pooled.cpc: Compute CPC by mean-correcting each group

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

Description

Subtracts the mean from each group in the data set to shift it to the origin, lumps the data, and computes principal components: if PCs for all groups are the same, this gives an estimate of CPC

Usage

pooled.cpc(x, f, 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
use	method for missing observations when computing covariances (see cov for details)

Value

A matrix of the common principal components (eigenvector of the variance-covariance matrix) of the pooled data

Author(s)

Ben Bolker

See Also

phillips.cpc

Examples

  X = simdata(npts=1000)
  pooled.cpc(X)

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