Mon, 20 Jun 2016

Package tuber updated to version 0.2.1 with previous version 0.2 dated 2016-01-17

Title: Client for the YouTube API
Description: Get comments posted on YouTube videos, information on how many times a video has been liked, search for videos with particular content, and much more. You can also scrape captions from a few videos. To learn more about the YouTube API, see <https://developers.google.com/youtube/v3/>.
Author: Gaurav Sood [aut, cre]
Maintainer: Gaurav Sood <gsood07@gmail.com>

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Package mlma updated to version 4.0-0 with previous version 3.0-0 dated 2016-05-13

Title: Multilevel Mediation Analysis
Description: Do a multilevel mediation analysis with generalized additive multilevel models.
Author: Qingzhao Yu, Bin Li
Maintainer: Qingzhao Yu <qyu@lsuhsc.edu>

Diff between mlma versions 3.0-0 dated 2016-05-13 and 4.0-0 dated 2016-06-20

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Package janeaustenr updated to version 0.1.1 with previous version 0.1.0 dated 2016-04-15

Title: Jane Austen's Complete Novels
Description: Full texts for Jane Austen's 6 completed novels, ready for text analysis. These novels are "Sense and Sensibility", "Pride and Prejudice", "Mansfield Park", "Emma", "Northanger Abbey", and "Persuasion".
Author: Julia Silge [aut, cre]
Maintainer: Julia Silge <julia.silge@gmail.com>

Diff between janeaustenr versions 0.1.0 dated 2016-04-15 and 0.1.1 dated 2016-06-20

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Package clarifai updated to version 0.3.0 with previous version 0.2 dated 2015-12-11

Title: Access to Clarifai API
Description: Get description of images from Clarifai API. For more information, see http://clarifai.com. Clarifai uses a large deep learning cloud to come up with descriptive labels of the things in an image. It also provides how confident it is about each of the labels.
Author: Gaurav Sood [aut, cre]
Maintainer: Gaurav Sood <gsood07@gmail.com>

Diff between clarifai versions 0.2 dated 2015-12-11 and 0.3.0 dated 2016-06-20

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Package ssa updated to version 1.1.1 with previous version 1.1.0 dated 2016-02-20

Title: Simultaneous Signal Analysis
Description: Procedures for analyzing simultaneous signals, e.g., features that are simultaneously significant in two different studies. Includes methods for detecting simultaneous signals and for identifying them under false discovery rate control.
Author: Dave Zhao [aut, cre]
Maintainer: Dave Zhao <sdzhao@illinois.edu>

Diff between ssa versions 1.1.0 dated 2016-02-20 and 1.1.1 dated 2016-06-20

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Package metansue updated to version 1.1 with previous version 1.0 dated 2015-11-11

Title: Meta-Analysis of Studies with Non Statistically-Significant Unreported Effects
Description: A novel meta-analytic method that allows an unbiased inclusion of studies with Non Statistically-Significant Unreported Effects (NSUEs). Briefly, the method first calculates the interval where the unreported effects (e.g. t-values) should be according to the threshold of statistical significance used in each study. Afterwards, maximizing likelihood techniques are used to impute the expected effect size of each study with NSUEs, accounting for between-study heterogeneity and potential covariates. Multiple imputations of the NSUEs are then randomly created based on the expected value, variance and statistical significance bounds. Finally, a restricted-maximum likelihood random-effects meta-analysis is separately conducted for each set of imputations, and estimations from these meta-analyses are pooled. Please read the reference in 'meta.nsue' for details of the procedure.
Author: Joaquim Radua
Maintainer: Joaquim Radua <jradua@fidmag.com>

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New package RPtests with initial version 0.1.0
Package: RPtests
Type: Package
Title: Goodness of Fit Tests for High-Dimensional Linear Regression Models
Version: 0.1.0
Authors@R: c( person("Rajen", "Shah", email = "r.shah@statslab.cam.ac.uk", role = c("aut", "cre")), person("Peter", "Buhlmann", email="peter.buehlmann@stat.math.ethz.ch ", role="aut"))
Description: Performs goodness of fits tests for both high and low-dimensional linear models. It can test for a variety of model misspecifications including nonlinearity and heteroscedasticity. In addition one can test the significance of potentially large groups of variables, and also produce p-values for the significance of individual variables in high-dimensional linear regression.
License: GPL (>= 2)
Imports: glmnet, parallel, randomForest, Rcpp, stats
LinkingTo: Rcpp
URL: http://arxiv.org/abs/1511.03334
LazyData: TRUE
RoxygenNote: 5.0.1
NeedsCompilation: yes
Packaged: 2016-06-20 09:27:25 UTC; rds37
Author: Rajen Shah [aut, cre], Peter Buhlmann [aut]
Maintainer: Rajen Shah <r.shah@statslab.cam.ac.uk>
Repository: CRAN
Date/Publication: 2016-06-20 20:33:14

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Package meta updated to version 4.4-1 with previous version 4.4-0 dated 2016-05-13

Title: General Package for Meta-Analysis
Description: User-friendly general package providing standard methods for meta-analysis and supporting Schwarzer, Carpenter, and Rücker, "Meta-Analysis with R" (2015): - fixed effect and random effects meta-analysis; - several plots (forest, funnel, Galbraith / radial, L'Abbe, Baujat, bubble); - statistical tests and trim-and-fill method to evaluate bias in meta-analysis; - import data from 'RevMan 5'; - prediction interval, Hartung-Knapp and Paule-Mandel method for random effects model; - cumulative meta-analysis and leave-one-out meta-analysis; - meta-regression (if R package 'metafor' is installed); - generalised linear mixed models (if R packages 'metafor', 'lme4', 'numDeriv', and 'BiasedUrn' are installed).
Author: Guido Schwarzer [cre, aut]
Maintainer: Guido Schwarzer <sc@imbi.uni-freiburg.de>

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Package GWsignif updated to version 1.1 with previous version 1.0 dated 2014-01-15

Title: Estimating Genome-Wide Significance for Whole Genome Sequencing Studies, Either Single SNP Tests or Region-Based Tests
Description: The correlations and linkage disequilibrium between tests can vary as a function of minor allele frequency thresholds used to filter variants, and also varies with different choices of test statistic for region-based tests. Appropriate genome-wide significance thresholds can be estimated empirically through permutation on only a small proportion of the whole genome.
Author: ChangJiang Xu and Celia M.T. Greenwood
Maintainer: ChangJiang Xu <changjiang.h.xu@gmail.com>

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Package FDboost updated to version 0.2-0 with previous version 0.1-0 dated 2016-03-14

Title: Boosting Functional Regression Models
Description: Regression models for functional data, i.e., scalar-on-function, function-on-scalar and function-on-function regression models, are fitted by a component-wise gradient boosting algorithm.
Author: Sarah Brockhaus [aut, cre], David Ruegamer [aut], Torsten Hothorn [ctb], with contributions by many others (see inst/CONTRIBUTIONS) [ctb]
Maintainer: Sarah Brockhaus <Sarah.Brockhaus@stat.uni-muenchen.de>

Diff between FDboost versions 0.1-0 dated 2016-03-14 and 0.2-0 dated 2016-06-20

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New package DSsim with initial version 1.0.5
Package: DSsim
Depends: graphics, splancs, mrds, mgcv, shapefiles, methods
Suggests: testthat, parallel, knitr, rmarkdown
Type: Package
Title: Distance Sampling Simulations
Version: 1.0.5
Date: 2016-06-17
LazyLoad: yes
Author: Laura Marshall <lhm@st-and.ac.uk>
Maintainer: Laura Marshall <lhm@st-and.ac.uk>
Description: Performs distance sampling simulations. It repeatedly generates instances of a user defined population within a given survey region, generates realisations of a survey design (currently these must be pregenerated using Distance software <http://distancesampling.org/>) and simulates the detection process. The data are then analysed so that the results can be compared for accuracy and precision across all replications. This will allow users to select survey designs which will give them the best accuracy and precision given their expectations about population distribution. Any uncertainty in population distribution or population parameters can be included by running the different survey designs for a number of different population descriptions. An example simulation can be found in the help file for make.simulation.
License: GPL (>= 2)
Collate: 'DDF.Data.R' 'generic.functions.R' 'DDF.Analysis.R' 'DS.Analysis.R' 'Survey.Design.R' 'PT.Design.R' 'PT.Systematic.Design.R' 'PT.Random.Design.R' 'LT.Design.R' 'LT.User.Specified.Design.R' 'LT.EqSpace.ZZ.Design.R' 'LT.EqAngle.ZZ.Design.R' 'LT.Random.Design.R' 'LT.Systematic.Design.R' 'Density.R' 'Population.Description.R' 'Region.R' 'Region.Table.R' 'Sample.Table.R' 'Obs.Table.R' 'Single.Obs.DDF.Data.R' 'Transect.R' 'Line.Transect.R' 'Detectability.R' 'Population.R' 'LT.Survey.Results.R' 'Survey.Results.R' 'DSM.Analysis.R' 'Simulation.R' 'Class.Constructors.R' 'Design.Summary.R' 'Survey.R' 'LT.Survey.R' 'Point.Transect.R' 'PT.Survey.R' 'Population.Summary.R' 'Simulation.Summary.R' 'Single.Obs.LT.Survey.R' 'Single.Obs.PT.Survey.R' 'accumulate.PP.results.R' 'add.dist.error.R' 'add.summary.results.R' 'calc.area.R' 'calc.poss.detect.dists.lines.R' 'calc.poss.detect.dists.points.R' 'check.intersection.R' 'check.shapefile.R' 'coords.from.shapefile.R' 'create.bins.R' 'data.for.distance.R' 'description.summary.R' 'generate.pop.D.R' 'generate.pop.N.R' 'get.ave.density.R' 'get.bound.box.R' 'get.line.sampler.info.R' 'get.point.sampler.info.R' 'get.shapefile.names.R' 'get.surface.constant.R' 'get.surface.gam.R' 'hn.detect.R' 'hr.detect.R' 'in.polygons.R' 'is.gap.R' 'modify.strata.for.analysis.R' 'rename.duplicates.R' 'save.sim.results.R' 'simulate.detections.R' 'single.simulation.loop.R' 'store.ddf.results.R' 'store.dht.results.R' 'uf.detect.R'
RoxygenNote: 5.0.1
NeedsCompilation: no
Packaged: 2016-06-20 11:13:22 UTC; laura
Repository: CRAN
Date/Publication: 2016-06-20 20:25:41

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Package benchmarkmeData updated to version 0.3.0 with previous version 0.2.2 dated 2016-02-23

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

Diff between benchmarkmeData versions 0.2.2 dated 2016-02-23 and 0.3.0 dated 2016-06-20

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Package averisk updated to version 1.0.2 with previous version 1.0.1 dated 2016-01-14

Title: Calculation of Average Population Attributable Fractions and Confidence Intervals
Description: Average population attributable fractions are calculated for a set of risk factors (either binary or ordinal valued) for both prospective and case- control designs. Confidence intervals are found by Monte Carlo simulation. The method can be applied to either prospective or case control designs, provided an estimate of disease prevalence is provided. In addition to an exact calculation of AF, an approximate calculation, based on randomly sampling permutations has been implemented to ensure the calculation is computationally tractable when the number of risk factors is large.
Author: John Ferguson [aut, cre]
Maintainer: John Ferguson <john.ferguson@nuigalway.ie>

Diff between averisk versions 1.0.1 dated 2016-01-14 and 1.0.2 dated 2016-06-20

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Package xyloplot updated to version 1.3 with previous version 1.1 dated 2016-05-20

Title: A Method for Creating Xylophone-Like Frequency Density Plots
Description: A method for creating vertical histograms sharing a y-axis using base graphics.
Author: Daniel Greene
Maintainer: Daniel Greene <dg333@cam.ac.uk>

Diff between xyloplot versions 1.1 dated 2016-05-20 and 1.3 dated 2016-06-20

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Package withr updated to version 1.0.2 with previous version 1.0.1 dated 2016-02-04

Title: Run Code 'With' Temporarily Modified Global State
Description: A set of functions to run code 'with' safely and temporarily modified global state. Many of these functions were originally a part of the 'devtools' package, this provides a simple package with limited dependencies to provide access to these functions.
Author: Jim Hester [aut, cre], Kirill Müller [aut], Hadley Wickham [aut], Winston Chang [aut], RStudio [cph]
Maintainer: Jim Hester <james.f.hester@gmail.com>

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Package sjstats updated to version 0.2.0 with previous version 0.1.0 dated 2016-05-23

Title: Collection of Convenient Functions for Common Statistical Computations
Description: Collection of convenient functions for common statistical computations, which are not directly provided by R's base or stats packages. This package aims at providing, first, shortcuts for statistical measures, which otherwise could only be calculated with additional effort (like standard errors or root mean squared errors). Second, these shortcut functions are generic (if appropriate), and can be applied not only to vectors, but also to other objects as well (e.g., the Coefficient of Variation can be computed for vectors, linear models, or linear mixed models; the r2()-function returns the r-squared value for 'lm', 'glm', 'merMod' or 'lme' objects). The focus of most functions lies on summary statistics or fit measures for regression models, including generalized linear models and mixed effects models. However, some of the functions also deal with other statistical measures, like Cronbach's Alpha, Cramer's V, Phi etc.
Author: Daniel Lüdecke <d.luedecke@uke.de>
Maintainer: Daniel Lüdecke <d.luedecke@uke.de>

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Package quanteda updated to version 0.9.7-16 with previous version 0.9.6-9 dated 2016-05-20

Title: Quantitative Analysis of Textual Data
Description: A fast, flexible toolset for for the management, processing, and quantitative analysis of textual data in R.
Author: Kenneth Benoit [aut, cre], Paul Nulty [aut], Kohei Watanabe [ctb], Benjamin Lauderdale [ctb], Adam Obeng [ctb], Pablo Barberá [ctb]
Maintainer: Kenneth Benoit <kbenoit@lse.ac.uk>

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Package npbr updated to version 1.3 with previous version 1.2 dated 2015-07-13

Title: Nonparametric Boundary Regression
Description: A variety of functions for the best known and most innovative approaches to nonparametric boundary estimation. The selected methods are concerned with empirical, smoothed, unrestricted as well as constrained fits under both separate and multiple shape constraints. They cover robust approaches to outliers as well as data envelopment techniques based on piecewise polynomials, splines, local linear fitting, extreme values and kernel smoothing. The package also seamlessly allows for Monte Carlo comparisons among these different estimation methods. Its use is illustrated via a number of empirical applications and simulated examples.
Author: Abdelaati Daouia <Abdelaati.Daouia@tse-fr.eu>, Thibault Laurent <thibault.laurent@univ-tlse1.fr>, Hohsuk Noh <word5810@gmail.com>
Maintainer: Thibault Laurent <thibault.laurent@univ-tlse1.fr>

Diff between npbr versions 1.2 dated 2015-07-13 and 1.3 dated 2016-06-20

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Package dlsem updated to version 1.2.0 with previous version 1.0.3 dated 2016-06-13

Title: Distributed-Lag Structural Equation Modelling
Description: Estimation and path analysis functionalities for structural equation models with polynomial lag shapes.
Author: Alessandro Magrini
Maintainer: Alessandro Magrini <magrini@disia.unifi.it>

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Package bibliometrix updated to version 0.8 with previous version 0.5 dated 2016-05-30

Title: Bibliometric and Co-Citation Analysis Tool
Description: Tool for quantitative research in scientometrics and bibliometrics. It provides various routines for importing bibliographic data from SCOPUS and Thomson Reuters' ISI Web of Knowledge databases, performing bibliometric analysis and building data matrices for co-citation, coupling and scientific collaboration analysis.
Author: Massimo Aria [cre, aut], Corrado Cuccurullo [aut]
Maintainer: Massimo Aria <aria@unina.it>

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Package abbyyR updated to version 0.5.0 with previous version 0.4.0 dated 2016-05-16

Title: Access to Abbyy Optical Character Recognition (OCR) API
Description: Get text from images of text using Abbyy Cloud Optical Character Recognition (OCR) API. Easily OCR images, barcodes, forms, documents with machine readable zones, e.g. passports. Get the results in a variety of formats including plain text and XML. To learn more about the Abbyy OCR API, see http:// ocrsdk.com/.
Author: Gaurav Sood [aut, cre]
Maintainer: Gaurav Sood <gsood07@gmail.com>

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Package powerCRT (with last version 0.1.0) was removed from CRAN

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

2016-06-16 0.1.0

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Package mscstexta4r updated to version 0.1.1 with previous version 0.1.0 dated 2016-06-14

Title: R Client for the Microsoft Cognitive Services Text Analytics REST API
Description: R Client for the Microsoft Cognitive Services Text Analytics REST API, including Sentiment Analysis, Topic Detection, Language Detection, and Key Phrase Extraction. An 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: Phil Ferriere [aut, cre]
Maintainer: Phil Ferriere <pferriere@hotmail.com>

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Package visNetwork updated to version 1.0.1 with previous version 1.0.0 dated 2016-05-03

Title: Network Visualization using 'vis.js' Library
Description: Provides an R interface to the 'vis.js' JavaScript charting library. It allows an interactive visualization of networks.
Author: Almende B.V. [aut, cph] (vis.js library in htmlwidgets/lib, http://visjs.org, http://www.almende.com/home), Benoit Thieurmel [aut, cre] (R interface)
Maintainer: Benoit Thieurmel <benoit.thieurmel@datastorm.fr>

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 visNetwork-1.0.1/visNetwork/man/visNetwork-shiny.Rd                      |    2 
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Package smbinning updated to version 0.3 with previous version 0.2 dated 2015-06-13

Title: Optimal Binning for Scoring Modeling
Description: The main purpose of the package is to categorize a numeric variable into bins mapped to a binary target variable for its ulterior usage in scoring modeling. This functionality reduces dramatically the time consuming process of finding the optimal cut points for a given numeric variable, quickly calculates the Information Value, either for one variable at the time or all at once in one line of code; and also outputs 'SQL' codes, tables, and plots used throughout the development stage. The package also allows the user to understand the data via exploratory data analysis in one step, establish customized cut points for numeric characteristics, and run the analysis for categorical variables.
Author: Herman Jopia
Maintainer: Herman Jopia <hjopia@gmail.com>

Diff between smbinning versions 0.2 dated 2015-06-13 and 0.3 dated 2016-06-20

 DESCRIPTION                 |   19 +
 MD5                         |   26 +-
 NAMESPACE                   |    3 
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New package OneR with initial version 1.2
Package: OneR
Type: Package
Title: Machine Learning Classification Algorithm with Enhancements
Version: 1.2
Date: 2016-06-20
Author: Holger von Jouanne-Diedrich
Maintainer: Holger von Jouanne-Diedrich <holger.jouanne-diedrich@h-ab.de>
Description: Implements the One Rule (OneR) Machine Learning classification algorithm with enhancements for sophisticated handling of missing values and numeric data together with extensive diagnostic functions. It is useful as a baseline for machine learning models and the rules are often helpful heuristics.
License: MIT + file LICENSE
URL: http://vonjd.github.io/OneR/
BugReports: http://github.com/vonjd/OneR/issues
LazyData: TRUE
RoxygenNote: 5.0.1
NeedsCompilation: no
Packaged: 2016-06-20 07:39:29 UTC; Holger
Repository: CRAN
Date/Publication: 2016-06-20 10:20:33

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Package units updated to version 0.2 with previous version 0.1 dated 2016-06-13

Title: Measurement Units of Physical Quantities for R Vectors
Description: Support for measurement units of physical quantities in R vectors, based on the udunits library from unidata.
Author: Edzer Pebesma [aut, cre]
Maintainer: Edzer Pebesma <edzer.pebesma@uni-muenster.de>

Diff between units versions 0.1 dated 2016-06-13 and 0.2 dated 2016-06-20

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 11 files changed, 145 insertions(+), 59 deletions(-)

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New package TTCA with initial version 0.1.0
Package: TTCA
Type: Package
Title: Transcript Time Course Analysis
Version: 0.1.0
Date: 2016-06-16
Author: Marco Albrecht
Maintainer: Marco Albrecht <marco.albrecht@posteo.de>
Description: The analysis of microarray time series promises a deeper insight into the dynamics of the cellular response following stimulation. A common observation in this type of data is that some genes respond with quick, transient dynamics, while other genes change their expression slowly over time. The existing methods for the detection of significant expression dynamics often fail when the expression dynamics show a large heterogeneity, and often cannot cope with irregular and sparse measurements. The method proposed here is specifically designed for the analysis of perturbation responses. It combines different scores to capture fast and transient dynamics as well as slow expression changes, and deals with low replicate numbers and irregular sampling times. The results are given in the form of tables linked to figures. These allow to quickly recognize the relevance of detection, to identify possible false positives and to distinguish between changes in the early and later expression. An extension of the method allows the analysis of the expression dynamics of functional groups of genes, providing a quick overview of the cellular response. The performance of this package was tested on microarray data derived from lung cancer cells stimulated with epidermal growth factor. See publication "TTCA: An R package for the identification of differentially expressed genes in time course microarray data".
LazyData: TRUE
License: EUPL
Depends: R(>= 2.10)
Imports: Matrix, quantreg, tcltk2, RISmed, VennDiagram, MASS
RoxygenNote: 5.0.1
NeedsCompilation: no
Packaged: 2016-06-20 05:57:09 UTC; Marco
Repository: CRAN
Date/Publication: 2016-06-20 08:19:10

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Package squid updated to version 0.1.1 with previous version 0.1.0 dated 2016-06-01

Title: Statistical Quantification of Individual Differences
Description: A simulation-based tool made to help researchers to become familiar with multilevel variations, and to build up sampling designs for their study. This tool has two main objectives: First, it provides an educational tool useful for students, teachers and researchers who want to learn to use mixed-effects models. Users can experience how the mixed-effects model framework can be used to understand distinct biological phenomena by interactively exploring simulated multilevel data. Second, it offers research opportunities to those who are already familiar with mixed-effects models, as it enables the generation of data sets that users may download and use for a range of simulation-based statistical analyses such as power and sensitivity analysis of multilevel and multivariate data.
Author: Hassen Allegue [aut, cre], Yimen G. Araya-Ajoy [aut], Niels J. Dingemanse [aut], Ned A. Dochtermann [aut], Laszlo Z. Garamszegi [aut], Shinichi Nakagawa [aut], Denis Reale [aut], Holger Schielzeth [aut], David F. Westneat [aut]
Maintainer: Hassen Allegue <hassen.allegue@gmail.com>

Diff between squid versions 0.1.0 dated 2016-06-01 and 0.1.1 dated 2016-06-20

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 MD5                                                    |   14 
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 README.md                                              |   20 -
 inst/shiny-squid/source/text/portal/TXTportal.R        |   16 -
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New package ROI.plugin.ipop with initial version 0.2-1
Package: ROI.plugin.ipop
Version: 0.2-1
Date: 2016-06-18
Title: ROI Plug-in {ipop}
Authors@R: c( person("Florian", "Schwendinger", role = "ctb"), person("Stefan", "Theussl", role = c("aut", "cre"), email = "Stefan.Theussl@R-Project.org"), person("Diethelm", "Wuertz", role = "ctb") )
Description: Enhances the R Optimization Infrastructure ('ROI') package by registering the ipop solver from package 'kernlab'.
Imports: methods, ROI (>= 0.2-1), kernlab, slam
License: GPL-3
URL: http://R-Forge.R-project.org/projects/roi
NeedsCompilation: no
Packaged: 2016-06-19 20:46:26 UTC; theussl
Author: Florian Schwendinger [ctb], Stefan Theussl [aut, cre], Diethelm Wuertz [ctb]
Maintainer: Stefan Theussl <Stefan.Theussl@R-Project.org>
Repository: CRAN
Date/Publication: 2016-06-20 07:55:12

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Package rebmix updated to version 2.8.2 with previous version 2.8.1 dated 2016-03-27

Title: Finite Mixture Modeling, Clustering & Classification
Description: R functions for random univariate and multivariate finite mixture model generation, estimation, clustering and classification. Variables can be continuous, discrete, independent or dependent and may follow normal, lognormal, Weibull, gamma, binomial, Poisson or Dirac parametric families.
Author: Marko Nagode [aut, cre]
Maintainer: Marko Nagode <marko.nagode@fs.uni-lj.si>

Diff between rebmix versions 2.8.1 dated 2016-03-27 and 2.8.2 dated 2016-06-20

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Package networkreporting updated to version 0.1.1 with previous version 0.1.0 dated 2016-05-04

Title: Tools for using Network Reporting Estimators
Description: Functions useful for producing estimates from data that were collected using network reporting techniques like network scale-up, indirect sampling, network reporting, and sibling history.
Author: Dennis M. Feehan [aut, cre], Matthew J. Salganik [ths]
Maintainer: Dennis M. Feehan <feehan@berkeley.edu>

Diff between networkreporting versions 0.1.0 dated 2016-05-04 and 0.1.1 dated 2016-06-20

 DESCRIPTION                      |    6 +++---
 MD5                              |    8 ++++----
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 tests/testthat/test_estimators.R |    3 ++-
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New package IMPACT with initial version 0.1.0
Package: IMPACT
Version: 0.1.0
Date: 2016-06-12
Title: The Impact of Items
Author: Nery Sofia Huerta-Pacheco
Maintainer: Nery Sofia Huerta-Pacheco <nehuerta@uv.mx>
Depends: R(>= 3.1.0)
Description: Implement a multivariate analysis of the impact of items to identify a bias in the questionnaire validation of Likert-type scale variables. The items requires considering a null value (category doesn't have tendency). Offering frequency, importance and impact of the items.
License: GPL (>= 2)
URL: http://www.uv.mx/personal/nehuerta/impact
Encoding: UTF-8
NeedsCompilation: no
RoxygenNote: 5.0.1
Packaged: 2016-06-19 19:08:22 UTC; piahuerta
Repository: CRAN
Date/Publication: 2016-06-20 07:55:09

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Package futureheatwaves updated to version 1.0.1 with previous version 1.0.0 dated 2016-03-24

Title: Find, Characterize, and Explore Heat Waves in Climate Projections
Description: Inputs a directory of climate projection files and, for each, identifies and characterizes heat waves for specified study locations. The definition used to identify heat waves can be customized. Heat wave characterizations include several metrics of heat wave length, intensity, and timing in the year. The heat waves that are identified can be explored using a function to apply user-created functions across all generated heat wave files.This work was supported in part by grants from the National Institute of Environmental Health Sciences (R00ES022631), the National Science Foundation (1331399), and the Colorado State University Vice President for Research.
Author: Brooke Anderson [aut, cre], Colin Eason [aut], Elizabeth Barnes [aut]
Maintainer: Brooke Anderson <brooke.anderson@colostate.edu>

Diff between futureheatwaves versions 1.0.0 dated 2016-03-24 and 1.0.1 dated 2016-06-20

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Package Directional updated to version 2.1 with previous version 2.0 dated 2016-05-25

Title: Directional Statistics
Description: A collection of R functions for directional data analysis.
Author: Michail Tsagris, Giorgos Athineou, Anamul Sajib
Maintainer: Michail Tsagris <mtsagris@yahoo.gr>

Diff between Directional versions 2.0 dated 2016-05-25 and 2.1 dated 2016-06-20

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Package clusrank updated to version 0.2-2 with previous version 0.2-0 dated 2016-06-13

Title: Wilcoxon Rank Sum Test for Clustered Data
Description: Non-parametric tests (Wilcoxon rank sum test and Wilcoxon signed rank test) for clustered data.
Author: Yujing Jiang [aut, cre], Mei-Ling Ting Lee [ctb], Jun Yan [ctb]
Maintainer: Yujing Jiang <yujing.jiang@uconn.edu>

Diff between clusrank versions 0.2-0 dated 2016-06-13 and 0.2-2 dated 2016-06-20

 DESCRIPTION     |    6 +++---
 MD5             |    6 +++---
 R/clusranksum.R |    2 +-
 src/exact.cpp   |    5 +++--
 4 files changed, 10 insertions(+), 9 deletions(-)

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New package as.color with initial version 0.1
Package: as.color
Title: Assign Random Colors to Unique Items in a Vector
Version: 0.1
Authors@R: person("Silas", "Tittes", email = "silas.tittes@gmail.com", role = c("aut", "cre"))
Author: Silas Tittes [aut, cre]
Maintainer: Silas Tittes <silas.tittes@gmail.com>
Description: The as.color function takes an R vector of any class as an input, and outputs a vector of unique hexadecimal color values that correspond to the unique input values. This is most handy when overlaying points and lines for data that correspond to different levels or factors. The function will also print the random seed used to generate the colors. If you like the color palette generated, you can save the seed and reuse those colors.
Depends: R (>= 3.2.4)
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 5.0.1
NeedsCompilation: no
Packaged: 2016-06-19 17:03:00 UTC; silastittes
Repository: CRAN
Date/Publication: 2016-06-20 07:55:10

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