Comment on "Sequential Monte Carlo for Bayesian Computation" (P. Del Moral, A. Doucet, A. Jasra)

Details Comment on "Sequential Monte Carlo for Bayesian Computation" (P. Del Moral, A. Doucet, A. Jasra) Comment on "Sequential Monte Carlo for Bayesian Computation" (P. Del Moral, A. Doucet, A. Jasra)

2006-06-22

arxiv.org/abs/math/0606557v1

Mathematics

Statistics Theory

To appear in the published proceedings of the Eighth Valencia International Meeting on Bayesian Statistics

Scientific paper

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?

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