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[ai-geostats] Re: Who is J. W. Merks???

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  • Isobel Clark
    Jan Merks is an expert in sampling theory and works as an independent consultant out of Vancouver, Canada. He has a web site which I don t have to hand, where
    Message 1 of 6 , Apr 30 4:43 AM
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      Jan Merks is an expert in sampling theory and works as
      an independent consultant out of Vancouver, Canada. He
      has a web site which I don't have to hand, where all
      of these opinions are repeated and amplified.

      Jan first starting publishing anti-geostatistics
      articles in 1991 or 1992 and the article
      "Geostatistics or Voodoo Statistics" appeared in every
      mining publication from the Engineering and Mining
      Journal to the Northern Miner newspaper. He
      republishes every so often and had one a few years ago
      in the Mining Journal on April 1st.

      The articles start with a quotation from Tolstoy to
      the effect that even the most intelligent of people
      can turn a blind eye to facts that don't fit their own
      world view. It is ironic that he does not realise this
      quotation is apropriate to his own world view too.

      His basic premise is that geostatistics is a con job
      foisted on an unsuspecting industry by consultants
      trying to rip them off for large sums of money. He
      supports this view by pointing out that the
      semi-variogram is divided by the number of pairs of
      samples (N) and not by N-1 when every statistician
      knows that variances are divided by N-1 not N. The
      point missed here is that variances are divided by N-1
      because we estimate the population mean.
      Semi-variograms are not divided by N-1 because we
      assume the population mean (difference) to be zeto and
      do not estimate it.

      His second point is that kriging with (say) k samples
      should have k-1 degrees of freedom. This is not true
      becuase the variance/covariance or semi-variogram
      terms used in the kriging system are based on the
      total number of pairs used in the construction of the
      graph. I once asked Noel Cressie about this and he
      said that the degrees of freedom in the kriging system
      would be n(n-1) where n is the total number of samples
      in the data set.

      Back in 1992, I invited Dr Merks to come down to a
      course I was giving in Reno to put his point of view
      and debate it with myself and the students and staff
      at University of Nevada-Reno. I still have his letter
      on file. It basically says, I don't see the point you
      aren't going to listen anyway.

      Before you ask, the only reason I did this was because
      his articles referred to only two geostatistical
      publications: Michel David's Mining Geostatistics and
      my Practical Geostatistics (1979). He also couldn't
      spell my name right and I wanted to give him the
      opportunity to change that. It was several years
      before an editor pointed out to him that there is no
      'e' on the end of "Isobel Clark".

      Isobel
      http://uk.geocities.com/drisobelclark/practica.htm
    • Edzer J. Pebesma
      Thanks, Isobel, for the explanation. Some people never get it, the difference between design-based and model-based methods. From the other side it is also true
      Message 2 of 6 , Apr 30 6:51 AM
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        Thanks, Isobel, for the explanation. Some people never get it,
        the difference between design-based and model-based methods.
        From the other side it is also true that there are
        geostatisticians, even famous ones, who keep arguing that design-
        based methods (methods that essentially assume independent
        observations) are not applicable to spatial problems, even
        when spatial random sampling has been used.

        A useful reference for design-based methods is:

        DE GRUIJTER, J. J. & C. J. F. TER BRAAK (1990), Model-Free Estimation
        from Spatial Samples: A Reappraisal of Classical Sampling Theory.
        Mathematical Geology 22, pp. 407-415.
        --
        Edzer
      • WEIDONG LI
        Hi, I think this man just wants to get more attention by making some noise. Geostatistics is the great contribution of geoscientists outside the mainstream of
        Message 3 of 6 , Apr 30 7:49 AM
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          Hi,

          I think this man just wants to get more attention by making some noise.

          Geostatistics is the great contribution of geoscientists outside the
          mainstream of statistics to the science. I also ever met a reviewer.
          The guy never agree that parameters should estimated from correlated
          data.

          At the beginning of the development of kriging, I guess Professor G.
          Matheron must met lots of challenges. As Professor Journel pointed out,
          geostatistics does not pursue recognition of mainstream mathematics, it
          pursues recognition from practioners. It is great because it is useful.
          If just checking geostatistics purely from the view of conventional
          mathematics, there are lots of places to attack.

          But our understanding of geostatistics also should not stop on the
          conventional geostatistics. Geostatistics is also evolving. The recent
          proposed multi-point geostatistics is quite innovative. In addition,
          Markov chains are also evolving toward a new non-kriging geostatistics.


          Weidong Li
          ------------------------
          University of Wisconsin
          Department of Geography
          550 North Park Street
          Madison, WI 53706-1404
          426 Science Hall
          E-mail: weidong6616@...
          ----------------------

          ----- Original Message -----
          From: "Edzer J. Pebesma" <e.pebesma@...>
          Date: Saturday, April 30, 2005 6:51 am
          Subject: Re: [ai-geostats] Re: Who is J. W. Merks???

          > Thanks, Isobel, for the explanation. Some people never get it,
          > the difference between design-based and model-based methods.
          > From the other side it is also true that there are
          > geostatisticians, even famous ones, who keep arguing that design-
          > based methods (methods that essentially assume independent
          > observations) are not applicable to spatial problems, even
          > when spatial random sampling has been used.
          >
          > A useful reference for design-based methods is:
          >
          > DE GRUIJTER, J. J. & C. J. F. TER BRAAK (1990), Model-Free Estimation
          > from Spatial Samples: A Reappraisal of Classical Sampling Theory.
          > Mathematical Geology 22, pp. 407-415.
          > --
          > Edzer
          >
          >
          >
        • Fran Manns
          AI Geostats Subscribers, Isobel Clark(e), It seems that Merks is his own worst enemy. As a matter of interest, when one is a member of the geostatistics
          Message 4 of 6 , Apr 30 10:39 AM
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            AI Geostats Subscribers, Isobel Clark(e),

            It seems that Merks is his own worst enemy. As a matter of interest, when
            one is a member of the geostatistics church - ie member of a known
            geostatistical union, it is easy to criticise Merks for both his opacity and
            his criticism. Where there is smoke there is fire. The moment you believe
            your own hypothesis you are a dead duck scientifically.

            What geostatisticians never come to grips with in economic geology, where
            Merks consults for some of the senior players, is that your 'nugget effect'
            and the 'geologist's' nugget effect are homenyms for unreliability; but they
            do not mean the same thing. Practicing miners know that fudge factors, mine
            call factors, cutting, are used in the majority of metal mines in the
            world, simply because geostatistical forecasts are only accurate about 50%
            of the time (Aus IMM Special Publ. on Best Practices). It's garbage in,
            garbage out; bad data in bad data out. Danie Krige, however, actually
            published a summary paper in 2001 in SAJG in which he stated that the
            scientific mathematical underpinnings of geostatistics were well understood
            and not a lot of future research would be required in this field. He
            stopped just short of calling geostatistical theory a paradigm. I take
            issue with a field in which hundreds of data points, thousands of data
            points and perhaps tens of thousands of data points do not yield a
            trustworthy mean 50% of the time. I, like Merks believe that 30 or 31
            values should tell the tale: semi-variograms excepted. That means I accept
            them. I do not know whether Merks does or not. I find the semivariogram
            model intellectually satisfying.

            I do not accept averages or cut weighted averages for a block of ore, a
            stope in a mine, or a global average - for an annual report. This is where
            the voodoo operates.

            I have found ore bodies to be chaotic. Sampling with a drill is very
            reliable in order to define the geometry, volume, and specific gravity of a
            deposit. Drill an oriented pattern and a few angle holes the opposite
            direction to test your imagination and the tonnage of a deposit can be
            estimated with a fair degree of accuracy. To ask a drill to sample for
            grade is another story. Every metal distribution is diferent. Metal
            concentrations depend upon the distribution of nucleation sites or
            structural preparation of the host rock. Assays are rarely reproducible.
            Twinned holes are rarely reproducible. Give me the mean and standard
            deviation and standard error of the mean of a global ore reserve from a
            typical 'nuggety' ore deposite, and I can reproduces those statistics with a
            similar drill program of twinning holes. However, only 10 or 11% of the
            twinned holes will be similar; a few will be identical twins, a few will be
            fraternal and the rest of the twins will be just family. Some may deny
            their paternity/maternity completely. This mystery has got a common name in
            geostatistics but I do not remember what Krige calls it today. For the 50%
            of deposits that behave as predicted, bravo for (GEO)statistics. However,
            what about the rest? We sweep them under the rug and rely on cutting or the
            mine call factor and wait a year to adjust the numbers with a fudge factor.

            In the Old Lead Belt of Missouri, the 'dilution' factor was 10%. When the
            miners moved to the new lead belt they applied 10% dilution, but it was not
            enough and 15% 'dilution' was called for. ...And the new lead belt was
            known for massive galena. At Elmwood, Tennessee Zinc held off production
            for a time while they attempted to reconcile assay from underground mine
            opening samples to nearby drill holes; it didn't work. They just went ahead
            an mined it and worked backward from concentrate grade and tailings to
            determine the feed grade.

            Ore deposit grades are chaotic and, if you will, the sample we take is too
            small at least 50% of the time. We then split the sample to laboratory
            size, and the laboratory then splits it to a smaller size 50 - 30 - 15
            grams, depending on the cost of the assay (the budget). Bigger aliquots
            cost more. 50% of the time these samples are too small. Shall I say 50% of
            the deposits need custom sampleing. And the worst part of it is that we do
            not seem to account for that potentially fatal flaw at the beginning of the
            exercise. Colomak, NWT had a 25% shortfall from low grade ore. We do not
            think it significant to test for what the deposit is telling us before we
            begin the SOP of QCQA. [Standard Operating Procedure of Quality Control and
            Quality Assurance]. I say GIGO [Garbage in; garbage out.]. Isobel Clark
            calls it a systematic error - an error in data due to the method of
            collecting. Isobel also explains, near the back of her book, that if there
            is a systematic error, geostatistical methods are useless. At least that's
            my reading of it.

            For 50% of gold deposits, there is an error in data that results in lower
            ounces produced than estimated and higher cost per ounce than budgeted.
            This gives Merks his energy.

            I have found that by considering the sample assay collections to be random
            numbers from a uniform distribution, I can determine the minimum feed grade
            for a stope, or a global average for an annual report. This results in cost
            saving of not crushing, grinding and reacting rock to produce metal that is
            not present in the ore due to the 'inadequate sample effect', commonly known
            as the 'nugget effect'. Before continuing the assassination of Mr. Merks,
            it would be a good idea to address that 50% of gold deposits with the
            'nugget effect. As I have alluded, base metal mines have mine call factors
            too. How can we have such a wealth of numbers and not have better
            estimates?

            Outside the envelope, how about the application of regionalized variables to
            global warming, cooling, or whatever is happening. What is going on with
            cosmology/astronomy where we take very small samples of a virtually infinite
            universe? There are people who attempt to estimate meteorite impact
            frequency without understanding the 'inadequate sample effect'. It's not my
            business, but I'll say it anyway - Merks has his atitude because of his
            perception of treatment by most prelates of the geostatistical church. The
            better question then is why is J.W. Merks reacting from his experience.

            Yours truly,

            Fran Manns
            Artesian Geological Research, Toronto, Ontario
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