Sat, 19 Jan 2019

Package CARS updated to version 0.2.2 with previous version 0.2.1 dated 2018-11-20

Title: Covariate Assisted Ranking and Screening for Large-Scale Two-Sample Inference
Description: It implements the CARS procedure, which is a two-sample multiple testing procedure that utilizes an additional auxiliary variable to capture the sparsity information, hence improving power. The CARS procedure is shown to be asymptotically valid and optimal for FDR control. For more information, please see the website <http://www-bcf.usc.edu/~wenguans/Papers/CARS.html> and the accompanying paper.
Author: Weinan Wang [cre, aut]
Maintainer: Weinan Wang <weinanw@usc.edu>

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New package shinyrecap with initial version 0.1.0
Package: shinyrecap
Type: Package
Title: Shiny User Interface for Multiple Source Capture Recapture Models
Version: 0.1.0
Author: Ian E. Fellows
Maintainer: Ian E. Fellows <ian@fellstat.com>
Description: Implements user interfaces for log-linear models, Bayesian model averaging and Bayesian Dirichlet process mixture models.
License: MIT + file LICENCE
Imports: Rcapture, shiny, shinycssloaders, conting, ggplot2, reshape, CARE1, dga, LCMCR, ipc, future, promises, coda, testthat
URL: https://fellstat.github.io/shinyrecap/
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2019-01-11 23:11:06 UTC; ianfellows
Repository: CRAN
Date/Publication: 2019-01-19 23:40:03 UTC

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New package iva with initial version 0.1.0
Package: iva
Type: Package
Title: Instrumental Variable Analysis in Case-Control Association Studies
Version: 0.1.0
Author: Han Zhang, Kai Yu
Maintainer: Han Zhang <han.zhang2@nih.gov>
Imports: ucminf, Formula
Description: Mendelian randomization (MR) analysis is a special case of instrumental variable analysis with genetic instruments. It is used to estimate the unconfounded causal effect of an exposure. This package implements estimating and testing methods in Zhang et al. (2019) for MR analysis in case-control studies. It (1) estimates the causal effect of a quantitative exposure by the quasi empirical likelihood approach; (2) uses Lagrange multiplier test for testing the presence of causal; (3) provides a test for the presence of confounder.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2019-01-12 01:02:36 UTC; zhangh12
Repository: CRAN
Date/Publication: 2019-01-19 23:50:03 UTC

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New package hcandersenr with initial version 0.2.0
Type: Package
Package: hcandersenr
Title: H.C. Andersens Fairy Tales
Version: 0.2.0
Authors@R: person(given = "Emil", family = "Hvitfeldt", role = c("aut", "cre"), email = "emilhhvitfeldt@gmail.com")
Description: Texts for H.C. Andersens fairy tales, ready for text analysis. Fairy tales in German, Danish, English, Spanish and French.
License: MIT + file LICENSE
URL: https://github.com/EmilHvitfeldt/hcandersenr
Depends: R (>= 3.0.0)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-01-12 05:21:33 UTC; emilhvitfeldthansen
Author: Emil Hvitfeldt [aut, cre]
Maintainer: Emil Hvitfeldt <emilhhvitfeldt@gmail.com>
Repository: CRAN
Date/Publication: 2019-01-19 23:40:06 UTC

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New package handyplots with initial version 1.1.3
Package: handyplots
Type: Package
Title: Handy Plots
Version: 1.1.3
Date: 2019-01-11
Author: Jonathan Schwartz
Maintainer: Jonathan Schwartz <jzs1986@gmail.com>
Description: Several handy plots for quickly looking at the relationship between two numeric vectors of equal length. Quickly visualize scatter plots, residual plots, qq-plots, box plots, confidence intervals, and prediction intervals.
License: GPL (>= 2)
Imports: stats, graphics
Depends: R (>= 3.4)
NeedsCompilation: no
Packaged: 2019-01-11 20:39:12 UTC; schwartstack
Repository: CRAN
Date/Publication: 2019-01-19 23:40:10 UTC

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Package ppclust updated to version 0.1.2 with previous version 0.1.1 dated 2018-01-04

Title: Probabilistic and Possibilistic Cluster Analysis
Description: Partitioning clustering divides the objects in a data set into non-overlapping subsets or clusters by using the prototype-based probabilistic and possibilistic clustering algorithms. This package covers a set of the functions for Fuzzy C-Means (Bezdek, 1974) <doi:10.1080/01969727308546047>, Possibilistic C-Means (Krishnapuram & Keller, 1993) <doi:10.1109/91.227387>, Possibilistic Fuzzy C-Means (Pal et al, 2005) <doi:10.1109/TFUZZ.2004.840099>, Possibilistic Clustering Algorithm (Yang et al, 2006) <doi:10.1016/j.patcog.2005.07.005>, Possibilistic C-Means with Repulsion (Wachs et al, 2006) <doi:10.1007/3-540-31662-0_6> and the other variants of hard and soft clustering algorithms. The cluster prototypes and membership matrices required by these partitioning algorithms are initialized with different initialization techniques that are available in the package 'inaparc'. As the distance metrics, not only the Euclidean distance but also a set of the commonly used distance metrics are available to use with some of the algorithms in the package.
Author: Zeynel Cebeci [aut, cre], Figen Yildiz [aut], Alper Tuna Kavlak [aut], Cagatay Cebeci [aut], Hasan Onder [aut]
Maintainer: Zeynel Cebeci <zcebeci@cukurova.edu.tr>

Diff between ppclust versions 0.1.1 dated 2018-01-04 and 0.1.2 dated 2019-01-19

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Package NormalBetaPrime updated to version 2.2 with previous version 2.1 dated 2019-01-17

Title: Normal Beta Prime Prior
Description: Implements Bayesian linear regression, variable selection, normal means estimation, and multiple hypothesis testing using the normal-beta prime prior, as introduced by Bai and Ghosh (2019) <arXiv:1807.02421> and Bai and Ghosh (2019) <arXiv:1807.06539>. Normal means estimation and multiple testing for the Dirichlet-Laplace <doi:10.1080/01621459.2014.960967> and horseshoe+ priors <doi:10.1214/16-BA1028> are also available in this package.
Author: Ray Bai, Malay Ghosh
Maintainer: Ray Bai <Ray.Bai@pennmedicine.upenn.edu>

Diff between NormalBetaPrime versions 2.1 dated 2019-01-17 and 2.2 dated 2019-01-19

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Package MetaStan updated to version 0.0.3 with previous version 0.0.2 dated 2018-11-15

Title: Bayesian Meta-Analysis via 'Stan'
Description: Performs Bayesian meta-analysis using 'Stan'. Includes binomial-normal hierarchical models and option to use weakly informative priors for the heterogeneity parameter and the treatment effect parameter which are described in Guenhan, Roever, and Friede (2018) <arXiv:1809.04407>.
Author: Burak Kuersad Guenhan [aut, cre] (<https://orcid.org/0000-0002-7454-8680>), Trustees of Columbia University [cph] (src/init.cpp, tools/make_cpp.R, R/stanmodels.R)
Maintainer: Burak Kuersad Guenhan <burak.gunhan@med.uni-goettingen.de>

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New package germinationmetrics with initial version 0.1.3
Package: germinationmetrics
Title: Seed Germination Indices and Curve Fitting
Version: 0.1.3
Authors@R: c( person(given = "J.", family = "Aravind", email = "j.aravind@icar.gov.in", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-4791-442X")), person(given = "S.", family = "Vimala Devi", email = "vimala.devi@icar.gov.in", role = "aut"), person(given = "J.", family = "Radhamani", email = "jalli.radhamani@icar.gov.in", role = "aut"), person(given = c("Sherry", "Rachel"), family = "Jacob", email = "sherry.jacob@icar.gov.in", role = "aut"), person(given = c("Kalyani", "Srinivasan"), email = "kalyani.srinivasan@icar.gov.in", role = "aut"), person("ICAR-NBGPR", role = "cph", comment = c(url = "www.nbpgr.ernet.in")))
Description: Provides functions to compute various germination indices such as germinability, median germination time, mean germination time, mean germination rate, speed of germination, Timson's index, germination value, coefficient of uniformity of germination, uncertainty of germination process, synchrony of germination etc. from germination count data. Includes functions for fitting cumulative seed germination curves using four-parameter hill function and computation of associated parameters. See the vignette for more, including full list of citations for the methods implemented.
Copyright: 2017-2018, ICAR-NBPGR
License: GPL-2 | GPL-3
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.5.0)
VignetteBuilder: knitr
RoxygenNote: 6.1.1
Imports: broom, data.table, ggplot2, ggrepel, minpack.lm, plyr, Rdpack, utils, stats
Suggests: knitr, rmarkdown, reshape2, pander, XML, httr, RCurl
RdMacros: Rdpack
URL: https://github.com/aravind-j/germinationmetrics, https://aravind-j.github.io/germinationmetrics/ https://CRAN.R-project.org/package=germinationmetrics https://doi.org/10.5281/zenodo.1219630
BugReports: https://github.com/aravind-j/germinationmetrics/issues
NeedsCompilation: no
Packaged: 2019-01-19 18:44:38 UTC; J. Aravind
Author: J. Aravind [aut, cre] (<https://orcid.org/0000-0002-4791-442X>), S. Vimala Devi [aut], J. Radhamani [aut], Sherry Rachel Jacob [aut], Kalyani Srinivasan [aut], ICAR-NBGPR [cph] (www.nbpgr.ernet.in)
Maintainer: J. Aravind <j.aravind@icar.gov.in>
Repository: CRAN
Date/Publication: 2019-01-19 22:30:03 UTC

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Package emstreeR updated to version 2.1.1 with previous version 2.1.0 dated 2018-12-06

Title: Fast Computing Euclidean Minimum Spanning Trees
Description: Computes Euclidean Minimum Spanning Trees (EMST) using the Dual-Tree Boruvka algorithm (March, Ram, Gray, 2010, <doi:10.1145/1835804.1835882>) implemented in 'mlpack' - the C++ Machine Learning library (Curtin, 2005, <doi:10.21105/joss.00726>). 'emstreeR' heavily relies on 'RcppMLPACK' and 'Rcpp' to work as a wrapper, so that R users have access to the C++ fast EMST algorithm without having to deal with the R-'Rcpp'-C++ integration. The package also provides functions and an S3 method for readily plotting the Minimum Spanning Trees (MST) using either 'base' R, 'scatterplot3d' or 'ggplot2' style.
Author: Allan Quadros [aut, cre], Andre Cancado [ctb]
Maintainer: Allan Quadros <allanvcq@gmail.com>

Diff between emstreeR versions 2.1.0 dated 2018-12-06 and 2.1.1 dated 2019-01-19

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Package ecmwfr updated to version 1.0.1 with previous version 1.0.0 dated 2019-01-17

Title: Interface to the 'ECMWF' Data Web Services
Description: Programmatic interface to the 'ECMWF' public dataset web services (<https://www.ecmwf.int/>). Allows for easy downloads of climate data directly to your R work space or your computer.
Author: Koen Hufkens [aut, cre]
Maintainer: Koen Hufkens <koen.hufkens@gmail.com>

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New package dsm with initial version 2.2.17
Package: dsm
Maintainer: Laura Marshall <lhm@st-andrews.ac.uk>
License: GPL (>= 2)
Title: Density Surface Modelling of Distance Sampling Data
LazyLoad: yes
Author: David L. Miller, Eric Rexstad, Louise Burt, Mark V. Bravington, Sharon Hedley.
Description: Density surface modelling of line transect data. A Generalized Additive Model-based approach is used to calculate spatially-explicit estimates of animal abundance from distance sampling (also presence/absence and strip transect) data. Several utility functions are provided for model checking, plotting and variance estimation.
Version: 2.2.17
URL: http://github.com/DistanceDevelopment/dsm
BugReports: https://github.com/DistanceDevelopment/dsm/issues
Depends: R (>= 3.0), mgcv (>= 1.8-23), mrds (>= 2.1.16), numDeriv
Imports: nlme, ggplot2, plyr, statmod
Suggests: Distance, sp, tweedie, testthat
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-01-19 21:46:29 UTC; lhm
Repository: CRAN
Date/Publication: 2019-01-19 22:30:20 UTC

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Package DescTools updated to version 0.99.27 with previous version 0.99.26 dated 2018-11-13

Title: Tools for Descriptive Statistics
Description: A collection of miscellaneous basic statistic functions and convenience wrappers for efficiently describing data. The author's intention was to create a toolbox, which facilitates the (notoriously time consuming) first descriptive tasks in data analysis, consisting of calculating descriptive statistics, drawing graphical summaries and reporting the results. The package contains furthermore functions to produce documents using MS Word (or PowerPoint) and functions to import data from Excel. Many of the included functions can be found scattered in other packages and other sources written partly by Titans of R. The reason for collecting them here, was primarily to have them consolidated in ONE instead of dozens of packages (which themselves might depend on other packages which are not needed at all), and to provide a common and consistent interface as far as function and arguments naming, NA handling, recycling rules etc. are concerned. Google style guides were used as naming rules (in absence of convincing alternatives). The 'camel style' was consequently applied to functions borrowed from contributed R packages as well.
Author: Andri Signorell. Includes R source code and/or documentation previously published by (in alphabetical order): Ken Aho, Andreas Alfons, Nanina Anderegg, Tomas Aragon, Antti Arppe, Adrian Baddeley, Kamil Barton, Ben Bolker, Hans W. Borchers, Frederico Caeiro, Stephane Champely, Daniel Chessel, Leanne Chhay, Clint Cummins, Michael Dewey, Harold C. Doran, Stephane Dray, Charles Dupont, Dirk Eddelbuettel, Jeff Enos, Claus Ekstrom, Martin Elff, Kamil Erguler, Richard W. Farebrother, John Fox, Romain Francois, Michael Friendly, Tal Galili, Matthias Gamer, Joseph L. Gastwirth, Yulia R. Gel, Juergen Gross, Gabor Grothendieck, Frank E. Harrell Jr, Richard Heiberger, Michael Hoehle, Christian W. Hoffmann, Soeren Hojsgaard, Torsten Hothorn, Markus Huerzeler, Wallace W. Hui, Pete Hurd, Rob J. Hyndman, Pablo J. Villacorta Iglesias, Christopher Jackson, Matthias Kohl, Mikko Korpela, Max Kuhn, Detlew Labes, Duncan Temple Lang, Friederich Leisch, Jim Lemon, Dong Li, Martin Maechler, Arni Magnusson, Daniel Malter, George Marsaglia, John Marsaglia, Alina Matei, David Meyer, Weiwen Miao, Giovanni Millo, Yongyi Min, David Mitchell, Markus Naepflin, Daniel Navarro, Henric Nilsson, Klaus Nordhausen, Derek Ogle, Hong Ooi, Nick Parsons, Sandrine Pavoine, Tony Plate, Roland Rapold, William Revelle, Tyler Rinker, Brian D. Ripley, Caroline Rodriguez, Nathan Russell, Nick Sabbe, Venkatraman E. Seshan, Greg Snow, Michael Smithson, Karline Soetaert, Werner A. Stahel, Alec Stephenson, Mark Stevenson, Matthias Templ, Terry Therneau, Yves Tille, Adrian Trapletti, Joshua Ulrich, Kevin Ushey, Jeremy VanDerWal, Bill Venables, John Verzani, Gregory R. Warnes, Stefan Wellek, Hadley Wickham, Rand R. Wilcox, Peter Wolf, Daniel Wollschlaeger, Thomas Yee, Achim Zeileis
Maintainer: Andri Signorell <andri@signorell.net>

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Package effectFusion updated to version 1.1.1 with previous version 1.1 dated 2019-01-07

Title: Bayesian Effect Fusion for Categorical Predictors
Description: Variable selection and Bayesian effect fusion for categorical predictors in linear and logistic regression models. Effect fusion aims at the question which categories have a similar effect on the response and therefore can be fused to obtain a sparser representation of the model. Effect fusion and variable selection can be obtained either with a prior that has an interpretation as spike and slab prior on the level effect differences or with a sparse finite mixture prior on the level effects. The regression coefficients are estimated with a flat uninformative prior after model selection or by taking model averages. Posterior inference is accomplished by an MCMC sampling scheme which makes use of a data augmentation strategy (Polson, Scott & Windle (2013)) based on latent Polya-Gamma random variables in the case of logistic regression. The code for data augmentation is taken from Polson et al. (2013), who own the copyright.
Author: Daniela Pauger [aut], Magdalena Leitner [aut, cre], Helga Wagner [aut] (<https://orcid.org/0000-0002-7003-9512>), Gertraud Malsiner-Walli [aut] (<https://orcid.org/0000-0002-1213-4749>), Nicholas G. Polson [ctb], James G. Scott [ctb], Jesse Windle [ctb], Bettina Grün [ctb] (<https://orcid.org/0000-0001-7265-4773>)
Maintainer: Magdalena Leitner <magdalena.leitner@jku.at>

Diff between effectFusion versions 1.1 dated 2019-01-07 and 1.1.1 dated 2019-01-19

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Package seacarb updated to version 3.2.11 with previous version 3.2.10 dated 2018-10-24

Title: Seawater Carbonate Chemistry
Description: Calculates parameters of the seawater carbonate system and assists the design of ocean acidification perturbation experiments.
Author: Jean-Pierre Gattuso [aut, cre, cph], Jean-Marie Epitalon [aut], Heloise Lavigne [aut], James Orr [aut], Bernard Gentili [ctb], Mathilde Hagens [ctb], Andreas Hofmann [ctb], Jens-Daniel Mueller [ctb], Aurélien Proye [ctb], James Rae [ctb], Karline Soetaert [ctb]
Maintainer: Jean-Pierre Gattuso <gattuso@obs-vlfr.fr>

Diff between seacarb versions 3.2.10 dated 2018-10-24 and 3.2.11 dated 2019-01-19

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Package ethnobotanyR updated to version 0.1.2 with previous version 0.1.0 dated 2019-01-08

Title: Calculate Quantitative Ethnobotany Indices
Description: Calculate common quantitative ethnobotany indices to assess the cultural significance of plant species based on informant consensus. The package closely follows the paper by Tardio and Pardo-de-Santayana (2008). Tardio, J., and M. Pardo-de-Santayana, 2008. Cultural Importance Indices: A Comparative Analysis Based on the Useful Wild Plants of Southern Cantabria (Northern Spain) 1. Economic Botany, 62(1), 24-39. <doi:10.1007/s12231-007-9004-5>.
Author: Cory Whitney
Maintainer: Cory Whitney <whitney.cory@gmail.com>

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Package RProbSup updated to version 2.0 with previous version 1.0 dated 2018-12-03

Title: Calculates Probability of Superiority
Description: The A() function calculates the A statistic, a nonparametric measure of effect size for two independent groups that’s also known as the probability of superiority (Ruscio, 2008), along with its standard error and a confidence interval constructed using bootstrap methods (Ruscio & Mullen, 2012). Optional arguments can be specified to calculate variants of the A statistic developed for other research designs (e.g., related samples, more than two independent groups or related samples; Ruscio & Gera, 2013). <DOI: 10.1037/1082-989X.13.1.19>. <DOI: 10.1080/00273171.2012.658329>. <DOI: 10.1080/00273171.2012.738184>.
Author: John Ruscio
Maintainer: John Ruscio <ruscio@tcnj.edu>

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Package BeyondBenford updated to version 1.1 with previous version 1.0 dated 2018-12-03

Title: Compare the Goodness of Fit of Benford's and Blondeau Da Silva's Digit Distributions to a Given Dataset
Description: Allows to compare the goodness of fit of Benford's and Blondeau Da Silva's digit distributions in a dataset. It is used to check whether the data distribution is consistent with theoretical distributions highlighted by Blondeau Da Silva or not (through the dat.distr() function): this ideal theoretical distribution must be at least approximately followed by the data for the use of Blondeau Da Silva's model to be well-founded. It also enables to plot histograms of digit distributions, both observed in the dataset and given by the two theoretical approaches (with the digit.ditr() function). Finally, it proposes to quantify the goodness of fit via Pearson's chi-squared test (with the chi2() function).
Author: Blondeau Da Silva Stephane
Maintainer: Blondeau Da Silva Stephane <Stephane.Blondeau-Da-Silva@ac-limoges.fr>

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Package parglm updated to version 0.1.1 with previous version 0.1.0 dated 2018-12-09

Title: Parallel GLM
Description: Provides a parallel estimation method for generalized linear models without compiling with a multithreaded LAPACK or BLAS.
Author: Benjamin Christoffersen [cre, aut], Anthony Williams [cph], Boost developers [cph]
Maintainer: Benjamin Christoffersen <boennecd@gmail.com>

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Package mapsapi updated to version 0.3.9 with previous version 0.3.7 dated 2018-07-23

Title: 'sf'-Compatible Interface to 'Google Maps' APIs
Description: Interface to the 'Google Maps' APIs: (1) routing directions based on the 'Directions' API, returned as 'sf' objects, either as single feature per alternative route, or a single feature per segment per alternative route; (2) travel distance or time matrices based on the 'Distance Matrix' API; (3) geocoded locations based on the 'Geocode' API, returned as 'sf' objects, either points or bounds.
Author: Michael Dorman [aut, cre], Tom Buckley [ctb], Alex Dannenberg [ctb]
Maintainer: Michael Dorman <dorman@post.bgu.ac.il>

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Package smartdata updated to version 1.0.2 with previous version 1.0.1 dated 2019-01-07

Title: Data Preprocessing
Description: Eases data preprocessing tasks, providing a data flow based on a pipe operator which eases cleansing, transformation, oversampling, or instance/feature selection operations.
Author: Ignacio Cordón [aut, cre], Francisco Charte [aut], Julián Luengo [aut], Salvador García [aut], Francisco Herrera [aut]
Maintainer: Ignacio Cordón <nacho.cordon.castillo@gmail.com>

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Package MIIVsem updated to version 0.5.3 with previous version 0.5.2 dated 2017-05-19

Title: Model Implied Instrumental Variable (MIIV) Estimation of Structural Equation Models
Description: Functions for estimating structural equation models using instrumental variables.
Author: Zachary Fisher [aut, cre], Kenneth Bollen [aut], Kathleen Gates [aut], Mikko Rönkkö [aut]
Maintainer: Zachary Fisher <fish.zachary@gmail.com>

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Package CrossVA updated to version 0.9.5 with previous version 0.9.4 dated 2018-12-11

Title: Verbal Autopsy Data Transform for Use with Various Coding Algorithms
Description: Enables transformation of Verbal Autopsy data collected with the WHO 2016 questionnaire (versions 1.4.1 & 1.5.1) for automated coding of Cause of Death using different computer algorithms. Currently supports user-supplied mappings, and provides unvalidated, experimental-stage mapping definitions to transform to InterVA4, InterVA5, Tariff 2, and InSilicoVA. This package is made available by WHO, in collaboration with the Swiss Tropical and Public Health Institute and the Bloomberg Data for Health Initiative.
Author: Eungang Choi [aut], Sam Clark [aut], Zehang Li [aut], Nicolas Maire [aut], Jason Thomas [aut, cre]
Maintainer: Jason Thomas <jarathomas@gmail.com>

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