Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1148083 | Journal of Statistical Planning and Inference | 2015 | 15 Pages |
Abstract
In the need for low assumption inferential methods in infinite-dimensional settings, Bayesian adaptive estimation via a prior distribution that does not depend on the regularity of the function to be estimated nor on the sample size is valuable. We elucidate relationships among the main approaches followed to design priors for minimax-optimal rate-adaptive estimation meanwhile shedding light on the underlying ideas.
Keywords
Related Topics
Physical Sciences and Engineering
Mathematics
Applied Mathematics
Authors
Catia Scricciolo,