RFhurst(x, y = NULL, z = NULL, data, sort = TRUE,
block.sequ = unique(round(exp(seq(log(min(3000, dimen[1]/5)),
log(dimen[1]),
len = min(100, dimen[1]))))),
fft.m = c(1, min(1000, (fft.len - 1)/10)),
fft.max.length = Inf, method = c("dfa", "fft", "var"),
mode = c("plot", "interactive"),
pch = 16, cex = 0.2, cex.main = 0.85,
printlevel = RFoptions()$general$printlevel, height = 3.5,
...)
TRUE
then the coordinates are permuted
such that the largest grid length is in x
-direction; this is
of interest for algorithms that slice higher dimensional fields
into one-dimensional sections.x
-direction is
larger than fft.max.length
then the segments of length
fft.max.length
are considered, shifted by
fft.max.length/2
(WOSA-estimator).'nographics'
, 'plot'
, or 'interactive'
: [object Object],[object Object],[object Object]
Usually only one mode is given. Two modes may make sense
in the combination c("plot", "inpch
.'plot'
or 'interactive'
printlevel
is 0 or 1
nothing is printed.
If printlevel=2
warnings and the regression results
are given. If printlevel>2
tracing information is given.dfa
, varmeth
, fft
corresponding to
the three methods given in the Details.
Each of the elements is itself a list that contains the
following elements.NULL
or the restricted x-coordinates given
by the user in the interactive plotNULL
or y-coordinates according to x.u
NULL
or the coefficients of
x.u
and y.u
NULL
or the Hurst coefficient corresponding to the
user's regression lineThe function calculates the Hurst coefficient by various methods:
aggregated variation
periodogram
RFoptions(seed=0)
.randomfields.options = options()$warn; options(warn=0)
x <- runif(1000)
if (interactive()) {
h <- RFhurst(1:length(x), data=x)
} else {
h <- RFhurst(1:length(x), data=x, mode = "nographics")
}
options(warn = .randomfields.options)
RFoptions(seed=NA)
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