| Issue |
ESAIM: PS
Volume 20, 2016
|
|
|---|---|---|
| Page(s) | 143 - 153 | |
| DOI | https://doi.org/10.1051/ps/2016008 | |
| 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.
shota.gugushvili@math.leidenuniv.nl
2 Korteweg-de Vries Institute for Mathematics, University of
Amsterdam, PO Box 94248, 1090 GE Amsterdam, The Netherlands.
spreij@uva.nl
Received:
9
September
2014
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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