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: |
1.4.0 |
| Depends: |
R (≥ 3.1) |
| Imports: |
ggplot2, rgeos, plyr, sp, raster, stats |
| Suggests: |
testthat, knitr, rmarkdown |
| Published: |
2020-05-24 |
| Author: |
Wagner Silva [aut, cre, ths],
Renata Souza [aut],
Francisco Cysneiros [aut] |
| Maintainer: |
Wagner Silva <wjfs at cin.ufpe.br> |
| BugReports: |
https://github.com/wagnerjorge/psda/issues |
| License: |
GPL-2 |
| URL: |
https://github.com/wagnerjorge/psda |
| NeedsCompilation: |
no |
| Citation: |
psda citation info |
| Materials: |
README |
| CRAN checks: |
psda results |
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