Good, great, or lucky? Screening for firms with sustained superior performance using heavy-tailed priors

DOI10.1214/11-AOAS512zbMath1235.91144arXiv1010.5223OpenAlexW3104944253MaRDI QIDQ2428740

Nicholas G. Polson, James G. Scott

Publication date: 20 April 2012

Published in: The Annals of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1010.5223

zbMATH Keywords

multiple testingsparsitynormal scale mixturescorporate benchmarkingtype-II beta distribution

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Statistical methods; economic indices and measures (91B82)

Related Items

A weakly informative prior for Bayesian dynamic model selection with applications in fMRI, Conditions for posterior contraction in the sparse normal means problem, The horseshoe estimator: posterior concentration around nearly black vectors, Fully Bayesian logistic regression with hyper-LASSO priors for high-dimensional feature selection, Spatially Dependent Multiple Testing Under Model Misspecification, With Application to Detection of Anthropogenic Influence on Extreme Climate Events

Uses Software

• EBayesThresh

Cites Work

• Microarrays, empirical Bayes and the two-groups model
• A robust generalized Bayes estimator and confidence region for a multivariate normal mean
• Estimation of the mean of a multivariate normal distribution
• Bayesian prediction in \(M/M/1\) queues
• A generalization of the beta distribution with applications
• On the construction of Bayes minimax estimators
• Needles and straw in haystacks: Empirical Bayes estimates of possibly sparse sequences
• An exploration of aspects of Bayesian multiple testing
• A guided random walk through some high dimensional problems
• Adapting to unknown sparsity by controlling the false discovery rate
• On the half-Cauchy prior for a global scale parameter
• Bayesian Treed Gaussian Process Models With an Application to Computer Modeling
• The horseshoe estimator for sparse signals
• Mixtures of g Priors for Bayesian Variable Selection
• A representation of the posterior mean for a location model
• Approximate non-Gaussian filtering with linear state and observation relations
• Multiple Hypothesis Testing by Clustering Treatment Effects
• Proper Bayes Minimax Estimators of the Multivariate Normal Mean
• A Bayesian Mixture Model for Differential Gene Expression
• Prior distributions for variance parameters in hierarchical models (Comment on article by Browne and Draper)
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item