Try this
stdev = SQRT((fSumSqr - SQR(fSum) / iCount) / (iCount - 1));
if correlation index is equal to correlation coefficient then
corrcoef = ( fSumXY - fSumX*fSumY/iCount ) / SQRT( (fSumXSqr - SQR(fSumX)/iCount) * (fSumYSqr - SQR(fSumY)/iCount) );
be carefully about denominator, can't be zero!!! but if numerator is also equal zero then corrcoef = 1 because all zeros have "perfect" correlation.
fSumSqr - sum of all squared values fSum - sum of all values iCount - number of values (elements) fSumXY - sum of all X * Y fSumX - sum of all X values fSumY - sum of all Y values fSumXSqr - sum of all X squared values fSumYSqr - sum of all Y squared values
Hope, it helps you.
Regard Stefan Majtan
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On Wed, 5 Nov 2003 21:54:13 -0000, Jim Wilson <[EMAIL PROTECTED]> wrote:
Hi all,
I have a table of regularly spaced points each of which has numerous
different attributes. I am interested in the local spatial correlations
between these attributes so I'm writing a mbx to calculate the R squared
value for each point. To do this I'm looping through the table, selecting
each point in turn then selecting all the points within e.g. 40 meters of
this point and then calculating a set of figures from this local selection.
The basis of these figures is the standard deviation and the R squared value
(correlation index).
So the question is: Does anyone have an example of calculating the standard deviation and correlation index of a column (or even a function ) or a suggestion of an easy way to go about this?
I'm statistically a virgin so be gentle! (don't know if that's quite what I
meant to say....)
TIA
Jim
Jim Wilson Hilton of Fern, Brechin. Angus, Scotland
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