rlibkriging (version 0.9-1)

simulate.NuggetKriging: Simulation from a NuggetKriging model object.

Description

This method draws paths of the stochastic process at new input points conditional on the values at the input points used in the fit.

Usage

# S3 method for NuggetKriging
simulate(
  object,
  nsim = 1,
  seed = 123,
  x,
  with_nugget = TRUE,
  will_update = FALSE,
  ...
)

Value

a matrix with nrow(x) rows and nsim

columns containing the simulated paths at the inputs points given in x.

Arguments

object

S3 NuggetKriging object.

nsim

Number of simulations to perform.

seed

Random seed used.

x

Points in model input space where to simulate.

with_nugget

Set to FALSE if wish to remove the nugget in the simulation.

will_update

Set to TRUE if wish to use update_simulate(...) later.

...

Ignored.

Author

Yann Richet

Examples

f <- function(x) 1 - 1 / 2 * (sin(12 * x) / (1 + x) + 2 * cos(7 * x) * x^5 + 0.7)
plot(f)
set.seed(123)
X <- as.matrix(runif(10))
y <- f(X) + 0.1  *rnorm(nrow(X))
points(X, y, col = "blue")

k <- NuggetKriging(y, X, kernel = "matern3_2")

x <- seq(from = 0, to = 1, length.out = 101)
s <- simulate(k, nsim = 3, x = x)

lines(x, s[ , 1], col = "blue")
lines(x, s[ , 2], col = "blue")
lines(x, s[ , 3], col = "blue")