The problem of estimation of the parameters of two-parameter inverse Weibull distributions has been considered. We establish existence and uniqueness of the maximum likelihood estimators of the scale and shape parameters. We derive Bayes estimators of the parameters under the entropy loss function. Hierarchical Bayes estimator, equivariant estimator and a class of minimax estimators are derived when shape parameter is known. Ordered Bayes estimators using information about second population are also derived. We investigate the reliability of multi-component stress-strength model using classical and Bayesian approaches. Risk comparison of the classical and Bayes estimators is done using Monte Carlo simulations. Applications of the proposed estimators are shown using real data sets.

考虑了两参数逆威布尔分布的参数估计问题。我们建立了尺度和形状参数的最大似然估计量的存在性和唯一性。我们推导出熵损失函数下参数的贝叶斯估计量。当形状参数已知时，可以推导出层次贝叶斯估计器、等变估计器和一类极小极大估计器。还导出了使用关于第二总体的信息的有序贝叶斯估计量。我们使用经典和贝叶斯方法研究多分量应力强度模型的可靠性。经典和贝叶斯估计量的风险比较是使用蒙特卡罗模拟完成的。使用真实数据集显示了所提出的估计器的应用。