simulate,NoiseKM-method: Simulation from a `NoiseKM` Object

Description

The simulate method is used to simulate paths from the kriging model described in object.

Usage

# S4 method for NoiseKM
simulate(
  object,
  nsim = 1,
  seed = NULL,
  newdata,
  cond = TRUE,
  nugget.sim = 0,
  checkNames = FALSE,
  ...
)

Value

A numeric matrix with nrow(newdata) rows and

nsim columns containing as its columns the simulated paths at the input points given in newdata.

XXX method simulate NoiseKM

Arguments

object: A NoiseKM object.
nsim: Integer: number of response vectors to simulate.
seed: Random seed.
newdata: Numeric matrix with it rows giving the points where the simulation is to be performed.
cond: Logical telling wether the simulation is conditional or not. Only TRUE is accepted for now.
nugget.sim: Numeric. A postive nugget effect used to avoid numerical instability.
checkNames: Check consistency between the design data X within object and newdata. The default is FALSE. XXXY Not used!!!
...: Ignored.

Author

Yann Richet yann.richet@irsn.fr

Details

Without a dedicated simulate method for the class "NoiseKM", this method would have been inherited from the "km" class. The dedicated method is expected to run faster. A comparison can be made by coercing a NoiseKM object to a km object with as.km before calling simulate.

Examples

Run this code

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(5))
y <- f(X) + 0.01*rnorm(nrow(X))
points(X, y, col = 'blue')
k <- NoiseKM(design = X, response = y, covtype = "gauss", noise=rep(0.01^2,nrow(X)))
x <- seq(from = 0, to = 1, length.out = 101)
s_x <- simulate(k, nsim = 3, newdata = x)
lines(x, s_x[ , 1], col = 'blue')
lines(x, s_x[ , 2], col = 'blue')
lines(x, s_x[ , 3], col = 'blue')

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