auto.pca

Automatic Variable Reduction Using Principal Component Analysis

CRAN Package

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.

  • Version0.3
  • R versionunknown
  • LicenseGPL-2
  • Needs compilation?No
  • Last release09/12/2017

Team

Insights

Last 30 days

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.

Last 365 days

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.

Data provided by CRAN

Binaries

Dependencies

  • Imports2 packages
  • Suggests1 package