Define Point Process Model for Metropolis-Hastings Simulation.
Builds a description of a point process model for use in simulating the model by the Metropolis-Hastings algorithm.
rmhmodel(...)
... |
Arguments specifying the point process model in some format. |
Simulated realisations of many point process models
can be generated using the Metropolis-Hastings algorithm
rmh
. The algorithm requires the model to be specified
in a particular format: an object of class "rmhmodel"
.
The function rmhmodel
takes a
description of a point process model in some other format, and
converts it into an object of class "rmhmodel"
.
It also checks that the parameters of the model are valid.
The function rmhmodel
is generic, with methods
for
an object of class "ppm"
, obtained by a call to the
model-fitting function ppm
.
See rmhmodel.ppm
.
a list of parameter values in a certain format.
See rmhmodel.list
.
parameter values specified as separate arguments to ...
.
See rmhmodel.default
.
An object of class "rmhmodel"
, which is essentially
a list of parameter values for the model.
There is a print
method for this class, which prints
a sensible description of the model chosen.
Adrian Baddeley Adrian.Baddeley@curtin.edu.au
and Rolf Turner r.turner@auckland.ac.nz
Diggle, P. J. (2003) Statistical Analysis of Spatial Point Patterns (2nd ed.) Arnold, London.
Diggle, P.J. and Gratton, R.J. (1984) Monte Carlo methods of inference for implicit statistical models. Journal of the Royal Statistical Society, series B 46, 193 – 212.
Diggle, P.J., Gates, D.J., and Stibbard, A. (1987) A nonparametric estimator for pairwise-interaction point processes. Biometrika 74, 763 – 770. Scandinavian Journal of Statistics 21, 359–373.
Geyer, C.J. (1999) Likelihood Inference for Spatial Point Processes. Chapter 3 in O.E. Barndorff-Nielsen, W.S. Kendall and M.N.M. Van Lieshout (eds) Stochastic Geometry: Likelihood and Computation, Chapman and Hall / CRC, Monographs on Statistics and Applied Probability, number 80. Pages 79–140.
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