Functional Horseshoe Priors for Subspace Shrinkage

DOI10.1080/01621459.2019.1654875zbMath1452.62523arXiv1606.05021OpenAlexW2968000259MaRDI QIDQ5146030

Valen E. Johnson, Minsuk Shin, Anirban Bhattacharya

Publication date: 22 January 2021

Published in: Journal of the American Statistical Association (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1606.05021

zbMATH Keywords

nonparametric regressionBayesian shrinkageposterior contractionadditive model

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Ridge regression; shrinkage estimators (Lasso) (62J07)

Related Items (4)

Bayesian Shrinkage for Functional Network Models, With Applications to Longitudinal Item Response Data ⋮ Horseshoe Regularisation for Machine Learning in Complex and Deep Models¹ ⋮ TAIL FORECASTING WITH MULTIVARIATE BAYESIAN ADDITIVE REGRESSION TREES ⋮ Bayesian sparse spiked covariance model with a continuous matrix shrinkage prior

Uses Software

• SemiPar

Cites Work

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• Bernstein-von Mises theorems for Gaussian regression with increasing number of regressors
• Component selection and smoothing in multivariate nonparametric regression
• A note on Bayes factor consistency in partial linear models
• Variable selection in nonparametric additive models
• Convergence rates of posterior distributions for non iid observations
• A note on the Bayes factor in a semiparametric regression model
• High-dimensional additive modeling
• Generalized additive models. With discussion
• Fast Bayesian model assessment for nonparametric additive regression
• Local asymptotics for regression splines and confidence regions
• Convergence rates of posterior distributions.
• A study of logspline density estimation
• On the half-Cauchy prior for a global scale parameter
• Inference with normal-gamma prior distributions in regression problems
• A Partially Linear Model Using a Gaussian Process Prior
• Asymptotic properties of penalized spline estimators
• The horseshoe estimator for sparse signals
• The Bayesian Lasso
• Bayesian lasso regression
• Generalized Cross-Validation as a Method for Choosing a Good Ridge Parameter
• 10.1162/15324430152748236
• Bayesian Model Averaging for Linear Regression Models
• Semiparametric Regression
• Sparse Additive Models
• Generalized double Pareto shrinkage
• Bayesian Model Selection in High-Dimensional Settings
• Stein's Estimation Rule and Its Competitors--An Empirical Bayes Approach
• Dirichlet–Laplace Priors for Optimal Shrinkage
• Model Selection and Estimation in Regression with Grouped Variables
• Ridge Regression: Biased Estimation for Nonorthogonal Problems
• A practical guide to splines.

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