Categorical Inputs, Sensitivity Analysis, Optimization and Importance Tempering with tgp Version 2, an R Package for Treed Gaussian Process Models

Categorical Inputs, Sensitivity Analysis, Optimization and Importance Tempering with tgp Version 2, an R Package for Treed Gaussian Process Models

This document describes the new features in version 2.x of the <b>tgp</b> package for R, implementing treed Gaussian process (GP) models. The topics covered include methods for dealing with categorical inputs and excluding inputs from the tree or GP part of the model; fully Bayesian sens...

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Bibliographic Details
Main Authors: Robert B. Gramacy, Matthew Taddy
Format: Article
Language:English
Published: Foundation for Open Access Statistics 2010-02-01
Series:Journal of Statistical Software
Subjects:
treed Gaussian process
categorical inputs
sensitivity analysis
experiment design
optimization
importance sampling
simulated tempering
Bayesian model averaging
R
Online Access:http://www.jstatsoft.org/v33/i06/paper

Internet

http://www.jstatsoft.org/v33/i06/paper

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