R: Weighted means, covariance and scattering matrices...

covw {mclust} | R Documentation

## Weighted means, covariance and scattering matrices conditioning on a weighted matrix

### Description

Compute efficiently (via Fortran code) the means, covariance and scattering matrices conditioning on a weighted or indicator matrix

### Usage

    covw(X, Z, normalize = TRUE)

### Arguments

`X` | A (n x p) data matrix, with n observations on p variables.
`Z` | A (n x G) matrix of weights, with G number of groups.
`normalize` | A logical indicating if rows of `Z` should be normalized to sum to one.

### Value

A list with the following components:

`mean` | A (p x G) matrix of weighted means.
`S` | A (p x p x G) array of weighted covariance matrices.
`W` | A (p x p x G) array of weighted scattering matrices.

### Author(s)

M. Fop and L. Scrucca

### Examples

    # Z as an indicator matrix
    X <- iris[,1:4]
    Z <- unmap(iris$Species)
    str(covw(X, Z))
    # Z as a matrix of weights
    mod <- Mclust(X, G = 3, modelNames = "VVV")
    str(covw(X, mod$z))

[Package mclust version 5.4.5 Index]