%0 Journal Article
	%A Autcha Araveeporn
	%D 2013
	%J International Journal of Mathematical and Computational Sciences
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 78, 2013
	%T The Maximum Likelihood Method of Random Coefficient Dynamic Regression Model
	%U https://publications.waset.org/pdf/5080
	%V 78
	%X The Random Coefficient Dynamic Regression (RCDR)
model is to developed from Random Coefficient Autoregressive
(RCA) model and Autoregressive (AR) model. The RCDR model
is considered by adding exogenous variables to RCA model. In this
paper, the concept of the Maximum Likelihood (ML) method is used
to estimate the parameter of RCDR(1,1) model. Simulation results
have shown the AIC and BIC criterion to compare the performance of
the the RCDR(1,1) model. The variables as the stationary and weakly
stationary data are good estimates where the exogenous variables
are weakly stationary. However, the model selection indicated that
variables are nonstationarity data based on the stationary data of the
exogenous variables.
	%P 1037 - 1042