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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