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

页码：221 / 228

页数：8

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