simulationDecompose: Gaussian Process Simulation: Decomposition

In martinzaefferer/COBBS: Continuous Optimization Benchmarks By Simulation

Gaussian Process Simulation: Decomposition

Description

(Conditional) Simulation via decomposition approach.

Usage

simulationDecompose(
  object,
  nsim = 1,
  xsim,
  conditionalSimulation = TRUE,
  returnAll = FALSE,
  ...
)

Arguments

object	fit of the GPR model (settings and parameters), of class cobbsGPR.
nsim	number of simulations
xsim	list of samples in input space, to be simulated
conditionalSimulation	logical, if set to TRUE (default), the simulation is conditioned with the training data of the GPR model. Else, the simulation is non-conditional.
returnAll	if set to TRUE, a list with the simulated values (y) and the corresponding covariance matrix (covar) of the simulated samples is returned.
...	further arguments, not used

Value

Returned value depends on the setting of object$simulationReturnAll

References

N. A. Cressie. Statistics for Spatial Data. JOHN WILEY & SONS INC, 1993.

C. Lantuejoul. Geostatistical Simulation - Models and Algorithms. Springer-Verlag Berlin Heidelberg, 2002.

See Also

gaussianProcessRegression, simulationSpectral

martinzaefferer/COBBS documentation built on July 19, 2023, 4:12 a.m.