FGN (version 2.0-12)

Boot.FitFGN: Simulate Fitted FGN Model

Description

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

Usage

"Boot"(obj, R = 1, ...)

Arguments

obj

the output from FitAR

R

number of bootstrap replications

...

optional arguments

Value

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.

Details

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

References

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

See Also

SimulateFGN, DHSimulate DLSimulate

Examples

#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)