simulate,NoiseKM-method | R Documentation |
NoiseKM
ObjectThe simulate
method is used to simulate paths from the
kriging model described in object
.
## S4 method for signature 'NoiseKM'
simulate(
object,
nsim = 1,
seed = NULL,
newdata,
cond = TRUE,
nugget.sim = 0,
checkNames = FALSE,
...
)
object |
A |
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 |
nugget.sim |
Numeric. A postive nugget effect used to avoid numerical instability. |
checkNames |
Check consistency between the design data
|
... |
Ignored. |
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
.
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
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(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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