文章基本信息

标题：Bayesian Inference on the Variance of Normal Distribution Using Moving Extremes Ranked Set Sampling
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作者：Al-Hadhrami, Said Ali ; Al-Omari, Amer Ibrahim
期刊名称：Journal of Modern Applied Statistical Methods
出版年度：2009
卷号：8
期号：1
页码：25
出版社：Wayne State University
摘要：Bayesian inference of the variance of the normal distribution is considered using moving extremes ranked set sampling (MERSS) and is compared with the simple random sampling (SRS) method. Generalized maximum likelihood estimators (GMLE), confidence intervals (CI), and different testing hypotheses are considered using simple hypothesis versus simple hypothesis, simple hypothesis versus composite alternative, and composite hypothesis versus composite alternative based on MERSS and compared with SRS. It is shown that modified inferences using MERSS are more efficient than their counterparts based on SRS.
关键词：Moving extremes ranked set sampling (MERSS); confidence interval; test hypothesis; Bayesian approach