buildGaussianProcess: Gaussian Process Model Interface

In SPOT: Sequential Parameter Optimization Toolbox

Gaussian Process Model Interface

Description

Gaussian Process Model Interface

Usage

buildGaussianProcess(x, y, control = list())

Arguments

x	matrix of input parameters. Rows for each point, columns for each parameter.
y	one column matrix of observations to be modeled.
control	list of control parameters. n subset size.

Value

an object of class "spotGaussianProcessModel", with a predict method and a print method.

Examples

N <- 200
x <- matrix( seq(from=-1, to = 1, length.out = N), ncol = 1)
y <- funSphere(x)  + rnorm(N, 0, 0.1)
fit <- buildGaussianProcess(x,y)
## Print model parameters
print(fit)
## Predict at new location
xNew <- matrix( c(-0.1, 0.1), ncol = 1)
predict(fit, xNew)
## True value at location
t(funSphere(xNew))

SPOT documentation built on June 26, 2022, 1:06 a.m.