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.