Use the covariance matrix for fitting error propagation

[mantid-roman]

This ticket is blocks : TRAC8977

At the moment to estimate the errors of the calculated values we are using the formula:
err = sqrt( sigma^2^ * J * J^T^ )

where sigma are standard deviations of the parameters and J is the Jacobian. This doesn't take into account correlation between the parameters and may lead to overestimated errors. I want to try to use a more accurate formula:

err = sqrt( J * C * J^T^ )

where C is the covariance matrix.

[mantid-roman]

This issue was originally trac ticket 9030

[mantid-roman]

http://trac.mantidproject.org/mantid/raw-attachment/ticket/9030/compare_errors.py
(uploaded by Gesner Passos on 2014-03-04T12:11:50)

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