Revision da8174e204c4b3c8aff0fa179a0b53656129ef8e authored by Martin Schlather on 01 March 2004, 00:00:00 UTC, committed by Gabor Csardi on 01 March 2004, 00:00:00 UTC
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\title{fractal dimension}
  The function estimates the fractal dimension of a process
fractal.dim(x, y = NULL, z = NULL, data,
           grid=TRUE, gridtriple = FALSE,
           bin= seq(min(ct$x[3, ]) / 2, 
             min((ct$x[2,]-ct$x[1,]) / 4, vario.n * min(ct$x[3,]) + 1),
          % box.sequ=unique(round(exp(seq(log(1),
          %   log(min(dim - 1, 50)), len=100)))),
          % box.enlarge.y=1,
          %   log(min(dim - 1, 50)), len=100)))),
           fft.m = c(65, 86), ## in % of range of l.lambda
           fft.shift = 50, # in %; 50:WOSA; 100: no overlapping
           method=c("variogram", "fft"), % "box", "range", 
           mode=c("plot", "interactive"),
           pch=16, cex=0.2, cex.main=0.85,
           PrintLevel = RFparameters()$Print,
  \item{x}{matrix of coordinates, or vector of x coordinates; if
    \code{x} is not given a grid with unit grid length is assumed}
  \item{y}{vector of y coordinates}
  \item{z}{vector of z coordinates}
%  \item{T}{vector of time coordinates. 
%    \code{T} must always be given in the \code{gridtriple} format,
%    independently how the spatial part is defined.
%  }
  \item{data}{the values measured.}
  \item{grid}{determines whether the vectors \code{x},
    \code{y}, and \code{z} should be
    interpreted as a grid definition, see Details.  \code{grid}
    does not apply for \code{T}.}
  \item{gridtriple}{logical. Only relevant if \code{grid==TRUE}.
    If \code{gridtriple==TRUE}
    then \code{x}, \code{y}, and \code{z} are of the
    form \code{c(start,end,step)}; if
    \code{gridtriple==FALSE} then \code{x}, \code{y}, and \code{z}
    must be vectors of ascending values.
  \item{bin}{sequence of bin boundaries for the empirical variogram}
  \item{vario.n}{first \code{vario.n} value of the empirical variogram
    are used for the regression fit that are not \code{NA}.}
  \item{sort}{If \code{TRUE} then the coordinates are permuted
    such that the largest grid length is in \code{x}-direction; this is
    of interest for algorithms that slice higher dimensional fields
    into one-dimensional sections.}
%  \item{box.sequ}{sequence of box length for which the number of
%    covering boxes is calculated.}
%  \item{box.enlarge.y}{The grid of coordinates is always standardised to
%    the marginal interval \eqn{[0, 1]}. The \code{data} are standardised
%    to the interval \eqn{[0, \code{box.enlarge.y}]}.}
%  \item{range.sequ}{sequence of box lengths; for each box length and a
%    covering set of boxes the sum of the ranges for the values in each
%    box is calculated.}
  \item{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.}
  \item{fft.max.length}{The first dimension of the data is cut into pieces
    of length \code{fft.max.length}.  For each piece the FFT is
    calculated and then the average for all pieces is taken.  The pieces
    may overlap, see the parameter \code{fft.shift}.}
  \item{fft.max.regr}{If the \code{fft.m} is too large, parts of the
    regression fit will take a very long time.
    Therefore, the regression fit is calculated only if the number points
    given by \code{fft.m} is less than \code{fft.max.regr}.
  \item{fft.shift}{This parameter is given in percent [of
    \code{fft.max.length}] and defines the overlap of the pieces defined
    by \code{fft.max.length}. If \eqn{\code{fft.shift}=50} the WOSA estimator is
    given; if \eqn{\code{fft.shift}=100} no overlap exist.}
    list of implemented methods to calculate the fractal dimension; see Details
  \item{mode}{character.  A vector with components
    'nographics', 'plot', or 'interactive': 
      \item{'nographics'}{no graphical output}
      \item{'plot'}{the regression line is plotted}
      \item{'interactive'}{the regression domain can be chosen interactively}
    Usually only one mode is given.  Two modes may make sense
    in the combination c("plot", "interactive") in which case all the
    results are plotted first, and then the interactive mode is called. 
    In the interactive mode, the regression domain is chosen by
    two mouse clicks with the left
    mouse; a right mouse click leaves the plot.
  \item{pch}{vector or scalar; sign by which data are plotted.}
  \item{cex}{vector or scalar; size of \code{pch}.}
  \item{cex.main}{The size of the title in the regression plots.}
  \item{PrintLevel}{integer.  If \code{PrintLevel} is 0 nothing is
    printed.  If \code{PrintLevel==1} error messages are printed. 
    If \code{PrintLevel==2} warnings and the regression results
    are given.  If \code{PrintLevel>2} tracing information is given.
  \item{height}{height of the grahics window}
  \item{...}{graphical parameters}
  The function calculates the fractal dimension by various methods:
    \item variogram method
%    \item box counting
%    \item min / max method
    \item Fourier transform
  The function returns a list with elements
  \code{vario}, %\code{box}, \code{range},
  \code{fft} corresponding to
  the 2 methods given in the Details.

  Each of the elements is itself a list that contains the
  following elements.
    \item{x}{the x-coordinates used for the regression fit}
    \item{y}{the y-coordinates used for the regression fit}
    \item{regr}{the return list of the \code{\link{lsfit}}}
    \item{sm}{smoothed curve through the (x,y) points}
    \item{x.u}{\code{NULL} or the restricted x-coordinates given
      by the user in the interactive plot}
    \item{y.u}{\code{NULL} or y-coordinates according to \code{x.u}}
    \item{regr.u}{\code{NULL} or the return list of
      \code{\link{lsfit}} for \code{x.u} and \code{y.u}}
    \item{D}{the fractal dimension}
    \item{D.u}{\code{NULL} or the fractal dimension corresponding to the
      user's regression line}
%  Overviews:
%  \itemize{
%    \item{-}{-}
%  }

  variogram method
    \item Constantine, A.G. and Hall, P. (1994)
    Characterizing surface smoothness via estimation of effective
    fractal dimension. \emph{J. R. Statist. Soc. Ser. B} \bold{56}, 97-113.

%  box counting
%  \itemize{
%    \item{-}{-}
%  }

%  min/max
%  \itemize{
%    \item{-}{-}
%  }

    \item Chan, Hall and Poskitt (1995)

\author{Martin Schlather, \email{}
  \code{\link{CovarianceFct}}, \code{\link{hurst}}
\keyword{ spatial }%-- one or more ...

%  LocalWords:  gridtriple sequ exp len fft Inf variogram pch cex PrintLevel NA
%  LocalWords:  RFparameters vario eqn WOSA nographics itemize
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