r-cran-tgp - 2.4-21-1 main

Bayesian nonstationary, semiparametric nonlinear regression and design by
treed Gaussian processes (GPs) with jumps to the limiting linear model (LLM).
Special cases also implemented include Bayesian linear models, CART, treed
linear models, stationary separable and isotropic GPs, and GP single-index
models. Provides 1-d and 2-d plotting functions (with projection and slice
capabilities) and tree drawing, designed for visualization of tgp-class
output. Sensitivity analysis and multi-resolution models are supported.
Sequential experimental design and adaptive sampling functions are also
provided, including ALM, ALC, and expected improvement. The latter supports
derivative-free optimization of noisy black-box functions.