摘要
对一类带有未知参数和小干扰项的奇异随机偏微分方程,基于连续样本轨道,给出了参数的极大似然估计,证明了当干扰项趋于0时,参数估计量的强相合性和渐近正态性.
In this paper, the singular stochastic partial differential equation with an unknown parameter and a small noise is studied. The maximum likelihood estimator of the parameter based on the continuous observation of the Fourier coefficients is proposed. The strong convergence and asymptotic normality of the estimator are established as the noise tends to zero.
出处
《应用概率统计》
CSCD
北大核心
2015年第2期183-192,共10页
Chinese Journal of Applied Probability and Statistics
基金
浙江省自然科学基金(LY14A010003)资助
关键词
随机偏微分方程
极大似然估计
强相合性
渐近正态性
Stochastic partial differential equation, maximum likelihood estimator, strong consistency, asymptotic normality.
