LPWN: Local polynomial Whittle plus noise estimator

Description Usage Arguments Details References Examples

View source: R/LPWN.R

Description

LPWN calculates the local polynomial Whittle plus noise estimator of Frederiksen et al. (2012).

Usage

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LPWN(data, m, R_short = 0, R_noise = 0)

Arguments

data

data vector

m

bandwith parameter specifying the number of Fourier frequencies.

R_short

number of (even) polynomial terms used for approximation of spectral density at the origin.

R_noise

number of (even) polynomial terms used for approximation of dependence in perturbation term.

Details

add details here.

References

Frederiksen, P., Nielsen, F. S., and Nielsen, M. O. (2012): Local polynomial Whittle estimation of perturbed fractional processes. Journal of Econometrics, Vol. 167, No.2, pp. 426-447.

Examples

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T<-2000
d<-0.2
series<-fracdiff.sim(n=T, d=d, ar=0.6)$series+rnorm(T)
LPWN(series, m=floor(1+T^0.8), R_short=1, R_noise=0)

FunWithR/LongMemoryTS documentation built on June 9, 2018, 12:22 a.m.