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arXiv 1111.1816math.PRmath.STstat.TH
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加性分数阶噪声下随机微分方程参数估计的最小二乘方法

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

Andreas Neuenkirch, Samy Tindel

摘要:

研究了Hurst参数H>1/2的加性分数阶噪声下随机微分方程漂移系数中未知参数的最小二乘估计。该估计是基于离散时间观测的随机微分方程,并利用遍历论和随机分析的工具,我们得到了它的强相合性。

英文摘要:

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.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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