Description Usage Arguments Details Value Author(s) References Examples

Calculates the size of back-projection errors, based on errors of common principal components

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`x` |
a numeric matrix (or data frame with all numeric values, or (if f is missing) a list of a data matrix and a grouping variable |

`f` |
a factor describing the group structure of the data |

`cpcmat` |
common principal components matrix (if already computed) |

`m` |
matrix of mean values of variables by group (if already computed) |

`eigvar` |
variances of eigenvalues (if already computed) |

`use` |
method for missing observations when computing covariances
(see |

`debug` |
(logical) print debugging information? |

`center` |
center group means on grand mean? |

Uses CPC, variances of CPC (eigenvector) components, and means of
groups to calculate total back-projection errors in variables.
If `cpcmat`

is not provided, calls `cpcvecfun`

to
compute CPC; if `eigvar`

is not provided, calls
`calc.cpcerr`

to calculate variances on eigenvalues.

If `new=TRUE`

, a matrix of back-projection errors by
variable and group; otherwise,
a vector of total back-projection errors in each variable.

Ben Bolker

Flury

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