Kriging Guide, Meaning , Facts, Information and Description
Kriging is a regression technique used in geostatistics. It is named after its inventor, Danie G. Krige. In the statistical community, it is more commonly known as Gaussian process regression.Kriging can best be understood as a form of Bayesian inference. Kriging starts with a prior distribution over functionss. This prior takes the form of a Gaussian process: samples from a function will be normally distributed, where the covariance between any two samples is the covariance function (or kernel) of the Gaussian process evaluated at the spatial location two points.
A set of values are then observed, each value associated with a spatial location. Now, a new value can be predicted at any new spatial location, by combining a the Gaussian prior with a Gaussian likelihood for each of the observed values. The resulting posterior distribution is also a Gaussian, with a mean and covariance than can be simply computed from the observed values, their variance, and the kernel matrix derived from the prior.
From the geological point of view, Kriging uses prior knowledge about the spatial distribution of a mineral: this prior knowledge encapsulates how minerals co-occur as a function of space. Then, given a series of measurements of mineral concentrations, Kriging can predict mineral concentrations at unobserved points.
This is an Article on Kriging. Page Contains Information, Facts Details or Explanation Guide About Kriging External link