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A ug 2 01 2 Posterior Consistency via Precision Operators for Bayesian Nonparametric Drift Estimation in SDEs
| Content Provider | Semantic Scholar |
|---|---|
| Author | Pokern, Yvo |
| Copyright Year | 2012 |
| Abstract | We study a Bayesian approach to nonparametric estimation of the periodic drift function of a one-dimensional diffusion from continuoustime data. Rewriting the likelihood in terms of local time of the process, and specifying a Gaussian prior with precision operator of differential form, we show that the posterior is also Gaussian with precision operator also of differential form. The resulting expressions are explicit and lead to algorithms which are readily implementable. Using new functional limit theorems for the local time of diffusions on the circle, we bound the rate at which the posterior contracts around the true drift function. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://authors.library.caltech.edu/69264/2/1202.0976v3.pdf |
| Language | English |
| Access Restriction | Open |
| Subject Keyword | Contract agreement Diffusion Normal Statistical Distribution Rewriting The Circle (file system) algorithm |
| Content Type | Text |
| Resource Type | Article |
