具有广义指数间隔到达时间的计数过程

IF 1.6 Q1 STATISTICS & PROBABILITY
Sahana Bhattacharjee
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引用次数: 2

摘要

本文介绍了一种基于广义指数分布到达间隔时间的计数方法。与现有泊松计数模型相比,这种新的计数模型的优势在于,到达间时间分布的危害函数是非常数的,因此分布依赖于持续时间,因此能够模拟分散和过分散的计数数据,而泊松计数模型的指数分布到达间时间不依赖于持续时间,相应的计数模型只能模拟等分散的数据。进一步探讨了该模型的一些性质。利用该模型进行了仿真,研究了不同参数值下模型的计数概率、均值和方差的变化规律。本文以诊所病人到达时间和百货商店顾客到达时间的真实数据集为例说明了所提出模型的使用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Counting Process with Generalized Exponential Inter-Arrival Times
This paper introduces a new counting process which is based on Generalized Exponentially distributed inter-arrival times. The advantage of this new count model over the existing Poisson count model is that the hazard function of the inter arrival time distribution is non-constant, so that the distribution is duration dependent and hence, is able to model both under dispersed and over dispersed count data, as opposed to the exponentially distributed inter arrival time of the Poisson count model, which is not duration dependent and the corresponding count model is able to model only equidispersed data. Further, some properties of this model are explored. Simulation from this new model is performed to study the behavior of count probabilities, mean and variance of the model for different values of the parameter. Use of the proposed model is illustrated with the help of real life data sets on arrival times of patients at a clinic and on arrival times of customers at a departmental store.
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来源期刊
Statistica
Statistica STATISTICS & PROBABILITY-
CiteScore
1.70
自引率
0.00%
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审稿时长
10 weeks
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