It is known that all the proportional reversed hazard (PRH) processes can be de?rived by a marginal transformation applied to a power function distribution (PFD) process. Kundu [8] investigated PRH processes that can be viewed as being ob?tained by marginal transformations applied to a particular PFD process that will be described and investigated and will be called a Kundu process. In the present note, in addition to studying the Kundu process, we introduce a new PFD process having Markovian and stationarity properties. We discuss distributional features of such processes, explore inferential aspects and include an example of applications of the PFD processes to real-life data.

翻译：已知所有比例逆危险率（PRH）过程均可通过对幂函数分布（PFD）过程进行边际变换推导得出。Kundu [8] 研究了可通过将边际变换应用于特定PFD过程获得的PRH过程，该特定PFD过程将予以描述、研究，并称为Kundu过程。在本报告中，除研究Kundu过程外，我们引入了一种具有马尔可夫性和平稳性的新PFD过程。我们讨论了此类过程的分布特征，探究了推断相关方面，并包含了将PFD过程应用于实际数据的一个示例。