ON BEST ASYMPTOTIC CONFIDENCE-INTERVALS FOR PARAMETERS OF STOCHASTIC-PROCESSES
成果类型：
Note
署名作者：
HEYDE, CC
刊物名称：
ANNALS OF STATISTICS
ISSN/ISSBN：
0090-5364
DOI：
10.1214/aos/1176348545
发表日期：
1992
页码：
603-607
关键词：
摘要：
This paper is concerned with the size of confidence intervals for parameters of stochastic processes based on limit laws with two competing normalizations, one producing asymptotic normality and the other asymptotic mixed normality. It is shown that, in a certain sense, the interval based on asymptotic normality is preferable on average. Applications to estimation of parameters in nonergodic stochastic processes and to estimation of steady-state parameters in a simulation are given to illustrate the theory.
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