| conditional {gmgm} | R Documentation |
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])
Arguments
gmm |
An object of class |
y |
A character vector containing the dependent variables (by default
the first variable of |
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. |
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
data(gmm_body)
cond <- conditional(gmm_body)