Get.Kriging.Parameters {rkriging}

Get Kriging Parameters

Description

This function can be used for extracting the estimates of the kriging parameters.

Usage

Get.Kriging.Parameters(kriging)

Arguments

kriging

a kriging class object

Value

nllh

negative log-likelihood of the kriging model

mu

mean of the kriging model

nu2

variance of the kriging model

sigma2

variance of the random noise when interpolation=FALSE

beta

coefficients of the basis functions for universal kriging

c

c for the rational / generalized rational kriging, see Joseph (2024)

c0

c0 for the generalized rational kriging, see Joseph (2024)

Author(s)

Chaofan Huang and V. Roshan Joseph

References

Joseph, V. R. (2006). Limit kriging. Technometrics, 48(4), 458-466.

Joseph, V. R. (2024). Rational Kriging. Journal of the American Statistical Association.

Rasmussen, C. E. & Williams, C. K. (2006). Gaussian Processes for Machine Learning. The MIT Press.

Santner, T. J., Williams, B. J., Notz, W. I., & Williams, B. J. (2003). The design and analysis of computer experiments (Vol. 1). New York: Springer.

See Also

Fit.Kriging.

Examples

# one dimensional example 
f <- function(x) {
  x <- 0.5 + 2*x
  y <- sin(10*pi*x)/(2*x) + (x-1)^4
  return (y)
}

set.seed(1234)
# train set
n <- 30
p <- 1
X <- matrix(runif(n),ncol=p)
y <- apply(X, 1, f)
newX <- matrix(seq(0,1,length=1001), ncol=p)

kriging <- Fit.Kriging(X, y, interpolation=TRUE, fit=TRUE, model="OK",
                       kernel.parameters=list(type="Gaussian"))
Get.Kriging.Parameters(kriging)