ensemble.test: Ensemble test for the identification of common eigenvectors

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

View source: R/ensemble.test.R

Description

Identifies the number of common eigenvectors in several groups using the ensemble test.

Usage

1
ensemble.test(origdata, standardize = FALSE)

Arguments

origdata

List of the sample data sets.

standardize

Logical, indicating whether the data columns should be standardized (mean=0, stdev=1) before performing the ensemble test (default = FALSE).

Details

Ensemble method to identify common eigenvectors in k groups: majority vote on number of common eigenvectors from Flury's AIC, Bootstrap Vector Correlation Distribution (BVD), Bootstrap Confidence Regions (BCR), Random Vector Correlations (RVC) and Bootstrap hypothesis test (BootTest) methods.

Value

Returns a list with the following components:

Results

Row 1: order of common eigenvectors in B; Row 2-5: results from AIC, BVD, BCR and RVC tests (1 = eigenvector common); Row 6: ensemble test common eigenvector indicator (1 = eigenvector common).

commonvecs

Positions of the common eigenvectors in the modal matrix.

commonvecmat

The estimated common eigenvectors, extracted from the modal matrix.

Note

Note that this implementation of the Ensemble test 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

flury.AIC, BVD, BCR, RVC, and BootTest

Examples

1
2
3
4
5
6
7
# 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]
ensemble.test(origdata = list(versicolor, virginica))

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