一种新的混合Poisson指数族计数模型及其在医疗数据中的应用
A New Count Model Generated from Mixed Poisson Transmuted Exponential Family with an application to Health Care Data
摘要：
本文引入了一种新的混合泊松分布。该分布是利用混合过程得到的，其中泊松分布为混合分布，嬗变指数分布为混合分布。研究了该模型的单峰性、矩、过色散、泰勒级数展开等分布性质。利用矩量法、矩量法和比例法以及极大似然估计对参数进行估计，并通过数据拟合实验，说明其优于现有的一些分布。此外，精算应用的背景下，总索赔分配进行了讨论。最后，我们讨论了一个计数回归模型的基础上提出的分布和它的有用性，一些建立良好的模型。
英文摘要：
In this paper, a new mixed Poisson distribution is introduced. This new distribution is obtained by utilizing mixing process, with Poisson distribution as mixed distribution and Transmuted Exponential distribution as mixing distribution. Some distributional properties like unimodality, moments, over-dispersion, Taylor series expansion of proposed model are studied. Estimation of the parameters using method of moments, method of moments and proportion and maximum likelihood estimation along with data fitting experiment to show its advantage over some existing distribution. Further, an actuarial applications in context of aggregate claim distribution is discussed. Finally, we discuss a count regression model based on proposed distribution and its usefulness over some well established model.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
