具有位置和尺度的绝对连续Marshall-Olkin二元Pareto分布的期望最大化算法
An EM algorithm for absolutely continuous Marshall-Olkin bivariate Pareto distribution with location and scale
摘要：
本文考虑了一类Block-Basu型二元Pareto分布。在这里，在标准的方式，首先马歇尔-奥尔金型奇异二元分布已被构造，然后通过去除类似于块和Basu模型的奇异分量，一个绝对连续BB-BVPA模型已被构造。此外，还引入了位置和尺度参数。因此，该模型有七个参数。导出了这种绝对连续分布的不同性质。由于参数的极大似然估计不能用封闭形式表示，我们提出用期望最大化算法来计算模型参数的估计。为了说明的目的，已经进行了一些模拟实验。该模型适合降雨数据的滑坡风险估计的背景下。
英文摘要：
In this paper, we have considered a Block-Basu type bivariate Pareto distribution. Here in the standard manner, first Marshall-Olkin type singular bivariate distribution has been constructed, and then by taking away the singular component similar to the Block and Basu model, an absolute continuous BB-BVPA model has been constructed. Further, the location and scale parameters also have been introduced. Therefore, the model has seven parameters. Different properties of this absolutely continuous distribution are derived. Since the maximum likelihood estimators of the parameters cannot be expressed in a closed form, we propose to use an EM algorithm to compute the estimators of the model parameters. Some simulation experiments have been performed for illustrative purposes. The model is fitted to rainfall data in the context of landslide risk estimation.
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