get.mpp.names {MarkedPointProcess} | R Documentation |
Model names for marked point process
Description
get.mpp.names
returns the names of implemented marked point processes
Usage
get.mpp.names()
Details
currently implemented models are
- nearest neighbour
the points are given by a stationary Poisson point process, and a
mark is the distance to the nearest neighbour within the process;
nearest neighbour
has one parameters, multiplied to the
calculated distance.
- random coins
We start in R^d, here d=2,
with a marked Poisson process where the points are given by
a stationary Poisson point process Phi
and the marks are i.i.d.
random objects (disks or cones) of dimension d+1.
At a point x of Phi the sum of the heights of the
objects that cover x is the mark of this model;
random coins
has three parameters, the first parameter
chooses the kind of coin function, the second the scale, the
third the height. Currently the available coin functions are
disk (1) and and cone (2).
- variance by coins
The marks are independent Gaussian random variables with mean 0
and standard deviation equal to
the mark of random coin model.
Value
get.mpp.names
returns a vector of names.
Author(s)
Martin Schlather, martin.schlather@math.uni-goettingen.de
http://www.stochastik.math.uni-goettingen.de/institute
See Also
simulateMPP
[Package
MarkedPointProcess version 0.2.9
Index]