| تعداد نشریات | 60 |
| تعداد شمارهها | 2,196 |
| تعداد مقالات | 17,789 |
| تعداد مشاهده مقاله | 54,730,360 |
| تعداد دریافت فایل اصل مقاله | 28,633,849 |
Inference on Pr(X > Y ) Based on Record Values From the Power Hazard Rate Distribution | ||
| Journal of Data Science and Modeling | ||
| مقاله 6، دوره 1، شماره 1، اسفند 2022، صفحه 59-76 اصل مقاله (380 K) | ||
| نوع مقاله: Research Manuscript | ||
| شناسه دیجیتال (DOI): 10.22054/jcsm.2018.9250 | ||
| نویسندگان | ||
| Bahman Tarvirdizade1؛ Nader Nematollahi* 2 | ||
| 1Ph.D. candidate in statistics, Allameh Tabataba'i University, Tehran, Iran. | ||
| 2Professor of statistics, Allameh Tabataba'i University, Tehran, Iran | ||
| چکیده | ||
| In this article, we consider the problem of estimating the stress-strength reliability $Pr (X > Y)$ based on upper record values when $X$ and $Y$ are two independent but not identically distributed random variables from the power hazard rate distribution with common scale parameter $k$. When the parameter $k$ is known, the maximum likelihood estimator (MLE), the approximate Bayes estimator and the exact confidence intervals of stress-strength reliability are obtained. When the parameter $k$ is unknown, we obtain the MLE and some bootstrap confidence intervals of stress-strength reliability. We also apply the Gibbs sampling technique to study the Bayesian estimation of stress-strength reliability and the corresponding credible interval. An example is presented in order to illustrate the inferences discussed in the previous sections. Finally, to investigate and compare the performance of the different proposed methods in this paper, a Monte Carlo simulation study is conducted. | ||
| کلیدواژهها | ||
| Bayes estimation؛ Maximum likelihood estimation؛ Monte Carlo simulation؛ Power hazard rate distribution؛ Record values؛ Stress-strength reliability | ||
|
آمار تعداد مشاهده مقاله: 441 تعداد دریافت فایل اصل مقاله: 765 |
||