simulate.Kriging | R Documentation |

`Kriging`

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

```
## S3 method for class 'Kriging'
simulate(object, nsim = 1, seed = 123, x, ...)
```

`object` |
S3 Kriging object. |

`nsim` |
Number of simulations to perform. |

`seed` |
Random seed used. |

`x` |
Points in model input space where to simulate. |

`...` |
Ignored. |

a matrix with `length(x)`

rows and `nsim`

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

.

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.

Yann Richet yann.richet@irsn.fr

```
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)
points(X, y, col = "blue")
k <- Kriging(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")
```

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