rmhcontrol
Set Control Parameters for Metropolis-Hastings Algorithm.
Sets up a list of parameters controlling the iterative behaviour of the Metropolis-Hastings algorithm.
Usage
rmhcontrol(...)
## S3 method for class 'default':
rmhcontrol(\dots, p=0.9, q=0.5, nrep=5e5,
expand=NULL, periodic=FALSE, ptypes=NULL,
x.cond=NULL, fixall=FALSE, nverb=0)
Arguments
- ...
- Arguments passed to methods.
- p
- Probability of proposing a shift (as against a birth/death)
- q
- Conditional probability of proposing a death given that a birth or death will be proposed
- nrep
- Total number of steps (proposals) of Metropolis-Hastings algorithm that should be run
- expand
- Either a numerical expansion factor,
or a window (object of class
"owin"
), specifying that simulations are to be performed in a domain larger than the original data window, then clipped to the original data window. - periodic
- (Logical) whether to simulate ``periodically'', i.e. on a torus formed by identifying opposite edges of a rectangle.
- ptypes
- For multitype point processes, the distribution of the mark attached to a new random point (when a birth is proposed)
- x.cond
- Conditioning points for conditional simulation.
- fixall
- (Logical) for multitype point processes, whether to fix the number of points of each type.
- nverb
- Progress reports will be printed every
nverb
iterations
Details
The Metropolis-Hastings algorithm, implemented as rmh
,
generates simulated realisations of point process models.
The function rmhcontrol
sets up a list of parameters which control the
iterative behaviour
and termination of the Metropolis-Hastings algorithm, for use in a
subsequent call to rmh
. It also checks that the
parameters are valid.
(A separate function rmhstart
determines the initial state of the algorithm,
and rmhmodel
determines the model to be simulated.)
The parameters are as follows: [object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Value
- An object of class
"rmhcontrol"
, which is essentially a list of parameter values for the algorithm. There is aprint
method for this class, which prints a sensible description of the parameters chosen.
References
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.
See Also
Examples
# parameters given as named arguments
c1 <- rmhcontrol(p=0.3,periodic=TRUE,nrep=1e6,nverb=1e5)
# parameters given as a list
liz <- list(p=0.9, nrep=1e4)
c2 <- rmhcontrol(liz)
# parameters given in rmhcontrol object
c3 <- rmhcontrol(c1)