Description Usage Arguments Details Value References See Also Examples
The function estimates the fractal dimension of a process
1 2 3 4 5 6 7 8 9 10 11 12 13 14 | RFfractaldim(x, y = NULL, z = NULL, data, grid,
bin=NULL,
vario.n=5,
sort=TRUE,
fft.m = c(65, 86), ## in % of range of l.lambda
fft.max.length=Inf,
fft.max.regr=150000,
fft.shift = 50, # in %; 50:WOSA; 100: no overlapping
method=c("variogram", "fft"),
mode = if (interactive ()) c("plot", "interactive") else "nographics",
pch=16, cex=0.2, cex.main=0.85,
printlevel = RFoptions()$basic$printlevel,
height=3.5,
...)
|
x |
\argX If
|
y,z |
\argYz |
data |
the values measured; it can also be an sp object |
grid |
\argGrid |
bin |
sequence of bin boundaries for the empirical variogram |
vario.n |
first |
sort |
If |
fft.m |
numeric vector of two components; interval of frequencies for which the regression should be calculated; the interval is given in percent of the range of the frequencies in log scale. |
fft.max.length |
The first dimension of the data is cut into pieces
of length |
fft.max.regr |
If the |
fft.shift |
This argument is given in percent [of
|
method |
list of implemented methods to calculate the fractal dimension; see Details |
mode |
character. A vector with components
Usually only one mode is given. Two modes may make sense
in the combination |
pch |
vector or scalar; sign by which data are plotted. |
cex |
vector or scalar; size of |
cex.main |
The size of the title in the regression plots. |
printlevel |
integer. If |
height |
height of the graphics window |
... |
graphical arguments |
The function calculates the fractal dimension by various methods:
variogram method
Fourier transform
The function returns a list with elements
vario
,
fft
corresponding to
the 2 methods given in the Details.
Each of the elements is itself a list that contains the following elements.
x |
the x-coordinates used for the regression fit |
y |
the y-coordinates used for the regression fit |
regr |
the return list of the |
sm |
smoothed curve through the (x,y) points |
x.u |
|
y.u |
|
regr.u |
|
D |
the fractal dimension |
D.u |
|
variogram method
Constantine, A.G. and Hall, P. (1994) Characterizing surface smoothness via estimation of effective fractal dimension. J. R. Statist. Soc. Ser. B 56, 97-113.
fft
Chan, Hall and Poskitt (1995)
1 2 3 4 5 6 | RFoptions(seed=0) ## *ANY* simulation will have the random seed 0; set
## RFoptions(seed=NA) to make them all random again
x <- seq(0, 10, 0.001)
z <- RFsimulate(RMexp(), x)
RFfractaldim(data=z)
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.