betasim: Simulate common eigenvector matrices

In tpepler/cpc: Common principal component (CPC) analysis and applications

Simulate common eigenvector matrices

Description

Simulates common eigenvector matrices of a specified size and CPC or CPC(q) structure.

Usage

betasim(k, p, q)

Arguments

k	The number of common eigenvector matrices required.
p	Number of rows/columns (variables), i.e. the size of the eigenvector matrices.
q	Number of eigenvectors that should be common to all of the matrices.

Details

The purpose of this function is for the simulation of common eigenvector matrices for use in simulation studies. CPC or CPC(q) matrices can be generated for several groups.

Value

Returns an array containing the common eigenvector matrices.

Author(s)

Theo Pepler

References

Pepler, P.T. (2014). The identification and application of common principal components. PhD dissertation in the Department of Statistics and Actuarial Science, Stellenbosch University.

Examples

# Generate three (partially) common eigenvector matrices of
# dimension p = 5, with a CPC(2) structure
betasim(k = 3, p = 5, q = 2)

tpepler/cpc documentation built on July 7, 2022, 2:13 a.m.