On the estimation of reliability based on mixture inverse Gaussian distributions

被引：0
|
作者：
Akman, O [1 ]
Sansgiry, P [1 ]
Minnotte, MC [1 ]
机构：
[1] Utah State Univ, Dept Math & Stat, Logan, UT 84322 USA
来源：
APPLIED STATISTICAL SCIENCE IV | 1999年 / 4卷
关键词：
stress-strength; length-biased; bootstrapping; jackknife; inverse Gaussian; kernel density estimation;
D O I：
暂无
中图分类号：
R19 [保健组织与事业（卫生事业管理）];
学科分类号：
摘要：
We consider the stress-strength problem in a biomedical setting in which a unit of strength X is subjected to environmental stress Y where X and Y are independent mixture inverse Gaussian random variables. We estimate the reliability function P(X > Y) by using sampling based parametric approaches, and a nonparametric method estimating the probability density function of X - Y.
引用
收藏
页码：221 / 228
页数：8
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