Interpolation
Kriging
an overview of Kriging objects
Description
Examples
Compatibility
Kriging is a method for unstructured spatial interpolation. It is based upon a variogram function which models the variance between two data points as a function of their distance. Typically, this is an increasing function, since points closer together are likely to have more similar values (less variance). Based on the variogram and the distances from the evaluation point to all input points, a weight for each input value is computed, and these weights are used to compute a weighted average which is the predicted value. The variograms supported by Maple, such as the Spherical and Exponential variograms, are detailed in the SetVariogram help page.
The following help pages describe the Kriging object and its methods further:
apply Kriging at a grid of values
Constructor
display the empirical variogram
fit parameters of a variogram
Interpolate at a point
Overview
Set the variogram for a Kriging object
$\mathrm{with}\left(\mathrm{Interpolation}\right)\:$
Create some data that is spatially correlated:
$\mathrm{points},\mathrm{data}\u2254\mathrm{Kriging}\left[\mathrm{GenerateSpatialData}\right]\left(\mathrm{Spherical}\left(1\,10\,1\right)\right)$
${}$
Create a Kriging object:
$k\u2254\mathrm{Kriging}\left(\mathrm{points}\,\mathrm{data}\right)$
${k}{\u2254}\left(\begin{array}{c}{\mathrm{Kriging\; int\ⅇrpolation\; ob\u0237\ⅇct\; with\; 30\; sampl\ⅇ\; points}}\\ {\mathrm{Variogram:\; Sph\ⅇrical(1.25259453854485,13.6487615617233,.5525536774)}}\end{array}\right)$
Use the Kriging object to interpolate at a given point:
$k\left(0.2\,0.3\right)$
${\mathrm{-2.75173577049668650}}$
The Interpolation[Kriging] command was introduced in Maple 2018.
For more information on Maple 2018 changes, see Updates in Maple 2018.
See Also
Interpolating at a point
SetVariogram
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