Title :
Importance sampling using the semi-regenerative method
Author :
Calvin, James M. ; Glynn, Peter W. ; Nakayama, Marvin K.
Author_Institution :
Dept. of Comput. Sci., New Jersey Inst. of Technol., Newark, NJ, USA
Abstract :
We discuss using the semi-regenerative method, importance sampling, and stratification to estimate the expected cumulative reward until hitting a fixed set of states for a discrete-time Markov chain on a countable state space. We develop a general theory for this problem and present several central limit theorems for our estimators. We also present some empirical results from applying these techniques to simulate a reliability model
Keywords :
Markov processes; discrete time systems; importance sampling; central limit theorems; countable state space; discrete-time Markov chain; expected cumulative reward; importance sampling; reliability model; semi-regenerative method; Computer science; Cranes; Discrete event simulation; Engineering management; Estimation theory; Monte Carlo methods; Random variables; Sampling methods; State estimation; State-space methods;
Conference_Titel :
Simulation Conference, 2001. Proceedings of the Winter
Conference_Location :
Arlington, VA
Print_ISBN :
0-7803-7307-3
DOI :
10.1109/WSC.2001.977320
