loocv.TAAG: Leave-One-Out Cross Validation Error of a TAG or TAAG Process

In TAG: Transformed Additive Gaussian Processes

Description

This function evaluates the leave-one-out cross validation errors of a TAG or TAAG process.

Usage

cv.TAAG(object, TAAG.indicator  = FALSE)

Arguments

object	object of class inheriting from "TAG" or "TAAG".
TAAG.indicator	logical. If TRUE, the object is from TAAG; otherwise, from TAG.

Value

The values returned from the function is a list containing:

CV	Leave-one-out cross validation errors in the original scale of y.
TCV	Leave-one-out cross validation errors in the transformed scale.

References

Lin, L.-H. and Joseph, V. R. (2020) "Transformation and Additivity in Gaussian Processes",Technometrics, 62, 525-535. DOI:10.1080/00401706.2019.1665592.

See Also

TAG and TAAG for the estimates of the parameters in the TAG and TAAG, respectively.

Examples

n <- 20
p <- 2
library(randtoolbox)
X <- sobol(n, dim = p, init = TRUE, scrambling = 2, seed = 20, normal = FALSE)
y <- exp(2*sin(0.5*pi*X[,1]) + 0.5*cos(2.5*pi*X[,2]))
ini.TAG <- initial.TAG(y, X)
par.TAG <- TAG(ini.TAG)
cv.scores <- cv.TAAG(par.TAG)
(CV.TAG <- cv.scores$CV)
(TCV.TAG <- cv.scores$TCV)

TAG documentation built on June 8, 2021, 1:06 a.m.