In this thread, it was agreed to
- deprecate guessParametersErrors()
- create a new method, namely getSigma(), which simply returns the square root of the diagonal coefficients of the covariance matrix. If necessary, the values previously returned by guessParametersErrors() can easily be retrieved from getSigma() and getChiSquare().
The rationale for this decision is copied below from the mailing list
Independently of the explanation to be provided by Dimitri, I think that
there are code design arguments in favour of deprecating (and later,
deleting) the "guessParametersErrors" method, as follows.
In the context of the "optimization.general" package, one assumes that a
Jacobian matrix is available. From there, the code in "AbstractLeastSquares"
computes the covariance matrix, from which one can readily extract the
"sigma".
This can be done without computing the chi-square! [While, as you have
probably noticed, the "guessParametersErrors" will not behave nicely if you
don't call "updateResidualsAndCost()" beforehand.]
For the class to be self-consistent, the story can end here: Any additional
utilities can lead to wrong expectations from different types of users (as
we've demonstrated here).
Indeed, confidence intervals refer to additional variables (as Dimitri
wrote: "By how much can a parameter change before the normalized chi2
changes by <some number>?"). Being able to answer those questions also
involves the correlations between the parameters (cf. the plot I've attached
to MATH-784), whereas "guessParametersErrors" does not take them into
account.
This was done in r1334315.
Closing all resolved issue now available in released 3.3 version.