Maximum likelihood estimation for stationary point processes
AUTOR(ES)
Puri, Madan L.
RESUMO
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.
ACESSO AO ARTIGO
http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=322899Documentos Relacionados
- Maximum Likelihood Estimation of Population Parameters
- Maximum Likelihood Estimation of Linkage and Interference from Tetrad Data
- Comment concerning Maximum Likelihood Estimation of Linkage and Interference from Tetrad Data
- Maximum Likelihood Estimation of the Number of Nucleotide Substitutions from Restriction Sites Data
- The Application of the "Method of Maximum Likelihood" to the Estimation of Linkage