leverage {pcaMethods}R Documentation

Extract leverages of a PCA model

Description

The leverages of PCA model indicate how much influence each observation has on the PCA model. Observations with high leverage has caused the principal components to rotate towards them. It can be used to extract both "unimportant" observations as well as picking potential outliers.

Usage

leverage(object,...)

Arguments

object a pcaRes object
... not used

Details

Defined as Tr(T(T'T)^(-1)T')

Value

The observation leverages as a numeric vector

Author(s)

Henning Redestig

References

Introduction to Mult- and Megavaraite Data Analysis uing Projection Methods (PCA and PLS), L. Eriksson, E. Johansson, N. Kettaneh-Wold and S. Wold, Umetrics 1999, p. 466

Examples

data(iris)
pcIr <- pca(iris[,1:4])
## versicolor has the lowest leverage
plot(leverage(pcIr)~iris$Species)

[Package pcaMethods version 1.22.0 Index]