Bayesian Model Selection in Additive Partial Linear Models Via Locally Adaptive Splines

DOI10.1080/10618600.2021.1999827OpenAlexW3213884429MaRDI QIDQ5084431

Taeyoung Park, David A. van Dyk, Seonghyun Jeong

Publication date: 24 June 2022

Published in: Journal of Computational and Graphical Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2008.06213

zbMATH Keywords

nonparametric regressionfunction estimationmixtures of \(g\)-priorsBayesian adaptive regressionknot-selection

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (1)

Functional clustering methods for binary longitudinal data with temporal heterogeneity

Uses Software

• SemiPar

Cites Work

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• Robust specification of the roughness penalty prior distribution in spatially adaptive Bayesian P-splines models
• Posterior model consistency in variable selection as the model dimension grows
• On Bayesian model and variable selection using MCMC
• Bayesian semiparametric inference on functional relationships in linear mixed models
• Bayes and empirical-Bayes multiplicity adjustment in the variable-selection problem
• Fully Bayes factors with a generalized \(g\)-prior
• Criteria for Bayesian model choice with application to variable selection
• Component selection and smoothing in multivariate nonparametric regression
• Adaptive priors based on splines with random knots
• Locally adaptive Bayesian P-splines with a normal-exponential-gamma prior
• Variable selection in nonparametric additive models
• Statistical analysis of stellar evolution
• Nonparametric regression using Bayesian variable selection
• A practical guide to splines
• Fast Bayesian model assessment for nonparametric additive regression
• Posterior consistency of \(g\)-prior for variable selection with a growing number of parameters
• Analysis of binary longitudinal data with time-varying effects
• Optimal predictive model selection.
• Hyper-\(g\) priors for generalized linear models
• Calibration and empirical Bayes variable selection
• Bayesian curve-fitting with free-knot splines
• Mixtures ofg-Priors in Generalized Linear Models
• Can Tests for Jumps be Viewed as Tests for Clusters?
• Adaptive Bayesian Procedures Using Random Series Priors
• Adaptive sampling for Bayesian variable selection
• Mixtures of g Priors for Bayesian Variable Selection
• Partially Collapsed Gibbs Samplers
• Bayesian Model Averaging for Linear Regression Models
• Semiparametric Regression
• Sparse Additive Models
• Analysis of Poisson varying-coefficient models with autoregression
• Spike-and-Slab Priors for Function Selection in Structured Additive Regression Models
• Multivariate output analysis for Markov chain Monte Carlo
• Automatic structure recovery for additive models
• Minimax-optimal rates for sparse additive models over kernel classes via convex programming
• Estimation and variable selection for semiparametric additive partial linear models
• Benchmark priors for Bayesian model averaging.

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