A 2-dimensional data set that can be used to validate non-stationary models.
data frame with 441 observations on the following 4 variables.
Numeric vector describing the first dimension of
Numeric vector describing the second dimension of
Numeric vector describing the response
Numeric vector describing the true response
The true response is evaluated as
Z(X) = X1 * exp(-X1^2 -X2^2).
Zero-mean normal noise
sd=0.001 has been added to the true response
This data is used in the examples of the functions listed below in
the “See Also” section via the
Gramacy, R. B. (2020) Surrogates: Gaussian Process Modeling, Design and Optimization for the Applied Sciences. Boca Raton, Florida: Chapman Hall/CRC. https://bobby.gramacy.com/surrogates/
Gramacy, R. B. (2007). tgp: An R Package for Bayesian Nonstationary, Semiparametric Nonlinear Regression and Design by Treed Gaussian Process Models. Journal of Statistical Software, 19(9). https://www.jstatsoft.org/v19/i09
Robert B. Gramacy, Matthew Taddy (2010). Categorical Inputs, Sensitivity Analysis, Optimization and Importance Tempering with tgp Version 2, an R Package for Treed Gaussian Process Models. Journal of Statistical Software, 33(6), 1–48. https://www.jstatsoft.org/v33/i06/.
Gramacy, R. B., Lee, H. K. H. (2008). Bayesian treed Gaussian process models with an application to computer modeling. Journal of the American Statistical Association, 103(483), pp. 1119-1130. Also available as ArXiv article 0710.4536 https://arxiv.org/abs/0710.4536
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