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Proceedings of the National Academy of Sciences of the United States of America logoLink to Proceedings of the National Academy of Sciences of the United States of America
. 1986 Feb;83(3):541–545. doi: 10.1073/pnas.83.3.541

Maximum likelihood estimation for stationary point processes

Madan L Puri , Pham D Tuan
PMCID: PMC322899  PMID: 16593651

Abstract

In this paper we derive the log likelihood function for point processes in terms of their stochastic intensities by using the martingale approach. For practical purposes we work with an approximate log likelihood function that 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 martingales in continuous times are derived.

Keywords: compensator, stochastic intensity, martingale, natural increasing process, point process, predictable process

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