Tue, 09 Jul 2019

Package burnr updated to version 0.4.0 with previous version 0.3.1 dated 2019-03-08

Title: Fire-History Analysis in R
Description: Basic tools to analyze forest fire history data (e.g. FHX) in R.
Author: Steven Malevich [aut, cre], Christopher Guiterman [ctb], Ellis Margolis [ctb]
Maintainer: Steven Malevich <malevich@email.arizona.edu>

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Package svgViewR updated to version 1.4 with previous version 1.3 dated 2018-01-20

Title: 3D Animated Interactive Visualizations Using SVG
Description: Creates 3D animated, interactive visualizations that can be viewed in a web browser.
Author: Aaron Olsen, Alejandro Romero
Maintainer: Aaron Olsen <aarolsen@gmail.com>

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Package ezplot updated to version 0.3.0 with previous version 0.2.2 dated 2019-01-30

Title: Functions for Common Chart Types
Description: Wrapper for the 'ggplot2' package that creates a variety of common charts (e.g. bar, line, area, ROC, waterfall, pie) while aiming to reduce typing.
Author: Wojtek Kostelecki
Maintainer: Wojtek Kostelecki <wojtek.kostelecki@gmail.com>

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Package coala updated to version 0.5.3 with previous version 0.5.2 dated 2017-10-30

Title: A Framework for Coalescent Simulation
Description: Coalescent simulators can rapidly simulate biological sequences evolving according to a given model of evolution. You can use this package to specify such models, to conduct the simulations and to calculate additional statistics from the results. It relies on existing simulators for doing the simulation, and currently supports the programs 'ms', 'msms' and 'scrm'. It also supports finite-sites mutation models by combining the simulators with the program 'seq-gen'.
Author: Paul Staab [aut, cre], Dirk Metzler [aut, ths], Jorge E. Amaya Romero [ctb]
Maintainer: Paul Staab <develop@paulstaab.de>

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Package rscala updated to version 3.2.15 with previous version 3.2.14 dated 2019-07-02

Title: Bridge Between 'R' and 'Scala' with Callbacks
Description: 'Scala' <http://www.scala-lang.org/> is embedded in 'R' and callbacks from 'Scala' to 'R' are available. Support is provided to write 'R' packages that access 'Scala'. After installation, please run 'rscala::scalaConfig()'.
Author: David B. Dahl [aut, cre]
Maintainer: David B. Dahl <dahl@stat.byu.edu>

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Package MKmisc updated to version 1.5 with previous version 1.4 dated 2019-05-21

Title: Miscellaneous Functions from M. Kohl
Description: Contains several functions for statistical data analysis; e.g. for sample size and power calculations, computation of confidence intervals and tests, and generation of similarity matrices.
Author: Matthias Kohl [aut, cre] (<https://orcid.org/0000-0001-9514-8910>)
Maintainer: Matthias Kohl <Matthias.Kohl@stamats.de>

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Package fastGraph updated to version 2.0 with previous version 1.3 dated 2019-06-24

Title: Fast Drawing and Shading of Graphs of Statistical Distributions
Description: Provides functionality to produce graphs of probability density functions and cumulative distribution functions with few keystrokes, allows shading under the curve of the probability density function to illustrate concepts such as p-values and critical values, and fits a simple linear regression line on a scatter plot with the equation as the main title.
Author: Steven T. Garren
Maintainer: Steven T. Garren <garrenst@jmu.edu>

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Package VWPre updated to version 1.2.0 with previous version 1.1.0 dated 2018-03-20

Title: Tools for Preprocessing Visual World Data
Description: Gaze data from the Visual World Paradigm requires significant preprocessing prior to plotting and analyzing the data. This package provides functions for preparing visual world eye-tracking data for statistical analysis and plotting. It can prepare data for linear analyses (e.g., ANOVA, Gaussian-family LMER, Gaussian-family GAMM) as well as logistic analyses (e.g., binomial-family LMER and binomial-family GAMM). Additionally, it contains various plotting functions for creating grand average and conditional average plots. See the vignette for samples of the functionality. Currently, the functions in this package are designed for handling data collected with SR Research Eyelink eye trackers using Sample Reports created in SR Research Data Viewer. While we would like to add functionality for data collected with other systems in the future, the current package is considered to be feature-complete; further updates will mainly entail maintenance and the addition of minor functionality.
Author: Vincent Porretta [aut, cre], Aki-Juhani Kyröläinen [aut], Jacolien van Rij [ctb], Juhani Järvikivi [ctb]
Maintainer: Vincent Porretta <vincentporretta@gmail.com>

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Package shinyAce updated to version 0.4.0 with previous version 0.3.3 dated 2019-01-03

Title: Ace Editor Bindings for Shiny
Description: Ace editor bindings to enable a rich text editing environment within Shiny.
Author: Vincent Nijs [aut, cre], Forest Fang [aut], Trestle Technology, LLC [aut], Jeff Allen [aut], Institut de Radioprotection et de Surete Nucleaire [cph], Ajax.org B.V. [ctb, cph] (Ace)
Maintainer: Vincent Nijs <radiant@rady.ucsd.edu>

Diff between shinyAce versions 0.3.3 dated 2019-01-03 and 0.4.0 dated 2019-07-09

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Package jmuOutlier updated to version 2.0 with previous version 1.5 dated 2019-06-24

Title: Permutation Tests for Nonparametric Statistics
Description: Performs a permutation test on the difference between two location parameters, a permutation correlation test, a permutation F-test, the Siegel-Tukey test, a ratio mean deviance test. Also performs some graphing techniques, such as for confidence intervals, vector addition, and Fourier analysis; and includes functions related to the Laplace (double exponential) and triangular distributions. Performs power calculations for the binomial test.
Author: Steven T. Garren
Maintainer: Steven T. Garren <GARRENST@JMU.EDU>

Diff between jmuOutlier versions 1.5 dated 2019-06-24 and 2.0 dated 2019-07-09

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New package ulid with initial version 0.3.0
Package: ulid
Type: Package
Title: Generate Universally Unique Lexicographically Sortable Identifiers
Version: 0.3.0
Date: 2019-07-04
Authors@R: c( person("Bob", "Rudis", email = "bob@rud.is", role = c("aut", "cre"), comment = c(ORCID = "0000-0001-5670-2640")), person("suyash", role = c("aut"), comment = "ULID C++ Port <https://github.com/suyash/ulid/>") )
Maintainer: Bob Rudis <bob@rud.is>
Description: Universally unique identifiers ('UUIDs') can be suboptimal for many uses-cases because they aren't the most character efficient way of encoding 128 bits of randomness; v1/v2 versions are impractical in many environments, as they require access to a unique, stable MAC address; v3/v5 versions require a unique seed and produce randomly distributed IDs, which can cause fragmentation in many data structures; v4 provides no other information than randomness which can cause fragmentation in many data structures. 'ULIDs' (<https://github.com/ulid/spec>) have 128-bit compatibility with 'UUID', 1.21e+24 unique 'ULIDs' per millisecond, are lexicographically sortable, canonically encoded as a 26 character string, as opposed to the 36 character 'UUID', use Crockford's 'base32' for better efficiency and readability (5 bits per character), are case insensitive, have no special characters (i.e. are 'URL' safe) and have a onotonic sort order (correctly detects and handles the same millisecond).
URL: https://gitlab.com/hrbrmstr/ulid
BugReports: https://gitlab.com/hrbrmstr/ulid/issues
SystemRequirements: C++11
NeedsCompilation: yes
Encoding: UTF-8
License: MIT + file LICENSE
Suggests: covr, tinytest, knitr, rmarkdown
Depends: R (>= 3.2.0)
Imports: Rcpp
RoxygenNote: 6.1.1
LinkingTo: Rcpp
VignetteBuilder: knitr
Packaged: 2019-07-05 19:49:06 UTC; hrbrmstr
Author: Bob Rudis [aut, cre] (<https://orcid.org/0000-0001-5670-2640>), suyash [aut] (ULID C++ Port <https://github.com/suyash/ulid/>)
Repository: CRAN
Date/Publication: 2019-07-09 16:00:02 UTC

More information about ulid at CRAN
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Package rjmcmc updated to version 0.4.5 with previous version 0.4.4 dated 2019-03-02

Title: Reversible-Jump MCMC Using Post-Processing
Description: Performs reversible-jump Markov chain Monte Carlo (Green, 1995) <doi:10.2307/2337340>, specifically the restriction introduced by Barker & Link (2013) <doi:10.1080/00031305.2013.791644>. By utilising a 'universal parameter' space, RJMCMC is treated as a Gibbs sampling problem. Previously-calculated posterior distributions are used to quickly estimate posterior model probabilities. Jacobian matrices are found using automatic differentiation. For a detailed description of the package, see Gelling, Schofield & Barker (2019) <doi:10.1111/anzs.12263>.
Author: Nick Gelling [aut, cre], Matthew R. Schofield [aut], Richard J. Barker [aut]
Maintainer: Nick Gelling <nickcjgelling@gmail.com>

Diff between rjmcmc versions 0.4.4 dated 2019-03-02 and 0.4.5 dated 2019-07-09

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Package mboxr updated to version 0.1.6 with previous version 0.1.5 dated 2019-04-21

Title: Reading, Extracting, and Converting an Mbox File into a Tibble
Description: Importing and converting an mbox file into a tibble object.
Author: JooYoung Seo [aut, cre] (<https://orcid.org/0000-0002-4064-6012>), Soyoung Choi [aut] (<https://orcid.org/0000-0002-0998-3352>)
Maintainer: JooYoung Seo <jooyoung@psu.edu>

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Package matrixTests updated to version 0.1.5 with previous version 0.1.4 dated 2019-06-25

Title: Fast Statistical Hypothesis Tests on Rows and Columns of Matrices
Description: Functions to perform fast statistical hypothesis tests on rows/columns of matrices. The main goals are: 1) speed via vectorization, 2) output that is detailed and easy to use, 3) compatibility with tests implemented in R (like those available in the 'stats' package).
Author: Karolis Koncevičius [aut, cre]
Maintainer: Karolis Koncevičius <karolis.koncevicius@gmail.com>

Diff between matrixTests versions 0.1.4 dated 2019-06-25 and 0.1.5 dated 2019-07-09

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Package GpGp updated to version 0.2.1 with previous version 0.2.0 dated 2019-06-29

Title: Fast Gaussian Process Computation Using Vecchia's Approximation
Description: Functions for fitting and doing predictions with Gaussian process models using Vecchia's (1988) approximation. Package also includes functions for reordering input locations, finding ordered nearest neighbors (with help from 'FNN' package), grouping operations, and conditional simulations. Covariance functions for spatial and spatial-temporal data on Euclidean domains and spheres are provided. The original approximation is due to Vecchia (1988) <http://www.jstor.org/stable/2345768>, and the reordering and grouping methods are from Guinness (2018) <doi:10.1080/00401706.2018.1437476>. Model fitting employs a Fisher scoring algorithm described in Guinness (2019) <arXiv:1905.08374>.
Author: Joseph Guinness [aut, cre], Matthias Katzfuss [aut]
Maintainer: Joseph Guinness <joeguinness@gmail.com>

Diff between GpGp versions 0.2.0 dated 2019-06-29 and 0.2.1 dated 2019-07-09

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Package bamdit updated to version 3.3.2 with previous version 3.2.1 dated 2018-09-17

Title: Bayesian Meta-Analysis of Diagnostic Test Data
Description: Functions for Bayesian meta-analysis of diagnostic test data which are based on a scale mixtures bivariate random-effects model.
Author: Pablo Emilio Verde [aut, cre]
Maintainer: Pablo Emilio Verde <pabloemilio.verde@hhu.de>

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New package babelwhale with initial version 1.0.0
Package: babelwhale
Version: 1.0.0
Title: Talking to 'Docker' and 'Singularity' Containers
Description: Provides a unified interface to interact with 'docker' and 'singularity' containers. You can execute a command inside a container, mount a volume or copy a file.
Authors@R: c( person( "Robrecht", "Cannoodt", email = "rcannood@gmail.com", role = c("aut"), comment = c(ORCID = "0000-0003-3641-729X", github = "rcannood") ), person( "Wouter", "Saelens", email = "wouter.saelens@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-7114-6248", github = "zouter") ) )
URL: https://github.com/dynverse/babelwhale
BugReports: https://github.com/dynverse/babelwhale/issues
License: GPL-3
Depends: R (>= 3.0.0)
Imports: crayon, dplyr, dynutils, processx, purrr, utils
SystemRequirements: Docker and/or Singularity (>=3.0)
Encoding: UTF-8
LazyData: true
ByteCompile: true
RoxygenNote: 6.1.1
Suggests: testthat
NeedsCompilation: no
Packaged: 2019-07-05 07:07:27 UTC; rcannood
Author: Robrecht Cannoodt [aut] (<https://orcid.org/0000-0003-3641-729X>, rcannood), Wouter Saelens [aut, cre] (<https://orcid.org/0000-0002-7114-6248>, zouter)
Maintainer: Wouter Saelens <wouter.saelens@gmail.com>
Repository: CRAN
Date/Publication: 2019-07-09 14:50:04 UTC

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Package matrixNormal updated to version 0.0.1 with previous version 0.0.0 dated 2018-10-30

Title: The Matrix Normal Distribution
Description: Computes densities, probabilities, and random deviates of the Matrix Normal (Iranmanesh et al. (2010) <doi:10.7508/ijmsi.2010.02.004>). Also includes simple but useful matrix functions. See the vignette for more information.
Author: Paul Hargarten [aut, cre]
Maintainer: Paul Hargarten <hargartenp@vcu.edu>

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Package electionsBR updated to version 0.3.1 with previous version 0.3.0 dated 2017-06-06

Title: R Functions to Download and Clean Brazilian Electoral Data
Description: Offers a set of functions to easily download and clean Brazilian electoral data from the Superior Electoral Court website. Among others, the package retrieves data on local and federal elections for all positions (city councilor, mayor, state deputy, federal deputy, governor, and president) aggregated by state, city, and electoral zones.
Author: Denisson Silva [aut, cre], Fernando Meireles [aut], Beatriz Costa [ctb]
Maintainer: Denisson Silva <denissoncsol@gmail.com>

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Package srvyr updated to version 0.3.5 with previous version 0.3.4 dated 2019-01-20

Title: 'dplyr'-Like Syntax for Summary Statistics of Survey Data
Description: Use piping, verbs like 'group_by' and 'summarize', and other 'dplyr' inspired syntactic style when calculating summary statistics on survey data using functions from the 'survey' package.
Author: Greg Freedman Ellis [aut, cre], Thomas Lumley [ctb], Tomasz Żółtak [ctb], Ben Schneider [ctb]
Maintainer: Greg Freedman Ellis <greg.freedman@gmail.com>

Diff between srvyr versions 0.3.4 dated 2019-01-20 and 0.3.5 dated 2019-07-09

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Package rstan updated to version 2.19.2 with previous version 2.18.2 dated 2018-11-07

Title: R Interface to Stan
Description: User-facing R functions are provided to parse, compile, test, estimate, and analyze Stan models by accessing the header-only Stan library provided by the 'StanHeaders' package. The Stan project develops a probabilistic programming language that implements full Bayesian statistical inference via Markov Chain Monte Carlo, rough Bayesian inference via 'variational' approximation, and (optionally penalized) maximum likelihood estimation via optimization. In all three cases, automatic differentiation is used to quickly and accurately evaluate gradients without burdening the user with the need to derive the partial derivatives.
Author: Jiqiang Guo [aut], Jonah Gabry [aut], Ben Goodrich [cre, aut], Daniel Lee [ctb], Krzysztof Sakrejda [ctb], Modrak Martin [ctb], Trustees of Columbia University [cph], Oleg Sklyar [cph] (R/cxxfunplus.R), The R Core Team [cph] (R/pairs.R, R/dynGet.R), Jens Oehlschlaegel-Akiyoshi [cph] (R/pairs.R)
Maintainer: Ben Goodrich <benjamin.goodrich@columbia.edu>

Diff between rstan versions 2.18.2 dated 2018-11-07 and 2.19.2 dated 2019-07-09

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Package micemd updated to version 1.6.0 with previous version 1.5.0 dated 2018-11-21

Title: Multiple Imputation by Chained Equations with Multilevel Data
Description: Addons for the 'mice' package to perform multiple imputation using chained equations with two-level data. Includes imputation methods dedicated to sporadically and systematically missing values. Imputation of continuous, binary or count variables are available. Following the recommendations of Audigier, V. et al (2018) <doi:10.1214/18-STS646>, the choice of the imputation method for each variable can be facilitated by a default choice tuned according to the structure of the incomplete dataset. Allows parallel calculation and overimputation for 'mice'.
Author: Vincent Audigier [aut, cre] (CNAM MSDMA team), Matthieu Resche-Rigon [aut] (INSERM ECSTRA team)
Maintainer: Vincent Audigier <vincent.audigier@cnam.fr>

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Package AzureGraph updated to version 1.0.3 with previous version 1.0.2 dated 2019-06-05

Title: Simple Interface to 'Microsoft Graph'
Description: A simple interface to the 'Microsoft Graph' API <https://docs.microsoft.com/en-us/graph/overview>. 'Graph' is a comprehensive framework for accessing data in various online Microsoft services. Currently, this package aims to provide an R interface only to the 'Azure Active Directory' part, with a view to supporting interoperability of R and 'Azure': users, groups, registered apps and service principals. However it can be easily extended to cover other services. Part of the 'AzureR' family of packages.
Author: Hong Ooi [aut, cre], Microsoft [cph]
Maintainer: Hong Ooi <hongooi@microsoft.com>

Diff between AzureGraph versions 1.0.2 dated 2019-06-05 and 1.0.3 dated 2019-07-09

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Package tsiR updated to version 0.4.2 with previous version 0.4.1 dated 2019-01-29

Title: An Implementation of the TSIR Model
Description: An implementation of the time-series Susceptible-Infected-Recovered (TSIR) model using a number of different fitting options for infectious disease time series data. The manuscript based on this package can be found here <https://doi:10.1371/0185528>. The method implemented here is described by Finkenstadt and Grenfell (2000) <DOI: 10.1111/1467-9876.00187>.
Author: Alexander D. Becker [aut, cre], Sinead E. Morris [ctb], Ottar N. Bjornstad [ctb]
Maintainer: Alexander D. Becker <adbecker@princeton.edu>

Diff between tsiR versions 0.4.1 dated 2019-01-29 and 0.4.2 dated 2019-07-09

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Package reproducible updated to version 0.2.9 with previous version 0.2.8 dated 2019-03-18

Title: A Set of Tools that Enhance Reproducibility Beyond Package Management
Description: Collection of high-level, robust, machine- and OS-independent tools for making deeply reproducible and reusable content in R. This includes light weight package management (similar to 'packrat' and 'checkpoint', but more flexible, lightweight, simpler and less tested than both), tools for caching, downloading and verifying or writing checksums, post-processing of common spatial datasets, and accessing GitHub repositories. Some features are still under active development.
Author: Eliot J B McIntire [aut, cre] (<https://orcid.org/0000-0002-6914-8316>), Alex M Chubaty [aut] (<https://orcid.org/0000-0001-7146-8135>), Tati Micheletti [ctb] (<https://orcid.org/0000-0003-4838-8342>), Ceres Barros [ctb] (<https://orcid.org/0000-0003-4036-977X>), Ian Eddy [ctb] (<https://orcid.org/0000-0001-7397-2116>), Her Majesty the Queen in Right of Canada, as represented by the Minister of Natural Resources Canada [cph]
Maintainer: Eliot J B McIntire <eliot.mcintire@canada.ca>

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Package rehh updated to version 3.0.0 with previous version 2.0.4 dated 2019-02-13

Title: Searching for Footprints of Selection using 'Extended Haplotype Homozygosity' Based Tests
Description: Population genetic data such as 'Single Nucleotide Polymorphisms' (SNPs) is often used to identify genomic regions that have been under recent natural or artificial selection and might provide clues about the molecular mechanisms of adaptation. One approach, the concept of an 'Extended Haplotype Homozygosity' (EHH), introduced by (Sabeti 2002) <doi:10.1038/nature01140>, has given rise to several statistics designed for whole genome scans. The package provides functions to compute three of these, namely: 'iHS' (Voight 2006) <doi:10.1371/journal.pbio.0040072> for detecting positive or 'Darwinian' selection within a single population as well as 'Rsb' (Tang 2007) <doi:10.1371/journal.pbio.0050171> and 'XP-EHH' (Sabeti 2007) <doi:10.1038/nature06250>, targeted at differential selection between two populations. Various plotting functions are also included to facilitate visualization and interpretation of these statistics. Due to changes in the API, albeit mostly minor, this version is not compatible with versions 2.0.X.
Author: Mathieu Gautier, Alexander Klassmann and Renaud Vitalis
Maintainer: Alexander Klassmann <rehh@oneoverx.eu>

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New package DynamicGP with initial version 1.1-3
Package: DynamicGP
Title: Modelling and Analysis of Dynamic Computer Experiments
Version: 1.1-3
Description: Emulating and solving inverse problems for dynamic computer experiments. It contains two major functionalities: (1) localized GP model for large-scale dynamic computer experiments using the algorithm proposed by Zhang et al. (2018) <arXiv:1611.09488>; (2) solving inverse problems in dynamic computer experiments. The current version only supports 64-bit version of R.
License: GPL (>= 2)
Date: 2019-06-27
Authors@R: c(person(given="Ru", family="Zhang", role = c("aut", "cre"), email="heavenmarshal@gmail.com"), person(given=c("Chunfang","Devon"), family="Lin", role= "aut"), person(given="Pritam", family="Ranjan", role= "aut"), person(given=c("Robert","B"), family="Gramacy", role= "ctb"), person(given="Nicolas", family="Devillard", role="ctb"), person(given="Jorge", family="Nocedal", role="ctb"), person(given=c("Jose","Luis"), family="Morales", role="ctb"), person(given="Ciyou", family="Zhu", role="ctb"), person(given="Richard", family="Byrd", role="ctb"), person(given="Peihuang", family="Lu-Chen", role="ctb"), person(given="Berend", family="Hasselman", role="ctb"), person("University of Chicago", role="cph"), person("University of California", role="cph"))
Maintainer: Ru Zhang <heavenmarshal@gmail.com>
Depends: R (>= 2.14)
Imports: lhs, parallel, stats
NeedsCompilation: yes
Packaged: 2019-07-09 04:20:33 UTC; heave
Author: Ru Zhang [aut, cre], Chunfang Devon Lin [aut], Pritam Ranjan [aut], Robert B Gramacy [ctb], Nicolas Devillard [ctb], Jorge Nocedal [ctb], Jose Luis Morales [ctb], Ciyou Zhu [ctb], Richard Byrd [ctb], Peihuang Lu-Chen [ctb], Berend Hasselman [ctb], University of Chicago [cph], University of California [cph]
Repository: CRAN
Date/Publication: 2019-07-09 11:50:10 UTC

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Package blob updated to version 1.2.0 with previous version 1.1.1 dated 2018-03-25

Title: A Simple S3 Class for Representing Vectors of Binary Data ('BLOBS')
Description: R's raw vector is useful for storing a single binary object. What if you want to put a vector of them in a data frame? The 'blob' package provides the blob object, a list of raw vectors, suitable for use as a column in data frame.
Author: Hadley Wickham [aut], Kirill Müller [cre], RStudio [cph]
Maintainer: Kirill Müller <krlmlr+r@mailbox.org>

Diff between blob versions 1.1.1 dated 2018-03-25 and 1.2.0 dated 2019-07-09

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Package alfr updated to version 1.2.0 with previous version 1.1.0 dated 2019-07-03

Title: Connectivity to 'Alfresco' Content Management Repositories
Description: Allows you to connect to an 'Alfresco' content management repository and interact with its contents using simple and intuitive functions. You will be able to establish a connection session to the 'Alfresco' repository, read and upload content and manage folder hierarchies. For more details on the 'Alfresco' content management repository see <https://www.alfresco.com/ecm-software/document-management>.
Author: Roy Wetherall <rwetherall@gmail.com>
Maintainer: Roy Wetherall <rwetherall@gmail.com>

Diff between alfr versions 1.1.0 dated 2019-07-03 and 1.2.0 dated 2019-07-09

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 alfr-1.2.0/alfr/NAMESPACE                                                                                  |    7 
 alfr-1.2.0/alfr/NEWS.md                                                                                    |   12 
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 alfr-1.2.0/alfr/R/alf_node.R                                                                               |   53 +-
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 alfr-1.2.0/alfr/R/alfr.R                                                                                   |   15 
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 alfr-1.2.0/alfr/inst/WORDLIST                                                                              |only
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 alfr-1.2.0/alfr/man/alfr.Rd                                                                                |   14 
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 alfr-1.2.0/alfr/tests/spelling.R                                                                           |only
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 alfr-1.2.0/alfr/tests/testthat/testalf_session.R                                                           |   50 ++
 alfr-1.2.0/alfr/vignettes/working_with_content.Rmd                                                         |    8 
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Package WMWssp updated to version 0.4.0 with previous version 0.3.7 dated 2019-03-11

Title: Wilcoxon-Mann-Whitney Sample Size Planning
Description: Calculates the minimal sample size for the Wilcoxon-Mann-Whitney test that is needed for a given power and two sided type I error rate. The method works for metric data with and without ties, count data, ordered categorical data, and even dichotomous data. But data is needed for the reference group to generate synthetic data for the treatment group based on a relevant effect. For details, see Brunner, E., Bathke A. C. and Konietschke, F: Rank- and Pseudo-Rank Procedures in Factorial Designs - Using R and SAS, Springer Verlag, to appear.
Author: Arne C. Bathke [aut], Edgar Brunner [aut], Martin Happ [aut, cre] (<https://orcid.org/0000-0003-0009-2665>), Frank Konietschke [aut]
Maintainer: Martin Happ <martin.happ@aon.at>

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Package shar updated to version 0.5 with previous version 0.4 dated 2019-05-27

Title: Species-Habitat Associations
Description: Analyse species-habitat associations in R. Therefore, information about the location of the species is needed and about the environmental conditions. To test for significance habitat associations, one of the two components is randomized. Methods are mainly based on Plotkin et al. (2000) <doi:10.1006/jtbi.2000.2158> and Harms et al. (2001) <doi:10.1111/j.1365-2745.2001.00615.x>.
Author: Maximillian H.K. Hesselbarth [aut, cre] (<https://orcid.org/0000-0003-1125-9918>), Marco Sciaini [aut] (<https://orcid.org/0000-0002-3042-5435>)
Maintainer: Maximillian H.K. Hesselbarth <maximilian.hesselbarth@uni-goettingen.de>

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Package lslx updated to version 0.6.7 with previous version 0.6.6 dated 2019-05-02

Title: Semi-Confirmatory Structural Equation Modeling via Penalized Likelihood or Least Squares
Description: Fits semi-confirmatory structural equation modeling (SEM) via penalized likelihood (PL) or penalized least squares (PLS).
Author: Po-Hsien Huang [cre, aut], Wen-Hsin Hu [aut]
Maintainer: Po-Hsien Huang <psyphh@gmail.com>

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Package LexisNexisTools updated to version 0.2.3 with previous version 0.2.2 dated 2019-01-27

Title: Working with Files from 'LexisNexis'
Description: My PhD supervisor once told me that everyone doing newspaper analysis starts by writing code to read in files from the 'LexisNexis' newspaper archive (retrieved e.g., from <http://www.nexis.com/> or any of the partner sites). However, while this is a nice exercise I do recommend, not everyone has the time. This package takes TXT files downloaded from the newspaper archive of 'LexisNexis', reads them into R and offers functions for further processing.
Author: Johannes Gruber [aut, cre]
Maintainer: Johannes Gruber <j.gruber.1@research.gla.ac.uk>

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Package hms updated to version 0.5.0 with previous version 0.4.2 dated 2018-03-10

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

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Package BVAR updated to version 0.1.5 with previous version 0.1.3 dated 2019-05-03

Title: Hierarchical Bayesian Vector Autoregression
Description: Toolkit for the estimation of hierarchical Bayesian vector autoregressions. Implements hierarchical prior selection for conjugate priors in the fashion of Giannone, Lenza & Primiceri (2015) <doi:10.1162/REST_a_00483>. Allows for the computation of impulse responses and forecasts and provides functionality for assessing results.
Author: Nikolas Kuschnig [aut, cre], Lukas Vashold [aut], Michael McCracken [dtc] (author of the FRED-QD dataset)
Maintainer: Nikolas Kuschnig <nikolas.kuschnig@wu.ac.at>

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Package bnstruct updated to version 1.0.6 with previous version 1.0.5 dated 2019-07-02

Title: Bayesian Network Structure Learning from Data with Missing Values
Description: Bayesian Network Structure Learning from Data with Missing Values. The package implements the Silander-Myllymaki complete search, the Max-Min Parents-and-Children, the Hill-Climbing, the Max-Min Hill-climbing heuristic searches, and the Structural Expectation-Maximization algorithm. Available scoring functions are BDeu, AIC, BIC. The package also implements methods for generating and using bootstrap samples, imputed data, inference.
Author: Francesco Sambo [aut], Alberto Franzin [aut, cre]
Maintainer: Alberto Franzin <afranzin@ulb.ac.be>

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Package stoRy updated to version 0.1.3 with previous version 0.1.2 dated 2018-02-25

Title: Functions for the Analysis of Star Trek Thematic Data
Description: An implementation of 1) the hypergeometric test for over-representation of literary themes in a storyset (a list of stories) relative to a background list of stories, and 2) a recommendation system that takes a user-selected story as input and returns a ranked list of similar stories on the basis of shared themes. The package is currently implemented for the episodes of the Star Trek television franchise series The Original Series (TOS), The Animated Series (TAS), The Next Generation (TNG), and Voyager (VOY).
Author: Paul Sheridan, Mikael Onsjö
Maintainer: Paul Sheridan <paul.sheridan.stats@gmail.com>

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Package catchr updated to version 0.2.1 with previous version 0.2.0 dated 2019-02-05

Title: Taking the Pain Out of Catching and Handling Conditions
Description: R has a unique way of dealing with warnings, errors, messages, and other conditions, but it can often be troublesome to users coming from different programming backgrounds. The purpose of this package is to provide flexible and useful tools for handling R conditions with less hassle. In order to lower the barrier of entry, keep code clean and readable, and reduce the amount of typing required, `catchr` uses a very simple domain-specific language that simplifies things on the front-end. This package aims to maintain a continuous learning curve that lets new users jump straight in to condition-handling, while simultaneously offering depth and complexity for more advanced users.
Author: Zachary Burchill [aut, cre, cph]
Maintainer: Zachary Burchill <zach.burchill.code@gmail.com>

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Package serieslcb updated to version 0.4.0 with previous version 0.3.0 dated 2019-03-08

Title: Lower Confidence Bounds for Binomial Series System
Description: Calculate and compare lower confidence bounds for binomial series system reliability. The R 'shiny' application, launched by the function launch_app(), weaves together a workflow of customized simulations and delta coverage calculations to output recommended lower confidence bound methods.
Author: Edward Schuberg
Maintainer: Edward Schuberg <eschu003@ucr.edu>

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