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

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

sigma

A positive-definite symmetric matrix, Σs,t\Sigma_{s,t}, specifying the covariance matrix among grid points. If sigma is a scalar, creates a random Gaussian process with Σs,t=\Sigma_{s,t}=sigmaI (by default sigma=1).
If sigma is a vector, creates a random Gaussian process with Σs,t=\Sigma_{s,t}=diag(sigma).
If sigma is a character: create a random process using the covariance matrix Σs,t\Sigma_{s,t} indicated in the argument,

  • "OU" or "OrnsteinUhlenbeck", creates a random Ornstein Uhlenbeck process with Σs,t=σ22θeθ(s+t)(e2θ(s+t)1)\Sigma_{s,t}=\frac{\sigma^2}{2\theta}e^{-\theta\left(s+t\right)} \left(e^{2\theta\left(s+t\right)}-1\right), by default θ=1/(3range(t))\theta=1/(3range(t)), σ2=1\sigma^2={1}.

  • "brownian" or "wiener", creates a random Wiener process with Σs,t=σ2min(s,t)\Sigma_{s,t}=\sigma^2 min(s,t), by default σ2=1\sigma^2=1.

  • "fbrownian", creates a random fractional brownian process with Σs,t=σ2H/2s2H+t2Hst2H\Sigma_{s,t}=\sigma^{2H}/2{|s|^{2H}+|t|^{2H}-|s-t|^{2H}}, by default σ2=1\sigma^2=1 and H=0.5H=0.5 (brownian process).

  • "vexponential", creates a random gaussian process with exponential variogram Σs,t=σ2e(stθ)\Sigma_{s,t}=\sigma^2 e^{\left(-\frac{\left|s-t\right|}{\theta}\right)}, by default θ=0.2range(t)\theta={0.2 range(t)}, σ2=1\sigma^2={1}.

par.list

List of parameter to process, by default "scale" σ2=1\sigma^2=1, "theta" θ=0.2range(t)\theta=0.2 range(t) and "H"=0.5.

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 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)


[Package fda.usc version 2.1.0 Index]