DSpars: Create a parameter set specifying a direct sampling algorithm
Description
Create a parameter set describing a direct sampling algorithm to multipoint simulation.
All parameters except nsim are optional, as they have default values reasonable
according to experience.
an S3-list of class "gmDirectSamplingParameters" containing the six 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
direct sampling.
Arguments
nsim
number of realisations desired (attention: current algorithm is slow, start with small values!)
scanFraction
maximum fraction of the training image to be scanned on each iteration
patternSize
number of observations used for conditioning the simulation
gof
maximum acceptance discrepance between a data event in the training image and the conditioning data event
seed
an object specifying if and how the random number generator should be
initialized, see ?simulate in base "stats" package