Automatic Variable Reduction Using Principal Component Analysis
R package auto.pca version 0.3
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.
Software
Imports: psych,plyr
Suggests: knitr
Navinkumar Nedunchezhian <navinkumar.nedunchezhian@gmail.com>
Comprehensive R Archive Network (CRAN)
Navinkumar Nedunchezhian
GPL-2
2017-09-12
application/tgz
https://CRAN.R-project.org/package=auto.pca