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Asymptotically minimax empirical Bayes estimation of a sparse normal
  mean vector
v1v2v3 (latest)

Asymptotically minimax empirical Bayes estimation of a sparse normal mean vector

27 April 2013
Ryan Martin
S. Walker
ArXiv (abs)PDFHTML

Papers citing "Asymptotically minimax empirical Bayes estimation of a sparse normal mean vector"

14 / 14 papers shown
Title
Dirichlet-Laplace priors for optimal shrinkage
Dirichlet-Laplace priors for optimal shrinkage
A. Bhattacharya
D. Pati
Natesh S. Pillai
David B. Dunson
106
441
0
21 Jan 2014
Optimal rates of convergence for sparse covariance matrix estimation
Optimal rates of convergence for sparse covariance matrix estimation
T. Cai
Harrison H. Zhou
151
246
0
13 Feb 2013
Needles and Straw in a Haystack: Posterior concentration for possibly
  sparse sequences
Needles and Straw in a Haystack: Posterior concentration for possibly sparse sequences
I. Castillo
A. van der Vaart
136
252
0
06 Nov 2012
A nonparametric empirical Bayes framework for large-scale multiple
  testing
A nonparametric empirical Bayes framework for large-scale multiple testing
Ryan Martin
S. Tokdar
51
44
0
20 Jun 2011
Estimation of a sparse group of sparse vectors
Estimation of a sparse group of sparse vectors
F. Abramovich
V. Grinshtein
81
4
0
10 Apr 2011
Optimal rates of convergence for covariance matrix estimation
Optimal rates of convergence for covariance matrix estimation
Tommaso Cai
Cun-Hui Zhang
Harrison H. Zhou
170
474
0
19 Oct 2010
Optimal rates of convergence for estimating the null density and
  proportion of nonnull effects in large-scale multiple testing
Optimal rates of convergence for estimating the null density and proportion of nonnull effects in large-scale multiple testing
T. Tony Cai
Jiashun Jin
138
73
0
11 Jan 2010
A Selective Overview of Variable Selection in High Dimensional Feature
  Space (Invited Review Article)
A Selective Overview of Variable Selection in High Dimensional Feature Space (Invited Review Article)
Jianqing Fan
Jinchi Lv
603
913
0
06 Oct 2009
Nonparametric empirical Bayes and compound decision approaches to
  estimation of a high-dimensional vector of normal means
Nonparametric empirical Bayes and compound decision approaches to estimation of a high-dimensional vector of normal means
L. Brown
E. Greenshtein
132
155
0
12 Aug 2009
General maximum likelihood empirical Bayes estimation of normal means
General maximum likelihood empirical Bayes estimation of normal means
Wenhua Jiang
Cun-Hui Zhang
345
216
0
12 Aug 2009
Gibbs posterior for variable selection in high-dimensional
  classification and data mining
Gibbs posterior for variable selection in high-dimensional classification and data mining
Wenxin Jiang
M. Tanner
92
116
0
31 Oct 2008
A comparison of the Benjamini-Hochberg procedure with some Bayesian
  rules for multiple testing
A comparison of the Benjamini-Hochberg procedure with some Bayesian rules for multiple testing
M. Bogdan
J. Ghosh
S. Tokdar
103
100
0
16 May 2008
Aggregation by exponential weighting, sharp PAC-Bayesian bounds and
  sparsity
Aggregation by exponential weighting, sharp PAC-Bayesian bounds and sparsity
A. Dalalyan
Alexandre B. Tsybakov
149
176
0
19 Mar 2008
Sparsistency and rates of convergence in large covariance matrix
  estimation
Sparsistency and rates of convergence in large covariance matrix estimation
Clifford Lam
Jianqing Fan
235
610
0
26 Nov 2007
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