Abstract
We investigate the theoretical performance of Bayes factor estimators at a single point in wavelet regression models with independent and identically distributed errors that are not necessarily normally distributed. We compare these estimators in terms of their frequentist pointwise optimality in Besov spaces for certain combinations of error and prior distributions.
Original language | English |
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Pages (from-to) | 513-541 |
Number of pages | 29 |
Journal | Sankhya A |
Volume | 68 |
Issue number | 4 |
Publication status | Published - 1 Dec 2006 |
Keywords / Materials (for Non-textual outputs)
- Bayesian inference
- Besov spaces
- Nonparametric regression
- Optimality
- Pointwise risk
- Wavelets