DLSimulate function

Simulate linear time series

The Durbin-Levinsion recursions are used to simulate a stationary time series given an unit innovation sequence and given autocovariance function. Requires [REMOVE_ME]$O(n^2) [REMOVE_ME_2]$ flops.

Description

The Durbin-Levinsion recursions are used to simulate a stationary time series given an unit innovation sequence and given autocovariance function. Requires

flops.

DLSimulate(n, r, useC = TRUE, rand.gen = rnorm, ...)

Arguments

• n: length of time series to be generated
• r: autocovariances, lags 0, ...,
• useC: =TRUE, use C interface. Otherwise direct computation.
• rand.gen: random number generator to use
• ...: optional arguments passed to rand.gen

Details

See Hipel and McLeod (1994) or McLeod, Yu and Krougly (2007).

Returns

simulated time series of length n

References

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

Author(s)

A.I. McLeod

See Also

DHSimulate, SimGLP, arima.sim

Examples

#Simulate hyperbolic decay time series 
#with Hurst coefficient, H=0.9
n<-2000
H<-0.9
alpha<-2*(1-H)  #hyperbolic decay parameter
r<-(1/(1:n))^alpha
z<-DLSimulate(n, r)
plot.ts(z)
#can use HurstK function in FGN library to estimate H