# simulate.NuggetKriging: Simulation from a 'NuggetKriging' model object. In rlibkriging: Kriging Models using the 'libKriging' Library

 simulate.NuggetKriging R Documentation

## 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 class 'NuggetKriging'
simulate(object, nsim = 1, seed = 123, 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. `...` Ignored.

### Value

a matrix with `length(x)` rows and `nsim` columns containing the simulated paths at the inputs points given in `x`.

### Note

The names of the formal arguments differ from those of the `simulate` methods for the S4 classes `"km"` and `"KM"`. The formal `x` corresponds to `newdata`. These names are chosen Python and Octave interfaces to libKriging.

### Author(s)

Yann Richet yann.richet@irsn.fr

### 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")
``````

rlibkriging documentation built on July 9, 2023, 5:53 p.m.