Boot.FitFGN: Simulate Fitted FGN Model
In FGN: Fractional Gaussian Noise and power law decay time series model fitting

Description Usage Arguments Details Value Author(s) References See Also Examples

Simulate a realization from a fitted AR model. This is useful in the parametric bootstrap. Generic function for "Boot" method.

1 2	## S3 method for class 'FitFGN' Boot(obj, R = 1, ...)

`obj`	the output from FitAR
`R`	number of bootstrap replications
`...`	optional arguments

The method of Davies and Harte (1987) is used if it is applicable, otherwise the Durbin-Levinsion recursion is used.

If R=1, a simulated time series with the same length as the original fitted time series is produced. Otherwise if R>1, a matrix with R columns and number of rows equal to the length of the series containing R replications of the bootstrap.

A.I. McLeod

McLeod, A.I., Yu, Hao, Krougly, Zinovi L. (2007). Algorithms for Linear Time Series Analysis, Journal of Statistical Software.

SimulateFGN, DHSimulate DLSimulate

#Example 1
#Fit a FGN model and determine the bootstrap sd of H
#Measure cpu time. With R=250, it takes about 23 sec 
#on 3.6 GHz Pentium IV.
## Not run: 
data(NileMin)
outNileMin<-FitFGN(NileMin)
start<-proc.time()[1]
R<-25
Hs<-numeric(R)
Z<-Boot(outNileMin, R=R)
for (i in 1:R)
    Hs[i]<-GetFitFGN(Z[,i])$H
BootSD<-sd(Hs) #this is the bootstrap sd
end<-proc.time()[1]
totTim<-end-start

## End(Not run)