On Convergence Rates of Empirical Bayes Procedures

Empirical Bayes procedures are commonly used based on the supposed asymptotic equivalence with fully Bayesian procedures, which, however, has not so far received full theoretical support in terms of uncertainty quantification. In this note, we provide some results on contraction rates of empirical Bayes posterior distributions which are illustrated in nonparametric curve estimation using Dirichlet process mixture models.

[1]  Peter A. Frost,et al.  An Empirical Bayes Approach to Efficient Portfolio Selection , 1986, Journal of Financial and Quantitative Analysis.

[2]  A. V. D. Vaart,et al.  Posterior convergence rates of Dirichlet mixtures at smooth densities , 2007, 0708.1885.

[3]  A. V. D. Vaart,et al.  Entropies and rates of convergence for maximum likelihood and Bayes estimation for mixtures of normal densities , 2001 .

[4]  D. Freedman,et al.  On the consistency of Bayes estimates , 1986 .

[5]  Edward I. George,et al.  Empirical Bayes vs. Fully Bayes Variable Selection , 2008 .

[6]  Thomas M. Cover,et al.  Empirical Bayes stock market portfolios , 1986 .

[7]  Catia Scricciolo Adaptive Bayesian Density Estimation in $L^{p}$-metrics with Pitman-Yor or Normalized Inverse-Gaussian Process Kernel Mixtures , 2014 .

[8]  Ramsés H. Mena,et al.  Bayesian non‐parametric inference for species variety with a two‐parameter Poisson–Dirichlet process prior , 2009 .

[9]  A. V. D. Vaart,et al.  Adaptive Bayesian density estimation with location-scale mixtures , 2010 .

[10]  E. Belitser,et al.  On the empirical Bayes approach to adaptive filtering , 2002 .

[11]  James G. Scott,et al.  Bayes and empirical-Bayes multiplicity adjustment in the variable-selection problem , 2010, 1011.2333.

[12]  Jun S. Liu Nonparametric hierarchical Bayes via sequential imputations , 1996 .

[13]  H. Robbins An Empirical Bayes Approach to Statistics , 1956 .

[14]  Judith Rousseau,et al.  Bayes and empirical Bayes : Do they merge? , 2012, 1204.1470.

[15]  Michael I. Jordan,et al.  Nonparametric empirical Bayes for the Dirichlet process mixture model , 2006, Stat. Comput..

[16]  L. Wasserman,et al.  Asymptotic inference for mixture models by using data‐dependent priors , 2000 .

[17]  A. V. D. Vaart,et al.  Convergence rates of posterior distributions for non-i.i.d. observations , 2007, 0708.0491.

[18]  A. V. D. Vaart,et al.  Empirical Bayes scaling of Gaussian priors in the white noise model , 2013 .

[19]  Judith Rousseau,et al.  Posterior concentration rates for empirical Bayes procedures, with applications to Dirichlet Process mixtures , 2014, 1406.4406.

[20]  J. Ghosh,et al.  Posterior consistency for semi-parametric regression problems , 2003 .

[21]  J. Rousseau Rates of convergence for the posterior distributions of mixtures of betas and adaptive nonparamatric estimation of the density , 2010, 1001.1615.

[22]  M. Clyde,et al.  Flexible empirical Bayes estimation for wavelets , 2000 .

[23]  S. Ghosal,et al.  Adaptive Bayesian multivariate density estimation with Dirichlet mixtures , 2011, 1109.6406.

[24]  Dean Phillips Foster,et al.  Calibration and Empirical Bayes Variable Selection , 1997 .

[25]  J. Rousseau,et al.  Empirical Bayes methods in classical and Bayesian inference , 2014, METRON.

[26]  John D. Storey,et al.  Empirical Bayes Analysis of a Microarray Experiment , 2001 .