# NOT RUN {
## 1D Example
n <- 5
d <- 1
computer_simulator <- function(x){
x <- 2*x+0.5
sin(10*pi*x)/(2*x) + (x-1)^4
}
set.seed(3)
library(lhs)
x <- maximinLHS(n,d)
y <- computer_simulator(x)
xvec <- seq(from = 0, to = 1, length.out = 10)
GPmodel <- GP_fit(x, y)
head(fitted(GPmodel))
lapply(predict(GPmodel, xvec), head)
## 1D Example 2
n <- 7
d <- 1
computer_simulator <- function(x) {
log(x+0.1)+sin(5*pi*x)
}
set.seed(1)
library(lhs)
x <- maximinLHS(n,d)
y <- computer_simulator(x)
xvec <- seq(from = 0,to = 1, length.out = 10)
GPmodel <- GP_fit(x, y)
head(fitted(GPmodel))
predict(GPmodel, xvec)
## 2D Example: GoldPrice Function
computer_simulator <- function(x) {
x1 <- 4*x[,1] - 2
x2 <- 4*x[,2] - 2
t1 <- 1 + (x1 + x2 + 1)^2*(19 - 14*x1 + 3*x1^2 - 14*x2 +
6*x1*x2 + 3*x2^2)
t2 <- 30 + (2*x1 -3*x2)^2*(18 - 32*x1 + 12*x1^2 + 48*x2 -
36*x1*x2 + 27*x2^2)
y <- t1*t2
return(y)
}
n <- 10
d <- 2
set.seed(1)
library(lhs)
x <- maximinLHS(n,d)
y <- computer_simulator(x)
GPmodel <- GP_fit(x,y)
# fitted values
head(fitted(GPmodel))
# new data
xvector <- seq(from = 0,to = 1, length.out = 10)
xdf <- expand.grid(x = xvector, y = xvector)
predict(GPmodel, xdf)
# }
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