modelKrigingDistanceCalculation: Kriging: Distance Matrix Calculation

Description Usage Arguments Value See Also

View source: R/modelKriging.R

Description

Calculate and scale the distance matrix used in a Kriging model. Include definiteness correction. Not to be called directly.

Usage

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modelKrigingDistanceCalculation(
  x,
  distanceFunction,
  parameters = NA,
  distances,
  scaling,
  combineDistances,
  indefiniteMethod,
  indefiniteType,
  indefiniteRepair,
  lower
)

Arguments

x

list of samples in input space

distanceFunction

a suitable distance function of type f(x1,x2), returning a scalar distance value, preferably between 0 and 1. Maximum distances larger 1 are no problem, but may yield scaling bias when different measures are compared. Should be non-negative and symmetric. It can also be a list of several distance functions. In this case, Maximum Likelihood Estimation (MLE) is used to determine the most suited distance measure. The distance function may have additional parameters.

parameters

parameters passed to the distance function as a vector.

distances

precomputed distances, set to NA if not available.

scaling

boolean, whether to scale the distance matrix.

combineDistances

boolean, whether to combine the distances of different functions.

indefiniteMethod

method for handling non-conditionally-definite matrices.

indefiniteType

type of handling for non-conditionally-definite matrices.

indefiniteRepair

whether to further repair other conditions (beside definiteness).

lower

lower boundary for distance function parameters.

Value

a list with elements D (distance matrix), maxD (maximal distance for scaling purpose).

See Also

modelKriging


CEGO documentation built on May 14, 2021, 1:08 a.m.