@article{JSSv019i09, title={tgp: An R Package for Bayesian Nonstationary, Semiparametric Nonlinear Regression and Design by Treed Gaussian Process Models}, volume={19}, url={https://www.jstatsoft.org/index.php/jss/article/view/v019i09}, doi={10.18637/jss.v019.i09}, abstract={The tgp package for R is a tool for fully Bayesian nonstationary, semiparametric nonlinear regression and design by treed Gaussian processes with jumps to the limiting linear model. Special cases also implemented include Bayesian linear models, linear CART, stationary separable and isotropic Gaussian processes. In addition to inference and posterior prediction, the package supports the (sequential) design of experiments under these models paired with several objective criteria. 1-d and 2-d plotting, with higher dimension projection and slice capabilities, and tree drawing functions (requiring maptree and combinat packages), are also provided for visualization of tgp objects.}, number={9}, journal={Journal of Statistical Software}, author={Gramacy, Robert B.}, year={2007}, pages={1–46} }