UDF.Kernel {rkriging} | R Documentation |
User Defined Function (UDF) Kernel
Description
This function specifies a kernel with the user defined R function.
Usage
UDF.Kernel(lengthscale, kernel.function)
Arguments
lengthscale |
a vector for the positive length scale parameters |
kernel.function |
user defined kernel function |
Details
The User Defined Function (UDF) kernel is given by
where is the user defined kernel function that takes
as input,
where
is the euclidean distance between and
weighted by
the length scale parameters
's.
Value
A User Defined Function (UDF) Kernel Class Object.
Author(s)
Chaofan Huang and V. Roshan Joseph
References
Duvenaud, D. (2014). The kernel cookbook: Advice on covariance functions.
Rasmussen, C. E. & Williams, C. K. (2006). Gaussian Processes for Machine Learning. The MIT Press.
See Also
MultiplicativeUDF.Kernel, Get.Kernel, Evaluate.Kernel.
Examples
n <- 5
p <- 3
X <- matrix(rnorm(n*p), ncol=p)
lengthscale <- c(1:p)
kernel.function <- function(sqdist) {return (exp(-sqrt(sqdist)))}
# approach 1
kernel <- UDF.Kernel(lengthscale, kernel.function=kernel.function)
Evaluate.Kernel(kernel, X)
# approach 2
kernel <- Get.Kernel(lengthscale, type="UDF",
parameters=list(kernel.function=kernel.function))
Evaluate.Kernel(kernel, X)
[Package rkriging version 1.0.1 Index]