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

Estimates stepwise common principal components to simultaneously diagonalise several covariance matrices.

1 | ```
stepwisecpc(covmats, nvec)
``` |

`covmats ` |
Array containing the covariance matrices for the groups, created with a command such as covmats <- array(NA, dim = c(p, p, k)), where p refers to the number of rows/columns of each covariance matrix, and k is the number of groups (or covariance matrices). |

`nvec ` |
Vector containing the sample sizes of the k groups. |

Returns a list with the values:

`B ` |
Orthogonal matrix containing the estimated common eigenvectors in the columns. |

`eigenvals ` |
Matrix of which the columns contain the estimated eigenvalues of the k covariance matrices under the CPC model. |

Sarel Steel, Theo Pepler

Trendafilov, N. T. (2010). Stepwise estimation of common principal components. Computational Statistics and Data Analysis, 54(12): 3446-3457.

1 2 3 4 5 6 7 8 9 10 11 12 13 | ```
# Estimate the modal matrix for the versicolor and virginica groups
# under the common eigenvector assumption.
data(iris)
versicolor <- iris[51:100, 1:4]
virginica <- iris[101:150, 1:4]
# Create array containing the covariance matrices
S <- array(NA, dim = c(4, 4, 2))
S[, , 1] <- cov(versicolor)
S[, , 2] <- cov(virginica)
stepwisecpc(covmats = S, nvec = c(nrow(versicolor), nrow(virginica)))
``` |

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