auto.pca v0.3

0

Monthly downloads

0th

Percentile

Automatic Variable Reduction Using Principal Component Analysis

PCA done by eigenvalue decomposition of a data correlation matrix, here it automatically determines the number of factors by eigenvalue greater than 1 and it gives the uncorrelated variables based on the rotated component scores, Such that in each principal component variable which has the high variance are selected. It will be useful for non-statisticians in selection of variables. For more information, see the <http://www.ijcem.org/papers032013/ijcem_032013_06.pdf> web page.

Functions in auto.pca

Name Description
auto.pca Automatic Variable Reduction Using Principal Component Analysis
No Results!

Last month downloads

Details

Type Package
Date 2017-09-03
License GPL-2
LazyData TRUE
NeedsCompilation no
Packaged 2017-09-12 02:08:08 UTC; NSD
Repository CRAN
Date/Publication 2017-09-12 09:24:21 UTC
suggests knitr
imports plyr , psych
Contributors Navinkumar Nedunchezhian

Include our badge in your README

[![Rdoc](http://www.rdocumentation.org/badges/version/auto.pca)](http://www.rdocumentation.org/packages/auto.pca)