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MODEL REFERENCE ADAPTIVE SYSTEM ESTIMATES FOR COUNTING PROCESSES
Author(s) -
Thavaneswaran A.
Publication year - 1986
Publication title -
statistica neerlandica
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.52
H-Index - 39
eISSN - 1467-9574
pISSN - 0039-0402
DOI - 10.1111/j.1467-9574.1986.tb01165.x
Subject(s) - estimator , mathematics , adaptive estimator , maximum likelihood , estimation theory , process (computing) , random variate , counting process , algorithm , mathematical optimization , computer science , statistics , random variable , operating system
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.