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AI-GEOSTATS: cross-validation

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  • Ercan Yesilirmak
    Dear list members My question is as folows: For a variable after getting a number of models all of which seem well, how to decide which one is the best among
    Message 1 of 3 , Mar 25, 2002
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      Dear list members

      My question is as folows:

      For a variable after getting a number of models all of
      which seem well, how to decide which one is the best
      among them based on cross-validation results.
      i.e., How to use cross-validation results of a model
      to compare with those of others?

      Best regards
      Ercan Yesilirmak


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    • Soeren Nymand Lophaven
      Dear Ercan Cross validation could for example be performed by discarding a single observation from the dataset and predicting this single observation based on
      Message 2 of 3 , Mar 26, 2002
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        Dear Ercan

        Cross validation could for example be performed by discarding a single
        observation from the dataset and predicting this single observation based on
        the rest of the dataset and with the proposed model. This is repeated for all
        the observations in the dataset, and as a measure of the goodness of the model
        you could calculate

        GOM = sum[(observation - predicted)^2]/n

        If you have n observations this procedure is referred to as n-fold cross
        validation. Altenatively you could split your dataset into 10 parts,
        then discarding one part and predicting this part based on the other 9
        parts and the proposed model, would give you 10-fold cross validation.

        If you want to compare different models, off course the one which gives
        the lowest GOM - value is the best for predicting the variable.

        Best regards / Venlig hilsen

        Søren Lophaven
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        E-mail: snl@... | http://www.imm.dtu.dk/~snl
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        On Mon, 25 Mar 2002, Ercan Yesilirmak wrote:

        > Dear list members
        >
        > My question is as folows:
        >
        > For a variable after getting a number of models all of
        > which seem well, how to decide which one is the best
        > among them based on cross-validation results.
        > i.e., How to use cross-validation results of a model
        > to compare with those of others?
        >
        > Best regards
        > Ercan Yesilirmak
        >
        >
        > __________________________________________________
        > Do You Yahoo!?
        > Yahoo! Movies - coverage of the 74th Academy Awards®
        > http://movies.yahoo.com/
        >
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        > * To post a message to the list, send it to ai-geostats@...
        > * As a general service to the users, please remember to post a summary of any useful responses to your questions.
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        > * Support to the list is provided at http://www.ai-geostats.org
        >


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      • Tomislav Malvić
        Dear all, Question is about evaluation of cross-validation results (MSE), performed as part of kriging/cokriging interpolation on different oil fields. Does
        Message 3 of 3 , Nov 26, 2003
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          Dear all,

          Question is about evaluation of cross-validation results (MSE), performed as
          part of kriging/cokriging interpolation on different oil fields.

          Does anybody have experience with comparing of different MSE values in
          similar lithofacies? Is it necessary to have (for comparison) same number of
          wells/data in each lithofacies or it can differ in some range?

          Maybe somebody knows for papers/tables where absolute MSE values (regarding
          interpolation method, number of data and analysed facies) and their meaning
          are published.

          Best regards,

          Tomislav Malvic, INA oil company, Croatia


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