acvfFGN: Autocovariance of FGN

In FGN: Fractional Gaussian Noise and power law decay time series model fitting

Description

The FGN time series is an example of a time series exhibiting long-range dependence and characterized by the fact that its autocorrelation function exhibits hyperbolic decay rather than exponential decay found in stationary ARMA time series. The FGN and other alternatives are discussed in Hipel and McLeod (2005).

Usage

acvfFGN(H, maxlag)

Arguments

H	Hurst parameter
maxlag	acvf computed at lags 0,1,...,maxlag

Value

value of the autocorrelation at lag(s) k

Note

The parameter H should be in (0,1). An error message is given if it is not.

Author(s)

A.I. McLeod

References

Hipel, K.W. and McLeod, A.I., (2005). Time Series Modelling of Water Resources and Environmental Systems. Electronic reprint of our book orginally published in 1994. http://www.stats.uwo.ca/faculty/aim/1994Book/.

See Also

LLFGN, acf

Examples

#compute the acf at lags 0,1,...,10 when H=0.7
acvfFGN(0.7, 10) 

Example output

 [1] 1.00000000 0.31950791 0.18875254 0.14617344 0.12249870 0.10695009
 [7] 0.09577227 0.08725940 0.08050989 0.07499683 0.07038926

FGN documentation built on May 30, 2017, 7:19 a.m.