First-order observation-driven integer-valued autoregressive processes

被引：36
|
作者：
Zheng, Haitao [1 ]
Basawa, Ishwar V. [1 ]
机构：
[1] Univ Georgia, Dept Stat, Athens, GA 30602 USA
来源：
STATISTICS & PROBABILITY LETTERS | 2008年 / 78卷 / 01期
关键词：
models of count data; thinning models; observation-driven model; INAR models; random coefficient models; conditional least squares; maximum likelihood;
D O I：
10.1016/j.spl.2007.04.017
中图分类号：
O21 [概率论与数理统计]; C8 [统计学];
学科分类号：
020208 ; 070103 ; 0714 ;
摘要：
A first-order observation-driven integer-valued autoregressive model is introduced. Ergodicity of the process is established. Conditional least squares and maximum likelihood estimators of the model parameters are derived. The performances of these estimators are compared via simulation. The models are applied to a real data set. (C) 2007 Elsevier B.V. All rights reserved.
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页码：1 / 9
页数：9
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