In this paper, we consider estimation of parameters for a two-parameter Kumaraswamy-exponential distribution based on adaptive type-II progressive censoring schemes which is a mixture of type-I and progressive type-II censoring schemes. The maximum likelihood estimators of the parameters are obtained. Bayes estimators are also obtained using different loss functions such as squared error loss function, LINEX loss function, and entropy loss function. For Bayes estimation, we use the importance sampling method. A simulation study is then performed for comparing various estimators developed in this paper. All Bayesian estimates are compared with the corresponding maximum likelihood estimates numerically in terms of their bias and mean square error values and found that Bayes estimators perform better than MLEs for α and β. A real data set is also used for illustration.

中文翻译：

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基于自适应II型渐进删失方案的Kumaraswamy-指数分布参数估计

在本文中，我们考虑了基于自适应 II 类渐进式删失方案的双参数 Kumaraswamy 指数分布的参数估计，该方案是 I 类和渐进式 II 类删失方案的混合。获得参数的最大似然估计量。贝叶斯估计量也是使用不同的损失函数获得的，例如平方误差损失函数、LINEX 损失函数和熵损失函数。对于贝叶斯估计，我们使用重要性抽样方法。然后进行模拟研究以比较本文中开发的各种估计器。将所有贝叶斯估计与相应的最大似然估计在偏差和均方误差值方面进行数值比较，发现贝叶斯估计在 α 和 β 方面的性能优于 MLE。