Classification and categorical inputs with treed Gaussian process models

DOI10.1007/s00357-011-9083-yzbMath1226.62057arXiv0904.4891OpenAlexW2055649884MaRDI QIDQ649163

Tamara Broderick, Robert B. Gramacy

Publication date: 30 November 2011

Published in: Journal of Classification (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/0904.4891

zbMATH Keywords

Bayesian model averaginglatent variabletreed models

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Bayesian inference (62F15) Trees (05C05) Monte Carlo methods (65C05) Inference from stochastic processes (62M99)

Related Items (1)

Analyzing stochastic computer models: a review with opportunities

Uses Software

• R
• UCI-ml
• rpart
• tgp
• nnet
• e1071

Cites Work

• Spatial variation. 2nd ed
• Multivariate adaptive regression splines
• Interpolation of spatial data. Some theory for kriging
• Adaptive Rejection Sampling for Gibbs Sampling
• The elements of statistical learning. Data mining, inference, and prediction
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