Convergence rate of maximum likelihood estimator of parameter in stochastic partial differential equation

Using the recent results obtained by combining Malliavin calculus and Stein’s method, we study the rate of convergence of the distribution of the maximum likelihood estimator of a parameter appearing in a stochastic partial differential equation. The aim of this paper is to develop the new technique...

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Bibliographic Details
Published in:Journal of the Korean Statistical Society 2015, 44(2), , pp.312-320
Main Authors: Kim, Yoon Tae, Park, Hyun Suk
Format: Article
Language:English
Subjects:
Applied Statistics
Bayesian Inference
Cylindrical Brownian motion
Malliavin calculus
Maximum likelihood estimator
Multiple stochastic integral
Statistical Theory and Methods
Statistics
Statistics and Computing/Statistics Programs
Stochastic partial differential equation
통계학
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Summary:Using the recent results obtained by combining Malliavin calculus and Stein’s method, we study the rate of convergence of the distribution of the maximum likelihood estimator of a parameter appearing in a stochastic partial differential equation. The aim of this paper is to develop the new techniques, allowing us to improve the rate, given by Mishra and Prakasa Rao (2004), to O(1/N).
ISSN:1226-3192
2005-2863
DOI:10.1016/j.jkss.2015.01.001