| Sampling
paradox
|
Dynamic
stochastic system
Mineral processing plant
Random variable: grade |
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|
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| Static
stochastic system
Mineral deposit
Random variable: grade |
|
| Mathematical Statistics |
Geostatistics |
| Functional independence fundamental |
Functional
dependence ubiquitous |
| Weighted
averages have variances |
Kriged
estimates lack variances |
| Variances
are statistically sound |
Kriging
variances are pseudo variances |
| Spatial
dependence verified |
Spatial
dependence assumed |
| Degrees
of freedom indispensable |
Degrees
of freedom dismissed |
| Unbiased
confidence limits quantify risk |
Unbiased
confidence limits are lacking |
| Variograms display spatial dependence |
Semi-variograms
make pseudo science |
| Smoothing makes no statistical sense |
Smoothing
makes geostatistical sense |
| Mathematical statistics is a science |
Geostatistics is a scientific fraud |
Click here and read an early 1990s vintage of a blatantly biased, shamelessly self-serving geostatistical peer review by Dr M Armstrong, Associate Editor, Journal of Mathematical Geology.
Click here and peruse how Professor Dr A G Journel, Standford's prominent geostatistical scholar, prevaricates about spatial dependence, "classical Fischerian [sic] statistics" and degrees of freedom on the first page of his letter to Professor Dr R Ehrlich, Editor, Journal of Mathematical Statistics.
Click here and examine my retro review of Journel and Huijbregts's Mining Geostatistics, the second textbook on geostatistics, and the first one in which authors refer to the zero kriging variance.
Click here and look at the variance formula that vanished somewhere in South Africa on Professor D G Krige's watch, and that Professor G Matheron and his disciples did without when their novelty science evolved so fortuitously.
Click here to find out who cautioned against oversmoothing to solve the rise of kriging covariances and the fall of kriging variances, which seems to imply that the requirement of functional independence can be violated a little but not a lot.
Click here and wonder about the nimble workings of geostatistical minds as degrees of freedom became a burden when a small set of measured data gives a large set of calculated distance-weighted averages-cum-kriged estimates.
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