MAXIMUM LIKELIHOOD ESTIMATION OF PARAMETERS IN RENEWAL AND MARKOV-RENEWAL PROCESSES

Sampling procedures using randomized observation-points are suggested for estimating parameters in renewal and Markov renewal models. The usual asymptotic properties of the maximum likelihood method are shown to hold. The method we suggest provides a solution to the ML estimation problem in either or both of the following situations: (i) observations on between-event intervals are unavailable, (ii) the interval densities are unknown or difficult to evaluate while their Laplace-Stieltjes transforms are known.