# Selected Papers and Datasets

**2021** Resampling plans and the estimation of prediction error
**2021** Empirical Bayes: Concepts and methods
**2020** Prediction, estimation, and attribution
**2020** The automatic construction of bootstrap confidence intervals, with B. Narasimhan
**2018** Bayes, oracle Bayes, and empirical Bayes
**2016** A *g*-modeling program for deconvolution and empirical Bayes estimation, with B. Narasimhan
**2016** Curvature and inference for maximum likelihood estimates
**2015** The Bayes deconvolution problem
**2014** Two modeling strategies for empirical Bayes estimation
**2013** Frequentist accuracy of Bayesian estimates
**2013** Estimation and accuracy after model selection
**2013** Empirical Bayes modeling, computation, and accuracy
**2012** Bayesian inference and the parametric bootstrap
**2012** A 250-year argument: Belief, behavior, and the bootstrap
**2012** Model selection, estimation, and bootstrap smoothing
**2011** Tweedie's formula and selection bias
**2011** The bootstrap and Markov chain Monte Carlo
**2010** False discovery rates and copy number variation, with N. Zhang
**2009** The future of indirect evidence and a Rejoinder
**2009** Correlated *z*-values and the accuracy of large-scale statistical estimates
**2008** Empirical Bayes estimates for large-scale prediction problems
**2008** Row and column correlations (Are a set of microarrays independent of each other?) (March)
**2007** Simultaneous inference: When should hypothesis testing problems be combined?
**2007** Doing thousands of hypothesis tests at the same time
**2006** Microarrays, empirical Bayes, and the two-groups model
**2006** Testing the significance of sets of genes
**2006** Size, power, and false discovery rates
**2006** Correlation and large-scale simultaneous significance testing