Volume 20, 2016
|Page(s)||143 - 153|
|Published online||14 July 2016|
Posterior contraction rate for non-parametric Bayesian estimation of the dispersion coefficient of a stochastic differential equation
1 Mathematical Institute, Leiden University, P.O. Box 9512,
2300 RA Leiden, The Netherlands.
2 Korteweg-de Vries Institute for Mathematics, University of Amsterdam, PO Box 94248, 1090 GE Amsterdam, The Netherlands.
Revised: 30 April 2015
Accepted: 14 March 2016
We consider the problem of non-parametric estimation of the deterministic dispersion coefficient of a linear stochastic differential equation based on discrete time observations on its solution. We take a Bayesian approach to the problem and under suitable regularity assumptions derive the posteror contraction rate. This rate turns out to be the optimal posterior contraction rate.
Mathematics Subject Classification: 62G20 / 62M05
Key words: Dispersion coefficient / non-parametric Bayesian estimation / posterior contraction rate / stochastic differential equation
© EDP Sciences, SMAI 2016
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