Distribution families (RR commands)
Distribution families to specify random parameters in the model definition.
See Bayesian Modelling for a less technical introduction to hierarchical modelling.
When simulating Gaussian random fields, the random parameters
are drawn only once at the very beginning.
So, if the argument n
in RFsimulate
is greater than 1
then n
simulations conditional
on a single realization of the random parameters are
performed. See the examples below.
There are (simple) multivariate versions and additional versions to the distributions families implemented. Further, any distribution family defined in R can be used, see the examples below.
These functions will allow for Bayesian modelling. (Future project).
The allowance of random parameters is a very recent, developing feature of RandomFields.
Future changings of the behaviour are not unlikely.
A further random element is RMsign
, which is an
operator on shape functions. As an exception its name starts with
RM
and not with RR
.
Martin Schlather, schlather@math.uni-mannheim.de, https://www.wim.uni-mannheim.de/schlather/
RC, RF, RM, RP, Other models
,
RFdistr
,
RMmodelgenerator
, R.
RFoptions(seed=0) ## *ANY* simulation will have the random seed 0; set ## RFoptions(seed=NA) to make them all random again ## here, the scale is given by an exponential variable: model <- RMgauss(scale=exp()) for (i in 1:4) { RFoptions(seed = i) # each leads to a simulation with a different scale parameter plot(model) ## random plot(RFsimulate(model, x=seq(0,10,0.1))) readline("press return") } # but here, all 4 simulations have the same (but random) scale: plot(RFsimulate(model, x=seq(0,10,0.1), n=4)) ## hierarchical models are also possible: ## here, the scale is given by an exponential variable whose ## rate is given by a uniform variable model <- RMgauss(scale=exp(rate=unif())) plot(model) plot(RFsimulate(model, x=seq(0,10,0.1))) ## HOWEVER, the next model is deterministic with scale \code{e=2.718282}. model <- RMgauss(scale=exp(1)) plot(model) plot(RFsimulate(model, x=seq(0,10,0.1)))
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