arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2005.03187math.PRmath.STstat.TH
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混合Poisson随机和的收敛性与推断

Convergence and inference for mixed Poisson random sums

Wagner Barreto-Souza, Gabriela Oliveira, Roger W. C. Silva

摘要:

本文给出了一类混合泊松分布下随机数项部分和的极限分布。得到的弱极限是一个正态分布和一个指数族的混合,我们称之为正态指数族(NEF)定律。引入新的稳定性概念,建立了α-稳定分布与NEF律之间的关系.我们提出了估计的NEF模型的参数,通过矩的方法,也通过最大似然法,这是通过一个期望最大化算法进行。蒙特卡洛模拟研究,以检查所提出的估计和金融市场的实证说明的性能。

英文摘要:

In this paper we obtain the limit distribution for partial sums with a random number of terms following a class of mixed Poisson distributions. The resulting weak limit is a mixing between a normal distribution and an exponential family, which we call by normal exponential family (NEF) laws. A new stability concept is introduced and a relationship between α-stable distributions and NEF laws is established. We propose estimation of the parameters of the NEF models through the method of moments and also by the maximum likelihood method, which is performed via an Expectation-Maximization algorithm. Monte Carlo simulation studies are addressed to check the performance of the proposed estimators and an empirical illustration on financial market is presented.

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。

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