ON CONTINUOUS AND DISCRETE SAMPLING FOR PARAMETER ESTIMATION IN MARKOVIAN SWITCHING DIFFUSIONS

被引：0
|
作者：
Zhen, Yuhang [1 ]
Xi, Fubao [1 ]
机构：
[1] Beijing Inst Technol, Sch Math & Stat, Beijing 100081, Peoples R China
来源：
NUMERICAL ALGEBRA CONTROL AND OPTIMIZATION | 2024年
基金：
中国国家自然科学基金;
关键词：
Maximum likelihood estimator; convergence; stochastic differential equation; Markovian switching; STOCHASTIC DIFFERENTIAL-EQUATIONS;
D O I：
10.3934/naco.2024012
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
Parameter estimation of stochastic differential equation has recently been discussed by many authors. The aim of this paper is to study the rates of convergence of approximate maximum likelihood estimator. More precisely, for Markovian switching diffusions, we first show the convergence rates of the continuous maximum likelihood estimator under the Lipschitz conditions. Then we also discuss the probabilistic bounds on |Theta n,T - Theta T| under the non -Lipschitz conditions.
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页数：13
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