calc.cpcerr: Calculate errors of CPC eigenvectors

In bbolker/cpcbp: common principal components/back-projection analysis

Description

Use Flury's formulas to calculate variance-covariance matrix of first CPC eigenvector components (or variances of all CPC eigenvector components)

Usage

calc.cpcerr(x, f, cpcmat = NULL,  calc.cov = TRUE, use="complete.obs")

Arguments

x	a numeric matrix (or data frame) with all numeric values, or (if f is missing) a list of a data matrix and a grouping variable
f	a factor describing the group structure of the data
cpcmat	CPC matrix
calc.cov	(logical) calculate variance-covariance matrix of elements of first eigenvector?
use	method for missing observations when computing covariances (see cov for details)

Value

Either (if calc.cov==TRUE) the variance-covariance matrix of the elements of the first common principal component eigenvector, or (if calc.cov==FALSE) the variances of the elements of all of the CPC values

Author(s)

Ben Bolker

Examples

  X=simdata(npts=200)
  calc.cpcerr(X)
  calc.cpcerr(X,calc.cov=FALSE)

bbolker/cpcbp documentation built on May 11, 2019, 9:28 p.m.