rlibkriging (version 0.9-1)

simulate.NoiseKriging: Simulation from a NoiseKriging 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 NoiseKriging
simulate(
  object,
  nsim = 1,
  seed = 123,
  x,
  with_noise = NULL,
  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 NoiseKriging object.

nsim

Number of simulations to perform.

seed

Random seed used.

x

Points in model input space where to simulate.

with_noise

Set to array of values if wish to add the noise 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) + X/10 * rnorm(nrow(X))
points(X, y, col = "blue")

k <- NoiseKriging(y, (X/10)^2, 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")