Comment on "Sequential Monte Carlo for Bayesian Computation" (P. Del Moral, A. Doucet, A. Jasra)
Statistics Theory
2007-06-13 v1 Probability
Statistics Theory
Abstract
The main question concerns another recent advance in sequential Monte Carlo, the use of a mixture transition kernel that automatically adapts to the target distribution (Douc et al. 2006). Is there a class of static inference problems for which the backward-kernel approach is better suited, or is it too early to predict which method may have better performance in a particular situation?
Keywords
Cite
@article{arxiv.math/0606557,
title = {Comment on "Sequential Monte Carlo for Bayesian Computation" (P. Del Moral, A. Doucet, A. Jasra)},
author = {David R. Bickel},
journal= {arXiv preprint arXiv:math/0606557},
year = {2007}
}
Comments
To appear in the published proceedings of the Eighth Valencia International Meeting on Bayesian Statistics