R: Covariance Matrix Estimation from princomp Object
covPC
R Documentation
Covariance Matrix Estimation from princomp Object
Description
computes the covariance matrix from a princomp object.
The number of components k can be given as input.
Usage
covPC(x, k, method)
Arguments
x
an object of class princomp.
k
number of PCs to use for covariance estimation (optional).
method
method how the PCs have been estimated (optional).
Details
There are several possibilities to estimate the principal components (PCs)
from an input data matrix, including the functions PCAproj and
PCAgrid. This function uses the estimated PCs to reconstruct
the covariance matrix. Not all PCs have to be used, the number k of
PCs (first k PCs) can be given as input to the function.
Value
cov
the estimated covariance matrix
center
the center of the data, as provided from the princomp object.
method
a string describing the method that was used to calculate the
PCs.
C. Croux, P. Filzmoser, M. Oliveira, (2007).
Algorithms for Projection-Pursuit Robust Principal Component Analysis,
Chemometrics and Intelligent Laboratory Systems, Vol. 87, pp. 218-225.
See Also
PCAgrid, PCAproj, princomp
Examples
# multivariate data with outliers
library(mvtnorm)
x <- rbind(rmvnorm(200, rep(0, 6), diag(c(5, rep(1,5)))),
rmvnorm( 15, c(0, rep(20, 5)), diag(rep(1, 6))))
pc <- princomp(x)
covPC(pc, k=2)