The illusion of the illusion of sparsity: an exercise in prior sensitivity
type: Item
instance of: scholarly article
title: The illusion of the illusion of sparsity: an exercise in prior sensitivity
DOI: 10.1214/21-BJPS503
author: Bruno Fava
author: Hedibert F. Lopes
published in: Brazilian Journal of Probability and Statistics
publication date: 2022-02-21T00:00:00Z
full work available at URL: https://arxiv.org/abs/2009.14296
Mathematics Subject Classification ID: 62-XX
Mathematics Subject Classification ID: 92-XX
zbMATH DE Number: 7477281
zbMATH Keywords: Bayesian econometrics
zbMATH Keywords: high dimensional data
zbMATH Keywords: model selection
zbMATH Keywords: shrinkage
zbMATH Keywords: sparsity
MaRDI profile type: Publication
cites work: Sparse models and methods for optimal instruments with an application to eminent domain
cites work: \(\ell_1\)-penalized quantile regression in high-dimensional sparse models
cites work: Inference on Treatment Effects after Selection among High-Dimensional Controls
cites work: Dirichlet–Laplace Priors for Optimal Shrinkage
cites work: Economic Predictions With Big Data: The Illusion of Sparsity
cites work: Inference with normal-gamma prior distributions in regression problems
cites work: Efficient Sampling for Gaussian Linear Regression With Arbitrary Priors
cites work: Ridge Regression: Biased Estimation for Nonorthogonal Problems
cites work: Spike and slab variable selection: frequentist and Bayesian strategies
cites work: Bayesian Variable Selection in Linear Regression
cites work: The Bayesian Lasso
cites work: The Spike-and-Slab LASSO
cites work: Forecasting Using Principal Components From a Large Number of Predictors
OpenAlex ID: W3091443386
describes a project that uses: GitHub
description: scientific article; zbMATH DE number 7477281