2009 journal article
Area variance estimators for simulation using folded standardized time series
IIE TRANSACTIONS, 41(2), 134–144.
author keywords: Steady-state simulation; simulation output analysis methods; method of standardized time series; batching; variance estimation
UN Sustainable Development Goal Categories
16. Peace, Justice and Strong Institutions
(OpenAlex)
Source: Web Of Science
Added: August 6, 2018
We estimate the variance parameter of a stationary simulation-generated process using “folded” versions of standardized time series area estimators. Asymptotically as the sample size increases, different folding levels yield unbiased estimators that are independent scaled chi-squared variates, each with one degree of freedom. This result is exploited to formulate improved variance estimators based on the combination of multiple levels as well as the use of batching. The improved estimators preserve the asymptotic bias properties of their predecessors, but have substantially lower asymptotic variances. The performance of the new variance estimators is demonstrated in a first-order autoregressive process with autoregressive parameter 0.9 and in the queue-waiting-time process for an M/M/1 queue with server utilization 0.8. [Supplementary materials are available for this article. Go to the publisher's online edition of IIE Transactions for the following free supplemental resource: Appendix]