rmhmodel(...)
"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.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
[object Object],[object Object],[object Object]
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.
rmhmodel.ppm
,
rmhmodel.default
,
rmhmodel.list
,
rmh
,
rmhcontrol
,
rmhstart
,
ppm
,
Strauss
,
Softcore
,
StraussHard
,
Triplets
,
MultiStrauss
,
MultiStraussHard
,
DiggleGratton
,
PairPiece