Parameter Estimation for Dothan Model Driven by Small Symmetrical Noise Based on Discrete Observation

被引：0
|
作者：
Jiao, Huiping [1 ]
Zhou, Piaopiao [1 ]
Li, Heling [2 ]
Wei, Chao [3 ]
机构：
[1] Zhengzhou Univ Technol, Sch Basic Sci, Zhengzhou 450044, Peoples R China
[2] Hebi Qibin Middle Sch, Hebi 458000, Peoples R China
[3] Anyang Normal Univ, Sch Math & Stat, Anyang 455000, Peoples R China
来源：
ENGINEERING LETTERS | 2022年 / 30卷 / 04期
关键词：
Dothan model; small symmetrical noise; least square estimation; consistency; asymptotic distribution; ORNSTEIN-UHLENBECK PROCESSES; LEAST-SQUARES ESTIMATOR;
D O I：
暂无
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
In this paper, we consider the parameter estimation problem for discretely observed Dothan model driven by small symmetrical noise. The least square method is applied to obtain the drift parameter estimators. The consistency and asymptotic distribution of the estimators are derived when a small dispersion coefficient epsilon -> 0. Some simulations are made to demonstrate the applicability of the results.
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页码：1210 / 1216
页数：7
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