1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
|
\name{diffseries}
\alias{diffseries}
\title{Fractionally Differenciate Data}
\description{
Differenciates the time series data using
the approximated binomial expression of the long-memory filter and an estimate of
the memory parameter in the ARFIMA(p,d,q) model.
}
\usage{
diffseries(x, d)
}
\arguments{
\item{x}{numeric vector or univariate time series.}
\item{d}{number specifiying the fractional difference order.}
}
\value{the fractionally differenced series \code{x}.}
\details{
Since 2018, we are using (an important correction of) the fast
algorithm based on the discrete Fourier transform (\code{\link{fft}})
by Jensen and Nielsen which is significantly faster for large
\code{n = length(x)}.
}
\references{
See those in \code{\link{fdSperio}}; additionally
Reisen, V. A. and Lopes, S. (1999)
Some simulations and applications
of forecasting long-memory time series models;
\emph{Journal of Statistical Planning and Inference} \bold{80}, 269--287.
Reisen, V. A. Cribari-Neto, F. and Jensen, M.J. (2003)
Long Memory Inflationary Dynamics. The case of Brazil.
\emph{Studies in Nonlinear Dynamics and Econometrics} \bold{7}(3), 1--16.
Jensen, Andreas Noack and Nielsen, Morten \enc{Ørregaard}{Oerregaard} (2014)
A Fast Fractional Difference Algorithm.
\emph{Journal of Time Series Analysis} \bold{35}(5), 428--436;
\doi{10.1111/jtsa.12074}.
}
\author{Valderio A. Reisen \email{valderio@cce.ufes.br} and Artur
J. Lemonte (first slow version), now hidden as \code{diffseries.0()}.
Current version: Jensen and Nielsen (2014); tweaks by Martin Maechler, 2018.
}
\seealso{\code{\link{fracdiff.sim}}}
\examples{
memory.long <- fracdiff.sim(80, d = 0.3)
str(mGPH <- fdGPH(memory.long$series))
r <- diffseries(memory.long$series, d = mGPH$d)
#acf(r) # shouldn't show structure - ideally
}
\keyword{ts}
|
