AN INVESTIGATION OF FINITE-SAMPLE BEHAVIOR OF CONFIDENCE-INTERVAL ESTIMATORS
成果类型：
Article
署名作者：
SARGENT, RG; KANG, K; GOLDSMAN, D
署名单位：
United States Department of Defense; United States Navy; University System of Georgia; Georgia Institute of Technology
刊物名称：
OPERATIONS RESEARCH
ISSN/ISSBN：
0030-364X
DOI：
10.1287/opre.40.5.898
发表日期：
1992
页码：
898-914
关键词：
摘要：
We investigate the small-sample behavior and convergence properties of confidence interval estimators (CIEs) for the mean of a stationary discrete process. We consider CIEs arising from nonoverlapping batch means, overlapping batch means, and standardized time series, all of which are commonly used in discrete-event simulation. The performance measures of interest are the coverage probability, and the expected value and variance of the half-length. We use empirical and analytical methods to make detailed comparisons regarding the behavior of the CIEs for a variety of stochastic processes. All the CIEs under study are asymptotically valid; however, they are usually invalid for small sample sizes. We find that for small samples, the bias of the variance parameter estimator figures significantly in CIE coverage performance-the less bias the better. A secondary role is played by the marginal distribution of the stationary process. We also point out that some CIEs require fewer observations before manifesting the properties for CIE validity.