mclustMarginalParams {mclustAddons}R Documentation

Marginal parameters from fitted GMMs via mclust

Description

Function to compute the marginal parameters from a fitted Gaussian mixture models.

Usage

mclustMarginalParams(object, ...)

gmm2margParams(pro, mu, sigma, ...)

Arguments

object

An object of class Mclust or densityMclust.

...

Further arguments passed to or from other methods.

pro

A vector of mixing proportions for each mixture component.

mu

A matrix of mean vectors for each mixture component. For a d-variate dataset on G components, the matrix has dimension (d \times G).

sigma

An array of covariance matrices for each mixture component. For a d-variate dataset on G components, the array has dimension (d \times d \times G).

Details

Given a G-component GMM with estimated mixture weight \pi_k, mean vector \mu_{k}, and covariance matrix \Sigma_{k}, for mixture component k = 1, \dots, G, then the marginal distribution has:

Value

Returns a list of two components for the mean and covariance of the marginal distribution.

Author(s)

Luca Scrucca

References

Frühwirth-Schnatter S. (2006) Finite Mixture and Markov Switching Models, Springer, Sec. 6.1.1

See Also

mclust::Mclust(), mclust::densityMclust().

Examples

x = iris[,1:4]
mod = Mclust(x, G = 3)
mod$parameters$pro
mod$parameters$mean
mod$parameters$variance$sigma
mclustMarginalParams(mod)


[Package mclustAddons version 0.9.1 Index]