perturbFGN: Simulation of a perturbed fGn

In wonsang/wfGn: Estimation of the Hurst Parameter for Contaminated Fractional Gaussian Noises

Description

Simulation of a sample path of a fractional Gaussian noise contaminated by outliers or an additive Gaussian noise

Usage

perturbFGN(n, H, C = 1, type = "no", p=.005, SNR=NULL, plot = FALSE)

Arguments

n	sample size
H	Hurst parameter in (0,1)
C	scaling coefficient. Default is 1.
type	type of perturbation. Possible modes are "no","WN","AO".
p	the ratio of perturbation by outliers. Default is 0.005.
SNR	Signal to noise ratio
plot	plot of perturbed fGn. Default is FALSE.

Details

The types of contamination are listed below. The most parts of this function were adopted from the package dvfBm.

"no"

no contamination

"AO"

contamination by additive outliers of 0.5%

"WN"

contamination by i.i.d. standard Gaussian noise

Value

a vector of length n.

Author(s)

Wonsang You

References

S. Achard and J.-F. Coeurjolly (2009). Discrete variations of the fractional Brownian in the presence of outliers and an additive noise.

See Also

circFGN, wFGN

Examples

ts1<-perturbFGN(1000,0.2,type="no",plot=TRUE)
ts2<-perturbFGN(1000,0.7,type="AO",SNR=20,plot=TRUE)
ts3<-perturbFGN(10000,0.3,type="WN",SNR=10,plot=TRUE)

wonsang/wfGn documentation built on May 14, 2019, 9:25 p.m.