CEGO: modelKrigingInit – R documentation

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CEGO

modelKrigingInit

Kriging: Initial guess and bounds

Description

Initialize parameter tuning for the Kriging model, setting the initial guess as well as bound constraints.

Usage

modelKrigingInit(
  startTheta = NULL,
  lowerTheta = NULL,
  upperTheta = NULL,
  useLambda,
  lambdaLower,
  lambdaUpper,
  combineDistances,
  nd,
  distanceParameters = F,
  distanceParametersLower = NA,
  distanceParametersUpper = NA
)

Arguments

`startTheta`	user provided start guess (optional).
`lowerTheta`	lower boundary for theta values (log scale), the kernel parameters.
`upperTheta`	upper boundary for theta values (log scale), the kernel parameters.
`useLambda`	boolean, whether nugget effect (lambda) is used.
`lambdaLower`	lower boundary for lambda (log scale).
`lambdaUpper`	upper boundary for lambda (log scale).
`combineDistances`	boolean, whether multiple distances are combined.
`nd`	number of distance function.
`distanceParameters`	whether the distance function parameters should be optimized
`distanceParametersLower`	lower boundary for parameters of the distance function, default is `NA` which means there are no distance function parameters. If several distance functions are supplied, this should be a list of lower boundary vectors for each function.
`distanceParametersUpper`	upper boundary for parameters of the distance function, default is `NA` which means there are no distance function parameters. If several distance functions are supplied, this should be a list of upper boundary vectors for each function.

Value

a list with elements x0 (start guess), lower (lower bound), upper (upper bound).