POSTERIOR CONTRACTION RATES FOR NON-PARAMETRIC STATE AND DRIFT ESTIMATION

被引:2
|
作者
Reich, Sebastian [1 ]
Rozdeba, Paul J. [1 ]
机构
[1] Univ Potsdam, Inst Math, Karl Liebknecht Str 24-25, D-14476 Potsdam, Germany
来源
FOUNDATIONS OF DATA SCIENCE | 2020年 / 2卷 / 03期
关键词
State and parameter estimation; Bayesian inference; posterior contraction rates; stochastic partial differential equations; Kalman-Bucy filter; KALMAN-BUCY FILTER;
D O I
10.3934/fods.2020016
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
We consider combined state and drift estimation problem for the linear stochastic heat equation. The infinite-dimensional Bayesian inference problem is formulated in terms of the Kalman-Bucy filter over an extended state space, and its long-time asymptotic properties are studied. Asymptotic posterior contraction rates in the unknown drift function are the main contribution of this paper. Such rates have been studied before for stationary non-parametric Bayesian inverse problems, and here we demonstrate the consistency of our time-dependent formulation with these previous results building upon scale separation and a slow manifold approximation.
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页码:333 / 349
页数:17
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