Estimation in regression models with stationary,dependent errors |
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| Authors: | C.A. Mc Gilchrist R.L. Sandland L.J. Hills |
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| Affiliation: | 1. Department of Statistics , University of NSW , Kensington, Australia;2. CSIRO Division of Mathematics and Statistics , Cronulla, Australia;3. School of Mathematical Sciences , NSW Institute of Technology , Broadway, Australia |
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| Abstract: | Often the unknown covariance structure of a stationary, dependent, Gaussian error sequence can be simply parametrised. The error sequence can either be directly observed or observed only through a random sequence containing a deterministic regression model. The method of scoring is used here, in conjunction with recursive estimation techniques, to effect the maximum likelihood estimation of the covariance parameters. Sequences of recursive residuals, useful in model diagnostics and data analysis, are obtained in the estimation procedure. |
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| Keywords: | stationary error regression time series method of scoring recursive estimations recursive residuals |
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