Parameter Estimation and Subset Selection for Separable lower Triangular Bilinear Models

Parameter estimation and subset selection for separable lower triangular bilinear (SLTBL) models are considered. Under a flat prior, we present an expectation-maximization (EM) algorithm to obtain the maximum likelihood estimation. Furthermore, two sub-procedures are designed to select the best subset model after an initial fitting. Example with two simulated and one real data set illustrate the feasibility and validity of the proposed methods. Copyright 2005 Blackwell Publishing Ltd.