Hardcore krigers and cocksure smoothers were silent after Bre-X had gone bust. So much so that none served on the task force. They would have had a tough time to explain why kriging variances rise first and then fall. Or to prove why spatial dependence may be assumed without proof. Without genuine geostatisticians on board the task force was in limbo. The more so since I had proved that Bre-X was a salting scam. My son and I had shown in 1992 how to verify spatial dependence by applying Fisher’s F-test to the variance of test results for gold determined in bulk samples taken from a set of rounds in a drift, and the first variance term of the ordered set. Stanford’s Journel wrote to Professor Dr R Ehrlich, Editor, Journal of Mathematics Geology, (in those days!) that I am, “… too encumbered with Fischerian (sic) statistics.” I confess to have worked with Fisher’s F-test most of my life. So what?
The Mining Standard Task Force was put to work in July 1997. MSTF released its Interim Report in June 1998, and published its Final Report in January 1999. MSTF’s Final Report is high on verbiage but low on sound sampling practices and proven statistical methods.
It took a while to find out that Setting New Standards had done nothing to improve sampling practices in mineral exploration. The task force could have but did not show how to derive unbiased confidence limits for metal contents and grades of mineral inventories. Sadly, geostatistics was very much alive when I looked at CIM’s website under APCOM 2009. The program for this event set the stage for another krige-and-smooth bash. But this time the stage was set on my home turf. The scientific fraud behind the Bre-X fraud turned out to be alive ten years after MSTF’s Final Report had been released. It is as much alive as it was on Journel’s watch in 1992. So much for setting new standards!
I dug into my data base and retrieved test results for gold and silver determined in pairs of interleaved bulk samples taken from 1 m³ volumes of crushed gossan ore mined from a vertical pit. I had designed this sampling program to test for spatial dependence, to derive confidence limits for gold and silver contents and grades, and to estimate the intrinsic variances of gold and silver. The same test proved that the intrinsic variance of gold in Bre-X’s gold resource was statistically identical to zero. My son and I submitted to APCOM 2009 for review a paper on Metrology in Mineral Exploration. It was accepted as “a highly specialized topic reserved for the advanced geostatistician.” How about that!
My coauthor was talking about EMF in Europe. His presentation was also of interest at L’Ecole des Mines in Nantes. So, his mom and my partner for life listened to my APCOM 2009 talk in Vancouver, BC. I asked again why the variance of Agterberg’s distance-weighted average point grade had gone missing. The question was met with solemn silence. My spouse got some kind of revised textbook on a CD. Long ago I had bought a copy of the original edition. What it taught me was not to mess around with sloppy semi-variograms. That's why I took a systematic walk, tested for spatial dependence between hypothetical uranium concentrations, and counted degrees of freedom properly.
NRCan’s Emeritus Scientist is loath to bring back the long-lost variance of his distance-weighted average point grade. But then, how could JMG’s Editor-in-Chief possibly do what Rio Tinto wants him to do if each and every weighted average point grade were to have its own variance? He may need but a few boreholes. But what he does need most of all are infinite sets of distance-weighted average point grades to play with by hook or by crook. I really don’t give a fiddle about JMG’s Editor-in-Chief and his models. What I want is a world free of Matheron’s mad science of geostatistics.
I agree with H G Wells. I like statistical thinking. And I like to write about it. A good grasp of statistics is needed to bridge the gap between sampling theory and sampling practice. I have written a great deal about spatial dependence in sample spaces and sampling units. I want to write much more. My website gets a load of traffic. I blog for fun and play mind games when I do. I found out in 2007 that geostatistics plays a role in the study of climate change. It was some Canadian hockey stick that struck a panic button around the world. The study of climate change is much more relevant to the world than unbiased mineral inventories are to mining investors. Securities commissions ought to set rules and regulations that protect the public at large against all sorts of scientific frauds. The kriging machine will be shredded as soon as the ugly factoids are clear to investors. Surely, geoscientists should apply classical statistics when they study climate change. After all, functions without variances are as dead as dodos. CRIRSCO does not think so but I know!
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