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[ai-geostats] Solution to Positive Definite Problems

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  • Dean Monroe
    Thanks to Isobel Clark: I have a sub-set of data that does not appear to be anisotropic, nor does it contain bad outliers; however, my kriging of this data
    Message 1 of 1 , Oct 27, 2004
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      Thanks to Isobel Clark:

       

                  I have a sub-set of data that does not appear to be anisotropic, nor does it contain “bad” outliers; however, my kriging of this data errors out the system by saying the covariance matrix is not positive definite.  How do you fix a problem such as this?  What might be some common causes of this problem?

       

      Thanks in advance,

       

      Response:

      (1) you may have points which are very close together if not with identical co-ordinates. Bear in mind that 'close together' depends on the precision of your software. Most software works to around 8 significant figures. If you co-ordinates are in the millions, the computer will not be able to see the difference between two samples at a distance less than (say) 1.

      First check your data for duplicate samples (most common occurrence!).

       

       

      Using Arcview to export X,Y locations into Splus tends to lose precision if you don’t watch what you are doing, especially for large values (UTM coordinates).  Thanks for the solution.

       

      Dean Monroe

      OSU Environmental Sciences

       

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