Contributed Discussion to Uncertainty Quantification for the Horseshoe by Stéphanie van der Pas, Botond Szabó and Aad van der Vaart

Abstract

We begin by introducing the main ideas of the paper under discussion. We discuss some interesting issues regarding adaptive component-wise credible intervals. We then briefly touch upon the concepts of self-similarity and excessive bias restriction. This is then followed by some comments on the extensive simulation study carried out in the paper.

2 pages

References in corpus (6)

• Needles and Straw in a Haystack: Posterior concentration for possibly sparse sequences
• General maximum likelihood empirical Bayes estimation of normal means
• Confidence bands in density estimation
• The Horseshoe Estimator: Posterior Concentration around Nearly Black Vectors
• Contributed Discussion to Uncertainty Quantification for the Horseshoe by Stéphanie van der Pas, Botond Szabó and Aad van der Vaart
• Adaptive nonparametric confidence sets

Cited by in corpus (6)

• Contributed Discussion to Uncertainty Quantification for the Horseshoe by Stéphanie van der Pas, Botond Szabó and Aad van der Vaart
• General framework for projection structures
• Joint Mean-Covariance Estimation via the Horseshoe with an Application in Genomic Data Analysis
• Incorporating prior information and borrowing information in high-dimensional sparse regression using the horseshoe and variational Bayes
• Convergence Rates of Empirical Bayes Posterior Distributions: A Variational Perspective
• Bayesian Shrinkage towards Sharp Minimaxity