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- TL;DR Summary
- I would like to be able to prove that we can swap the mean and partial derivatives on the defintion of a Fisher element matrix : this defintion involves the mean of a product of derivatives on Likelihood. I have also tried to formulate it with the ##chi^2## and the matrix of covariance of observables (noted "Cov" below). All of this is done in the goal that observable big "O" that I introduce is independent and so I have just to sum the extra elements calculated from "O".