tgp (version 1.0-1)

friedman.1.data: First Friedman Dataset

Description

Function to generate X and Y values from the 10-dim first Friedman data set used to validate the Multivariate Adaptive Regression Splines (MARS) model. This function is stationary, with three non-linear and interacting variables, along with two linear, and five irrelevant effects.

Usage

friedman.1.data(n = 100)

Arguments

n

Number of samples

Value

• Output is a data.frame with columns
• X1{describing the 10-d sampled inputs} Y{sample responses (with N(0,1) noise)} Ytruth{true responses (without noise)}
• Friedman, J. H. (1991). Multivariate adaptive regression splines. Annals of Statistics, 19, No. 1, 1--67.

  Gramacy, R. B. & Lee, H. K. H. (2005). Gaussian Processes and Limiting Linear Models. available as UCSC Technical Report ams2005-17 http://www.ams.ucsc.edu/reports/trview.php?content=view&name=ams2005-17

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

  http://people.ucsc.edu/~boobles/tgp.php

  [object Object]

  Examples using data is are in the package vignette. Read vignette("tgp", package="tgp").

  tgp, bgpllm, btlm, blm, bgp, btgpllm bgp

  datasets

Details

10-dim inputs X are drawn from N(0,1), and responses are N(m(X),1) where m(X) = E(X) = 10*sin(pi*X[,1]*X[,2]) + 20*(X[,3]-0.5)^2 + 10*X[,4] + 5*X[,5]