Sun, 13 Aug 2017

Package RProtoBuf updated to version 0.4.10 with previous version 0.4.9 dated 2017-03-06

Title: R Interface to the 'Protocol Buffers' 'API' (Version 2 or 3)
Description: Protocol Buffers are a way of encoding structured data in an efficient yet extensible format. Google uses Protocol Buffers for almost all of its internal 'RPC' protocols and file formats. Additional documentation is available in two included vignettes one of which corresponds to our paper in the Journal of Statistical Software (2016, v71i02). Either version 2 or 3 of the 'Protocol Buffers' 'API' is supported.
Author: Romain Francois, Dirk Eddelbuettel, Murray Stokely and Jeroen Ooms
Maintainer: Dirk Eddelbuettel <edd@debian.org>

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Package HRM updated to version 0.7.1 with previous version 0.6.9 dated 2017-08-04

Title: High-Dimensional Repeated Measures
Description: Methods for testing main and interaction effects in possibly high-dimensional repeated measures in factorial designs. The observations of the subjects are assumed to be multivariate normal. It is possible to use up to 2 whole- and 3 subplot factors.
Author: Martin Happ [aut, cre], Harrar W. Solomon [aut], Arne C. Bathke [aut]
Maintainer: Martin Happ <martin.happ@aon.at>

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Package grec updated to version 1.1.1 with previous version 1.1.0 dated 2017-07-29

Title: GRadient-Based RECognition of Spatial Patterns in Environmental Data
Description: Provides algorithms for detection of spatial patterns from oceanographic data using image processing methods based on Gradient Recognition.
Author: Wencheng Lau-Medrano [aut, cre]
Maintainer: Wencheng Lau-Medrano <luis.laum@gmail.com>

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Package modmarg updated to version 0.6.0 with previous version 0.5.0 dated 2017-06-05

Title: Calculating Marginal Effects and Levels with Errors
Description: Calculate predicted levels and marginal effects from 'glm' objects, using the delta method to calculate standard errors. This is an R-based version of the 'margins' command from Stata.
Author: Alex Gold [aut], Nat Olin [ctb], Annie Wang [aut, cre]
Maintainer: Annie Wang <anniejw6@gmail.com>

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Package HHG updated to version 2.1 with previous version 2.0 dated 2016-10-26

Title: Heller-Heller-Gorfine Tests of Independence and Equality of Distributions
Description: Heller-Heller-Gorfine ('HHG') tests are a set of powerful statistical tests of multivariate k-sample homogeneity and independence. For the univariate case, the package also offers implementations of the 'MinP DDP' and 'MinP ADP' tests, which are consistent against all continuous alternatives but are distribution-free, and are thus much faster to apply.
Author: Barak Brill & Shachar Kaufman, based in part on an earlier implementation by Ruth Heller and Yair Heller.
Maintainer: Barak Brill <barakbri@mail.tau.ac.il>

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Package rdpla updated to version 0.2.0 with previous version 0.1.0 dated 2016-10-14

Title: Client for the Digital Public Library of America ('DPLA')
Description: Interact with the Digital Public Library of America <https://dp.la> ('DPLA') 'REST' 'API' <https://dp.la/info/developers/codex/> from R, including search and more.
Author: Scott Chamberlain [aut, cre]
Maintainer: Scott Chamberlain <myrmecocystus@gmail.com>

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Package canvasXpress updated to version 0.16.7 with previous version 0.16.6 dated 2017-07-18

Title: Visualization Package for CanvasXpress in R
Description: Enables creation of visualizations using the CanvasXpress framework in R. CanvasXpress is a standalone JavaScript library for reproducible research with complete tracking of data and end-user modifications stored in a single PNG image that can be played back. See <http://canvasxpress.org> for more information.
Author: Isaac Neuhaus [aut, cre], Connie Brett [ctb]
Maintainer: Connie Brett <connie@aggregate-genius.com>

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Package pcnetmeta updated to version 2.5 with previous version 2.4 dated 2016-04-24

Title: Patient-Centered Network Meta-Analysis
Description: Performs arm-based network meta-analysis for datasets with binary, continuous, and count outcomes using the Bayesian methods of Zhang et al (2014) <doi:10.1177/1740774513498322> and Lin et al (2017) <doi:10.18637/jss.v080.i05>.
Author: Lifeng Lin, Jing Zhang, and Haitao Chu
Maintainer: Lifeng Lin <linl@stat.fsu.edu>

Diff between pcnetmeta versions 2.4 dated 2016-04-24 and 2.5 dated 2017-08-13

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Package OrgMassSpecR updated to version 0.5-3 with previous version 0.5-2 dated 2017-08-11

Title: Organic Mass Spectrometry
Description: Organic/biological mass spectrometry data analysis.
Author: Nathan Dodder [cre, aut, cph], Katharine Mullen [ctb]
Maintainer: Nathan Dodder <ndodder@mail.sdsu.edu>

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New package esvis with initial version 0.1.0
Package: esvis
Type: Package
Title: Visualization and Estimation of Effect Sizes
Version: 0.1.0
Authors@R: person("Daniel", "Anderson", email = "daniela@uoregon.edu", role = c("aut", "cre"))
Description: A variety of methods are provided to estimate and visualize distributional differences in terms of effect sizes. Particular emphasis is upon evaluating differences between two or more distributions across the entire scale, rather than at a single point (e.g., differences in means). For example, Probability-Probability (PP) plots display the difference between two or more distributions, matched by their empirical CDFs (see Ho and Reardon, 2012; <doi:10.3102/1076998611411918>), allowing for examinations of where on the scale distributional differences are largest or smallest. The area under the PP curve (AUC) is an effect-size metric, corresponding to the probability that a randomly selected observation from the x-axis distribution will have a higher value than a randomly selected observation from the y-axis distribution. Binned effect size plots are also available, in which the distributions are split into bins (set by the user) and separate effect sizes (Cohen's d) are produced for each bin - again providing a means to evaluate the consistency (or lack thereof) of the difference between two or more distributions at different points on the scale. Evaluation of empirical CDFs is also provided, with built-in arguments for providing annotations to help evaluate distributional differences at specific points (e.g., semi-transparent shading). All function take a consistent argument structure. Calculation of specific effect sizes is also possible. The following effect sizes are estimable: (a) Cohen's d, (b) Hedges' g, (c) percentage above a cut, (d) transformed (normalized) percentage above a cut, (e) area under the PP curve, and (f) the V statistic (see Ho, 2009; <doi:10.3102/1076998609332755>), which essentially transforms the area under the curve to standard deviation units. By default, effect sizes are calculated for all possible pairwise comparisons, but a reference group (distribution) can be specified.
Depends: R (>= 3.1)
Imports: sfsmisc
URL: https://github.com/DJAnderson07/esvis
BugReports: https://github.com/DJAnderson07/esvis/issues
License: MIT + file LICENSE
LazyData: true
RoxygenNote: 6.0.1
Suggests: testthat
NeedsCompilation: no
Packaged: 2017-08-12 21:28:33 UTC; Daniel
Author: Daniel Anderson [aut, cre]
Maintainer: Daniel Anderson <daniela@uoregon.edu>
Repository: CRAN
Date/Publication: 2017-08-13 09:51:14 UTC

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Package BLPestimatoR updated to version 0.1.5 with previous version 0.1.4 dated 2017-05-05

Title: Performs a BLP Demand Estimation
Description: Provides the estimation algorithm to perform the demand estimation described in Berry, Levinsohn and Pakes (1995) <DOI:10.2307/2171802> . The routine uses analytic gradients and offers a large number of implemented integration methods and optimization routines.
Author: Daniel Brunner (aut), Constantin Weiser (ctr), Andre Romahn (ctr)
Maintainer: Daniel Brunner <daniel.brunner@hhu.de>

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Package threejs updated to version 0.3.1 with previous version 0.2.2 dated 2016-04-01

Title: Interactive 3D Scatter Plots, Networks and Globes
Description: Create interactive 3D scatter plots, network plots, and globes using the 'three.js' visualization library (<https://threejs.org>).
Author: B. W. Lewis [aut, cre], Three.js authors [cph] (three.js JavaScript library), Alexey Stukalov [ctb], Yihui Xie [ctb], Andreas Briese [ctb], B. Thieurmel [ctb]
Maintainer: B. W. Lewis <blewis@illposed.net>

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Package TAM updated to version 2.6-2 with previous version 2.5-14 dated 2017-08-08

Title: Test Analysis Modules
Description: Includes marginal maximum likelihood estimation of uni- and multidimensional item response models (Rasch, 2PL, 3PL, Generalized Partial Credit, Multi Facets, Nominal Item Response, Structured Latent Class Analysis, Mixture Distribution IRT Models, Located Latent Class Models) and joint maximum likelihood estimation for models from the Rasch family. Latent regression models and plausible value imputation are also supported.
Author: Alexander Robitzsch [aut, cre], Thomas Kiefer [aut], Margaret Wu [aut]
Maintainer: Alexander Robitzsch <robitzsch@ipn.uni-kiel.de>

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Package sparklyr updated to version 0.6.2 with previous version 0.6.1 dated 2017-08-06

Title: R Interface to Apache Spark
Description: R interface to Apache Spark, a fast and general engine for big data processing, see <http://spark.apache.org>. This package supports connecting to local and remote Apache Spark clusters, provides a 'dplyr' compatible back-end, and provides an interface to Spark's built-in machine learning algorithms.
Author: Javier Luraschi [aut, cre], Kevin Ushey [aut], JJ Allaire [aut], RStudio [cph], The Apache Software Foundation [aut, cph]
Maintainer: Javier Luraschi <javier@rstudio.com>

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Package osmdata updated to version 0.0.5 with previous version 0.0.4 dated 2017-06-21

Title: Import 'OpenStreetMap' Data as Simple Features or Spatial Objects
Description: Download and import of 'OpenStreetMap' ('OSM') data as 'sf' or 'sp' objects. 'OSM' data are extracted from the 'Overpass' web server and processed with very fast 'C++' routines for return to 'R'.
Author: Mark Padgham [aut, cre], Bob Rudis [aut], Robin Lovelace [aut], Maƫlle Salmon [aut], Andrew Smith [ctb], Marcin Kalicinski [ctb, cph] (Author of included RapidXML code), Finkelstein Noam [ctb, cph] (Author of included stub.R code), Bartnik Lukasz [ctb, cph] (Author of included stub.R code)
Maintainer: Mark Padgham <mark.padgham@email.com>

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Package OpenMx updated to version 2.7.16 with previous version 2.7.15 dated 2017-08-08

Title: Extended Structural Equation Modelling
Description: Facilitates treatment of statistical model specifications as things that can be generated and manipulated programmatically. Structural equation models may be specified with reticular action model matrices or paths, linear structural relations matrices or paths, or directly in matrix algebra. Fit functions include full information maximum likelihood, maximum likelihood, and weighted least squares. Example models include confirmatory factor, multiple group, mixture distribution, categorical threshold, modern test theory, differential equations, state space, and many others.
Author: Steven M. Boker [aut], Michael C. Neale [aut], Hermine H. Maes [aut], Michael J. Wilde [ctb], Michael Spiegel [aut], Timothy R. Brick [aut], Ryne Estabrook [aut], Timothy C. Bates [aut], Paras Mehta [ctb], Timo von Oertzen [ctb], Ross J. Gore [aut], Michael D. Hunter [aut], Daniel C. Hackett [ctb], Julian Karch [ctb], Andreas M. Brandmaier [ctb], Joshua N. Pritikin [aut, cre], Mahsa Zahery [aut], Robert M. Kirkpatrick [aut], Yang Wang [ctb], Charles Driver [ctb], Massachusetts Institute of Technology [cph], S. G. Johnson [cph], Association for Computing Machinery [cph], Dieter Kraft [cph], Stefan Wilhelm [cph], Manjunath B G [cph]
Maintainer: Joshua N. Pritikin <jpritikin@pobox.com>

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More information about OpenMx at CRAN
Permanent link

Package kSamples updated to version 1.2-7 with previous version 1.2-6 dated 2017-06-14

Title: K-Sample Rank Tests and their Combinations
Description: Compares k samples using the Anderson-Darling test, Kruskal-Wallis type tests with different rank score criteria, Steel's multiple comparison test, and the Jonckheere-Terpstra (JT) test. It computes asymptotic, simulated or (limited) exact P-values, all valid under randomization, with or without ties, or conditionally under random sampling from populations, given the observed tie pattern. Except for Steel's test and the JT test it also combines these tests across several blocks of samples. Also analyzed are 2 x t contingency tables and their blocked combinations using the Kruskal-Wallis criterion. Steel's test is inverted to provide simultaneous confidence bounds for shift parameters. A plotting function compares tail probabilities obtained under asymptotic approximation with those obtained via simulation or exact calculations.
Author: Fritz Scholz [aut, cre], Angie Zhu [aut]
Maintainer: Fritz Scholz <fscholz@u.washington.edu>

Diff between kSamples versions 1.2-6 dated 2017-06-14 and 1.2-7 dated 2017-08-13

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More information about kSamples at CRAN
Permanent link

Package hansard updated to version 0.5.2 with previous version 0.5.0 dated 2017-07-10

Title: Provides Easy Downloading Capabilities for the UK Parliament API
Description: Provides functions to download data from the <http://www.data.parliament.uk/> APIs. Because of the structure of the API, there is a named function for each type of available data for ease of use, as well as some functions designed to retrieve specific pieces of commonly used data. Functions for each new API will be added as and when they become available.
Author: Evan Odell [aut, cre]
Maintainer: Evan Odell <evanodell91@gmail.com>

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More information about hansard at CRAN
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Package future updated to version 1.6.0 with previous version 1.5.0 dated 2017-05-26

Title: Unified Parallel and Distributed Processing in R for Everyone
Description: The purpose of this package is to provide a lightweight and unified Future API for sequential and parallel processing of R expression via futures. The simplest way to evaluate an expression in parallel is to use `x %<-% { expression }` with `plan(multiprocess)`. This package implements sequential, multicore, multisession, and cluster futures. With these, R expressions can be evaluated on the local machine, on in parallel a set of local machines, or distributed on a mix of local and remote machines. Extensions to this package implements additional backends for processing futures via compute cluster schedulers etc. Because of its unified API, there is no need to modify code in order switch from sequential on the local machine to, say, distributed processing on a remote compute cluster. Another strength of this package is that global variables and functions are automatically identified and exported as needed, making it straightforward to tweak existing code to make use of futures.
Author: Henrik Bengtsson [aut, cre, cph]
Maintainer: Henrik Bengtsson <henrikb@braju.com>

Diff between future versions 1.5.0 dated 2017-05-26 and 1.6.0 dated 2017-08-13

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Package DoE.base updated to version 0.31 with previous version 0.30 dated 2017-03-24

Title: Full Factorials, Orthogonal Arrays and Base Utilities for DoE Packages
Description: Package DoE.base creates full factorial experimental designs and designs based on orthogonal arrays for (industrial) experiments. Additionally, it provides utility functions for the class design, which is also used by other packages for designed experiments.
Author: Ulrike Groemping [aut, cre], Boyko Amarov [ctb], Hongquan Xu [ctb]
Maintainer: Ulrike Groemping <groemping@beuth-hochschule.de>

Diff between DoE.base versions 0.30 dated 2017-03-24 and 0.31 dated 2017-08-13

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More information about DoE.base at CRAN
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Package d3r updated to version 0.6.8 with previous version 0.6.6 dated 2017-06-27

Title: 'd3.js' Utilities for R
Description: Helper functions for using 'd3.js' in R.
Author: Mike Bostock [aut, cph] (d3.js library in htmlwidgets/lib, http://d3js.org), Kent Russell [aut, cre] (R interface), Gregor Aisch [aut, cph] (d3-jetpack creator, https://github.com/gka/d3-jetpack), Adam Pearce [aut] (core contributor to d3-jetpack), Ben Ortiz [ctb]
Maintainer: Kent Russell <kent.russell@timelyportfolio.com>

Diff between d3r versions 0.6.6 dated 2017-06-27 and 0.6.8 dated 2017-08-13

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More information about d3r at CRAN
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