Kriging | Wikipedia audio article
Channel: wikipedia tts
Date: 2019-10-06

This is an audio version of the Wikipedia Article:
https://en.wikipedia.org/wiki/Kriging


00:01:08 1 Main principles
00:01:42 1.1 Related terms and techniques
00:02:51 1.2 Geostatistical estimator
00:07:26 1.3 Linear estimation
00:09:42 2 Methods
00:11:25 2.1 Ordinary kriging
00:15:26 2.2 Simple kriging
00:23:26 2.3 Properties
00:30:17 3 Applications
00:31:26 3.1 Design and analysis of computer experiments
00:32:34 4 See also
00:33:43 5 References



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SUMMARY
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In statistics, originally in geostatistics, kriging or Gaussian process regression is a method of interpolation for which the interpolated values are modeled by a Gaussian process governed by prior covariances.  Under suitable assumptions on the priors, kriging gives the best linear unbiased prediction of the intermediate values.  Interpolating methods based on other criteria such as smoothness (e.g., smoothing spline) need not yield the most likely intermediate values.  The method is widely used in the domain of spatial analysis and computer experiments. The technique is also known as Wiener–Kolmogorov prediction, after Norbert Wiener and Andrey Kolmogorov.

The theoretical basis for the method was developed by the French mathematician Georges Matheron in 1960, based on the Master's thesis of Danie G. Krige, the pioneering plotter of distance-weighted average gold grades at the Witwatersrand reef complex in South Africa. Krige sought to estimate the most likely distribution of gold based on samples from a few boreholes.  The English verb is to krige and the most common noun is kriging; both are often pronounced with a hard "g", following the pronunciation of the name "Krige". The word is sometimes capitalized as Kriging in the literature.