Needles and Straw in a Haystack : Posterior Concentration for Possibly Sparse Sequences

@inproceedings{Vaart2012NeedlesAS,
  title={Needles and Straw in a Haystack : Posterior Concentration for Possibly Sparse Sequences},
  author={Aad van der Vaart},
  year={2012}
}
We consider full Bayesian inference in the multivariate normal mean model in the situation that the mean vector is sparse. The prior distribution on the vector of means is constructed hierarchically by first choosing a collection of nonzero means and next a prior on the nonzero values. We consider the posterior distribution in the frequentist set-up that the observations are generated according to a fixed mean vector, and are interested in the posterior distribution of the number of nonzero… CONTINUE READING
Highly Influential
This paper has highly influenced 11 other papers. REVIEW HIGHLY INFLUENTIAL CITATIONS
Highly Cited
This paper has 52 citations. REVIEW CITATIONS

Citations

Publications citing this paper.

52 Citations

051015'13'15'17'19
Citations per Year
Semantic Scholar estimates that this publication has 52 citations based on the available data.

See our FAQ for additional information.

References

Publications referenced by this paper.
Showing 1-10 of 23 references

Supplement to “Needles and Straw in a Haystack: Posterior concentration for possibly sparse sequences.

I. CASTILLO, A. W. VAN DER VAART
2012
View 4 Excerpts
Highly Influenced

Maximum Entropy and the Nearly Black Object

Liana David, Donoho, Iain M. Johnstonet, Alan S. Stern
2008
View 5 Excerpts
Highly Influenced

Calibration and Empirical Bayes Variable Selection

A. U.S.
1997
View 5 Excerpts
Highly Influenced

Bayes and empirical-Bayes multiplicity adjustment in the variable-selection problem

J. G. SCOTT, J. O. BERGER
Ann. Statist • 2010
View 2 Excerpts

Lower bounds for posterior rates with Gaussian process priors

I. CASTILLO
Electron. J. Stat • 2008
View 1 Excerpt

Similar Papers

Loading similar papers…