyan Wang [aut] (<https://orcid.org/0000-0003-4992-4311>), Paul Nulty [aut] (<https://orcid.org/0000-0002-7214-4666>), Adam Obeng [aut] (<https://orcid.org/0000-0002-2906-4775>), Stefan Müller [aut] (<https://orcid.org/0000-0002-6315-4125>), Akitaka Matsuo [aut] (<https://orcid.org/0000-0002-3323-6330>), Patrick O. Perry [aut] (<https://orcid.org/0000-0001-7460-127X>), Jouni Kuha [aut] (<https://orcid.org/0000-0002-1156-8465>), Benjamin Lauderdale [aut] (<https://orcid.org/0000-0003-3090-0969>), William Lowe [aut] (<https://orcid.org/0000-0002-1549-6163>), Christian Müller [ctb], Lori Young [dtc] (Lexicoder Sentiment Dictionary 2015), Stuart Soroka [dtc] (Lexicoder Sentiment Dictionary 2015), Ian Fellows [cph] (authored wordcloud C source code (modified)), European Research Council [fnd] (ERC-2011-StG 283794-QUANTESS)
Maintainer: Kenneth Benoit <kbenoit@lse.ac.uk>

Diff between quanteda versions 1.3.13 dated 2018-11-01 and 1.3.14 dated 2018-11-19

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New package metR with initial version 0.2.0
Type: Package
Package: metR
Title: Tools for Easier Analysis of Meteorological Fields
Version: 0.2.0
Date: 2018-11-02
Authors@R: person(given = "Elio", family = "Campitelli", role = c("cre", "aut"), email = "elio.campitelli@cima.fcen.uba.ar", comment = c(ORCID = "0000-0002-7742-9230"))
Description: Many useful functions and extensions for dealing with meteorological data in the tidy data framework. Extends 'ggplot2' for better plotting of scalar and vector fields and provides commonly used analysis methods in the atmospheric sciences.
License: GPL-3
URL: https://github.com/eliocamp/metR
BugReports: https://github.com/eliocamp/metR/issues
Depends: R (>= 2.10)
Imports: checkmate, curl, data.table, digest, dplyr, fields, Formula, formula.tools, ggplot2, grid, gridExtra, gtable, lubridate, maps, maptools, Matrix, memoise, plyr, RCurl, scales, sp, stringr
Suggests: covr, irlba, knitr, ncdf4, pkgdown, reshape2, rmarkdown, testthat, udunits2, vdiffr, viridis
ByteCompile: yes
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-11-03 15:43:03 UTC; elio
Author: Elio Campitelli [cre, aut] (<https://orcid.org/0000-0002-7742-9230>)
Maintainer: Elio Campitelli <elio.campitelli@cima.fcen.uba.ar>
Repository: CRAN
Date/Publication: 2018-11-19 19:30:02 UTC

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New package hillR with initial version 0.4.0
Package: hillR
Type: Package
Title: Diversity Through Hill Numbers
Version: 0.4.0
Date: 2018-11-13
Author: Daijiang Li
Maintainer: Daijiang Li <daijianglee@gmail.com>
Description: Calculate taxonomic, functional and phylogenetic diversity measures through Hill Numbers proposed by Chao, Chiu and Jost (2014) <doi:10.1146/annurev-ecolsys-120213-091540>.
License: MIT + file LICENSE
LazyData: TRUE
Depends: R (>= 3.1)
Imports: FD, plyr, ade4, ape, tibble
RoxygenNote: 6.1.0
Suggests: testthat, vegetarian, covr
URL: https://github.com/daijiang/hillR
BugReports: https://github.com/daijiang/hillR/issues
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2018-11-14 03:58:44 UTC; dli
Repository: CRAN
Date/Publication: 2018-11-19 19:20:05 UTC

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New package DiPs with initial version 0.1.1
Package: DiPs
Type: Package
Title: Directional Penalties for Optimal Matching in Observational Studies
Version: 0.1.1
Author: Ruoqi Yu
Maintainer: Ruoqi Yu <ruoqiyu@wharton.upenn.edu>
Description: Improves the balance of optimal matching with near-fine balance by giving penalties on the unbalanced covariates with the unbalanced directions. Many directional penalties can also be viewed as Lagrange multipliers, pushing a matched sample in the direction of satisfying a linear constraint that would not be satisfied without penalization. Rosenbaum, P.R. (1989). <DOI:10.1080/01621459.1989.10478868>. Yang, D., Small, D. S., Silber, J. H., and Rosenbaum, P. R. (2012). <DOI:10.1111/j.1541-0420.2011.01691.x>.
License: MIT+file LICENSE
Encoding: UTF-8
LazyData: true
Imports: rcbalance, stats, liqueueR, plyr, mvnfast, methods
Suggests: optmatch
Note: One minimum cost flow problem may have several or many solutions that are equivalent in providing the same minimum total or mean cost. Minor differences between computers or implementations may have the minor consequence of altering which equivalent solution is produced.
NeedsCompilation: no
Packaged: 2018-11-17 21:03:16 UTC; Ruoqi Yu
Repository: CRAN
Date/Publication: 2018-11-19 19:20:18 UTC

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New package dabestr with initial version 0.1.0
Package: dabestr
Type: Package
Title: Data Analysis using Bootstrap-Coupled Estimation
Version: 0.1.0
Authors@R: c( person("Joses W.", "Ho", email = "joseshowh@gmail.com", role = c("cre", "aut")), person("Tayfun", "Tumkaya", role = c("aut")) )
Maintainer: Joses W. Ho <joseshowh@gmail.com>
Description: Data Analysis using Bootstrap-Coupled ESTimation. Estimation statistics is a simple framework that avoids the pitfalls of significance testing. It uses familiar statistical concepts: means, mean differences, and error bars. More importantly, it focuses on the effect size of one's experiment/intervention, as opposed to a false dichotomy engendered by P values. An estimation plot has two key features: 1. It presents all datapoints as a swarmplot, which orders each point to display the underlying distribution. 2. It presents the effect size as a bootstrap 95% confidence interval on a separate but aligned axes. Estimation plots are introduced in Ho et al (2018) <doi:10.1101/377978>.
License: file LICENSE
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.5.0), boot, magrittr
Imports: cowplot, dplyr, ggplot2 (>= 3.0), grid, forcats, ggforce, ggbeeswarm, rlang, simpleboot, stringr, tibble, tidyr
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown, tufte, testthat, vdiffr
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-11-13 14:19:53 UTC; joseshowh
Author: Joses W. Ho [cre, aut], Tayfun Tumkaya [aut]
Repository: CRAN
Date/Publication: 2018-11-19 19:20:10 UTC

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New package uavRst with initial version 0.5-0
Package: uavRst
Type: Package
Title: Unmanned Aerial Vehicle Remote Sensing Tools
Version: 0.5-0
Date: 2018-11-11
Authors@R: c(person("Florian", "Detsch", role = c("ctb")), person("Hanna", "Meyer", email = "hanna.meyer@uni-marburg.de", role = c("aut")), person("Thomas", "Nauss", email = "nauss@uni-marburg.de", role = c("ctb")), person("Lars", "Opgenoorth", email = "opgenoorth@uni-marburg.de", role = c("ctb")), person("Chris", "Reudenbach", email = "reudenbach@uni-marburg.de", role = c("cre","aut")), person("Environmental Informatics Marburg", role = c("ctb")) )
Encoding: UTF-8
Maintainer: Chris Reudenbach <reudenbach@uni-marburg.de>
Description: Support the analysis of drone derived imagery and point clouds as a cheap and easy to use alternative/complement to light detection and ranging data. It provides functionality to analyze poor quality digital aerial images as taken by low budget ready to fly drones. This includes supported machine learning based classification functions, comprehensive texture analysis, segmentation algorithms as well as forest relevant analyzes of metrics and measures on the derived products.
License: GPL (>= 3) | file LICENSE
Depends: R (>= 3.1.0)
Imports: raster, foreach
Suggests: knitr, stringr, sp, sf, htmlwidgets, htmltools, Rcpp, rgdal, rgeos, gdalUtils, tools, caret, zoo, data.table, parallel, spatial.tools, velox, link2GI, doParallel, CAST, glcm, crayon, ForestTools, itcSegment, pROC, methods, RSAGA, reshape2, rgrass7, randomForest, rLiDAR, rlas, lidR, rmarkdown, mapview
LinkingTo: Rcpp
RoxygenNote: 6.1.1
SystemRequirements: GNU make
NeedsCompilation: yes
Packaged: 2018-11-13 00:39:19 UTC; creu
Author: Florian Detsch [ctb], Hanna Meyer [aut], Thomas Nauss [ctb], Lars Opgenoorth [ctb], Chris Reudenbach [cre, aut], Environmental Informatics Marburg [ctb]
Repository: CRAN
Date/Publication: 2018-11-19 19:00:03 UTC

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Package tensorflow updated to version 1.10 with previous version 1.9 dated 2018-08-07

Title: R Interface to 'TensorFlow'
Description: Interface to 'TensorFlow' <https://www.tensorflow.org/>, an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more 'CPUs' or 'GPUs' in a desktop, server, or mobile device with a single 'API'. 'TensorFlow' was originally developed by researchers and engineers working on the Google Brain Team within Google's Machine Intelligence research organization for the purposes of conducting machine learning and deep neural networks research, but the system is general enough to be applicable in a wide variety of other domains as well.
Author: JJ Allaire [aut, cre], RStudio [cph, fnd], Yuan Tang [aut, cph] (<https://orcid.org/0000-0001-5243-233X>), Dirk Eddelbuettel [ctb, cph], Nick Golding [ctb, cph], Tomasz Kalinowski [ctb, cph], Google Inc. [ctb, cph] (Examples and Tutorials)
Maintainer: JJ Allaire <jj@rstudio.com>

Diff between tensorflow versions 1.9 dated 2018-08-07 and 1.10 dated 2018-11-19

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New package stevedore with initial version 0.9.0
Package: stevedore
Title: Docker Client
Version: 0.9.0
Description: Work with containers over the Docker API. Rather than using system calls to interact with a docker client, using the API directly means that we can receive richer information from docker. The interface in the package is automatically generated using the 'OpenAPI' (a.k.a., 'swagger') specification, and all return values are checked in order to make them type stable.
License: MIT + file LICENSE
Authors@R: c(person("Rich", "FitzJohn", role = c("aut", "cre"), email = "rich.fitzjohn@gmail.com"))
URL: https://github.com/richfitz/stevedore
BugReports: https://github.com/richfitz/stevedore/issues
Imports: crayon, curl (>= 2.3.0), jsonlite, yaml (>= 2.1.18)
Suggests: knitr, openssl, redux, reticulate, rmarkdown, testthat, withr
SystemRequirements: docker
RoxygenNote: 6.1.1
VignetteBuilder: knitr
Encoding: UTF-8
ByteCompile: TRUE
Language: en-GB
NeedsCompilation: no
Packaged: 2018-11-12 08:32:15 UTC; rich
Author: Rich FitzJohn [aut, cre]
Maintainer: Rich FitzJohn <rich.fitzjohn@gmail.com>
Repository: CRAN
Date/Publication: 2018-11-19 18:30:02 UTC

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Package spartan updated to version 3.0.2 with previous version 3.0.1 dated 2018-05-16

Title: Simulation Parameter Analysis R Toolkit ApplicatioN: 'spartan'
Description: Computer simulations are becoming a popular technique to use in attempts to further our understanding of complex systems. 'spartan', first described in our 2013 publication in PLoS Computational Biology, provided code for four techniques described in available literature which aid the analysis of simulation results, at both single and multiple timepoints in the simulation run. The first technique addresses aleatory uncertainty in the system caused through inherent stochasticity, and determines the number of replicate runs necessary to generate a representative result. The second examines how robust a simulation is to parameter perturbation, through the use of a one-at-a-time parameter analysis technique. Thirdly, a latin hypercube based sensitivity analysis technique is included which can elucidate non-linear effects between parameters and indicate implications of epistemic uncertainty with reference to the system being modelled. Finally, a further sensitivity analysis technique, the extended Fourier Amplitude Sampling Test (eFAST) has been included to partition the variance in simulation results between input parameters, to determine the parameters which have a significant effect on simulation behaviour. Version 1.3 added support for Netlogo simulations, aiding simulation developers who use Netlogo to build their simulations perform the same analyses. Version 2.0 added the ability to read all simulations in from a single CSV file in addition to the prescribed folder structure in previous versions. Version 3.0 offers significant additional functionality that permits the creation of emulations of simulation results, derived using the same sampling techniques in the global sensitivity analysis techniques, and the generation of combinations of these machine learning algorithms to one create one predictive tool, more commonly known as an ensemble model. Version 3.0 also improved the standard of the graphs produced in the original sensitivity analysis techniques, and introduced a polar plot to examine parameter sensitivity.
Author: Kieran Alden [cre, aut], Mark Read [aut], Paul Andrews [aut], Jason Cosgrove [aut], Mark Coles [aut], Jon Timmis [aut]
Maintainer: Kieran Alden <kieran.alden@gmail.com>

Diff between spartan versions 3.0.1 dated 2018-05-16 and 3.0.2 dated 2018-11-19

 DESCRIPTION                                                      |    8 
 MD5                                                              |  500 +--
 NAMESPACE                                                        |  184 -
 NEWS.md                                                          |   48 
 R/abc_utilities.R                                                |   56 
 R/efast_analysis.R                                               |  150 +
 R/efast_plotting.R                                               |   70 
 R/efast_sampling.R                                               |   27 
 R/efast_utilities.R                                              |    2 
 R/emulation_generation.R                                         |   37 
 R/emulation_plotting.R                                           |   34 
 R/emulation_sensitivity_analysis.R                               |  124 
 R/emulation_utilities.R                                          |   88 
 R/ensemble_generation.R                                          |   44 
 R/ensemble_utilities.R                                           |   42 
 R/lhc_analysis.R                                                 |   94 
 R/lhc_plotting.R                                                 |  241 +
 R/lhc_prcc_utilities.R                                           |    2 
 R/lhc_sampling.R                                                 |   14 
 R/method_argument_check.R                                        |   32 
 R/netlogo_sampling_utilities.R                                   |    7 
 R/robustness_analysis.R                                          | 1004 ++++---
 R/robustness_plotting.R                                          |  151 -
 R/robustness_sampling.R                                          |   32 
 R/spartan_utilities.R                                            |  217 +
 build/vignette.rds                                               |binary
 inst/doc/emulation_ensembles.R                                   |  556 ++--
 inst/doc/emulation_ensembles.Rmd                                 |  768 ++---
 inst/doc/emulation_ensembles.html                                | 1010 +++----
 inst/doc/netlogo.R                                               |  478 +--
 inst/doc/netlogo.Rmd                                             |    2 
 inst/doc/netlogo.html                                            |  950 ++-----
 inst/doc/sensitivity_analysis.R                                  |  618 ++--
 inst/doc/sensitivity_analysis.html                               | 1310 ++++------
 man/a_test_results.Rd                                            |   50 
 man/aa_getATestResults.Rd                                        |   99 
 man/aa_getATestResults_overTime.Rd                               |   74 
 man/aa_graphATestsForSampleSize.Rd                               |   54 
 man/aa_graphSampleSizeSummary.Rd                                 |   88 
 man/aa_sampleSizeSummary.Rd                                      |   78 
 man/aa_sampleSizeSummary_overTime.Rd                             |   65 
 man/aa_summariseReplicateRuns.Rd                                 |   98 
 man/aa_summariseReplicateRuns_overTime.Rd                        |   73 
 man/add_parameter_value_to_file.Rd                               |   56 
 man/analysenetwork_structures.Rd                                 |   68 
 man/append_time_to_argument.Rd                                   |   42 
 man/atest.Rd                                                     |   34 
 man/build_curve_results_from_r_object.Rd                         |only
 man/build_performance_statistics.Rd                              |   62 
 man/calculate_atest_score.Rd                                     |   56 
 man/calculate_fold_MSE.Rd                                        |   46 
 man/calculate_medians_for_all_measures.Rd                        |   48 
 man/calculate_prcc_for_all_measures.Rd                           |   60 
 man/calculate_prccs_all_parameters.Rd                            |   50 
 man/calculate_weights_for_ensemble_model.Rd                      |   59 
 man/check_acceptable_model_type.Rd                               |   36 
 man/check_argument_positive_int.Rd                               |   38 
 man/check_boolean.Rd                                             |   38 
 man/check_column_ranges.Rd                                       |   44 
 man/check_confidence_interval.Rd                                 |   46 
 man/check_consistency_result_type.Rd                             |   42 
 man/check_double_value_in_range.Rd                               |   46 
 man/check_file_exist.Rd                                          |   38 
 man/check_file_exists.Rd                                         |   34 
 man/check_file_extension.Rd                                      |   24 
 man/check_filepath_exists.Rd                                     |   38 
 man/check_function_dependent_paramvals.Rd                        |   38 
 man/check_global_param_sampling_args.Rd                          |   38 
 man/check_graph_output_type.Rd                                   |   38 
 man/check_input_args.Rd                                          |   38 
 man/check_lengths_parameters_ranges.Rd                           |   34 
 man/check_lhs_algorithm.Rd                                       |   38 
 man/check_list_all_integers.Rd                                   |   38 
 man/check_nested_filepaths.Rd                                    |   38 
 man/check_netlogo_parameters_and_values.Rd                       |   40 
 man/check_numeric_list_values.Rd                                 |   42 
 man/check_package_installed.Rd                                   |   34 
 man/check_parameters_and_ranges.Rd                               |   44 
 man/check_paramvals_length_equals_parameter_length.Rd            |   36 
 man/check_robustness_parameter_and_ranges_lengths.Rd             |   40 
 man/check_robustness_paramvals_contains_baseline.Rd              |   38 
 man/check_robustness_range_contains_baseline.Rd                  |   38 
 man/check_robustness_range_or_values.Rd                          |   40 
 man/check_robustness_sampling_args.Rd                            |   42 
 man/check_text.Rd                                                |   38 
 man/check_text_list.Rd                                           |   38 
 man/close_and_write_netlogo_file.Rd                              |   32 
 man/compare_all_values_of_parameter_to_baseline.Rd               |   70 
 man/construct_result_filename.Rd                                 |   42 
 man/createAndEvaluateFolds.Rd                                    |   86 
 man/createTrainingFold.Rd                                        |   56 
 man/create_abc_settings_object.Rd                                |   79 
 man/create_ensemble.Rd                                           |   98 
 man/create_neural_network.Rd                                     |   64 
 man/createtest_fold.Rd                                           |   51 
 man/dataset_precheck.Rd                                          |only
 man/denormalise_dataset.Rd                                       |   42 
 man/determine_optimal_neural_network_structure.Rd                |   58 
 man/efast_cvmethod.Rd                                            |   62 
 man/efast_generate_medians_for_all_parameter_subsets.Rd          |  142 -
 man/efast_generate_medians_for_all_parameter_subsets_overTime.Rd |  115 
 man/efast_generate_sample.Rd                                     |  107 
 man/efast_generate_sample_netlogo.Rd                             |   98 
 man/efast_get_overall_medians.Rd                                 |  116 
 man/efast_get_overall_medians_overTime.Rd                        |   72 
 man/efast_graph_Results.Rd                                       |   69 
 man/efast_netlogo_get_overall_medians.Rd                         |   72 
 man/efast_netlogo_run_Analysis.Rd                                |  102 
 man/efast_parameterdist.Rd                                       |   46 
 man/efast_process_netlogo_result.Rd                              |   84 
 man/efast_run_Analysis.Rd                                        |  152 -
 man/efast_run_Analysis_from_DB.Rd                                |only
 man/efast_run_Analysis_overTime.Rd                               |  108 
 man/efast_sd.Rd                                                  |   24 
 man/efast_setfreq.Rd                                             |   24 
 man/efast_ttest.Rd                                               |   26 
 man/emulate_efast_sampled_parameters.Rd                          |   92 
 man/emulate_lhc_sampled_parameters.Rd                            |   98 
 man/emulated_lhc_values.Rd                                       |   54 
 man/emulation_algorithm_settings.Rd                              |  137 -
 man/emulator_parameter_evolution.Rd                              |   72 
 man/emulator_predictions.Rd                                      |   72 
 man/ensemble_abc_wrapper.Rd                                      |   50 
 man/execute_checks.Rd                                            |   44 
 man/exemplar_sim_output.Rd                                       |   68 
 man/extract_predictions_from_result_list.Rd                      |   45 
 man/format_efast_result_for_output.Rd                            |   60 
 man/generate_a_test_results_header.Rd                            |   38 
 man/generate_a_test_score.Rd                                     |   50 
 man/generate_efast_parameter_sets.Rd                             |   62 
 man/generate_emulator_model.Rd                                   |   77 
 man/generate_emulators_and_ensemble.Rd                           |  152 -
 man/generate_ensemble_from_existing_emulations.Rd                |  112 
 man/generate_ensemble_training_set.Rd                            |   68 
 man/generate_headers_for_atest_file.Rd                           |   34 
 man/generate_list_of_checks.Rd                                   |   38 
 man/generate_medians_for_param_set.Rd                            |   74 
 man/generate_model_formula.Rd                                    |   40 
 man/generate_parameter_table.Rd                                  |   46 
 man/generate_prcc_results_header.Rd                              |   34 
 man/generate_predictions_from_emulator.Rd                        |   56 
 man/generate_requested_emulations.Rd                             |  150 -
 man/generate_sensitivity_indices.Rd                              |   62 
 man/generate_summary_stats_for_all_param_sets.Rd                 |   80 
 man/getMediansSubset.Rd                                          |   76 
 man/get_argument_correct_case.Rd                                 |   42 
 man/get_correct_file_path_for_function.Rd                        |   40 
 man/get_file_and_object_argument_names.Rd                        |   40 
 man/get_max_and_median_atest_scores.Rd                           |   43 
 man/get_median_results_for_all_measures.Rd                       |   38 
 man/get_medians_for_size_subsets.Rd                              |   65 
 man/graph_Posteriors_All_Parameters.Rd                           |   54 
 man/graph_sample_size_results.Rd                                 |   50 
 man/import_model_result.Rd                                       |   52 
 man/initialise_netlogo_xml_file.Rd                               |   61 
 man/join_strings.Rd                                              |   40 
 man/join_strings_nospace.Rd                                      |   36 
 man/join_strings_space.Rd                                        |   36 
 man/kfoldCrossValidation.Rd                                      |   62 
 man/lhc_calculatePRCCForMultipleTimepoints.Rd                    |   52 
 man/lhc_constructcoeff_dataset.Rd                                |   24 
 man/lhc_generateLHCSummary.Rd                                    |  116 
 man/lhc_generateLHCSummary_overTime.Rd                           |   92 
 man/lhc_generatePRCoEffs.Rd                                      |  103 
 man/lhc_generatePRCoEffs_db_link.Rd                              |only
 man/lhc_generatePRCoEffs_overTime.Rd                             |   74 
 man/lhc_generateTimepointFiles.Rd                                |   58 
 man/lhc_generate_lhc_sample.Rd                                   |  111 
 man/lhc_generate_lhc_sample_netlogo.Rd                           |   76 
 man/lhc_generate_netlogo_PRCoEffs.Rd                             |   56 
 man/lhc_graphMeasuresForParameterChange.Rd                       |  111 
 man/lhc_graphMeasuresForParameterChange_from_db.Rd               |only
 man/lhc_graphMeasuresForParameterChange_overTime.Rd              |   96 
 man/lhc_netlogo_graphMeasuresForParameterChange.Rd               |   84 
 man/lhc_plotCoEfficients.Rd                                      |   66 
 man/lhc_polarplot.Rd                                             |   70 
 man/lhc_process_netlogo_result.Rd                                |   74 
 man/lhc_process_sample_run_subsets.Rd                            |  160 -
 man/lhc_process_sample_run_subsets_overTime.Rd                   |  132 -
 man/make_extension.Rd                                            |   40 
 man/make_filename.Rd                                             |   36 
 man/make_graph_title.Rd                                          |   60 
 man/make_lhc_plot.Rd                                             |   38 
 man/make_path.Rd                                                 |   36 
 man/meanSquaredError.Rd                                          |   40 
 man/normaliseATest.Rd                                            |   34 
 man/normalise_dataset.Rd                                         |   52 
 man/nsga2_set_user_params.Rd                                     |   78 
 man/num.decimals.Rd                                              |   34 
 man/oat_csv_result_file_analysis.Rd                              |  100 
 man/oat_csv_result_file_analysis_from_DB.Rd                      |only
 man/oat_csv_result_file_analysis_overTime.Rd                     |   76 
 man/oat_generate_netlogo_behaviour_space_XML.Rd                  |   68 
 man/oat_graphATestsForSampleSize.Rd                              |   81 
 man/oat_parameter_sampling.Rd                                    |   81 
 man/oat_plotResultDistribution.Rd                                |   87 
 man/oat_processParamSubsets.Rd                                   |  116 
 man/oat_processParamSubsets_overTime.Rd                          |   95 
 man/oat_process_netlogo_result.Rd                                |   84 
 man/output_ggplot_graph.Rd                                       |   36 
 man/output_param_sets_per_curve.Rd                               |   46 
 man/partition_dataset.Rd                                         |  118 
 man/pcor.mat.Rd                                                  |   24 
 man/pcor.rec.Rd                                                  |   24 
 man/pcor.test.Rd                                                 |   24 
 man/perform_aTest_for_all_sim_measures.Rd                        |   48 
 man/plotATestsFromTimepointFiles.Rd                              |   68 
 man/plotPRCCSFromTimepointFiles.Rd                               |   76 
 man/plot_compare_sim_observed_to_model_prediction.Rd             |   59 
 man/ploteFASTSiFromTimepointFiles.Rd                             |   54 
 man/prepare_parameter_value_list.Rd                              |   56 
 man/process_netlogo_parameter_range_info.Rd                      |   44 
 man/process_parameter_value_if_exists.Rd                         |   74 
 man/produce_accuracy_plots_all_measures.Rd                       |   52 
 man/produce_accuracy_plots_single_measure.Rd                     |   51 
 man/produce_atest_score_summary.Rd                               |   42 
 man/produce_summary_for_all_values_of_parameter.Rd               |   87 
 man/rSquared.Rd                                                  |   40 
 man/read_all_curve_results.Rd                                    |   59 
 man/read_from_csv.Rd                                             |   34 
 man/read_model_result_file.Rd                                    |   48 
 man/read_simulation_results.Rd                                   |   47 
 man/retrieve_results_for_comparison_result_set.Rd                |   38 
 man/sample_parameter_space.Rd                                    |   50 
 man/scale_lhc_sample.Rd                                          |   68 
 man/screen_nsga2_parameters.Rd                                   |   84 
 man/selectSuitableStructure.Rd                                   |   40 
 man/set.nsga_sensitivity_params.Rd                               |   64 
 man/sim_data_for_emulation.Rd                                    |   60 
 man/summarise_lhc_sweep_responses.Rd                             |  104 
 man/summarise_replicate_runs.Rd                                  |   54 
 man/tutorial_consistency_set.Rd                                  |   54 
 man/updateErrorForStructure.Rd                                   |   46 
 man/use_ensemble_to_generate_predictions.Rd                      |   65 
 man/visualise_data_distribution.Rd                               |   47 
 man/weight_emulator_predictions_by_ensemble.Rd                   |   58 
 man/write_data_to_csv.Rd                                         |   36 
 tests/testthat/helper_load_data.R                                |    3 
 tests/testthat/helper_netlogo.R                                  |   51 
 tests/testthat/test_aleatory_analysis.R                          |    5 
 tests/testthat/test_efast_analysis.R                             |  993 +++----
 tests/testthat/test_efast_sampling.R                             |   13 
 tests/testthat/test_efast_sampling_netlogo.R                     |    3 
 tests/testthat/test_emulation_sensitivity_analysis.R             |  169 -
 tests/testthat/test_evolution.R                                  |  157 -
 tests/testthat/test_input_argument.R                             | 1059 ++++----
 tests/testthat/test_lhc_sampling.R                               |    4 
 tests/testthat/test_lhc_sampling_netlogo.R                       |   91 
 tests/testthat/test_neural_network_utilities.R                   |  505 +--
 tests/testthat/test_robustness_analysis.R                        |   73 
 tests/testthat/test_robustness_sampling.R                        |    2 
 tests/testthat/test_spartan_utilities.R                          |   31 
 vignettes/emulation_ensembles.Rmd                                |  768 ++---
 vignettes/netlogo.Rmd                                            |    2 
 254 files changed, 12587 insertions(+), 12363 deletions(-)

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New package similr with initial version 1.0.0
Package: similr
Type: Package
Title: Text Similarity
Version: 1.0.0
Date: 2018-11-04
Author: Michael Holmes
Maintainer: Michael Holmes <mepstudies@gmail.com>
Description: Using brute-force string comparator algorithms, this package facilitates finding a particular string's closest match amongst a target vector of strings.
License: GPL (>= 2)
Imports: Rcpp, R6, stringr
LinkingTo: Rcpp
SystemRequirements: C++11
ByteCompile: true
NeedsCompilation: yes
RoxygenNote: 6.1.1
Encoding: UTF-8
Packaged: 2018-11-13 01:27:28 UTC; micha
Repository: CRAN
Date/Publication: 2018-11-19 19:00:08 UTC

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New package QuantumOps with initial version 1.0
Package: QuantumOps
Title: Performs Common Linear Algebra Operations Used in Quantum Computing
Version: 1.0
Date: 2018-11-11
Author: Salonik Resch
Maintainer: Salonik Resch <resc0059@umn.edu>
Description: Contains basic structures and operations used frequently in quantum computing. Intended to be a convenient tool to help in practicing the linear algebra involved in quantum operations. Has functionality for the creation of kets, bras, matrices and implements quantum gates, inner products, and tensor products.
Depends: R (>= 3.1.0)
License: GPL-3
RoxygenNote: 5.0.1
NeedsCompilation: no
Packaged: 2018-11-11 18:53:45 UTC; mike
Repository: CRAN
Date/Publication: 2018-11-19 18:10:11 UTC

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New package psica with initial version 1.0.0
Package: psica
Type: Package
Title: Decision Tree Analysis for Probabilistic Subgroup Identification with Multiple Treatments
Version: 1.0.0
Author: Oleg Sysoev, Krzysztof Bartoszek, Katarina Ekholm Selling and Lotta Ekstrom
Maintainer: Oleg Sysoev <Oleg.Sysoev@liu.se>
Description: In the situation when multiple alternative treatments or interventions available, different population groups may respond differently to different treatments. This package implements a method that discovers the population subgroups in which a certain treatment has a better effect than the other alternative treatments. This is done by first estimating the treatment effect for a given treatment and its uncertainty by computing random forests, and the resulting model is summarized by a decision tree in which the probabilities that the given treatment is best for a given subgroup is shown in the corresponding terminal node of the tree.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Imports: grid, gridBase, randomForest, rpart, partykit, party, BayesTree
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2018-11-12 10:13:30 UTC; olesy12
Repository: CRAN
Date/Publication: 2018-11-19 18:30:05 UTC

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New package pivmet with initial version 0.1.0
Package: pivmet
Type: Package
Title: Pivotal Methods for Bayesian Relabelling and k-Means Clustering
Version: 0.1.0
Date: 2018-11-08
Author: Leonardo Egidi[aut, cre], Roberta Pappadà[aut], Francesco Pauli[aut], Nicola Torelli[aut]
Maintainer: Leonardo Egidi <legidi@units.it>
License: GPL-2
Description: Collection of pivotal algorithms for: relabelling the MCMC chains in order to undo the label switching problem in Bayesian mixture models; initializing the centers of the classical k-means algorithm in order to obtain a better clustering solution.
URL: https://github.com/leoegidi/pivmet
Encoding: UTF-8
LazyData: true
LazyLoad: yes
Depends: bayesmix, rjags, runjags, mvtnorm, RcmdrMisc
Imports: cluster, mclust, MASS
Suggests: knitr
VignetteBuilder: knitr
RoxygenNote: 6.1.0
BuildManual: yes
NeedsCompilation: no
Packaged: 2018-11-12 11:20:17 UTC; leoeg
Repository: CRAN
Date/Publication: 2018-11-19 18:50:06 UTC

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New package npordtests with initial version 1.0
Package: npordtests
Type: Package
Title: Nonparametric Tests for Equality of Location Against Ordered Alternatives
Version: 1.0
Date: 2018-10-26
Depends: R (>= 2.15.0)
Author: Bulent Altunkaynak [aut, cre], Hamza Gamgam [aut]
Maintainer: Bulent Altunkaynak <bulenta@gazi.edu.tr>
Description: Performs nonparametric tests for equality of location against ordered alternatives.
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2018-11-12 22:50:55 UTC; bulent
Repository: CRAN
RoxygenNote: 6.1.1
Encoding: UTF-8
Date/Publication: 2018-11-19 18:50:09 UTC

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New package NBDesign with initial version 1.0.0
Package: NBDesign
Type: Package
Version: 1.0.0
Date: 2018-11-11
Title: Design and Monitoring of Clinical Trials with Negative Binomial Endpoint
Description: Calculates various functions needed for design and monitoring clinical trials with negative binomial endpoint with variable follow-up.
Authors@R: c( person(given="Xiaodong", family="Luo", email = "Xiaodong.Luo@sanofi.com", role =c("aut", "cre")), person("Sanofi", role = "cph"))
Depends: R (>= 3.1.2)
Imports: stats,PWEALL,MASS
License: GPL (>= 2)
RoxygenNote: 5.0.1
LazyData: true
NeedsCompilation: no
Packaged: 2018-11-11 17:43:55 UTC; Administrator
Author: Xiaodong Luo [aut, cre], Sanofi [cph]
Maintainer: Xiaodong Luo <Xiaodong.Luo@sanofi.com>
Repository: CRAN
Date/Publication: 2018-11-19 18:10:14 UTC

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New package MPTmultiverse with initial version 0.1
Package: MPTmultiverse
Title: Multiverse Analysis of Multinomial Processing Tree Models
Version: 0.1
Description: Statistical or cognitive modeling usually requires a number of more or less arbitrary choices creating one specific path through a 'garden of forking paths'. The multiverse approach (Steegen, Tuerlinckx, Gelman, & Vanpaemel, 2016, <doi:10.1177/1745691616658637>) offers a principled alternative in which results for all possible combinations of reasonable modeling choices are reported. MPTmultiverse performs a multiverse analysis for multinomial processing tree (MPT, Riefer & Batchelder, 1988, <doi:10.1037/0033-295X.95.3.318>) models combining maximum-likelihood/frequentist and Bayesian estimation approaches with different levels of pooling (i.e., data aggregation). For the frequentist approaches, no pooling (with and without parametric or nonparametric bootstrap) and complete pooling are implemented using MPTinR <https://cran.r-project.org/package=MPTinR>. For the Bayesian approaches, no pooling, complete pooling, and three different variants of partial pooling are implemented using TreeBUGS <https://cran.r-project.org/package=TreeBUGS>. The main function is fit_mpt() who performs the multiverse analysis in one call.
Authors@R: c( person("Henrik", "Singmann", role = c("aut", "cre"), email="singmann@gmail.com", comment=c(ORCID="0000-0002-4842-3657")) , person(c("Daniel", "W."), "Heck", email = "heck@uni-mannheim.de", role = c("aut")) , person("Marius", "Barth", email = "marius.barth@uni-koeln.de", role = c("aut")) , person("Frederik", "Aust", email = "frederik.aust@uni-koeln.de", role = c("ctb"), comment = c(ORCID = "0000-0003-4900-788X")) )
URL: https://github.com/mpt-network/MPTmultiverse
BugReports: https://github.com/mpt-network/MPTmultiverse/issues
Depends: R (>= 2.11.1),
Imports: parallel, magrittr, tidyr, dplyr, tibble, rlang, reshape2, ggplot2, MPTinR, TreeBUGS, runjags, coda, purrr, broom, readr
Suggests: knitr, rmarkdown, testthat
LazyData: yes
VignetteBuilder: knitr
RoxygenNote: 6.1.0
License: GPL-2
NeedsCompilation: no
Packaged: 2018-11-11 22:31:44 UTC; henrik
Author: Henrik Singmann [aut, cre] (<https://orcid.org/0000-0002-4842-3657>), Daniel W. Heck [aut], Marius Barth [aut], Frederik Aust [ctb] (<https://orcid.org/0000-0003-4900-788X>)
Maintainer: Henrik Singmann <singmann@gmail.com>
Repository: CRAN
Date/Publication: 2018-11-19 18:20:11 UTC

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New package irteQ with initial version 1.0.0
Package: irteQ
Type: Package
Title: Linking and Equating Methods in Unidimensional Item Response Theory
Version: 1.0.0
Description: IRT-based methods are used to estimate IRT linking coefficients and to perform IRT equating under the common item non-equivalent group design. For the IRT linking procedure, the Mean/Mean, Mean/Sigma, Haebara, and Stocking-Lord methods are available. For IRT test score equating, the true score equating and observed score equating methods are available. This package supports both dichotomous IRT models (1PL, 2PL and 3PL) and polytomous IRT models (graded response model, partial credit model, and generalized partial credit model). In addition to IRT linking and equating capabilities, there are several useful functions such as importing item and/or ability parameters from IRT software, generating simulated data, estimating the standard error of equating due to the random selection of common items, computing the conditional distribution of observed scores using the Lord-Wingersky recursion formula, computing item and test information functions, computing item and test characteristic curve functions, and plotting item and test characteristic curves and item and test information functions as well as scatter plots.
Depends: R (>= 3.4)
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Imports: stats, statmod, utils, reshape2, dplyr, tidyr, purrr, ggplot2, ggrepel, rlang
Authors@R: c(person("Hwanggyu", "Lim", email="hglim83@gmail.com", role=c("aut", "cre")), person("Francis", "O'Donnell", email="francisrick@me.com ", rol="ctb"), person("Craig S.", "Wells", email="cswells@educ.umass.edu ", rol="ctb") )
RoxygenNote: 6.1.0
Suggests: mirt
URL: https://github.com/hwangQ/irteQ
BugReports: https://github.com/hwangQ/irteQ/issues
NeedsCompilation: no
Packaged: 2018-11-12 06:18:29 UTC; kijja
Author: Hwanggyu Lim [aut, cre], Francis O'Donnell [ctb], Craig S. Wells [ctb]
Maintainer: Hwanggyu Lim <hglim83@gmail.com>
Repository: CRAN
Date/Publication: 2018-11-19 18:30:08 UTC

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New package GLSE with initial version 0.1.0
Package: GLSE
Type: Package
Title: Graphical Least Square Estimation
Version: 0.1.0
Author: Saeed Aldahmani
Maintainer: Saeed Aldahmani <saldahmani@uaeu.ac.ae>
Description: The Graphical Least Square Estimation 'GLSE' package consists of several functions. The first function (called GLSE()), which is the main function in this package, is for estimating linear regression via graphical models, especially when the number of observations is smaller than the number of variables. This function gives unbiased estimated regression models under some conditions on the predictors. Moreover, this function aims to deal with studies where all covariates need to be kept in the model (such as portfolio optimisation). The second function provides an estimation of the bootstrap standard errors of the 'GLSE' parameters. The third function generates data from multivariate normal distribution for regression purposes, and the fourth function generates data from multivariate t-distribution for the same purpose. Generating an undirected decomposable graph is carried out by the fifth function and its decomposability is tested in the sixth function. The seventh function gives a perfect sequence of the cliques and separators of the given decomposable graph. Finally, the last function gives the plot of the decomposale graph. The package supports both serial and parallel computations for estimating the graph.The 'GLSE' package is an implementation of the method introduced in Aldahmani, S., and Dai, H. (2015) <doi:10.5539/ijsp.v4n3p61>.
License: GPL-2
Imports: gRbase, igraph, mvtnorm, parallel, stats
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-11-12 12:48:37 UTC; saldahmani
Repository: CRAN
Date/Publication: 2018-11-19 18:50:18 UTC

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New package gginference with initial version 0.1.0
Package: gginference
Type: Package
Title: Visualise the Results of Inferential Statistics using 'ggplot2'
Version: 0.1.0
Date: 2018-10-24
Description: Visualise the results of F test to compare two variances, Student's t-test, test of equal or given proportions, Pearson's chi-squared test for count data and test for association/correlation between paired samples.
Authors@R: c( person("Charalampos", "Bratsas", , "cbratsas@math.auth.gr", role = "aut"), person("Anastasia", "Foudouli", , "anastasiafoudouli@gmail.com", role = "aut"), person("Kleanthis", "Koupidis", , "koupidis@okfn.gr", role = c("aut", "cre")) )
Maintainer: Kleanthis Koupidis <koupidis@okfn.gr>
URL: https://github.com/okgreece/gginference
BugReports: https://github.com/okgreece/gginference/issues
Depends: R (>= 3.4.0)
License: GPL-2 | file LICENSE
Encoding: UTF-8
LazyData: true
Imports: ggplot2, rlang, stats
RoxygenNote: 6.1.0.9000
Suggests: knitr, MASS, rmarkdown
NeedsCompilation: no
Packaged: 2018-11-05 13:23:02 UTC; akis_
Author: Charalampos Bratsas [aut], Anastasia Foudouli [aut], Kleanthis Koupidis [aut, cre]
Repository: CRAN
Date/Publication: 2018-11-19 18:10:03 UTC

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New package FlexScan with initial version 0.1.0
Package: FlexScan
Type: Package
Title: Flexible Scan Statistics
Version: 0.1.0
Author: Zhicheng Du, Yuantao Hao
Maintainer: Zhicheng Du <dgdzc@hotmail.com>
Depends: R (>= 2.10)
Description: An easy way to conduct flexible scan. Monte-Carlo method is used to test the spatial clusters given the cases, population, and shapefile. A table with formal style and a map with clusters are included in the result report. The method can be referenced at: Toshiro Tango and Kunihiko Takahashi (2005) <doi:10.1186/1476-072X-4-11>.
License: GPL-3
Imports: smerc, sp, spdep, methods, graphics
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2018-11-04 17:50:22 UTC; dgdzc
Repository: CRAN
Date/Publication: 2018-11-19 18:10:17 UTC

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New package ffmetadata with initial version 1.0.0
Package: ffmetadata
Type: Package
Title: Access to Fragile Families Metadata
Version: 1.0.0
Authors@R: c( person("Ryan", "Vinh", email = "rvinh@princeton.edu", role = c("aut", "cre")), person("Ian", "Fellows", email = "ian@fellstat.com", role = "aut"), person("Will", "Lowe", email = "wlowe@princeton.edu", role = "ctb"))
Description: A collection of functions that allows users to retrieve metadata for the Fragile Families challenge via a Web API (<http://api.metadata.fragilefamilies.princeton.edu>). Users can select and search metadata for relevant variables by filtering on different attribute names.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: jsonlite, httr
RoxygenNote: 6.1.1
Suggests: testthat, knitr, rmarkdown
VignetteBuilder: knitr
URL: https://github.com/fragilefamilieschallenge/ffmetadata
BugReports: https://github.com/fragilefamilieschallenge/ffmetadata/issues
NeedsCompilation: no
Packaged: 2018-11-13 01:25:26 UTC; ryanvinh
Author: Ryan Vinh [aut, cre], Ian Fellows [aut], Will Lowe [ctb]
Maintainer: Ryan Vinh <rvinh@princeton.edu>
Repository: CRAN
Date/Publication: 2018-11-19 19:00:11 UTC

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Package embed updated to version 0.0.2 with previous version 0.0.1 dated 2018-09-14

Title: Extra Recipes for Encoding Categorical Predictors
Description: Factor predictors can be converted to one or more numeric representations using simple generalized linear models <arXiv:1611.09477> or nonlinear models <arXiv:1604.06737>. All encoding methods are supervised.
Author: Max Kuhn [aut, cre], RStudio [cph]
Maintainer: Max Kuhn <max@rstudio.com>

Diff between embed versions 0.0.1 dated 2018-09-14 and 0.0.2 dated 2018-11-19

 DESCRIPTION                      |   12 ++---
 MD5                              |   32 ++++++++-------
 NAMESPACE                        |    8 +++
 NEWS.md                          |   11 +++++
 R/bayes.R                        |   44 ++++++++++++---------
 R/glm.R                          |   37 ++++++++++--------
 R/lme.R                          |   40 +++++++++++--------
 R/reexports.R                    |only
 R/tf.R                           |   80 ++++++++++++++++++++++-----------------
 man/reexports.Rd                 |only
 man/step_embed.Rd                |   38 +++++++++---------
 man/step_lencode_bayes.Rd        |    9 ++--
 man/step_lencode_glm.Rd          |   11 ++---
 man/step_lencode_mixed.Rd        |    8 +--
 tests/testthat/test_mixed.R      |   18 ++++----
 tests/testthat/test_no_pooling.R |   18 ++++----
 tests/testthat/test_pooling.R    |   19 ++++-----
 tests/testthat/test_tf.R         |   18 ++++----
 18 files changed, 228 insertions(+), 175 deletions(-)

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New package dqshiny with initial version 0.0.1
Package: dqshiny
Type: Package
Title: Enhance Shiny Apps with Customizable Modules
Version: 0.0.1
Author: Richard Kunze, Mirjam Rehr
Maintainer: Richard Kunze <richard.kunze@daqana.com>
Description: Provides highly customizable modules to enhance your shiny apps. Includes layout independent collapsible boxes and value boxes, a very fast autocomplete input, rhandsontable extensions for filtering and paging and much more.
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Imports: shiny, htmltools
Suggests: testthat, extrafont, ggplot2, jsonlite, rhandsontable, V8, htmlwidgets, shinytest
URL: https://github.com/daqana/dqshiny
BugReports: https://github.com/daqana/dqshiny/issues
NeedsCompilation: no
Packaged: 2018-11-12 14:50:28 UTC; richardkunze
Repository: CRAN
Date/Publication: 2018-11-19 18:50:13 UTC

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New package deckgl with initial version 0.1.8
Package: deckgl
Title: An R Interface to 'deck.gl'
Version: 0.1.8
Date: 2018-11-10
Authors@R: person("Stefan", "Kuethe", email = "crazycapivara@gmail.com", role = c("aut", "cre"))
Maintainer: Stefan Kuethe <crazycapivara@gmail.com>
Description: Makes 'deck.gl' <https://deck.gl/>, a WebGL-powered open-source JavaScript framework for visual exploratory data analysis of large datasets, available within R via the 'htmlwidgets' package. Furthermore, it supports basemaps from 'mapbox' <https://www.mapbox.com/> via 'mapbox-gl-js' <https://github.com/mapbox/mapbox-gl-js>.
URL: https://github.com/crazycapivara/deckgl/, https://crazycapivara.github.io/deckgl/
BugReports: https://github.com/crazycapivara/deckgl/issues/
Depends: R (>= 3.3)
Imports: htmlwidgets, htmltools, magrittr, base64enc, yaml, jsonlite, readr, tibble
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
Suggests: knitr, rmarkdown, testthat, rprojroot
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-11-10 20:53:42 UTC; gabbo
Author: Stefan Kuethe [aut, cre]
Repository: CRAN
Date/Publication: 2018-11-19 18:10:06 UTC

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New package BHSBVAR with initial version 1.0.0
Encoding: UTF-8
Package: BHSBVAR
Type: Package
Title: Structural Bayesian Vector Autoregression Models
Version: 1.0.0
Date: 2018-11-01
Author: Paul Richardson
Maintainer: Paul Richardson <p.richardson.54391@gmail.com>
Description: Provides a function for running Structural Bayesian Vector Autoregression models with the method developed by Baumeister and Hamilton (2015) <doi:10.3982/ECTA12356>, Baumeister and Hamilton (2017) <doi:10.3386/w24167>, and Baumeister and Hamilton (2018) <doi:10.1016/j.jmoneco.2018.06.005>. Functions for plotting impulse responses, historical decompositions, and posterior distributions of model parameters are also provided.
License: GPL (>= 3)
Depends: R (>= 3.5.0)
Imports: Rcpp (>= 0.12.19)
LinkingTo: Rcpp, RcppArmadillo
RoxygenNote: 6.1.1
Suggests: knitr
VignetteBuilder: knitr
LazyData: true
NeedsCompilation: yes
Packaged: 2018-11-12 02:35:59 UTC; prich
Repository: CRAN
Date/Publication: 2018-11-19 18:30:13 UTC

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Package StMoSim updated to version 3.1.1 with previous version 3.1 dated 2018-11-14

Title: Quantile-Quantile Plot with Several Gaussian Simulations
Description: Plots a QQ-Norm Plot with several Gaussian simulations.
Author: Matthias Salvisberg
Maintainer: Matthias Salvisberg <matthias.salvisberg@gmail.com>

Diff between StMoSim versions 3.1 dated 2018-11-14 and 3.1.1 dated 2018-11-19

 DESCRIPTION      |   17 +++---
 MD5              |   16 ++---
 NAMESPACE        |    3 -
 R/StMoSim.R      |   15 ++++-
 R/qqnormSim.R    |  147 +++++++++++++++++++++++++++++++++++++++++++++++--------
 man/StMoSim.Rd   |   15 ++++-
 man/qqnormSim.Rd |   88 +++++++++++++++++++++++++++++---
 src/Makevars     |    1 
 src/Makevars.win |    4 +
 9 files changed, 255 insertions(+), 51 deletions(-)

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New package rphylopic with initial version 0.2.0
Package: rphylopic
Title: Get 'Silhouettes' of 'Organisms' from 'Phylopic'
Description: Work with 'Phylopic' web service (<http://phylopic.org/api/>) to get 'silhouette' images of 'organisms', search names, and more. Includes functions for adding 'silhouettes' to both base plots and ggplot2 plots.
Version: 0.2.0
Authors@R: c( person("Scott", "Chamberlain", role = c("aut", "cre"), email = "myrmecocystus@gmail.com", comment = c(ORCID = "0000-0003-1444-9135")), person("David", "Miller", role = "ctb", email = "dave@ninepointeightone.net") )
License: MIT + file LICENSE
URL: https://github.com/sckott/rphylopic
BugReports: https://github.com/sckott/rphylopic/issues
Encoding: UTF-8
Language: en-US
Imports: ggplot2, crul (>= 0.5.2), jsonlite, grid, gridBase, graphics, png
Suggests: testthat, vcr (>= 0.2.0)
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2018-11-09 23:32:34 UTC; sckott
Author: Scott Chamberlain [aut, cre] (<https://orcid.org/0000-0003-1444-9135>), David Miller [ctb]
Maintainer: Scott Chamberlain <myrmecocystus@gmail.com>
Repository: CRAN
Date/Publication: 2018-11-19 18:00:03 UTC

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New package ref.ICAR with initial version 1.0
Package: ref.ICAR
Title: Objective Bayes Intrinsic Conditional Autoregressive Model for Areal Data
Version: 1.0
Author: Erica M. Porter, Matthew J. Keefe, Christopher T. Franck, and Marco A.R. Ferreira
Maintainer: Erica M. Porter <ericamp@vt.edu>
Depends: R (>= 3.1.0)
Description: Implements an objective Bayes intrinsic conditional autoregressive prior. This model provides an objective Bayesian approach for modeling spatially correlated areal data using an intrinsic conditional autoregressive prior on a vector of spatial random effects.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Imports: rgdal, spdep, mvtnorm, coda, MCMCglmm, Rdpack, graphics
RdMacros: Rdpack
Suggests: maptools, maps, MASS, sp, knitr, rmarkdown, RColorBrewer, captioner, rcrossref
VignetteBuilder: knitr
BuildManual: yes
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2018-11-09 23:46:50 UTC; EricaPorter
Repository: CRAN
Date/Publication: 2018-11-19 18:00:06 UTC

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New package rcosmo with initial version 1.0.0
Package: rcosmo
URL: https://github.com/VidaliLama/rcosmo
BugReports: https://github.com/VidaliLama/rcosmo/issues
Title: Cosmic Microwave Background Data Analysis
Version: 1.0.0
Authors@R: c(person("Daniel", "Fryer", role = c("aut", "cre"), email = "d.fryer@latrobe.edu.au", comment = c(ORCID = "0000-0001-6032-0522")), person("Andriy", "Olenko", role = "aut", email = "a.olenko@latrobe.edu.au", comment = c(ORCID = "0000-0002-0917-7000")), person("Ming", "Li", role = "aut", comment = c(ORCID = "0000-0002-1218-2804")), person("Yuguang", "Wang", role = "aut"))
Description: Handling and Analysing Spherical, HEALPix and Cosmic Microwave Background data on a HEALPix grid.
Depends: R (>= 3.4.0)
License: GPL-3 | file LICENSE
Encoding: UTF-8
LazyData: true
Imports: FITSio (>= 2.1-0), Rcpp (>= 0.12.11), mmap (>= 0.6-17), tibble (>= 1.4.2), rgl (>= 0.99.16), cli (>= 1.0.0), entropy (>= 1.2.1), geoR (>= 1.7-5.2.1), nnls (>= 1.4)
Suggests: knitr, rmarkdown, testthat, R.rsp, gsl
LinkingTo: Rcpp
RoxygenNote: 6.1.0
NeedsCompilation: yes
Packaged: 2018-11-10 00:05:13 UTC; danie
Author: Daniel Fryer [aut, cre] (<https://orcid.org/0000-0001-6032-0522>), Andriy Olenko [aut] (<https://orcid.org/0000-0002-0917-7000>), Ming Li [aut] (<https://orcid.org/0000-0002-1218-2804>), Yuguang Wang [aut]
Maintainer: Daniel Fryer <d.fryer@latrobe.edu.au>
Repository: CRAN
Date/Publication: 2018-11-19 18:00:09 UTC

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New package phylocomr with initial version 0.1.0
Package: phylocomr
Type: Package
Title: Interface to 'Phylocom'
Description: Interface to 'Phylocom' (<http://phylodiversity.net/phylocom/>), a library for analysis of 'phylogenetic' community structure and character evolution. Includes low level methods for interacting with the three executables, as well as higher level interfaces for methods like 'aot', 'ecovolve', 'bladj', 'phylomatic', and more.
Version: 0.1.0
Authors@R: c( person("Jeroen", "Ooms", role = "aut", email = "jeroen@berkeley.edu"), person("Scott", "Chamberlain", role = c("aut", "cre"), email = "sckott@protonmail.com", comment = c(ORCID="0000-0003-1444-9135")), person("Cam", "Webb", role = "cph", comment = "Author of libphylocom (see AUTHORS and COPYRIGHT files for details)"), person("David", "Ackerly", role = "cph", comment = "Author of libphylocom (see AUTHORS and COPYRIGHT files for details)"), person("Steven", "Kembel", role = "cph", comment = "Author of libphylocom (see AUTHORS and COPYRIGHT files for details)") )
URL: https://github.com/ropensci/phylocomr
BugReports: https://github.com/ropensci/phylocomr/issues
License: BSD_2_clause + file LICENSE
Encoding: UTF-8
Language: en-US
LazyData: true
VignetteBuilder: knitr
Imports: tibble, sys (>= 1.1)
Suggests: testthat, knitr, rmarkdown, ape
RoxygenNote: 6.1.1
X-schema.org-applicationCategory: Biodiversity
X-schema.org-keywords: phylogeny, Phylocom, phylodiversity, community structure, character evolution, species
X-schema.org-isPartOf: https://ropensci.org
NeedsCompilation: yes
Packaged: 2018-11-10 00:17:50 UTC; sckott
Author: Jeroen Ooms [aut], Scott Chamberlain [aut, cre] (<https://orcid.org/0000-0003-1444-9135>), Cam Webb [cph] (Author of libphylocom (see AUTHORS and COPYRIGHT files for details)), David Ackerly [cph] (Author of libphylocom (see AUTHORS and COPYRIGHT files for details)), Steven Kembel [cph] (Author of libphylocom (see AUTHORS and COPYRIGHT files for details))
Maintainer: Scott Chamberlain <sckott@protonmail.com>
Repository: CRAN
Date/Publication: 2018-11-19 18:00:16 UTC

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New package ordering with initial version 0.7.0
Package: ordering
Type: Package
Title: Test, Check, Verify, Investigate the Monotonic Properties of Vectors
Version: 0.7.0
Date: 2018-11-09
Authors@R: c( person("Christopher", "Brown", , "chris.brown@decisionpatterns.com", c("aut", "cre") ), person("Decision Patterns", role = "cph") )
Maintainer: Christopher Brown <chris.brown@decisionpatterns.com>
Description: Functions to test/check/verify/investigate the ordering of vectors. The 'is_[strictly_]*' family of functions test vectors for 'sorted', 'monotonic', 'increasing', 'decreasing' order; 'is_constant' and 'is_incremental' test for the degree of ordering. `ordering` provides a numeric indication of ordering -2 (strictly decreasing) to 2 (strictly increasing).
Suggests: testthat, na.tools(>= 0.3.0)
License: GPL (>= 2)
URL: https://github.com/decisionpatterns/ordering
BugReports: https://github.com/decisionpatterns/ordering/issues
RoxygenNote: 6.1.1
Repository: CRAN
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2018-11-09 23:29:18 UTC; cbrown
Author: Christopher Brown [aut, cre], Decision Patterns [cph]
Date/Publication: 2018-11-19 18:00:20 UTC

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New package ODS with initial version 0.2.0
Package: ODS
Type: Package
Title: Statistical Methods for Outcome-Dependent Sampling Designs
Version: 0.2.0
Authors@R: c(person("Yinghao", "Pan", role = c("aut", "cre"), email = "ypan8@uncc.edu"), person("Haibo", "Zhou", role = "aut", email = "zhou@bios.unc.edu"), person("Mark", "Weaver", role = "aut"), person("Guoyou", "Qin", role = "aut"), person("Jianwen", "Cai", role = "aut"))
Author: Yinghao Pan [aut, cre], Haibo Zhou [aut], Mark Weaver [aut], Guoyou Qin [aut], Jianwen Cai [aut]
Maintainer: Yinghao Pan <ypan8@uncc.edu>
Description: Outcome-dependent sampling (ODS) schemes are cost-effective ways to enhance study efficiency. In ODS designs, one observes the exposure/covariates with a probability that depends on the outcome variable. Popular ODS designs include case-control for binary outcome, case-cohort for time-to-event outcome, and continuous outcome ODS design (Zhou et al. 2002) <doi: 10.1111/j.0006-341X.2002.00413.x>. Because ODS data has biased sampling nature, standard statistical analysis such as linear regression will lead to biases estimates of the population parameters. This package implements four statistical methods related to ODS designs: (1) An empirical likelihood method analyzing the primary continuous outcome with respect to exposure variables in continuous ODS design (Zhou et al., 2002). (2) A partial linear model analyzing the primary outcome in continuous ODS design (Zhou, Qin and Longnecker, 2011) <doi: 10.1111/j.1541-0420.2010.01500.x>. (3) Analyze a secondary outcome in continuous ODS design (Pan et al. 2018) <doi: 10.1002/sim.7672>. (4) An estimated likelihood method analyzing a secondary outcome in case-cohort data (Pan et al. 2017) <doi: 10.1111/biom.12838>.
Depends: R (>= 3.5.0)
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
Imports: cubature (>= 1.4-1), survival (>= 2.42-3), utils, stats
URL: https://github.com/Yinghao-Pan/ODS
BugReports: https://github.com/Yinghao-Pan/ODS/issues
NeedsCompilation: no
Packaged: 2018-11-18 23:43:39 UTC; yinghaopan
Repository: CRAN
Date/Publication: 2018-11-19 17:50:03 UTC

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New package fdq with initial version 0.11
Package: fdq
Type: Package
Title: Forest Data Quality
Date: 2018-11-19
Version: 0.11
Authors@R: c(person("Caíque", "de Oliveira de Souza", email = "forestgrowthsoftware@gmail.com", role = c("aut", "cre")), person("Clayton", "Vieira Fraga Filho", email = "claytonfraga@gmail.com", role = c("ctb", "dtc")), person("Miquéias", "Fernandes", email = "contatomiqueiasfernandes@gmail.com", role = c("ctb")))
Maintainer: Caíque de Oliveira de Souza <forestgrowthsoftware@gmail.com>
Description: Forest data quality is a package that contains methods of analysis of forest databases, the purpose of the analyzes is to evaluate the quality of the data present in the databases focusing on the dimensions of consistency, pountuality and completeness. Databases can range from forest inventory data to growth model data. The package has methods to work with large volumes of data quickly, in addition in certain analyzes it is possible to generate the graphs for a better understanding of the analysis and reporting of the analyzed analysis.
License: GPL-3
Encoding: UTF-8
LazyData: true
Suggests: testthat
Depends: R(>= 3.0), Fgmutils
Imports: data.table, sqldf, randomcoloR, ggplot2, plyr, utils, stats
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2018-11-19 16:01:37 UTC; Clayton
Author: Caíque de Oliveira de Souza [aut, cre], Clayton Vieira Fraga Filho [ctb, dtc], Miquéias Fernandes [ctb]
Repository: CRAN
Date/Publication: 2018-11-19 17:10:03 UTC

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Package EdSurvey updated to version 2.2.2 with previous version 2.2.1 dated 2018-11-19

Title: Analysis of NCES Education Survey and Assessment Data
Description: Read in and analysis functions for education survey and assessment data from the National Center for Education Statistics (NCES) <https://nces.ed.gov/>, including National Assessment of Educational Progress (NAEP) data <https://nces.ed.gov/nationsreportcard/> and data from the International Assessment Database: OECD <http://www.oecd.org/>, including PISA, TALIS, PIAAC, and IEA <http://www.iea.nl/>, including TIMSS, TIMSS Advanced, PIRLS, ICCS, ICILS, and CivEd.
Author: Paul Bailey [aut, cre], Ren C'deBaca [ctb], Ahmad Emad [aut], Huade Huo [aut], Michael Lee [aut], Yuqi Liao [aut], Alex Lishinski [aut], Trang Nguyen [aut], Qingshu Xie [aut], Jiao Yu [aut], Ting Zhang [aut]
Maintainer: Paul Bailey <pbailey@air.org>

Diff between EdSurvey versions 2.2.1 dated 2018-11-19 and 2.2.2 dated 2018-11-19

 DESCRIPTION                          |    8 +--
 MD5                                  |   14 ++---
 man/examples/percentile.R            |    2 
 man/percentile.Rd                    |    2 
 tests/Examples/edsurvey-Ex.Rout.save |   90 ++++++++++++-----------------------
 tests/testthat/test-0-main.R         |    3 -
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Permanent link

New package collateral with initial version 0.4.2
Package: collateral
Title: Quickly Evaluate Captured Side Effects
Version: 0.4.2
Authors@R: person("James", "Goldie", email = "me@rensa.co", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-5024-6207"))
Description: The purrr package allows you to capture the side effects (errors, warning, messages and other output) of functions using safely() and quietly(). Using collateral, you can quickly see which elements of a list (or list-column) returned results, which threw errors and which returned warnings or other output.
URL: https://rensa.co/collateral/index.html, https://github.com/rensa/collateral
Depends: R (>= 3.1.0)
Imports: purrr, crayon, methods, pillar
License: GPL-3 | file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
BugReports: https://github.com/rensa/collateral/issues
Suggests: dplyr, knitr, magrittr, rmarkdown, tidyverse
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-11-09 08:05:14 UTC; rensa
Author: James Goldie [aut, cre] (<https://orcid.org/0000-0002-5024-6207>)
Maintainer: James Goldie <me@rensa.co>
Repository: CRAN
Date/Publication: 2018-11-19 18:00:23 UTC

More information about collateral at CRAN
Permanent link

Package MachineShop updated to version 0.2.0 with previous version 0.1-1 dated 2018-10-14

Title: Machine Learning Models and Tools
Description: Meta-package for statistical and machine learning with a common interface for model fitting, prediction, performance assessment, and presentation of results. Supports predictive modeling of numerical, categorical, and censored time-to-event outcomes and resample (bootstrap and cross-validation) estimation of model performance.
Author: Brian J Smith [aut, cre]
Maintainer: Brian J Smith <brian-j-smith@uiowa.edu>

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Package RZooRoH updated to version 0.2.2 with previous version 0.2.1 dated 2018-11-15

Title: Partitioning of Individual Autozygosity into Multiple Homozygous-by-Descent Classes
Description: Functions to identify Homozygous-by-Descent (HBD) segments associated with runs of homozygosity (ROH) and to estimate individual autozygosity (or inbreeding coefficient). HBD segments and autozygosity are assigned to multiple HBD classes with a model-based approach relying on a mixture of exponential distributions. The rate of the exponential distribution is distinct for each HBD class and defines the expected length of the HBD segments. These HBD classes are therefore related to the age of the segments (longer segments and smaller rates for recent autozygosity / recent common ancestor). The functions allow to estimate the parameters of the model (rates of the exponential distributions, mixing proportions), to estimate global and local autozygosity probabilities and to identify HBD segments with the Viterbi decoding. The method is fully described in Druet and Gautier (2017) <doi:10.1111/mec.14324>.
Author: Tom Druet, Naveen Kumar Kadri, Amandine Bertrand and Mathieu Gautier
Maintainer: Tom Druet <tom.druet@uliege.be>

Diff between RZooRoH versions 0.2.1 dated 2018-11-15 and 0.2.2 dated 2018-11-19

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Package shades updated to version 1.3.0 with previous version 1.2.0 dated 2018-04-26

Title: Simple Colour Manipulation
Description: Functions for easily manipulating colours, creating colour scales and calculating colour distances.
Author: Jon Clayden
Maintainer: Jon Clayden <code@clayden.org>

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New package ITGM with initial version 0.41
Package: ITGM
Type: Package
Title: Individual Tree Growth Modeling
Version: 0.41
Author: Clayton Vieira Fraga Filho, Miqueias Fernandes
Maintainer: Clayton Vieira Fraga Filho <forestgrowthsoftware@gmail.com>
Description: Individual tree model is an instrument to support the decision with regard to forest management. This package provides functions that let you work with data for this model. Also other support functions and extension related to this model are available.
License: GPL-2
LazyData: TRUE
Depends: Fgmutils (>= 0.8), R (>= 3.0)
Imports: gsubfn, data.table, sqldf, plyr
RoxygenNote: 6.1.1
Suggests: testthat
NeedsCompilation: no
Packaged: 2018-11-19 12:25:43 UTC; Clayton
Repository: CRAN
Date/Publication: 2018-11-19 13:10:03 UTC

More information about ITGM at CRAN
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Package EdSurvey updated to version 2.2.1 with previous version 2.0.3 dated 2018-05-16

Title: Analysis of NCES Education Survey and Assessment Data
Description: Read in and analysis functions for education survey and assessment data from the National Center for Education Statistics (NCES) <https://nces.ed.gov/>, including National Assessment of Educational Progress (NAEP) data <https://nces.ed.gov/nationsreportcard/> and data from the International Assessment Database: OECD <http://www.oecd.org/>, including PISA, TALIS, PIAAC, and IEA <http://www.iea.nl/>, including TIMSS, TIMSS Advanced, PIRLS, ICCS, ICILS, and CivEd.
Author: Paul Bailey [aut, cre], Ren C'deBaca [ctb], Ahmad Emad [aut], Huade Huo [aut], Michael Lee [aut], Yuqi Liao [aut], Alex Lishinski [aut], Trang Nguyen [aut], Qingshu Xie [aut], Jiao Yu [aut], Ting Zhang [aut]
Maintainer: Paul Bailey <pbailey@air.org>

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Package soilDB updated to version 2.3 with previous version 2.0-1 dated 2018-01-23

Title: Soil Database Interface
Description: A collection of functions for reading data from USDA-NCSS soil databases.
Author: Dylan Beaudette [cre], Jay Skovlin [aut], Stephen Roecker [aut]
Maintainer: Dylan Beaudette <dylan.beaudette@ca.usda.gov>

Diff between soilDB versions 2.0-1 dated 2018-01-23 and 2.3 dated 2018-11-19

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Package recipes updated to version 0.1.4 with previous version 0.1.3 dated 2018-06-16

Title: Preprocessing Tools to Create Design Matrices
Description: An extensible framework to create and preprocess design matrices. Recipes consist of one or more data manipulation and analysis "steps". Statistical parameters for the steps can be estimated from an initial data set and then applied to other data sets. The resulting design matrices can then be used as inputs into statistical or machine learning models.
Author: Max Kuhn [aut, cre], Hadley Wickham [aut], RStudio [cph]
Maintainer: Max Kuhn <max@rstudio.com>

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Package propr updated to version 4.1.1 with previous version 4.0.0 dated 2018-07-25

Title: Calculating Proportionality Between Vectors of Compositional Data
Description: The bioinformatic evaluation of gene co-expression often begins with correlation-based analyses. However, correlation lacks validity when applied to relative data, including count data generated by next-generation sequencing. This package implements several metrics for proportionality, including phi [Lovell et al (2015) <DOI:10.1371/journal.pcbi.1004075>] and rho [Erb and Notredame (2016) <DOI:10.1007/s12064-015-0220-8>]. This package also implements several metrics for differential proportionality. Unlike correlation, these measures give the same result for both relative and absolute data.
Author: Thomas Quinn [aut, cre], David Lovell [aut], Ionas Erb [aut], Anders Bilgrau [ctb], Greg Gloor [ctb]
Maintainer: Thomas Quinn <contacttomquinn@gmail.com>

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Package pollimetry updated to version 1.0.1 with previous version 1.0.0 dated 2018-09-11

Title: Estimate Pollinator Body Size and Co-Varying Ecological Traits
Description: Tools to estimate pollinator body size and co-varying traits. This package contains novel Bayesian predictive models of pollinator body size (for bees and hoverflies) as well as preexisting predictive models for pollinator body size (currently implemented for ants, bees, butterflies, flies, moths and wasps) as well as bee tongue length and foraging distance, total field nectar loads and wing loading. An additional GitHub repository <https://github.com/liamkendall/pollimetrydata> provides model objects to use the bodysize function internally. All models are described in Kendall et al (2018) <doi:10.1101/397604>.
Author: Liam Kendall [aut, cre], Ignasi Bartomeus [aut], Louis Sutter [ctb]
Maintainer: Liam Kendall <liam.k.kendall@gmail.com>

Diff between pollimetry versions 1.0.0 dated 2018-09-11 and 1.0.1 dated 2018-11-19

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Package CAST updated to version 0.3.1 with previous version 0.3.0 dated 2018-10-11

Title: 'caret' Applications for Spatial-Temporal Models
Description: Supporting functionality to run 'caret' with spatial or spatial-temporal data. 'caret' is a frequently used package for model training and prediction using machine learning. This package includes functions to improve spatial-temporal modelling tasks using 'caret'. It prepares data for Leave-Location-Out and Leave-Time-Out cross-validation which are target-oriented validation strategies for spatial-temporal models. To decrease overfitting and improve model performances, the package implements a forward feature selection that selects suitable predictor variables in view to their contribution to the target-oriented performance.
Author: Hanna Meyer [cre, aut], Chris Reudenbach [ctb], Marvin Ludwig [ctb], Thomas Nauss [ctb]
Maintainer: Hanna Meyer <hanna.meyer@geo.uni-marburg.de>

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Package clustvarsel updated to version 2.3.3 with previous version 2.3.2 dated 2018-04-09

Title: Variable Selection for Gaussian Model-Based Clustering
Description: Variable selection for Gaussian model-based clustering as implemented in the 'mclust' package. The methodology allows to find the (locally) optimal subset of variables in a data set that have group/cluster information. A greedy or headlong search can be used, either in a forward-backward or backward-forward direction, with or without sub-sampling at the hierarchical clustering stage for starting 'mclust' models. By default the algorithm uses a sequential search, but parallelisation is also available.
Author: Nema Dean [aut] (<https://orcid.org/0000-0002-5080-2517>), Adrian E. Raftery [aut], Luca Scrucca [aut, cre] (<https://orcid.org/0000-0003-3826-0484>)
Maintainer: Luca Scrucca <luca.scrucca@unipg.it>

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Package metacoder updated to version 0.3.0.1 with previous version 0.3.0 dated 2018-08-28

Title: Tools for Parsing, Manipulating, and Graphing Taxonomic Abundance Data
Description: A set of tools for parsing, manipulating, and graphing data classified by a hierarchy (e.g. a taxonomy).
Author: Zachary Foster [aut, cre], Niklaus Grunwald [ths], Rob Gilmore [ctb]
Maintainer: ORPHANED

Diff between metacoder versions 0.3.0 dated 2018-08-28 and 0.3.0.1 dated 2018-11-19

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Package colorSpec updated to version 0.7-5 with previous version 0.7-3 dated 2018-04-02

Title: Color Calculations with Emphasis on Spectral Data
Description: Calculate with spectral properties of light sources, materials, cameras, eyes, and scanners. Build complex systems from simpler parts using a spectral product algebra. For light sources, compute CCT and CRI. For object colors, compute optimal colors and Logvinenko coordinates. Work with the standard CIE illuminants and color matching functions, and read spectra from text files, including CGATS files. Estimate a spectrum from its response. A user guide and 8 vignettes are included.
Author: Glenn Davis [aut, cre]
Maintainer: Glenn Davis <gdavis@gluonics.com>

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Package secr updated to version 3.1.8 with previous version 3.1.7 dated 2018-10-04

Title: Spatially Explicit Capture-Recapture
Description: Functions to estimate the density and size of a spatially distributed animal population sampled with an array of passive detectors, such as traps, or by searching polygons or transects. Models incorporating distance-dependent detection are fitted by maximizing the likelihood. Tools are included for data manipulation and model selection.
Author: Murray Efford
Maintainer: Murray Efford <murray.efford@otago.ac.nz>

Diff between secr versions 3.1.7 dated 2018-10-04 and 3.1.8 dated 2018-11-19

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More information about secr at CRAN
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Package datarobot updated to version 2.10.0 with previous version 2.9.0 dated 2018-09-11

Title: 'DataRobot' Predictive Modeling API
Description: For working with the 'DataRobot' predictive modeling platform's API <https://www.datarobot.com/>.
Author: Ron Pearson [aut], Zachary Deane-Mayer [aut], David Chudzicki [aut], Dallin Akagi [aut], Sergey Yurgenson [aut], Thakur Raj Anand [aut], Peter Hurford [aut]
Maintainer: Peter Hurford <api-maintainer@datarobot.com>

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