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FW: [AI-GEOSTATS: MSE to compare different methods]

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  • WARR Benjamin
    Hi not sure if anyone included this reference as a response, but here is a paper by Pierre Goovaerts and Hirotaka Saito, 2000, Geostatistical interpolation of
    Message 1 of 1 , Jun 29, 2001
      Hi

      not sure if anyone included this reference as a response, but here is a
      paper by Pierre Goovaerts and Hirotaka Saito, 2000, Geostatistical
      interpolation of positively skewd and censored data in a Dioxin contaminated
      site, Environ, Sci, Technol. 34, 4228-4235,

      Benjamin Warr

      Research Associate
      Geostatistics - Environmental Science - Industrial Ecology
      Centre for the Management of Environmental Resource(CMER)
      INSEAD
      Boulevard de Constance,
      77305 Fontainebleau Cedex,
      France

      Tel: 33 (0)1 60 72 4456
      Fax: 33 (0)1 60 74 55 64
      e-mail: benjamin.warr@...


      > -----Original Message-----
      > From: Gregoire Dubois [mailto:gregoire.dubois@...]
      > Sent: Sunday, January 07, 2001 2:36 PM
      > To: Berterretche Mercedes
      > Cc: ai-geostats@...
      > Subject: Re: [AI-GEOSTATS: MSE to compare different methods]
      >
      >
      > Dear Mercedes,
      >
      > doing k fold cross validation (taking out X % of the samples)
      > will not give
      > you any reliable results unless you repeat the operation
      > several times. Taking
      > out 15% of the samples one time only will give you an MSE
      > that will depend
      > strongly on the data you have removed. Has the selection of
      > the 15% been made
      > randomly? You may get a strong bias if the 15% of the samples
      > have been taken
      > in one region in particular or if you have taken out extreme
      > values only. At
      > this stage, I would trust more the results obtained by standard cross
      > validation (leave one out method).
      >
      > I didn't check your previous mail but if you have few samples only,
      > k-fold cross validation won't help you much.
      >
      > If you have many samples, then you should repeat the
      > procedure at least 10
      > times to be sure that the way you have extracted the data
      > has not influenced
      > too much the results.
      > Also, if you have a phenomenon that fluctuates at different
      > scales, you may
      > have removed the short scale effect by taking out only few
      > samples (15% is not
      > much).
      >
      > My suggestion is the following: it is time consuming but
      > might be worth the
      > effort. The idea is to take out an increasing number of
      > samples (10, 20, 30,
      > 40, 50, 60, ...,X%) of samples, this 10 times, and see how
      > the average MSE
      > evolves. You may find out that methods A & B work better than
      > C & D when only
      > few samples are removed and that C & D give better results
      > than A & B when
      > more than 40% of the samples have been removed. This would
      > mean that C & D
      > describe better the general trend of the phenomenon while A
      > & B are more
      > sensitive to the local structures (since you have more dense data).
      >
      > If you don't have the time to proceed in such a way, you
      > should use standard
      > cross validation only and investigate the regions/samples
      > where you have the
      > highest errors.
      >
      > Just few thoughts.
      >
      > Gregoire
      >
      > "Berterretche, Mercedes" <Mercedes.Berterretche@...> wrote:
      > >
      > > I would like to thank Benjamin Warr for his siggestion about doing
      > > difference images instead of global measures as MSE.
      > >
      > > I'm confused because crossvalidation MSE (taking one sample out and
      > > recalculating) and validation MSE (taking 15 percent of the
      > samples out and
      > > recalculating) are giving me opposite results. The
      > validation method would
      > > allows me to compare kriging vs cokriging vs Kriging with
      > an external drift
      > > vs regression , but I don't know if I can trust the results
      > at this point.
      > >
      > > Does anybody have any input about this?
      > > Thanks in advance,
      > > Mercedes Berterretche
      > >
      > > --
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      >
      >
      > Gregoire Dubois (Ph.D.)
      > Institute of Mineralogy and Petrography
      > Dept. of Earth Sciences
      > University of Lausanne
      > Switzerland
      >
      > http://www.ai-geostats.org
      >
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