friedman.1.data {tgp}R Documentation

First Friedman Dataset

Description

Generate X and Y values from the 10-dim “first” Friedman data set used to validate the Multivariate Adaptive Regression Splines (MARS) model. This test function has three non-linear and interacting variables, along with two linear, and five which are irrelevant

Usage

friedman.1.data(n = 100)

Arguments

n Number of samples desired

Details

10-dim inputs X are drawn from N(0,1), and responses are N(m(X),1) where m(X) = E[X] and

E[X] = 10*sin(pi*X[,1]*X[,2]) + 20*(X[,3]-0.5)^2 + 10*X[,4] + 5*X[,5]

Value

Output is a data.frame with columns

X1... 10 describing the 10-d sampled inputs
Y sample responses (with N(0,1) noise)
Ytruth true responses (without noise)

Note

An example using this data is contained in the package vignette: vignette("tgp").

Author(s)

Robert B. Gramacy, rbgramacy@ams.ucsc.edu
Matt Taddy, taddy@ams.ucsc.edu

References

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). http://www.jstatsoft.org/v19/i09

Friedman, J. H. (1991). Multivariate adaptive regression splines. “Annals of Statistics”, 19, No. 1, 1–67.

Gramacy, R. B., Lee, H. K. H. (2006). Bayesian treed Gaussian process models. Available as UCSC Technical Report ams2006-01.

Chipman, H., George, E., & McCulloch, R. (2002). Bayesian treed models. Machine Learning, 48, 303–324.

http://www.ams.ucsc.edu/~rbgramacy/tgp.html

See Also

bgpllm, btlm, blm, bgp, btgpllm, bgp


[Package tgp version 2.0-1 Index]