MarkedPointProcess {MarkedPointProcess} | R Documentation |
This package allows for simulating and analysing marked point processes
The following functionalities are provided:
get.mpp.names
: returns the names of the
implemented models
mpp.characteristics
: returns
characteristics for the marks of marked point processes such as
the mark variogram, Stoyan's kmm function, the E function and the
V function
rfm.test
: MC test whether E or V is a constant.
If any of these hypotheses are rejected, the investigated marked
point process cannot be considered as random field model, i.e. a
model where the marks are independent of the locations (however the
random field model allows that the marks themselves are spatially
dependent)
simulateMPP
: simulation of marked point
processes
srd.jrssb
: function that generates the results
published by Schlather, Ribeiro, Diggle (2004)
splitmodel
: auxilliary function that splits a
user defined model in a pure Gaussian random field part and a pure
marked point process part
Further, a forestry data set is provided, see BITOEK.
The work has been financially supported by the German Federal Ministry of Research and Technology (BMFT) grant PT BEO 51-0339476C during 2000-03.
Martin Schlather, martin.schlather@math.uni-goettingen.de http://www.stochastik.math.uni-goettingen.de/institute
Schlather, M., Ribeiro, P. and Diggle, P. (2004) Detecting Dependence Between Marks and Locations of Marked Point Processes J. R. Statist. Soc., Ser. B 66, 79-83.