
Last chance! 50% off unlimited learning
Sale ends in
Gaussian Process Model Interface
buildGaussianProcess(x, y, control = list())
matrix of input parameters. Rows for each point, columns for each parameter.
one column matrix of observations to be modeled.
list of control parameters. n
subset size.
an object of class "spotGaussianProcessModel"
,
with a predict
method and a print
method.
# NOT RUN {
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))
# }
Run the code above in your browser using DataLab