rproc2fdata {fda.usc} | R Documentation |
Simulate several random processes.
Description
Simulate Functional Data from different processes: Ornstein Uhlenbeck, Brownian, Fractional Brownian, Gaussian or Exponential variogram.
Usage
rproc2fdata(
n,
t = NULL,
mu = rep(0, length(t)),
sigma = 1,
par.list = list(scale = 1, theta = 0.2 * diff(rtt), H = 0.5),
norm = FALSE,
verbose = FALSE,
...
)
Arguments
n |
Number of functional curves to be generated. |
t |
Discretization points. |
mu |
|
sigma |
A positive-definite symmetric matrix,
|
par.list |
List of parameter to process, by default |
norm |
If |
verbose |
If |
... |
Further arguments passed to or from other methods. |
Value
Return the functional random processes as a fdata
class
object.
Author(s)
Manuel Febrero-Bande, Manuel Oviedo de la Fuente manuel.oviedo@udc.es
Examples
## Not run:
par(mfrow=c(3,2))
lent<-30
tt<-seq(0,1,len=lent)
mu<-fdata(rep(0,lent),tt)
plot(rproc2fdata(200,t=tt,sigma="OU",par.list=list("scale"=1)))
plot(rproc2fdata(200,mu=mu,sigma="OU",par.list=list("scale"=1)))
plot(rproc2fdata(200,t=tt,sigma="vexponential"))
plot(rproc2fdata(200,t=tt,sigma=1:lent))
plot(rproc2fdata(200,t=tt,sigma="brownian"))
plot(rproc2fdata(200,t=tt,sigma="wiener"))
#plot(rproc2fdata(200,seq(0,1,len=30),sigma="oo")) # this is an error
## End(Not run)