View source: R/ensemble.test.R
ensemble.test | R Documentation |
Identifies the number of common eigenvectors in several groups using the ensemble test.
ensemble.test(origdata, standardize = FALSE)
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). |
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.
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 that this implementation of the Ensemble test can currently handle only two groups of data.
Theo Pepler
Pepler, P.T. (2014). The identification and application of common principal components. PhD dissertation in the Department of Statistics and Actuarial Science, Stellenbosch University.
flury.AIC
, BVD
, BCR
, RVC
, and BootTest
# 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))
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