Abstract
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).
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