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Parameter Estimation and Subset Selection for Separable lower Triangular Bilinear Models
Author(s) -
Wang HaiBin
Publication year - 2005
Publication title -
journal of time series analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.576
H-Index - 54
eISSN - 1467-9892
pISSN - 0143-9782
DOI - 10.1111/j.1467-9892.2005.00421.x
Subject(s) - mathematics , bilinear interpolation , separable space , maximization , selection (genetic algorithm) , model selection , expectation–maximization algorithm , mathematical optimization , set (abstract data type) , estimation theory , maximum likelihood , estimation , algorithm , statistics , computer science , artificial intelligence , mathematical analysis , management , economics , programming language
. 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.