Estimation of stress-strength reliability from unit-Burr Ⅲ distribution under records data

Abstract

<abstract><p>This paper explores estimation of stress-strength reliability based on upper record values. When the strength and stress variables follow unit-Burr Ⅲ distributions, a generalized inferential approach is proposed for estimating stress-strength reliability (SSR). Under the common strength and stress parameter case, two types of pivotal quantities are constructed respectively, and then the generalized point and interval estimates for SSR are proposed in consequence, where the associated Monte-Carlo sampling approach is provided for computation. In addition, when strength and stress variables feature unequal model parameters, different generalized point and confidence interval estimates are also established in this regard. Extensive simulation studies are conducted to examine the behavior of proposed methods. Finally, a real-life data example is presented for illustration.</p></abstract>

Analysis of the Stress–Strength Model Using Uniform Truncated Negative Binomial Distribution under Progressive Type-II Censoring

“…In a superb monograph published by Kotz et al [1], the various SSR models created before 2001 were described in detail. Although the improvements for the stress-strength models under complete samples have received a great deal of attention see for instance [2][3][4][5][6][7][8][9][10], much focus has been placed on the situation where the data are record values, see [11][12][13][14][15][16][17].…”

Stress–Strength Reliability Analysis for Different Distributions Using Progressive Type-II Censoring with Binomial Removal

“…Numerous studies on the S-S model using complete and censored samples have been conducted by [2][3][4][5][6][7][8][9][10][11][12] and others. Some recent studies concerning SS models can be found in [13][14][15][16][17][18][19].…”