Cramer-Von Mises Variance Estimators for Simulations
| dc.contributor.author | Seila, Andrew F. | |
| dc.contributor.author | Goldsman, David | |
| dc.contributor.author | Kang, Keebom | |
| dc.contributor.corporate | Operations Research (OR) | |
| dc.contributor.corporate | Graduate School of Operational and Information Sciences (GSOIS) | |
| dc.contributor.department | Administrative Sciences | en_US |
| dc.date | 1993-09 | |
| dc.date.accessioned | 2013-03-07T21:52:23Z | |
| dc.date.available | 2013-03-07T21:52:23Z | |
| dc.date.issued | 1993-09 | |
| dc.description.abstract | We study estimators for the variance parameter sigma(2) of a stationary process. The estimators are based on weightings yield estimators that are 'first-order unbiased' for sigma (2) We derive an expression for the asymptotic variance of the new estimators; this expression is then used to obtain the first-order unbiased estimator having the smallest variance among fixed-degree polynomial weighting functions. Although our work is based on asymptotic theory, we present exact and empirical examples to demonstrate the new estimators' small-sample robustness. | en_US |
| dc.description.distributionstatement | Approved for public release; distribution is unlimited. | |
| dc.description.funder | O&MN direct funding | en_US |
| dc.description.sponsorship | Naval Postgraduate School, Monterey, California. | en_US |
| dc.description.uri | http://archive.org/details/cramervonmisesva00gold | |
| dc.identifier.npsreport | NPS-AS-93-028 | |
| dc.identifier.oclc | NA | |
| dc.identifier.uri | https://hdl.handle.net/10945/29785 | |
| dc.language.iso | en_US | |
| dc.publisher | Monterey, California. Naval Postgraduate School | en_US |
| dc.rights | This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States. | en_US |
| dc.subject.author | Simulation | en_US |
| dc.subject.author | Stationary Process | en_US |
| dc.subject.author | Variance Estimation | en_US |
| dc.subject.author | Standardized Time Series | en_US |
| dc.subject.author | Cramer-Von Mises Estimator | en_US |
| dc.subject.lcsh | WEIGHTING FUNCTIONS | en_US |
| dc.title | Cramer-Von Mises Variance Estimators for Simulations | en_US |
| dc.type | Technical Report | en_US |
| dspace.entity.type | Publication | |
| relation.isOrgUnitOfPublication | 58745961-c46a-45ad-ae9c-d139d1ba1041 | |
| relation.isOrgUnitOfPublication | dd7f1b97-9c92-402d-b910-27f080946cde | |
| relation.isOrgUnitOfPublication.latestForDiscovery | dd7f1b97-9c92-402d-b910-27f080946cde |