Exact Maximum Likelihood Estimation of Vector Arma Processes
The problems of evaluating and subsequently maximizing the exact likelihood function of vector autoregressive moving average (ARMA) models are considered separately. A new and efficient procedure for evaluating the exact likelihood function is presented. This method puts together a set of useful features that can only be found separately in currently available algorithms. A procedure for maximizing the exact likelihood function, which takes full advantage of the properties offered by the evaluation algorithm, is also considered. Combining these two procedures, a new algorithm for exact maximum likelihood estimation of vector ARMA models is obtained. Comparisons with existing procedures, in terms of both analytical arguments and a numerical example, are given to show that the new estimation algorithm performs at least as well as existing ones, and that relevant real situations occur in which it does better.
Advances in statistical analysis and statistical computing
TSE, Yiu Kuen and TSE, Y. M..
Exact Maximum Likelihood Estimation of Vector Arma Processes. (1989). Advances in statistical analysis and statistical computing. 2, 71-84. Research Collection School Of Economics.
Available at: http://ink.library.smu.edu.sg/soe_research/757
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