BCR: Bootstrap confidence regions (BCR) method

Description Usage Arguments Details Value Note Author(s) References See Also Examples

View source: R/BCR.R

Description

Identifies the number of common eigenvectors in several groups using the bootstrap confidence regions (BCR) method.

Usage

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BCR(origdata, reps = 1000)

Arguments

origdata

List of the sample data sets.

reps

Number of bootstrap replications to use.

Details

Calculates 95% bootstrap confidence regions for eigenvector pairs; if the regions overlap, the eigenvectors are considered to be common.

Value

Returns a data frame with the columns:

Common eigenvector

Order of the eigenvectors in the model matrix.

common.ind

Indicator of eigenvector commonness (1 = common eigenvector).

Note

Note that this implementation of the BCR method can currently handle only two groups of data.

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.

See Also

ensemble.test

Examples

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# Determine number of common eigenvectors in the covariance matrices of the 
# versicolor and virginica groups

data(iris)
versicolor <- iris[51:100, 1:4]
virginica <- iris[101:150, 1:4]
BCR(origdata = list(versicolor, virginica))

tpepler/cpc documentation built on Nov. 19, 2017, 1:19 p.m.