psda: Polygonal Symbolic Data Analysis

A toolbox in symbolic data framework as a statistical learning and data mining solution for symbolic polygonal data analysis. This study is a new approach in data analysis and it was proposed by Silva et al. (2019) <doi:10.1016/j.knosys.2018.08.009>. The package presents the estimation of main descriptive statistical measures, e.g, mean, covariance, variance, correlation and coefficient of variation. In addition, a method to obtain polygonal data from classical data is presented. Empirical probability distribution function based on symbolic polygonal histogram and a regression model with its main measures are presented.

Version: 1.3.2
Depends: R (≥ 3.1)
Imports: ggplot2, rgeos, plyr, sp, raster, stats
Suggests: testthat
Published: 2019-06-24
Author: Wagner Silva [aut, cre, ths], Renata Souza [aut], Francisco Cysneiros [aut]
Maintainer: Wagner Silva <wjfs at cin.ufpe.br>
License: GPL-2
NeedsCompilation: no
Citation: psda citation info
CRAN checks: psda results

Downloads:

Reference manual: psda.pdf
Package source: psda_1.3.2.tar.gz
Windows binaries: r-devel: psda_1.3.2.zip, r-release: psda_1.3.2.zip, r-oldrel: psda_1.3.2.zip
OS X binaries: r-release: psda_1.3.2.tgz, r-oldrel: psda_1.3.2.tgz
Old sources: psda archive

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