Maximum Likelihood Estimation for Stationary Point Processes.
INDIANA UNIV AT BLOOMINGTON DEPT OF MATHEMATICS
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In this paper we derive the log likelihood function for point processes in terms of their stochastic intensities, using the martingale approach. For practical purposes we work with an approximate log likelihood function which is shown to possess the usual asymptotic properties of a log likelihood function. The resulting estimates are strongly consistent and asymptotically normal under some regularity conditions. As a by-product, a strong law of large numbers and a central limit theorem for continuous martingale are derived. Author
- Statistics and Probability