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Both the capitalised 'Kriging' and non-capitalised 'kriging' words are found in the literature, however I have found the non-capitalisation instance more widespread in primary publications. Therefore it seems appropriate to restore this to what the article had pre-March 2016. Feel free to jump in and
1302:
Adams, B.M., Bauman, L.E., Bohnhoff, W.J., Dalbey, K.R., Ebeida, M.S., Eddy, J.P., Eldred, M.S., Hough, P.D., Hu, K.T., Jakeman, J.D., Swiler, L.P., and Vigil, D.M., "DAKOTA, A Multilevel
Parallel Object-Oriented Framework for Design Optimization, Parameter Estimation, Uncertainty Quantification, and
1366:
It is not appropriate to redirect
Gaussian Process Regression (GPR) to Kriging. When the random field is stationary Gaussian, Kriging and GPR have similarities, but Kriging (OK and its variants) is in general builts on the top of intrinsically stationary random fields (not Gaussian random fields).
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I think the explanation given in the Dakota User Manual version 6, chapter 8.4.3.5 is a bit better than the wiki article's. For instance equation 8.20 in the user manual is insightful from the background of function approximation. This wiki article lacks anything as clear and simple as the
1447:
First, the tack-on is unclear whether it references Krige or his thesis. Second, is "pioneering plotter of" merely an elegant variation of the staid "which considers the"? If so, I prescribe woodshed, bullet, gun, hasty grave. I think "pioneering" is already implied here. —
1492:
We need to add a pronunciation of this word as I have heard in the industry three different pronunciations. Danie G. Krige was South
African. So, Krige is pronounced Kreeg-a, Therefore, the correct pronunciation for Kriging is Kreeg-ing not Kryg-ing nor Kry-jing.
382:
In section "Geostatistical estimator" prior to the first set of equations of the section, the article says: "the correlation between two random variables solely depends on the spatial distance...", and then proceeds to introduce several expressions in terms of
1577:
The proof that in simple kriging the sum of weights equals 1 is wrong. It implicitly assumes that the means are non zero. If the means are zero, the equation can't be divided by it. I'm not a professional so I don't know what the right thing to do is.
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This sentence, while admirably attempting to explain the concept in simple
English, adds nothing pertinent; in my opinion, it adds confusion. The idea that something results from a random process or not is ambiguous, given the
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Remove this sentence "The
English verb is to krige and the most common noun is kriging; both are often pronounced with a hard "g", following an Anglicized pronunciation of the name "Krige"."
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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,
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This article says, "The first step in geostatistical modulation is to create a random process that best describes the set of observed data."
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This means that, when the samples are farther away from {\displaystyle x_{0}}x_{0}, the estimation becomes worse.
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This means that, the farther the samples are away from {\displaystyle x_{0}}x_{0}, the worse the estimation.
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This means that, when the samples are farther away from {\displaystyle x_{0}}x_{0}, the worse the estimation.
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https://www.researchgate.net/post/Why_should_data_follow_normal_distribution_for_ordinary_kriging_analysis
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Sensitivity
Analysis: Version 5.4 User's Manual," Sandia Technical Report SAND2014-4633, July 2014.
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on
Knowledge. If you would like to participate, please visit the project page, where you can join
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I second this opinion. This section is confusing in several places as it doesn't define symbols.
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refers to correlation. Going further with the explanation, however, one finds that the formula:
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resource. If you would like to participate, you can choose to edit this article, or visit the
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distance-weighted average gold grades at the
Witwatersrand reef complex in South Africa.
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What does "modulation" here mean? Is this supposed to say "geostatistical modeling"?
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means, this section is confusing to someone novel in the matter as me.
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I plan to update the pronunciation to /kri:gɪŋ/ which is KREE-ging -
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explanation given in the user manual. The manual is available from
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5. Application (potentially with R/ArcGIS/Python modules)
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cannot be the covariance since a few equations later,
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1387:2.1 Intrinsic Stationarity
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1381:1. Background
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