Likelihood Ratio Derivative Estimators for Stochastic Systems
P. W. Glynn
Proceedings of the 1989 Winter Simulation Conference, 374-380 (1989)
This paper discusses likelihood ratio derivative estimation techniques for stochastic systems. After a brief review of the basic concepts, likelihood ratio derivative estimators are presented for the following classes of stochastic processes: time homogeneous dlscrete-time Markov chains, non-time homogeneous discrete-time Markov chains, time homogeneous continuous-time Markov chains, semi-Markov processes, nontime homogeneous continuous-time Markov chains, and generalized semi-Markov processes.