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gmgm (version 1.1.2)

conditional: Conditionalize a Gaussian mixture model

Description

This function conditionalizes a Gaussian mixture model (Sun et al., 2006).

Usage

conditional(gmm, y = rownames(gmm$mu)[1])

Value

A list with elements:

alpha

A numeric vector containing the mixture proportions.

mu_x

A numeric matrix containing the marginal mean vectors of the explanatory variables bound by column.

sigma_x

A list containing the marginal covariance matrices of the explanatory variables.

coeff

A list containing the regression coefficient matrices of the dependent variables on the explanatory variables.

sigma_c

A list containing the conditional covariance matrices.

Arguments

gmm

An object of class gmm.

y

A character vector containing the dependent variables (by default the first variable of gmm).

References

Sun, S., Zhang, C. and Yu, G. (2006). A Bayesian Network Approach to Traffic Flow Forecasting. IEEE Transactions on Intelligent Transportation Systems, 7(1):124--132.

Examples

Run this code
data(gmm_body)
cond <- conditional(gmm_body)

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