simulateFunction: simulateFunction

In SPOT: Sequential Parameter Optimization Toolbox

simulateFunction

Description

Simulation-based Function Generator. Generate functions via simulation of Kriging models, e.g., for assessment of optimization algorithms with non-conditional or conditional simulation, based on real-world data.

Usage

simulateFunction(
  object,
  nsim = 1,
  seed = NA,
  method = "spectral",
  xsim = NA,
  Ncos = 10,
  conditionalSimulation = TRUE
)

Arguments

object	an object generated by buildKriging
nsim	the number of simulations, or test functions, to be created
seed	a random number generator seed. Defaults to NA; which means no seed is set. For sake of reproducibility, set this to some integer value.
method	"decompose" (default) or "spectral", specifying the method used for simulation. Note that "decompose" is can be preferable, since it is exact but may be computationally infeasible for high-dimensional xsim. On the other hand, "spectral" yields a function that can be evaluated at arbitrary sample locations.
xsim	list of samples in input space, for simulation (only used for decomposition-based simulation, not for spectral method)
Ncos	number of cosine functions (used with method="spectral" only)
conditionalSimulation	whether (TRUE) or not (FALSE) to use conditional simulation

Value

a list of functions, where each function is the interpolation of one simulation realization. The length of the list depends on the nsim parameter.

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

buildKriging, simulate.kriging

SPOT documentation built on June 26, 2022, 1:06 a.m.