fitting with weights given by covariance matrix


I wonder if there is a possibility to use a full covariance matrix for weighted regression instead of using a 1D wave with values of standard deviation (or inverse of standard deviation square). I couldn't find this information in the manual. I am using Igor Pro 7.

I have data points characterized by significant off-diagonal elements of a covariance matrix (for some points correlation is even ~0.9). Therefore, I believe I should include information about covariance in my analysis. 

I will be grateful for comments.




In reply to by johnweeks

Thank you for your response. I hope that this feature will appear soon. I don't think it should be hard to implement this, as anyway (at least I believe so) fit optimization is done using matrix formalism. 

The difficulties have to do as much with the public interface as with the math. We could require you to provide the full covariance matrix, but that's N^2 elements, and that gets big fast. In most cases, I think the off-diagonal elements are likely to be the same for a given diagonal, so perhaps it would be possible to accept a wave containing one element for each non-zero diagonal. But that decreases generality.

In any case, I'm afraid this would have to wait for at least Igor 10.