gmGeostats (version 0.11.3)

SequentialSimulation: Create a parameter set specifying a gaussian sequential simulation algorithm

Description

Create a parameter set describing a sequential simulation algorithm to two-point simulation, mostly for covariance or variogram-based gaussian random fields.

Usage

SequentialSimulation(
  nsim = 1,
  ng = NULL,
  rank = Inf,
  debug.level = 1,
  seed = NULL,
  ...
)

Value

an S3-list of class "gmSequentialSimulation" containing the four elements given as arguments to the function. This is just a compact way to provide further functions such as predict_gmSpatialModel

with appropriate triggers for choosing a prediction method or another, in this case for triggering sequential Gaussian simulation.

Arguments

nsim

number of realisations desired

ng

a neighbourhood specification, as obtained with function KrigingNeighbourhood()

rank

currently ignored (future functionality: obtain a reduced-rank simulation)

debug.level

degree of verbosity of results; negative values produce a progress bar; values can be extracted from gstat::predict.gstat()

seed

an object specifying if and how the random number generator should be initialized, see ?simulate in base "stats" package

...

further parameters, currently ignored

Examples

data("jura", package="gstat")
X = jura.pred[,1:2]
summary(X)
Zc = jura.pred[,7:10]
ng_local = KrigingNeighbourhood(maxdist=1, nmin=4, omax=5, force=TRUE)
(sgs_local = SequentialSimulation(nsim=100, ng=ng_local, debug.level=-1))
## then run predict(..., pars=sgs_local)