Filtered Likelihood for Point Processes
Stanford University - Management Science & Engineering
Boston University - Department of Finance & Economics
July 28, 2011
We develop likelihood estimators of the parameters of a marked point process and of incompletely observed explanatory factors that influence the arrival intensity and mark distribution. We provide conditions guaranteeing consistency and asymptotic normality as the sample period grows. We also establish an approximation to the likelihood and analyze the convergence and asymptotic properties of the associated estimators. Numerical results illustrate our approach.
Number of Pages in PDF File: 41
Keywords: point process, filtering, parametric maximum likelihood, asymptotic theory, likelihood approximation
Date posted: July 29, 2011 ; Last revised: November 7, 2014
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