Sun, 27 Jan 2019

Package dtwSat updated to version 0.2.5 with previous version 0.2.4 dated 2018-05-25

Title: Time-Weighted Dynamic Time Warping for Satellite Image Time Series Analysis
Description: Provides an implementation of the Time-Weighted Dynamic Time Warping (TWDTW) method for land cover mapping using satellite image time series. TWDTW is based on the Dynamic Time Warping technique and has achieved high accuracy for land cover classification using satellite data. The method is based on comparing unclassified satellite image time series with a set of known temporal patterns (e.g. phenological cycles associated with the vegetation). Using 'dtwSat' the user can build temporal patterns for land cover types, apply the TWDTW analysis for satellite datasets, visualize the results of the time series analysis, produce land cover maps, create temporal plots for land cover change, and compute accuracy assessment metrics.
Author: Victor Maus [aut, cre] (<https://orcid.org/0000-0002-7385-4723>), Marius Appel [ctb], Nikolas Kuschnig [ctb], Toni Giorgino [ctb]
Maintainer: Victor Maus <vwmaus1@gmail.com>

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New package shar with initial version 0.1
Type: Package
Package: shar
Title: Species-Habitat Associations
Version: 0.1
Authors@R: c(person("Maximillian H.K.", "Hesselbarth", email = "maximilian.hesselbarth@uni-goettingen.de", role = c("aut", "cre"), comment = c(ORCID = "0000-0003-1125-9918")), person("Marco", "Sciaini", email = "sciaini.marco@gmail.com", role = "aut", comment = c(ORCID = '0000-0002-3042-5435')))
Maintainer: Maximillian H.K. Hesselbarth <maximilian.hesselbarth@uni-goettingen.de>
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>.
License: GPL-3
URL: https://r-spatialecology.github.io/shar
BugReports: https://github.com/r-spatialecology/shar/issues
Depends: R (>= 3.1)
Imports: classInt, dplyr, raster, spatstat
RoxygenNote: 6.1.1
Suggests: covr, testthat, knitr, rmarkdown
VignetteBuilder: knitr
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2019-01-19 15:19:17 UTC; Maximilian
Author: Maximillian H.K. Hesselbarth [aut, cre] (<https://orcid.org/0000-0003-1125-9918>), Marco Sciaini [aut] (<https://orcid.org/0000-0002-3042-5435>)
Repository: CRAN
Date/Publication: 2019-01-27 23:50:02 UTC

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New package nonneg.cg with initial version 0.1
Package: nonneg.cg
Type: Package
Title: Non-Negative Conjugate-Gradient Minimizer
Version: 0.1
Date: 2019-01-03
Author: David Cortes
Maintainer: David Cortes <david.cortes.rivera@gmail.com>
Description: Minimize a differentiable function subject to all the variables being non-negative (i.e. >= 0), using a Conjugate-Gradient algorithm based on a modified Polak-Rubiere-Polyak formula as described in (Li, Can, 2013, <https://www.hindawi.com/journals/jam/2013/986317/abs/>).
License: BSD_2_clause + file LICENSE
Imports: Rcpp (>= 0.12.19)
LinkingTo: Rcpp
RoxygenNote: 6.1.1
NeedsCompilation: yes
Packaged: 2019-01-19 22:06:11 UTC; david
Repository: CRAN
Date/Publication: 2019-01-28 00:00:03 UTC

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New package neo4r with initial version 0.1.0
Package: neo4r
Title: A 'Neo4J' Driver
Version: 0.1.0
Authors@R: c(person(given = "Colin", family = "Fay", role = c("cre", "aut"), email = "contact@colinfay.me", comment = structure("0000-0001-7343-1846", .Names = "ORCID")), person(given = "ThinkR", role = "cph"), person(given = "Neo4J", role = "spn"))
Description: A Modern and Flexible 'Neo4J' Driver, allowing you to query data on a 'Neo4J' server and handle the results in R. It's modern in the sense it provides a driver that can be easily integrated in a data analysis workflow, especially by providing an API working smoothly with other data analysis and graph packages. It's flexible in the way it returns the results, by trying to stay as close as possible to the way 'Neo4J' returns data. That way, you have the control over the way you will compute the results. At the same time, the result is not too complex, so that the "heavy lifting" of data wrangling is not left to the user.
License: MIT + file LICENSE
URL: https://github.com/neo4j-rstats/neo4r
BugReports: https://github.com/neo4j-rstats/neo4r/issues
Imports: attempt, data.table, glue, httr, igraph, jsonlite, magrittr, purrr, R6, rlang, rstudioapi, shiny, tibble, tidyr, tidyselect, utils
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2019-01-18 22:59:45 UTC; colin
Author: Colin Fay [cre, aut] (<https://orcid.org/0000-0001-7343-1846>), ThinkR [cph], Neo4J [spn]
Maintainer: Colin Fay <contact@colinfay.me>
Repository: CRAN
Date/Publication: 2019-01-27 23:20:03 UTC

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Package unitizer updated to version 1.4.6 with previous version 1.4.5 dated 2017-11-24

Title: Interactive R Unit Tests
Description: Simplifies regression tests by comparing objects produced by test code with earlier versions of those same objects. If objects are unchanged the tests pass, otherwise execution stops with error details. If in interactive mode, tests can be reviewed through the provided interactive environment.
Author: Brodie Gaslam [aut, cre]
Maintainer: Brodie Gaslam <brodie.gaslam@yahoo.com>

Diff between unitizer versions 1.4.5 dated 2017-11-24 and 1.4.6 dated 2019-01-27

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Package mizer updated to version 1.0.1 with previous version 1.0 dated 2018-04-30

Title: Multi-Species sIZE Spectrum Modelling in R
Description: A set of classes and methods to set up and run multi-species, trait based and community size spectrum ecological models, focused on the marine environment.
Author: Finlay Scott [aut, cph], Julia Blanchard [aut, cph], Ken Andersen [aut, cph], Gustav Delius [ctb, cre], Richard Southwell [ctb]
Maintainer: Gustav Delius <gustav.delius@york.ac.uk>

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Package LexisNexisTools updated to version 0.2.2 with previous version 0.2.1 dated 2019-01-21

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 greybox updated to version 0.4.1 with previous version 0.4.0 dated 2019-01-04

Title: Toolbox for Model Building and Forecasting
Description: Implements functions and instruments for regression model building and its application to forecasting. The main scope of the package is in variables selection and models specification for cases of time series data. This includes promotional modelling, selection between different dynamic regressions with non-standard distributions of errors, selection based on cross validation, solutions to the fat regression model problem and more. Models developed in the package are tailored specifically for forecasting purposes. So as a results there are several methods that allow producing forecasts from these models and visualising them.
Author: Ivan Svetunkov [aut, cre] (Lecturer at Centre for Marketing Analytics and Forecasting, Lancaster University, UK)
Maintainer: Ivan Svetunkov <ivan@svetunkov.ru>

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Package benchmarkmeData updated to version 1.0.0 with previous version 0.5.1 dated 2017-08-29

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

Diff between benchmarkmeData versions 0.5.1 dated 2017-08-29 and 1.0.0 dated 2019-01-27

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Package MazamaSpatialUtils updated to version 0.6.0 with previous version 0.5.4 dated 2018-09-18

Title: Spatial Data Download and Utility Functions
Description: A suite of conversion scripts to create internally standardized spatial polygons data frames. Utility scripts use these data sets to return values such as country, state, timezone, watershed, etc. associated with a set of longitude/latitude pairs. (They also make cool maps.)
Author: Jonathan Callahan [aut, cre], Tom Bergamaschi [aut], Ruby Fore [aut], Will Leahy [aut], Helen Miller [aut], Henry Nguyen [aut], Robin Winstanley [aut], Alice Yang [aut]
Maintainer: Jonathan Callahan <jonathan.s.callahan@gmail.com>

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Package DHS.rates updated to version 0.6.0 with previous version 0.5.0 dated 2019-01-12

Title: Calculates Demographic Indicators
Description: Calculates key indicators such as fertility rates (Total Fertility Rate (TFR), General Fertility Rate (GFR), and Age Specific Fertility Rate (ASFR)) using Demographic and Health Survey (DHS) women/individual data, and childhood mortality probabilities and rates such as Neonatal Mortality Rate (NNMR), Post-neonatal Mortality Rate (PNNMR), Infant Mortality Rate (IMR), Child Mortality Rate (CMR), and Under-five Mortality Rate (U5MR). In addition to the indicators, the 'DHS.rates' package estimates sampling errors indicators such as Standard Error (SE), Design Effect (DEFT), Relative Standard Error (RSE) and Confidence Interval (CI). The package is developed according to the DHS methodology of calculating the fertility indicators and the childhood mortality rates outlined in the "Guide to DHS Statistics" (Croft, Trevor N., Aileen M. J. Marshall, Courtney K. Allen, et al. 2018, <https://dhsprogram.com/Data/Guide-to-DHS-Statistics/index.cfm>) and the DHS methodology of estimating the sampling errors indicators outlined in the "DHS Sampling and Household Listing Manual" (ICF International 2012, <https://dhsprogram.com/pubs/pdf/DHSM4/DHS6_Sampling_Manual_Sept2012_DHSM4.pdf>).
Author: Mahmoud Elkasabi
Maintainer: Mahmoud Elkasabi <mahmoud.elkasabi@icf.com>

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Package AmigaFFH updated to version 0.2.0 with previous version 0.1.2 dated 2018-03-14

Title: Commodore Amiga File Format Handler
Description: Modern software often poorly support older file formats. This package intends to handle many file formats that were native to the antiquated Commodore Amiga machine. This package focuses on file types from the older Amiga operating systems (<= 3.0). It will read and write specific file formats and coerces them into more contemporary data.
Author: Pepijn de Vries [aut, cre, dtc]
Maintainer: Pepijn de Vries <pepijn.devries@outlook.com>

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Package vtreat updated to version 1.3.5 with previous version 1.3.4 dated 2019-01-02

Title: A Statistically Sound 'data.frame' Processor/Conditioner
Description: A 'data.frame' processor/conditioner that prepares real-world data for predictive modeling in a statistically sound manner. 'vtreat' prepares variables so that data has fewer exceptional cases, making it easier to safely use models in production. Common problems 'vtreat' defends against: 'Inf', 'NA', too many categorical levels, rare categorical levels, and new categorical levels (levels seen during application, but not during training). Reference: "'vtreat': a data.frame Processor for Predictive Modeling", 'Zumel', 'Mount', 2016, DOI:10.5281/zenodo.1173314.
Author: John Mount [aut, cre], Nina Zumel [aut], Win-Vector LLC [cph]
Maintainer: John Mount <jmount@win-vector.com>

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Package stepR updated to version 2.0-3 with previous version 2.0-2 dated 2018-04-06

Title: Multiscale Change-Point Inference
Description: Allows fitting of step-functions to univariate serial data where neither the number of jumps nor their positions is known by implementing the multiscale regression estimators SMUCE (K. Frick, A. Munk and H. Sieling, 2014) <doi:10.1111/rssb.12047> and HSMUCE (F. Pein, H. Sieling and A. Munk, 2017) <doi:10.1111/rssb.12202>. In addition, confidence intervals for the change-point locations and bands for the unknown signal can be obtained.
Author: Pein Florian [aut, cre], Thomas Hotz [aut], Hannes Sieling [aut], Timo Aspelmeier [ctb]
Maintainer: Pein Florian <fpein@uni-goettingen.de>

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Package rms updated to version 5.1-3 with previous version 5.1-2 dated 2018-01-07

Title: Regression Modeling Strategies
Description: Regression modeling, testing, estimation, validation, graphics, prediction, and typesetting by storing enhanced model design attributes in the fit. 'rms' is a collection of functions that assist with and streamline modeling. It also contains functions for binary and ordinal logistic regression models, ordinal models for continuous Y with a variety of distribution families, and the Buckley-James multiple regression model for right-censored responses, and implements penalized maximum likelihood estimation for logistic and ordinary linear models. 'rms' works with almost any regression model, but it was especially written to work with binary or ordinal regression models, Cox regression, accelerated failure time models, ordinary linear models, the Buckley-James model, generalized least squares for serially or spatially correlated observations, generalized linear models, and quantile regression.
Author: Frank E Harrell Jr <f.harrell@vanderbilt.edu>
Maintainer: Frank E Harrell Jr <f.harrell@vanderbilt.edu>

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Package wavelets updated to version 0.3-0.1 with previous version 0.3-0 dated 2013-12-18

Title: Functions for Computing Wavelet Filters, Wavelet Transforms and Multiresolution Analyses
Description: Contains functions for computing and plotting discrete wavelet transforms (DWT) and maximal overlap discrete wavelet transforms (MODWT), as well as their inverses. Additionally, it contains functionality for computing and plotting wavelet transform filters that are used in the above decompositions as well as multiresolution analyses.
Author: Eric Aldrich <ealdrich@gmail.com>
Maintainer: Eric Aldrich <ealdrich@gmail.com>

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Package sigr updated to version 1.0.4 with previous version 1.0.3 dated 2018-11-04

Title: Succinct and Correct Statistical Summaries for Reports
Description: Succinctly and correctly format statistical summaries of various models and tests (F-test, Chi-Sq-test, Fisher-test, T-test, and rank-significance). The main purpose is unified reporting of experimental results, working around issue such as the difficulty of extracting model summary facts (such as with 'lm'/'glm'). This package also includes empirical tests, such as bootstrap estimates.
Author: John Mount [aut, cre], Nina Zumel [aut], Win-Vector LLC [cph]
Maintainer: John Mount <jmount@win-vector.com>

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Package purrr updated to version 0.3.0 with previous version 0.2.5 dated 2018-05-29

Title: Functional Programming Tools
Description: A complete and consistent functional programming toolkit for R.
Author: Lionel Henry [aut, cre], Hadley Wickham [aut], RStudio [cph, fnd]
Maintainer: Lionel Henry <lionel@rstudio.com>

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Package gplots updated to version 3.0.1.1 with previous version 3.0.1 dated 2016-03-30

Title: Various R Programming Tools for Plotting Data
Description: Various R programming tools for plotting data, including: - calculating and plotting locally smoothed summary function as ('bandplot', 'wapply'), - enhanced versions of standard plots ('barplot2', 'boxplot2', 'heatmap.2', 'smartlegend'), - manipulating colors ('col2hex', 'colorpanel', 'redgreen', 'greenred', 'bluered', 'redblue', 'rich.colors'), - calculating and plotting two-dimensional data summaries ('ci2d', 'hist2d'), - enhanced regression diagnostic plots ('lmplot2', 'residplot'), - formula-enabled interface to 'stats::lowess' function ('lowess'), - displaying textual data in plots ('textplot', 'sinkplot'), - plotting a matrix where each cell contains a dot whose size reflects the relative magnitude of the elements ('balloonplot'), - plotting "Venn" diagrams ('venn'), - displaying Open-Office style plots ('ooplot'), - plotting multiple data on same region, with separate axes ('overplot'), - plotting means and confidence intervals ('plotCI', 'plotmeans'), - spacing points in an x-y plot so they don't overlap ('space').
Author: Gregory R. Warnes, Ben Bolker, Lodewijk Bonebakker, Robert Gentleman, Wolfgang Huber Andy Liaw, Thomas Lumley, Martin Maechler, Arni Magnusson, Steffen Moeller, Marc Schwartz, Bill Venables
Maintainer: Gregory R. Warnes <greg@warnes.net>

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Package stacomiR updated to version 0.5.4.1 with previous version 0.5.4.0 dated 2018-10-11

Title: Fish Migration Monitoring
Description: Graphical outputs and treatment for a database of fish pass monitoring. It is a part of the 'STACOMI' open source project developed in France by the French Agency for Biodiversity (AFB) institute to centralize data obtained by fish pass monitoring. This version is available in French and English. See <http://stacomir.r-forge.r-project.org/> for more information on 'STACOMI'.
Author: Cedric Briand [aut, cre], Marion Legrand [aut], Timothee Besse [aut]
Maintainer: Cedric Briand <cedric.briand00@gmail.com>

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New package mme with initial version 0.1-6
Package: mme
Type: Package
Title: Multinomial Mixed Effects Models
Version: 0.1-6
Date: 2019-01-27
Author: E. Lopez-Vizcaino, M.J. Lombardia and D. Morales
Maintainer: E. Lopez-Vizcaino <esther.lopez@ige.eu>
Depends: R (>= 1.8.0), MASS
Imports: Matrix, methods
Description: Fit Gaussian Multinomial mixed-effects models for small area estimation: Model 1, with one random effect in each category of the response variable (Lopez-Vizcaino,E. et al., 2013) <doi:10.1177/1471082X13478873>; Model 2, introducing independent time effect; Model 3, introducing correlated time effect. mme calculates direct and parametric bootstrap MSE estimators (Lopez-Vizcaino,E et al., 2014) <doi:10.1111/rssa.12085>.
License: GPL (>= 2)
LazyData: yes
Packaged: 2019-01-27 12:43:14 UTC; Oscar Iglesias
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2019-01-27 15:40:13 UTC

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Package automl updated to version 1.2.7 with previous version 1.2.6 dated 2018-12-08

Title: Deep Learning with Metaheuristic
Description: Fits from simple regression to highly customizable deep neural networks either with gradient descent or metaheuristic, using automatic hyper parameters tuning and custom cost function. A mix inspired by the common tricks on Deep Learning and Particle Swarm Optimization.
Author: Alex Boulangé [aut, cre]
Maintainer: Alex Boulangé <aboul@free.fr>

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Package gWidgets updated to version 0.0-54.1 with previous version 0.0-54 dated 2014-08-27

Title: gWidgets API for Building Toolkit-Independent, Interactive GUIs
Description: Provides a toolkit-independent API for building interactive GUIs. At least one of the 'gWidgetsXXX packages', such as gWidgetstcltk, needs to be installed. Some icons are on loan from the scigraphica project <http://scigraphica.sourceforge.net>.
Author: John Verzani. Based on the iwidgets code of Simon Urbanek and suggestions by Simon Urbanek, Philippe Grosjean and Michael Lawrence
Maintainer: John Verzani <jverzani@gmail.com>

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Package DatabionicSwarm updated to version 1.1.1 with previous version 1.1.0 dated 2018-07-03

Title: Swarm Intelligence for Self-Organized Clustering
Description: Algorithms implementing populations of agents that interact with one another and sense their environment may exhibit emergent behavior such as self-organization and swarm intelligence. Here, a swarm system called databionic swarm (DBS) is introduced. DBS is able to adapt itself to structures of high-dimensional data such as natural clusters characterized by distance and/or density based structures in the data space. The first module is the parameter-free projection method called Pswarm (Pswarm()), which exploits the concepts of self-organization and emergence, game theory, swarm intelligence and symmetry considerations. The second module is the parameter-free high-dimensional data visualization technique, which generates projected points on the topographic map with hypsometric tints defined by the generalized U-matrix (GeneratePswarmVisualization()). The third module is the clustering method itself with non-critical parameters (DBSclustering()). Clustering can be verified by the visualization and vice versa. The term DBS refers to the method as a whole. It enables even a non-professional in the field of data mining to apply its algorithms for visualization and/or clustering to data sets with completely different structures drawn from diverse research fields. The package is based on the book of Thrun, M.C.: "Projection Based Clustering through Self-Organization and Swarm Intelligence" (2018) <DOI:10.1007/978-3-658-20540-9>. A comparison to 26 common clustering algorithms on 15 datasets is presented on the website.
Author: Michael Thrun [aut, cre, cph]
Maintainer: Michael Thrun <m.thrun@gmx.net>

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Package GeneralizedUmatrix updated to version 1.1.4 with previous version 1.1.2 dated 2018-07-03

Title: Credible Visualization for Two-Dimensional Projections of Data
Description: Projections are common dimensionality reduction methods, which represent high-dimensional data in a two-dimensional space. However, when restricting the output space to two dimensions, which results in a two dimensional scatter plot (projection) of the data, low dimensional similarities do not represent high dimensional distances coercively [Thrun, 2018]. This could lead to a misleading interpretation of the underlying structures [Thrun, 2018]. By means of the 3D topographic map the generalized Umatrix is able to depict errors of these two-dimensional scatter plots. The package is based on the book of Thrun, M.C.: "Projection Based Clustering through Self-Organization and Swarm Intelligence" (2018) <DOI:10.1007/978-3-658-20540-9>.
Author: Michael Thrun [aut, cre, cph], Alfred Ultsch [ths]
Maintainer: Michael Thrun <m.thrun@gmx.net>

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Package msgps updated to version 1.3.1 with previous version 1.3 dated 2012-05-17

Title: Degrees of Freedom of Elastic Net, Adaptive Lasso and Generalized Elastic Net
Description: Computes the degrees of freedom of the lasso, elastic net, generalized elastic net and adaptive lasso based on the generalized path seeking algorithm. The optimal model can be selected by model selection criteria including Mallows' Cp, bias-corrected AIC (AICc), generalized cross validation (GCV) and BIC.
Author: Kei Hirose
Maintainer: Kei Hirose <mail@keihirose.com>

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Package sampler updated to version 0.2.3 with previous version 0.2.2 dated 2018-07-20

Title: Sample Design, Drawing & Data Analysis Using Data Frames
Description: Determine sample sizes, draw samples, and conduct data analysis using data frames. It specifically enables you to determine simple random sample sizes, stratified sample sizes, and complex stratified sample sizes using a secondary variable such as population; draw simple random samples and stratified random samples from sampling data frames; determine which observations are missing from a random sample, missing by strata, duplicated within a dataset; and perform data analysis, including proportions, margins of error and upper and lower bounds for simple, stratified and cluster sample designs.
Author: Michael Baldassaro
Maintainer: Michael Baldassaro <mbaldassaro@gmail.com>

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Package WVPlots updated to version 1.0.8 with previous version 1.0.7 dated 2018-12-17

Title: Common Plots for Analysis
Description: Select data analysis plots, under a standardized calling interface implemented on top of 'ggplot2' and 'plotly'. Plots of interest include: 'ROC', gain curve, scatter plot with marginal distributions, conditioned scatter plot with marginal densities, box and stem with matching theoretical distribution, and density with matching theoretical distribution.
Author: John Mount [aut, cre], Nina Zumel [aut], Win-Vector LLC [cph]
Maintainer: John Mount <jmount@win-vector.com>

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 R/ScatterHist.R                |    4 ++--
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 vignettes/WVPlots_concept.Rmd  |    2 +-
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More information about WVPlots at CRAN
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Package BANOVA updated to version 1.1.2 with previous version 1.1.1 dated 2018-01-22

Title: Hierarchical Bayesian ANOVA Models
Description: It covers several Bayesian Analysis of Variance (BANOVA) models used in analysis of experimental designs in which both within- and between- subjects factors are manipulated. They can be applied to data that are common in the behavioral and social sciences. The package includes: Hierarchical Bayes ANOVA models with normal response, t response, Binomial (Bernoulli) response, Poisson response, ordered multinomial response and multinomial response variables. All models accommodate unobserved heterogeneity by including a normal distribution of the parameters across individuals. Outputs of the package include tables of sums of squares, effect sizes and p-values, and tables of predictions, which are easily interpretable for behavioral and social researchers. The floodlight analysis and mediation analysis based on these models are also provided. BANOVA uses 'Stan' and 'JAGS' as the computational platform.
Author: Chen Dong, Michel Wedel
Maintainer: Chen Dong <cdong@math.umd.edu>

Diff between BANOVA versions 1.1.1 dated 2018-01-22 and 1.1.2 dated 2019-01-27

 DESCRIPTION                          |    8 
 MD5                                  |   56 ++-
 NAMESPACE                            |    2 
 NEWS                                 |    7 
 R/BANOVA.mediation.R                 |  507 ++++++++++++++++++++++++++---------
 R/BANOVA.run.R                       |   63 ++--
 R/cal.flood.effects.R                |   44 +--
 R/cal.mediation.effects.R            |   12 
 R/cal.mediation.effects.individual.R |only
 R/design.matrix.R                    |    7 
 R/effect.matrix.factor.R             |    5 
 R/effect.matrix.interaction.R        |   12 
 R/effect.matrix.mediator.R           |   13 
 R/floodlight.analysis.R              |   32 +-
 R/multi.design.matrix.R              |   12 
 R/multi.effect.matrix.factor.R       |    5 
 R/multi.effect.matrix.interaction.R  |    5 
 R/multi.print.table.means.R          |   26 -
 R/print.BANOVA.mediation.R           |   15 -
 R/print.table.means.R                |   40 +-
 R/table.ANCOVA.R                     |   30 +-
 R/table.predictions.R                |   18 -
 R/util.R                             |only
 build/vignette.rds                   |binary
 inst/doc/banova_examples.html        |   28 +
 man/BANOVA-package.Rd                |    4 
 man/BANOVA.mediation.Rd              |    7 
 man/BANOVA.run.Rd                    |    7 
 man/colorad.Rd                       |   30 +-
 src/install.libs.R                   |    6 
 30 files changed, 698 insertions(+), 303 deletions(-)

More information about BANOVA at CRAN
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