DocumentCode
2119033
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
Volume
1
fYear
2001
fDate
2001
Firstpage
441
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Simulation Conference, 2001. Proceedings of the Winter
Conference_Location
Arlington, VA
Print_ISBN
0-7803-7307-3
Type
conf
DOI
10.1109/WSC.2001.977320
Filename
977320
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