Exact maximum likelihood estimation of structured or unit root multivariate time series models
نویسندگان
چکیده
The exact likelihood function of a Gaussian vector autoregressive-moving average (VARMA) model is evaluated in two non standard cases: (a) a parsimonious structured form, such as obtained in the echelon form structure or the scalar component model (SCM) structure; (b) a partially non stationary (unit root) model in error-correction form. The starting point is Shea’s algorithm (1987, 1989) for standard stationary and invertible VARMA models. Our algorithm also provides the parameter estimates and their standard errors. The small sample properties of our algorithm were studied by Monte Carlo methods. Examples with real data are provided.
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عنوان ژورنال:
- Computational Statistics & Data Analysis
دوره 50 شماره
صفحات -
تاریخ انتشار 2006