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Empirical bayes approach to parameter identification in linear stochastic difference equations
Authors:
H. Bunke a;
J. Gladitz a
| Affiliation: | a Zentralinstitut fur Mathematik und Mechanik, AdW der DDR, Berlin |
DOI:
10.1080/02331887908801468
Publication Frequency:
6 issues per year
Subjects:
Mathematical Statistics;
Statistical Theory & Methods;
Statistics;
Statistics for the Biological Sciences;
Stochastic Models & Processes;
Formats available:
PDF
(English)
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Abstract
Empirical Bayesian parameter estimators and predictors for linear stochastic difference equations are constructed and discussed. Some properties as consistency and asymptotic optimality are investigated. The given methods are illustrated by the example of a univariate first order autoregressive process.
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| Keywords: Linear model; Linear stochastic difference equations; Empirical Bayesian estimation; Prediction; Asymptotic optimality; First order autoregressive process |
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