A least square-type procedure for parameter estimation in stochastic differential equations with additive fractional noise

被引：5

作者：

Neuenkirch A. ^{[1
]}

Tindel S. ^{[2
]}

机构：

[1] Institut für Mathematik, Universität Mannheim, 68131 Mannheim, A5

[2] Institut Élie Cartan, Université de Lorraine, 54506 Vandœuvre-lès-Nancy Cedex

来源：

Statistical Inference for Stochastic Processes | 2014年 / 17卷 / 1期

关键词：

Ergodicity; Fractional Brownian motion; Least square procedure; Parameter estimation;

D O I：

10.1007/s11203-013-9084-z

中图分类号：

学科分类号：

摘要：

We study a least square-type estimator for an unknown parameter in the drift coefficient of a stochastic differential equation with additive fractional noise of Hurst parameter H > 1/2. The estimator is based on discrete time observations of the stochastic differential equation, and using tools from ergodic theory and stochastic analysis we derive its strong consistency. © 2013 Springer Science+Business Media Dordrecht.

引用

页码：99 / 120

页数：21

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