Confidence interval estimation using quasi-independent sequences

E. Chen and W. Kelton

IISE Transactions, 2010, vol. 42, issue 1, 83-93

Abstract: A Quasi-Independent (QI) subsequence is a subset of time series observations obtained by systematic sampling. Because the observations appear to be independent, as determined by the runs tests, classical statistical techniques can be used on those observations directly. This paper discusses implementation of a sequential procedure to determine the simulation run length to obtain a QI subsequence, and the batch size for constructing confidence intervals for an estimator of the steady-state mean of a stochastic process. The proposed QI procedures increase the simulation run length and batch size progressively until a certain number of essentially independent and identically distributed samples are obtained. The only (mild) assumption is that the correlations of the stochastic-process output sequence eventually die off as the lag increases. An experimental performance evaluation demonstrates the validity of the QI procedure.

Date: 2010
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/07408170903232266 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:uiiexx:v:42:y:2010:i:1:p:83-93

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/uiie20

DOI: 10.1080/07408170903232266

Access Statistics for this article

IISE Transactions is currently edited by Jianjun Shi

More articles in IISE Transactions from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().