kGauss: Gauss (Squared-Exponential) Kernel

In kergp: Gaussian Process Laboratory

Gauss (Squared-Exponential) Kernel

Description

Gauss (or squared exponential) covariance function.

Usage

kGauss(d)

Arguments

d	Dimension.

Value

An object of class "covMan" with default parameters: 1 for ranges and variance values.

References

C.E. Rasmussen and C.K.I. Williams (2006), Gaussian Processes for Machine Learning, the MIT Press, \Sexpr[results=rd]{tools:::Rd_expr_doi("10.7551/mitpress/3206.001.0001")}

Examples

kGauss()  # default: d = 1, nu = 5/2
myGauss <- kGauss(d = 2)
coef(myGauss) <- c(range = c(2, 5), sigma2 = 0.1)
myGauss

kergp documentation built on April 4, 2025, 2:29 a.m.