A note on Bayes factor consistency in partial linear models

DOI10.1016/j.jspi.2015.03.009zbMath1394.62042OpenAlexW2038356042MaRDI QIDQ899549

Taeryon Choi, Judith Rousseau

Publication date: 29 December 2015

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jspi.2015.03.009

zbMATH Keywords

consistencyHellinger distanceGaussian processesBayes factorFourier seriesKullback-Leibler neighborhoodslack of fit testing

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Asymptotic properties of nonparametric inference (62G20) Bayesian inference (62F15)

Related Items (6)

Bayes factor asymptotics for variable selection in the Gaussian process framework ⋮ Functional Horseshoe Priors for Subspace Shrinkage ⋮ Bayesian Analysis of the Proportional Hazards Model with Time‐Varying Coefficients ⋮ Bayesian Model Comparison with the Hyvärinen Score: Computation and Consistency ⋮ Posterior convergence for Bayesian functional linear regression ⋮ A Short Note on Almost Sure Convergence of Bayes Factors in the General Set-Up

Cites Work

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• Additive cubic spline regression with Dirichlet process mixture errors
• Adaptive nonparametric Bayesian inference using location-scale mixture priors
• Posterior consistency of Bayesian quantile regression based on the misspecified asymmetric Laplace density
• Rates of contraction of posterior distributions based on Gaussian process priors
• Consistency of objective Bayes factors as the model dimension grows
• Posterior convergence rates of Dirichlet mixtures at smooth densities
• Convergence rates of posterior distributions for non iid observations
• A note on the Bayes factor in a semiparametric regression model
• Consistency of Bayesian procedures for variable selection
• Asymptotic methods in statistical decision theory
• A note on the consistency of Bayes factors for testing point null versus nonparametric alternatives.
• Bayesian goodness-of-fit testing using infinite-dimensional exponential families
• Rates of convergence of posterior distributions.
• Nonparametric and semiparametric models.
• Bayesian variants of some classical semiparametric regression techniques
• Lower bounds for posterior rates with Gaussian process priors
• Consistency of Bayesian linear model selection with a growing number of parameters
• Nonparametric Bayesian model selection and averaging
• A computational Bayesian method for estimating the number of knots in regression splines
• A Partially Linear Model Using a Gaussian Process Prior
• Bayesian Goodness of Fit Testing with Mixtures of Triangular Distributions
• Frontiers of Statistical Decision Making and Bayesian Analysis
• Mixtures of g Priors for Bayesian Variable Selection
• Regression
• Bayesian and Conditional Frequentist Testing of a Parametric Model Versus Nonparametric Alternatives
• Bayes Factors
• Bayesian Inference for Semiparametric Regression Using a Fourier Representation
• Bayesian wavelet estimation of partially linear models
• On Priors With a Kullback–Leibler Property
• Prior distributions for variance parameters in hierarchical models (Comment on article by Browne and Draper)

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