基于二项稀疏算子的整值自回归模型的经验似然推断

doi:10.16039/j.cnki.cn22-1249.2019.01.020

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摘要

整值时间序列可出现在交通、金融、教育、环境、保险等很多领域。稀疏算子是研究整值时间序列的主要方法。本文采用经验似然法研究基于二项稀疏算子的一阶整值自回归模型，并给出新息项为泊松的BINAR(1)模型的经验似然推断及其最大经验似然的估计值。利用数值模拟来研究经验似然估计的表现。最后通过一个犯罪数据的实例给出模型的应用。

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	张庆春
	李晓梅
	范晓东

关键词: 二项稀疏算子 INAR(1)模型新息项经验似然

Abstract:

Integer value time series appear in many fields such as transportation, finance, education, environment, and insurance. The thinning operator is the main method to study the integer value time series.In this paper, the first-order integer value autoregressive model based on binomial thinning operator is studied by the empirical likelihood method, and the empirical likelihood inference of the BINAR(1) model with the Poisson innovation and its empirical likelihood estimation are given. The performance of empirical likelihood estimation is studied by means of numerical simulation. Finally, the application of the model is given through an example of crime data.

Key words: binomial thinning operator INAR(1) model innovation empirical likelihood method

出版日期: 2019-01-25 发布日期: 2019-01-25 整期出版日期: 2019-01-25

O212.1

引用本文:

张庆春, 李晓梅, 范晓东. 基于二项稀疏算子的整值自回归模型的经验似然推断 [J]. 吉林化工学院学报, 2019, 36(1): 90-93.
ZHANG Qing-chun, LI Xiao-mei, FAN Xiao-dong. Empirical Likelihood Inference for Integer Value Auto-regressive Model Based on Binomial Thinning Operator . Journal of Jilin Institute of Chemical Technology, 2019, 36(1): 90-93.

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https://xuebao.jlict.edu.cn/CN/10.16039/j.cnki.cn22-1249.2019.01.020 或 https://xuebao.jlict.edu.cn/CN/Y2019/V36/I1/90

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