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[ai-geostats] More about Merks

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  • JW
    Hello geostats aficionados, My thanks to Dr Isobel Clark for compiling an abbreviated biography. I should point out that Dr Merks is my son, a PhD in computing
    Message 1 of 1 , Jun 8, 2005
      Hello geostats aficionados,
      My thanks to Dr Isobel Clark for compiling an abbreviated biography. I should point out that Dr Merks is my son, a PhD in computing science and a lead architect of the Eclipse Modeling Framework. He is also the coauthor of "Precision Estimates for Ore Reserves", a paper that was praised by and published in Erzmetall after it was thoroughly thrashed by CIM's David and Sinclair, by JMG's Journel, Froideveaux and Armstrong, and by IMM's Dowd.
      I should also mention that I sent an email to Clark on June 30, 2004, and that she responded on July 18, 2004, "Sorry not to get back to you sooner. Things are a little crazy here. Will look at this stuff next week hopefully". Things may have remained crazy for quite some time because she never answered my questions, "Do you agree or disagree that each distance-weighted average has its own variance?" and, "Do you agree or disagree that the variance of a set of distance-weighted averages is a mathematical aberration?"
      Attached to my email was a spreadsheet template based on Clark's hypothetical uranium concentrations presented in her "Practical Geostatistics". Clark's set does not display a significant degree of spatial dependence within its sample space but she interpolates just the same. When Clark's coordinates stray beyond the sample space, the distance-weighted averages converge on the arithmetic mean and their variances on the central limit theorem as the weighting factors converge on 1/n. This spreadsheet template is posted on my website. Mathematical statistics is so foolproof and predictable! 
      When I was toiling in the trenches at Hecla's Grouse Creek mine to investigate why Hecla's assayers could not find the predicted gold grades, I found out that spatial dependence between blasthole grades dissipated between 10 and 20 m. Hecla's own staff geologist had developed a geostatistical model on the basis of widely spaced borehole grades that smoothed a few high grade stringers into a large block of high grade ore and blew a cool $93 million in the process. His father, a geostatistical scholar at the Colorado School of Mines, taught him everything he knew. So why should I go to the Colorado School of Mines and learn all about the junk science of interpolation without justification. The more so because I studied Clark's "Practical Geostatistics" when we wrote "Precision Estimates for Ore Reserves". A retro review of Clark's textbook is also posted on my website.
      Geostatistics converted Bre-X's bogus grades and Busang's barren rock into the largest phantom gold resource the world has never seen. Yet, geostatisticians persist in assuming spatial dependence, kriging, smoothing, and rigging the rules of mathematical statistics. If I were a betting man, I would wager that Dr Isobel Clark is the most likely geostatistician to encounter an epiphany and become a borne-again statistician.
      So do distance-weighted averages have variances or not? Are variances of SETS of distance-weighted averages valid or not? Prominent pundits such as Armstrong, Clark, Journel and Krige have yet to respond to these fundamental questions. Meanwhile, I have posted on my website the formula for the long lost variance of the distance-weighted average (kriged estimate or kriged estimator in geostats parlance).
      J W Merks
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