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

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

1 | ```
BCR(origdata, reps = 1000)
``` |

`origdata` |
List of the sample data sets. |

`reps` |
Number of bootstrap replications to use. |

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

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 that this implementation of the BCR method 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.

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