Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1150434 | Journal of Statistical Planning and Inference | 2009 | 7 Pages |
Abstract
The problem of nonparametric drift estimation for ergodic diffusions is studied from a Bayesian perspective. In particular, Gaussian process priors are exhibited that yield optimal contraction rates if the drift function belongs to a smoothness class.
Related Topics
Physical Sciences and Engineering
Mathematics
Applied Mathematics
Authors
Laura Panzar, Harry van Zanten,