MODEL REFERENCE ADAPTIVE SYSTEM ESTIMATES FOR COUNTING PROCESSES |
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| Authors: | A Thavaneswaran |
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| Institution: | Department of Statistics and Actuarial Science University of Waterloo Waterloo, Ontario Canada, N2L 3G1 |
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| Abstract: | The adaptive estimation procedure of the model reference adaptive system is modified and applied to counting process models. Maximum likelihood estimates constitute a subclass of the adaptive estimators considered. The adaptive estimator is shown to be strongly consistent and to converge in law to a normal variate. Applications are considered; for example properties of the adaptive estimate are obtained for a periodic intensity model. |
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| Keywords: | Counting Processes filtering algorithm stochastic differential equations M–filter |
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