Goodness‐of‐fit tests for Poisson count time series based on the Stein–Chen identity

IF 16.4 1区化学 Q1 CHEMISTRY, MULTIDISCIPLINARY

Accounts of Chemical Research Pub Date : 2021-07-09 DOI:10.1111/stan.12252

Boris Aleksandrov, C. Weiß, C. Jentsch

引用次数: 5

Abstract

To test the null hypothesis of a Poisson marginal distribution, test statistics based on the Stein–Chen identity are proposed. For a wide class of Poisson count time series, the asymptotic distribution of different types of Stein–Chen statistics is derived, also if multiple statistics are jointly applied. The performance of the tests is analyzed with simulations, as well as the question which Stein–Chen functions should be used for which alternative. Illustrative data examples are presented, and possible extensions of the novel Stein–Chen approach are discussed as well.

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基于Stein-Chen恒等式的泊松计数时间序列的拟合优度检验

为了检验泊松边际分布的零假设，提出了基于Stein-Chen恒等式的检验统计量。对于一类广泛的泊松计数时间序列，导出了不同类型的Stein-Chen统计量的渐近分布，以及多个统计量联合应用的渐近分布。通过仿真分析了测试的性能，并提出了Stein-Chen函数应该用于哪种替代方案的问题。给出了说明性的数据示例，并讨论了Stein-Chen方法的可能扩展。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Accounts of Chemical Research 化学-化学综合

CiteScore

31.40

自引率

1.10%

发文量

312

审稿时长

2 months

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