Bayesian neural tree models for nonparametric regression

DOI10.1111/anzs.12386zbMath1521.62048arXiv1909.00515OpenAlexW2971751269MaRDI QIDQ6075185

Ashis Kumar Chakraborty, Gauri Kamat, Tanujit Chakraborty

Publication date: 20 October 2023

Published in: Australian & New Zealand Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1909.00515

zbMATH Keywords

consistencynonparametric regressionhybrid modelBayesian neural tree

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Asymptotic properties of nonparametric inference (62G20) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Bayesian inference (62F15)

Cites Work

• Unnamed Item
• Unnamed Item
• Variable selection for BART: an application to gene regulation
• Bayesian frequentist hybrid inference
• Blending Bayesian and frequentist methods according to the precision of prior information with applications to hypothesis testing
• A bound on the expected maximal deviation of averages from their means.
• Multilayer feedforward networks are universal approximators
• The interplay of Bayesian and frequentist analysis
• Consistency of data-driven histogram methods for density estimation and classification
• Histogram regression estimation using data-dependent partitions
• A data-driven software tool for enabling cooperative information sharing among police departments
• A distribution-free theory of nonparametric regression
• Approximation properties of a multilayered feedforward artificial neural network
• Probability inequalities for likelihood ratios and convergence rates of sieve MLEs
• Posterior concentration for Bayesian regression trees and forests
• A novel distribution-free hybrid regression model for manufacturing process efficiency improvement
• A nonparametric ensemble binary classifier and its statistical properties
• Nonparametric regression with additional measurement errors in the dependent variable
• Adaptive regression estimation with multilayer feedforward neural networks
• Bayesian Nonparametrics via Neural Networks
• Nonparametric estimation via empirical risk minimization
• Learning representations by back-propagating errors
• Bayesian treed models

This page was built for publication: Bayesian neural tree models for nonparametric regression