由伽马序列驱动的双变量事件的一般随机模型

Q2 Mathematics
Charles K. Amponsah, Tomasz J. Kozubowski, Anna K. Panorska
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引用次数: 1

摘要

我们提出了一个描述(X,N)联合分布的新随机模型,其中N是计数变量,而X是N个独立随机变量的和。给出了该模型的主要性质,包括边缘分布和条件分布、积分变换、矩和参数估计。我们还详细讨论了N具有重尾离散Pareto分布的特殊情况。金融领域的一个例子说明了这种新的混合二元分布的建模潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A general stochastic model for bivariate episodes driven by a gamma sequence
We propose a new stochastic model describing the joint distribution of (X,N), where N is a counting variable while X is the sum of N independent gamma random variables. We present the main properties of this general model, which include marginal and conditional distributions, integral transforms, moments and parameter estimation. We also discuss in more detail a special case where N has a heavy tailed discrete Pareto distribution. An example from finance illustrates the modeling potential of this new mixed bivariate distribution.
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来源期刊
Journal of Statistical Distributions and Applications
Journal of Statistical Distributions and Applications Decision Sciences-Statistics, Probability and Uncertainty
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审稿时长
13 weeks
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