To produce more flexible model, the Bayesian and classical inference of the stress–strength parameter, R, is studied under Type-II progressive censored samples, when stress and strength are two independent Weibull-half-logistic variables. In classical inference, the maximum likelihood estimation, approximation maximum likelihood estimation, uniformly minimum variance unbiased estimate and asymptotic confidence intervals of R are considered. Moreover, in Bayesian inference, two approximation Bayes estimates, exact Bayes estimate and highest posterior density intervals of R, are derived. These estimations are considered in different cases. Furthermore, the Monte Carlo simulations are applied to compare the performance of different methods. Two data sets are analyzed for illustrative aims.

为了产生更灵活的模型，当应力和强度是两个独立的威布尔半逻辑变量时，在II型渐进删失样本下研究了应力-强度参数R的贝叶斯和经典推论。在经典推论中，考虑了R的最大似然估计，近似最大似然估计，一致最小方差无偏估计和渐近置信区间。另外，在贝叶斯推理中，两个近似贝叶斯估计，贝叶斯精确估计和的最高后验密度间隔ř，是派生的。在不同情况下考虑这些估计。此外，使用蒙特卡洛模拟来比较不同方法的性能。为了说明性目的，分析了两个数据集。