Estimation of stress–strength reliability in the inverse Gaussian distribution under progressively type II censored data
| Autor: | Nader Nematollahi, S. Rostamian |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
lcsh:T57-57.97
lcsh:Mathematics 010102 general mathematics Estimator Inverse Gaussian distribution Pivotal quantity lcsh:QA1-939 01 natural sciences Confidence interval 010101 applied mathematics Bayes' theorem symbols.namesake Gibbs sampling Generalized pivotal quantity Statistics lcsh:Applied mathematics. Quantitative methods Credible interval symbols Probability distribution 0101 mathematics EM algorithm Random variable Progressively type II censoring Mathematics |
| Zdroj: | Mathematical Sciences, Vol 13, Iss 2, Pp 175-191 (2019) |
| ISSN: | 2251-7456 2008-1359 |
| Popis: | The stress–strength parameter $$R = P(Y < X)$$ , as a reliability parameter, is considered in different statistical distributions. In the present paper, the stress–strength reliability is estimated based on progressively type II censored samples, in which $$X$$ and $$Y$$ are two independent random variables with inverse Gaussian distributions. The maximum likelihood estimate of $$R$$ via expectation–maximization algorithm and the Bayes estimate of $$R$$ are obtained. Furthermore, we obtain the bootstrap confidence intervals, HPD credible interval and confidence intervals based on generalized pivotal quantity for $$R$$ . Additionally, the performance of point estimators and confidence intervals are evaluated by a simulation study. Finally, the proposed methods are conducted on a set of real data for illustrative purposes. |
| Databáze: | OpenAIRE |
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