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) . 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.


Reference manual

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1.4.0 by Wagner Silva, a year ago


Report a bug at https://github.com/wagnerjorge/psda/issues

Browse source code at https://github.com/cran/psda

Authors: Wagner Silva [aut, cre, ths] , Renata Souza [aut] , Francisco Cysneiros [aut]

Documentation:   PDF Manual  

GPL-2 license

Imports ggplot2, rgeos, plyr, sp, raster, stats

Suggests testthat, knitr, rmarkdown

See at CRAN