On the small-sample optimality of multiple-regeneration estimators
Document Type
Conference Proceeding
Publication Date
1-1-1999
Abstract
We describe a simulation output analysis methodology suitable for stochastic processes that are regenerative with respect to multiple regeneration sequences. Our method exploits this structure to construct estimators that are more efficient than those that are obtained with the standard regenerative method. We illustrate the method in the setting of discrete-time Markov chains on a countable state space, and we present a result showing that the estimator is the uniform minimum variance unbiased estimator for finite-state-space discrete-time Markov chains. Some empirical results are given.
Identifier
0033333311 (Scopus)
Publication Title
Winter Simulation Conference Proceedings
External Full Text Location
https://doi.org/10.1145/324138.324451
ISSN
02750708
First Page
655
Last Page
661
Volume
1
Recommended Citation
Calvin, James M.; Glynn, Peter W.; and Nakayama, Marvin K., "On the small-sample optimality of multiple-regeneration estimators" (1999). Faculty Publications. 16014.
https://digitalcommons.njit.edu/fac_pubs/16014
