In this paper, we focus on the parametric inference based on the Tampered Random Variable (TRV) model for simple step-stress life testing (SSLT) using Type-II censored data. The baseline lifetime of the experimental units under normal stress conditions follows Gumbel Type-II distribution with $\alpha$ and $\lambda$ being the shape and scale parameters, respectively. Maximum likelihood estimator (MLE) and Bayes estimator of the model parameters are derived based on Type-II censored samples. We obtain asymptotic intervals of the unknown parameters using the observed Fisher information matrix. Bayes estimators are obtained using Markov Chain Monte Carlo (MCMC) method under squared error loss function and LINEX loss function. We also construct highest posterior density (HPD) intervals of the unknown model parameters. Extensive simulation studies are performed to investigate the finite sample properties of the proposed estimators. Finally, the methods are illustrated with the analysis of a real data set.
翻译:在本文中,我们侧重于基于坦佩雷随机变量(TRV)模型的参数推论,该模型用于使用二类审查数据进行简单的步式压力生命测试(SSLT),在正常压力条件下实验单位的基准寿命分别以Gumbel Type-II分布成形和比例参数。模型参数的最大可能性估计值(MLE)和Bayes估计值是根据二类审查样品得出的。我们利用观察到的渔业信息矩阵获得未知参数的抽取间隔。Bayes估计值是根据Markov链蒙特卡洛(MCMC)方法在方位错误损失函数和LINEX损失函数下取得的。我们还建造了未知模型参数的最高外延密度间隔。我们进行了广泛的模拟研究,以调查拟议的估计参数的有限样本特性。最后,通过对真实数据集进行分析,对方法进行了说明。