Accession Number:

ADA089117

Title:

Maximum Likelihood Estimation for Stationary Point Processes.

Descriptive Note:

Interim rept.,

Corporate Author:

INDIANA UNIV AT BLOOMINGTON DEPT OF MATHEMATICS

Personal Author(s):

• Tuan,Pham-Dinh
• Puri,Madan L.

Report Date:

1980-08-01

Pagination or Media Count:

29.0

Abstract:

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

Descriptors:

• *STOCHASTIC PROCESSES
• *ASYMPTOTIC NORMALITY
• RANDOM VARIABLES
• CONVERGENCE
• HEURISTIC METHODS
• VECTOR SPACES
• INTEGRAL EQUATIONS
• POISSON EQUATION
• CAUCHY PROBLEM
• COMPENSATORS
• THEOREMS

Subject Categories:

• Statistics and Probability

Distribution Statement:

APPROVED FOR PUBLIC RELEASE