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Statistical Inference for Pr(Y<X): The Normal Case

 

作者: Benjamin Reiser,   Irwin Guttman,  

 

期刊: Technometrics  (Taylor Available online 1986)
卷期: Volume 28, issue 3  

页码: 253-257

 

ISSN:0040-1706

 

年代: 1986

 

DOI:10.1080/00401706.1986.10488133

 

出版商: Taylor & Francis Group

 

关键词: Reliability;Maximum likelihood;Bayesian and sampling theory;Interval estimators

 

数据来源: Taylor

 

摘要:

This article examines statistical inference for Pr(Y<X), whereXandYare independent normal variates with unknown means and variances. The case of unequal variances is stressed.Xcan be interpreted as the strength of a component subjected to a stressY, and Pr(Y<X) is the component's reliability. Two approximate methods for obtaining confidence intervals and an approximate Bayesian probability interval are obtained. The actual coverage probabilities of these intervals are examined by simulation.

 

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