fracdiff: fdGPH – R documentation

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fdGPH

Geweke and Porter-Hudak Estimator for ARFIMA(p,d,q)

Description

Estimate the fractional (or “memory”) parameter d in the ARFIMA(p,d,q) model by the method of Geweke and Porter-Hudak (GPH). The GPH estimator is based on the regression equation using the periodogram function as an estimate of the spectral density.

Usage

fdGPH(x, bandw.exp = 0.5)

Arguments

`x`	univariate time series
`bandw.exp`	the bandwidth used in the regression equation

Details

The function also provides the asymptotic standard deviation and the standard error deviation of the fractional estimator.

The bandwidth is bw = trunc(n ^ bandw.exp), where 0 < bandw.exp < 1 and n is the sample size. Default bandw.exp = 0.5.

Value

`d`	GPH estimate
`sd.as`	asymptotic standard deviation
`sd.reg`	standard error deviation

Author(s)

Valderio A. Reisen and Artur J. Lemonte

References

see those in fdSperio.

Examples

memory.long <- fracdiff.sim(1500, d = 0.3)
fdGPH(memory.long$series)

fracdiff

Fractionally Differenced ARIMA aka ARFIMA(P,d,q) Models

v1.5-1

GPL (>= 2)

Authors

Martin Maechler [aut, cre] (<https://orcid.org/0000-0002-8685-9910>), Chris Fraley [ctb, cph] (S original; Fortran code), Friedrich Leisch [ctb] (R port, <https://orcid.org/0000-0001-7278-1983>), Valderio Reisen [ctb] (fdGPH() & fdSperio()), Artur Lemonte [ctb] (fdGPH() & fdSperio()), Rob Hyndman [ctb] (residuals() & fitted(), <https://orcid.org/0000-0002-2140-5352>)

Initial release

2020-01-20