cum_var: Determine the number of PCA basis vectors that capture a set...

In visualneurosciencelab/PlasticityPhenotypes: Creates a plasticity phenotype using features that correlate with PCA basis vectors

Description

Calculates the number of sequential PCA basis vectors required to explain a desired amount of the total cumulative variance.

Usage

cum_var(pca.eig.3, thresh)

Arguments

pca.eig.3	Consults the pca$eig$3 product contained in the PCA output from the FactoMineR package.
thresh	A desired threshold value of the percent total variance wished to be captured by sequential PCA basis vectors (values range from 0 – 100).

Value

Only those PCA basis vectors that contain the set threshold value of cumulative variance.

Examples

cum_var(
     pca.eig.3 = pca.scaled$eig[,3],
      thresh = 80
      )

visualneurosciencelab/PlasticityPhenotypes documentation built on Sept. 7, 2020, 2:18 p.m.