Disponible con una licencia de Geostatistical Analyst.
Tools to predict values at unmeasured locations.
| Tool | Description |
|---|---|
Interpolates a surface using a kernel that is based upon the heat equation and allows one to use raster and feature barriers to redefine distances between input points. | |
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Empirical Bayesian kriging is an interpolation method that accounts for the error in estimating the underlying semivariogram through repeated simulations. | |
Fits a smooth surface that is defined by a mathematical function (a polynomial) to the input sample points. | |
Uses the measured values surrounding the prediction location to predict a value for any unsampled location, based on the assumption that things that are close to one another are more alike than those that are farther apart. | |
A moving window predictor that uses the shortest distance between points so that points on either side of the line barriers are connected. | |
Fits the specified order (zero, first, second, third, and so on) polynomial, each within specified overlapping neighborhoods, to produce an output surface. | |
Recalculates the Range, Nugget, and Partial Sill semivariogram parameters based on a smaller neighborhood, moving through all location points. | |
Uses one of five basis functions to interpolate a surfaces that passes through the input points exactly. |