fda.usc (version 1.1.0)

rproc2fdata: Generate random process of fdata class.

Description

Generate Functional data from: Ornstein Uhlenbeck process, Brownian process, Gaussian process or Exponential variogram process.

Usage

rproc2fdata(n,t=NULL,mu=rep(0,length(t)),sigma=1,
par.list=list("scale"=1,"theta"=1/(3*diff(rtt))),norm=FALSE,verbose=FALSE,...)

Arguments

n

Number of functional data to generate.

t

Discretization points.

mu

vector which specifies the trend values at the discretization points, by default mu=$\mu(t)=0$. If mu is a fdata class object, t$=$argvals(mu).

sigma

A positive-definite symmetric matrix, $\Sigma_{s,t}$, specifying the covariance matrix of the variables. If sigma is a scalar, creates a random Gaussian process with $\Sigma_{s,t}=$sigmaI (by default sigma=

par.list

List of parameter to process, by default "scale" $\sigma^2=1$ and "theta" $\theta=1/(3range(t))$.

norm

If TRUE the norm of random projection is 1. Default is FALSE

verbose

If TRUE, information about procedure is printed. Default is FALSE.

...

Further arguments passed to or from other methods.

Value

• Return the functional random process of fdata class object.

Examples

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 a error