Fri, 19 Apr 2019

Package proxyC updated to version 0.1.2 with previous version 0.1.0 dated 2018-12-31

Title: Computes Proximity in Large Sparse Matrices
Description: Computes proximity between rows or columns of large matrices efficiently in C++. Functions are optimised for large sparse matrices using the Armadillo and Intel TBB libraries. Among several built-in similarity/distance measures, computation of correlation, cosine similarity and Euclidean distance is particularly fast.
Author: Kohei Watanabe [cre, aut, cph] (<https://orcid.org/0000-0001-6519-5265>)
Maintainer: Kohei Watanabe <watanabe.kohei@gmail.com>

Diff between proxyC versions 0.1.0 dated 2018-12-31 and 0.1.2 dated 2019-04-19

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Package ncmeta updated to version 0.0.4 with previous version 0.0.3 dated 2018-10-26

Title: Straightforward 'NetCDF' Metadata
Description: Extract metadata from 'NetCDF' data sources, these can be files, file handles or servers. This package leverages and extends the lower level functions of the 'RNetCDF' package providing a consistent set of functions that all return data frames. We introduce named concepts of 'grid', 'axis' and 'source' which are all meaningful entities without formal definition in the 'NetCDF' library <https://www.unidata.ucar.edu/software/netcdf/>. 'RNetCDF' matches the library itself with only the named concepts of 'variables', 'dimensions' and 'attributes'. 'ncmeta' provides a required framework for the in-development 'tidync' project <https://github.com/hypertidy/tidync>.
Author: Michael Sumner [aut, cre], Tomas Remenyi [ctb], Ben Raymond [ctb], David Blodgett [ctb]
Maintainer: Michael Sumner <mdsumner@gmail.com>

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Package frailtySurv updated to version 1.3.6 with previous version 1.3.5 dated 2018-08-28

Title: General Semiparametric Shared Frailty Model
Description: Simulates and fits semiparametric shared frailty models under a wide range of frailty distributions using a consistent and asymptotically-normal estimator. Currently supports: gamma, power variance function, log-normal, and inverse Gaussian frailty models.
Author: Vinnie Monaco [aut, cre], Malka Gorfine [aut], Li Hsu [aut]
Maintainer: Vinnie Monaco <contact@vmonaco.com>

Diff between frailtySurv versions 1.3.5 dated 2018-08-28 and 1.3.6 dated 2019-04-19

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Package splusTimeDate updated to version 2.5.0-142 with previous version 2.5.0-141 dated 2018-05-30

Title: Times and Dates from S-PLUS
Description: A collection of classes and methods for working with times and dates. The code was originally available in S-PLUS.
Author: TIBCO Software Inc.
Maintainer: Stephen Kaluzny <skaluzny@tibco.com>

Diff between splusTimeDate versions 2.5.0-141 dated 2018-05-30 and 2.5.0-142 dated 2019-04-19

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Package rvinecopulib updated to version 0.3.1.1.0 with previous version 0.3.0.1.1 dated 2018-08-22

Title: High Performance Algorithms for Vine Copula Modeling
Description: Provides an interface to 'vinecopulib', a C++ library for vine copula modeling based on 'Boost' and 'Eigen'. The 'rvinecopulib' package implements the core features of the popular 'VineCopula' package, in particular inference algorithms for both vine copula and bivariate copula models. Advantages over 'VineCopula' are a sleeker and more modern API, improved performances, especially in high dimensions, nonparametric and multi-parameter families. The 'rvinecopulib' package includes 'vinecopulib' as header-only C++ library (currently version 0.3.1). Thus users do not need to install 'vinecopulib' itself in order to use 'rvinecopulib'. Since their initial releases, 'vinecopulib' is licensed under the MIT License, and 'rvinecopulib' is licensed under the GNU GPL version 3.
Author: Thomas Nagler [aut, cre], Thibault Vatter [aut]
Maintainer: Thomas Nagler <info@vinecopulib.org>

Diff between rvinecopulib versions 0.3.0.1.1 dated 2018-08-22 and 0.3.1.1.0 dated 2019-04-19

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Package palasso updated to version 0.0.5 with previous version 0.0.4 dated 2019-03-08

Title: Paired Lasso Regression
Description: Implements sparse regression with paired covariates (Rauschenberger et al. 2019). For the optional shrinkage, install ashr (<https://github.com/stephens999/ashr>) and CorShrink (<https://github.com/kkdey/CorShrink>) from GitHub (see README).
Author: Armin Rauschenberger [aut, cre]
Maintainer: Armin Rauschenberger <a.rauschenberger@vumc.nl>

Diff between palasso versions 0.0.4 dated 2019-03-08 and 0.0.5 dated 2019-04-19

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Package memery updated to version 0.5.2 with previous version 0.5.0 dated 2018-05-17

Title: Internet Memes for Data Analysts
Description: Generates internet memes that optionally include a superimposed inset plot and other atypical features, combining the visual impact of an attention-grabbing meme with graphic results of data analysis. The package differs from related packages that focus on imitating and reproducing standard memes. Some packages do this by interfacing with online meme generators whereas others achieve this natively. This package takes the latter approach. It does not interface with online meme generators or require any authentication with external websites. It reads images directly from local files or via URL and meme generation is done by the package. While this is similar to the 'meme' package available on CRAN, it differs in that the focus is on allowing for non-standard meme layouts and hybrids of memes mixed with graphs. While this package can be used to make basic memes like an online meme generator would produce, it caters primarily to hybrid graph-meme plots where the meme presentation can be seen as a backdrop highlighting foreground graphs of data analysis results. The package also provides support for an arbitrary number of meme text labels with arbitrary size, position and other attributes rather than restricting to the standard top and/or bottom text placement. This is useful for proper aesthetic interleaving of plots of data between meme image backgrounds and overlain text labels. The package offers a selection of templates for graph placement and appearance with respect to the underlying meme. Graph templates also permit additional template-specific customization. Animated gif support is provided but this is optional and functional only if the 'magick' package is installed. 'magick' is not required unless gif functionality is desired.
Author: Matthew Leonawicz [aut, cre]
Maintainer: Matthew Leonawicz <matt_leonawicz@esource.com>

Diff between memery versions 0.5.0 dated 2018-05-17 and 0.5.2 dated 2019-04-19

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Package funHDDC updated to version 2.3.0 with previous version 2.2.0 dated 2018-10-08

Title: Univariate and Multivariate Model-Based Clustering in Group-Specific Functional Subspaces
Description: The funHDDC algorithm allows to cluster functional univariate (Bouveyron and Jacques, 2011, <doi:10.1007/s11634-011-0095-6>) or multivariate data (Schmutz et al., 2018) by modeling each group within a specific functional subspace.
Author: A Schmutz, J. Jacques & C. Bouveyron
Maintainer: Charles Bouveyron <charles.bouveyron@gmail.com>

Diff between funHDDC versions 2.2.0 dated 2018-10-08 and 2.3.0 dated 2019-04-19

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Package Directional updated to version 3.7 with previous version 3.6 dated 2019-03-25

Title: Directional Statistics
Description: A collection of functions for directional data analysis. Hypothesis testing, discriminant and regression analysis, MLE of distributions and more are included. The standard textbook for such data is the "Directional Statistics" by Mardia, K. V. and Jupp, P. E. (2000). Other references include Phillip J. Paine, Simon P. Preston Michail Tsagris and Andrew T. A. Wood (2018). An elliptically symmetric angular Gaussian distribution. Statistics and Computing 28(3): 689-697. <doi:10.1007/s11222-017-9756-4>, P. J. Paine, S. P. Preston, M. Tsagris and Andrew T. A. Wood (2019). Spherical regression models with general covariates and anisotropic errors. Statistics and Computing (to appear). <doi:10.1007/s11222-019-09872-2>.
Author: Michail Tsagris, Giorgos Athineou, Anamul Sajib, Eli Amson, Micah J. Waldstein
Maintainer: Michail Tsagris <mtsagris@yahoo.gr>

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Package chorrrds updated to version 0.1.9 with previous version 0.1.8 dated 2019-01-28

Title: Music Chords Extraction
Description: Extracts music chords from the 'CifraClub' website <https://www.cifraclub.com.br/>. The package also has functions for cleaning the extracted data and feature extraction.
Author: Bruna Wundervald
Maintainer: Bruna Wundervald <brunadaviesw@gmail.com>

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Package akmedoids updated to version 0.1.2 with previous version 0.1.1 dated 2019-04-18

Title: Anchored Kmedoids for Longitudinal Data Clustering
Description: Advances a novel adaptation of longitudinal k-means clustering technique (Genolini et al. (2015) <doi:10.18637/jss.v065.i04>) for grouping trajectories based on the similarities of their long-term trends and determines the optimal solution based on the Calinski-Harabatz criterion (Calinski and Harabatz (1974) <doi:10.1080/03610927408827101>). Includes functions to extract descriptive statistics and generate a visualisation of the resulting groups, drawing methods from the 'ggplot2' library (Wickham H. (2016) <doi:10.1007/978-3-319-24277-4>). The package also includes a number of other useful functions for exploring and manipulating longitudinal data prior to the clustering process.
Author: Monsuru Adepeju [cre, aut], Samuel Langton [aut], Jon Bannister [aut]
Maintainer: Monsuru Adepeju <monsuur2010@yahoo.com>

Diff between akmedoids versions 0.1.1 dated 2019-04-18 and 0.1.2 dated 2019-04-19

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Package capm updated to version 0.13.10 with previous version 0.13.9 dated 2018-11-26

Title: Companion Animal Population Management
Description: Quantitative analysis to support companion animal population management. Some functions assist survey sampling tasks (calculate sample size for simple and complex designs, select sampling units and estimate population parameters) while others assist the modelling of population dynamics. For demographic characterizations and population management evaluations see: "Baquero, et al." (2018), <doi:10.1016/j.prevetmed.2018.07.006>. For modelling of population dynamics see: "Baquero et al." (2016), <doi:10.1016/j.prevetmed.2015.11.009>. For sampling methods see: "Levy PS & Lemeshow S" (2013), "ISBN-10: 0470040076"; "Lumley" (2010), "ISBN: 978-0-470-28430-8".
Author: Oswaldo Santos Baquero [aut, cre], Marcos Amaku [ctb], Fernando Ferreira [ctb]
Maintainer: Oswaldo Santos Baquero <baquero@usp.br>

Diff between capm versions 0.13.9 dated 2018-11-26 and 0.13.10 dated 2019-04-19

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Package iMRMC updated to version 1.2.0 with previous version 1.1.0 dated 2017-12-12

Title: Multi-Reader, Multi-Case Analysis Methods (ROC, Agreement, and Other Metrics)
Description: Do Multi-Reader, Multi-Case (MRMC) analyses of data from imaging studies where clinicians (readers) evaluate patient images (cases). What does this mean? ... Many imaging studies are designed so that every reader reads every case in all modalities, a fully-crossed study. In this case, the data is cross-correlated, and we consider the readers and cases to be cross-correlated random effects. An MRMC analysis accounts for the variability and correlations from the readers and cases when estimating variances, confidence intervals, and p-values. The functions in this package can treat arbitrary study designs and studies with missing data, not just fully-crossed study designs. The initial package analyzes the reader-average area under the receiver operating characteristic (ROC) curve with U-statistics according to Gallas, Bandos, Samuelson, and Wagner 2009 <doi:10.1080/03610920802610084>. Additional functions analyze other endpoints with U-statistics (binary performance and score differences) following the work by Gallas, Pennello, and Myers 2007 <doi:10.1364/JOSAA.24.000B70>. Package development and documentation is at <https://github.com/DIDSR/iMRMC/tree/master>.
Author: Brandon Gallas
Maintainer: Brandon Gallas <Brandon.Gallas@fda.hhs.gov>

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Package forestChange updated to version 0.6 with previous version 0.5 dated 2019-03-26

Title: Computing Essential Biodiversity Variables from Global Forest Change Data
Description: Metrics of two Essential Biodiversity Variables: forest extents and forest fragmentation indices (O'connor et al., 2015) <doi:10.1002/rse2.4> are computed by processing Global Forest Change data (Hansen et al., 2013) <doi:10.1126/science.1244693>. The Forest Change Data are extracted using either Geographic Administrative Units, see <https://gadm.org/>, or user-defined polygons. Most of the procedures can be understood implementing two functions: FCPolygon() and EBVmetric().
Author: Wilson Lara <wilarhen@temple.edu>, Victor Gutierrez-Velez <victorhugo@temple.edu>
Maintainer: Wilson Lara <wilarhen@temple.edu>

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Package ecmwfr updated to version 1.2.0 with previous version 1.1.0 dated 2019-02-06

Title: Interface to 'ECMWF' and 'CDS' Data Web Services
Description: Programmatic interface to the European Centre for Medium-Range Weather Forecasts dataset web services (ECMWF; <https://www.ecmwf.int/>) and Copernicus's Climate Data Store (CDS; <https://cds.climate.copernicus.eu>). Allows for easy downloads of weather forecasts and climate reanalysis data in R.
Author: Koen Hufkens [aut, cre] (<https://orcid.org/0000-0002-5070-8109>), Reto Stauffer [ctb] (<https://orcid.org/0000-0002-3798-5507>), Elio Campitelli [ctb] (<https://orcid.org/0000-0002-7742-9230>)
Maintainer: Koen Hufkens <koen.hufkens@gmail.com>

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Package rngtools updated to version 1.3.1.1 with previous version 1.3.1 dated 2018-05-15

Title: Utility Functions for Working with Random Number Generators
Description: Provides a set of functions for working with Random Number Generators (RNGs). In particular, a generic S4 framework is defined for getting/setting the current RNG, or RNG data that are embedded into objects for reproducibility. Notably, convenient default methods greatly facilitate the way current RNG settings can be changed.
Author: Renaud Gaujoux [aut, cre]
Maintainer: Renaud Gaujoux <renozao@protonmail.com>

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Package tint updated to version 0.1.2 with previous version 0.1.1 dated 2019-04-01

Title: 'tint' is not 'Tufte'
Description: A 'tufte'-alike style for 'rmarkdown'. A modern take on the 'Tufte' design for pdf and html vignettes, building on the 'tufte' package with additional contributions from the 'knitr' and 'ggtufte' package, and also acknowledging the key influence of 'envisioned css'.
Author: Dirk Eddelbuettel and Jonathan Gilligan
Maintainer: Dirk Eddelbuettel <edd@debian.org>

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Package Omisc updated to version 0.1.1 with previous version 0.1.0 dated 2018-10-14

Title: Univariate Bootstrapping and Other Things
Description: Primarily devoted to implementing the Univariate Bootstrap (as well as the Traditional Bootstrap). In addition there are multiple functions for DeFries-Fulker behavioral genetics models. The univariate bootstrapping functions, DeFries-Fulker functions, regression and traditional bootstrapping functions form the original core. Additional features may come online later, however this software is a work in progress. For more information about univariate bootstrapping see: Lee and Rodgers (1998) and Beasley et al (2007) <doi.org/10.1037/1082-989X.12.4.414>.
Author: Patrick O'Keefe
Maintainer: Patrick O'Keefe <patrick.okeefe@vanderbilt.edu>

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Package jsmodule updated to version 0.8.1 with previous version 0.8.0 dated 2019-04-07

Title: 'RStudio' Addins and 'Shiny' Modules for Medical Research
Description: 'RStudio' addins and 'Shiny' modules for descriptive statistics, regression and survival analysis.
Author: Jinseob Kim [aut, cre] (<https://orcid.org/0000-0002-9403-605X>), Zarathu [cph, fnd]
Maintainer: Jinseob Kim <jinseob2kim@gmail.com>

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Package FADA updated to version 1.3.4 with previous version 1.3.3 dated 2018-02-07

Title: Variable Selection for Supervised Classification in High Dimension
Description: The functions provided in the FADA (Factor Adjusted Discriminant Analysis) package aim at performing supervised classification of high-dimensional and correlated profiles. The procedure combines a decorrelation step based on a factor modeling of the dependence among covariates and a classification method. The available methods are Lasso regularized logistic model (see Friedman et al. (2010)), sparse linear discriminant analysis (see Clemmensen et al. (2011)), shrinkage linear and diagonal discriminant analysis (see M. Ahdesmaki et al. (2010)). More methods of classification can be used on the decorrelated data provided by the package FADA.
Author: Emeline Perthame (Institut Pasteur, Paris, France), Chloe Friguet (Universite de Bretagne Sud, Vannes, France) and David Causeur (Agrocampus Ouest, Rennes, France)
Maintainer: David Causeur <david.causeur@agrocampus-ouest.fr>

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Package drake updated to version 7.2.0 with previous version 7.1.0 dated 2019-04-07

Title: A Pipeline Toolkit for Reproducible Computation at Scale
Description: A general-purpose computational engine for data analysis, drake rebuilds intermediate data objects when their dependencies change, and it skips work when the results are already up to date. Not every execution starts from scratch, there is native support for parallel and distributed computing, and completed projects have tangible evidence that they are reproducible. Extensive documentation, from beginner-friendly tutorials to practical examples and more, is available at the reference website <https://ropensci.github.io/drake/> and the online manual <https://ropenscilabs.github.io/drake-manual/>.
Author: William Michael Landau [aut, cre] (<https://orcid.org/0000-0003-1878-3253>), Alex Axthelm [ctb], Jasper Clarkberg [ctb], Kirill Müller [ctb], Ben Bond-Lamberty [ctb] (<https://orcid.org/0000-0001-9525-4633>), Tristan Mahr [ctb] (<https://orcid.org/0000-0002-8890-5116>), Miles McBain [ctb] (<https://orcid.org/0000-0003-2865-2548>), Ben Marwick [rev], Peter Slaughter [rev], Eli Lilly and Company [cph]
Maintainer: William Michael Landau <will.landau@gmail.com>

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More information about drake at CRAN
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Package clickR updated to version 0.4.32 with previous version 0.4.20 dated 2018-10-17

Title: Fix Data and Create Report Tables from Different Objects
Description: Tools for assessing data quality, performing exploratory analysis, fixing data errors in numerical, factor and date variables and creating report tables from models and summaries.
Author: Victoria Fornes Ferrer, David Hervas Marin
Maintainer: David Hervas Marin <ddhervas@yahoo.es>

Diff between clickR versions 0.4.20 dated 2018-10-17 and 0.4.32 dated 2019-04-19

 DESCRIPTION                  |    8 ++--
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 NEWS                         |    7 +++
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 man/report.merModLmerTest.Rd |    4 +-
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Package madness updated to version 0.2.6 with previous version 0.2.5 dated 2018-08-29

Title: Automatic Differentiation of Multivariate Operations
Description: An object that supports automatic differentiation of matrix- and multidimensional-valued functions with respect to multidimensional independent variables. Automatic differentiation is via 'forward accumulation'.
Author: Steven E. Pav [aut, cre] (<https://orcid.org/0000-0002-4197-6195>)
Maintainer: Steven E. Pav <shabbychef@gmail.com>

Diff between madness versions 0.2.5 dated 2018-08-29 and 0.2.6 dated 2019-04-19

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More information about madness at CRAN
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Package gibble updated to version 0.2.0 with previous version 0.1.2 dated 2018-10-31

Title: Geometry Decomposition
Description: Build a map of path-based geometry, this is a simple description of the number of parts in an object and their basic structure. Translation and restructuring operations for planar shapes and other hierarchical types require a data model with a record of the underlying relationships between elements. The gibble() function creates a geometry map, a simple record of the underlying structure in path-based hierarchical types. There are methods for the planar shape types in the 'sf' and 'sp' packages and for types in the 'trip' and in-development 'silicate' packages.
Author: Michael Sumner [aut, cre] (<https://orcid.org/0000-0002-2471-7511>)
Maintainer: Michael Sumner <mdsumner@gmail.com>

Diff between gibble versions 0.1.2 dated 2018-10-31 and 0.2.0 dated 2019-04-19

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More information about gibble at CRAN
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Package ICAOD updated to version 0.9.9 with previous version 0.9.8 dated 2019-01-14

Title: Optimal Designs for Nonlinear Models
Description: Finds optimal designs for nonlinear models using a metaheuristic algorithm called imperialist competitive algorithm ICA. See, for details, Masoudi et al. (2017) <doi:10.1016/j.csda.2016.06.014> and Masoudi et al. (2019) <doi:10.1080/10618600.2019.1601097>.
Author: Ehsan Masoudi [aut, cre], Heinz Holling [aut], Weng Kee Wong [aut]
Maintainer: Ehsan Masoudi <ehsan.masoudi@wwu.de>

Diff between ICAOD versions 0.9.8 dated 2019-01-14 and 0.9.9 dated 2019-04-19

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More information about ICAOD at CRAN
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