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Hello Oriol,
Isobel gave good advice when she suggested to download Chapter 4 of her
Practical Geostatistics. This book taught me more than David's
Geostatistical Ore Reserve Estimation and Journel and Huijbregts's
Mining Geostatistics combined because of its many practical examples.
For example, look at Clark's hypothetical uranium data (see Clark and the
Kriging Game at http://www.ai-geostats.org/documents/JW_Merks/
) and find out what happens if the variance of the distance-weighted average
were to resurface after it went missing on Krige's watch at the Witwatersrand
gold reef complex in South Africa in the 1950s. You should also peruse http://en.wikipedia.org/wiki/Geostatistics
to find out why statistically astute thinking was lacking when pioneering
geostatisticians replaced the genuine variance of a single distance-weighted
average with the pseudo kriging variance of some set of kriged
estimates. Study Clark's hypothetical uranium data step-by-step as
outlined on the Geostatistics talk page. It is possible to make the
variance of the distance-weighted average vanish again by the condition that
this variance be replaced with the kriging variance of some
set of kriged estimates if, and only if, the absolute difference between the
true variance and the Central Limit Theorem exceeds say 1% or
perhaps 5%. Conditional switching between real variances and voodoo
variances may not be a bright idea so early in your career.
Kind regards,
Jan W Merks
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- AI-GEOSTATS: generalize kriging variance to average-based... Oriol Falivene
- AI-GEOSTATS: Re: generalize kriging variance to aver... Isobel Clark
- Re: AI-GEOSTATS: Re: generalize kriging variance... JW
- Re: AI-GEOSTATS: Re: generalize kriging variance... Oriol Falivene
- RE: AI-GEOSTATS: Re: generalize kriging vari... Pierre Goovaerts
