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From Sébastien Brisard (JIRA) <>
Subject [jira] [Updated] (MATH-784) Javadoc of AbstractLeastSquaresOptimizer.guessParametersErrors() is too vague
Date Fri, 04 May 2012 12:26:50 GMT


Sébastien Brisard updated MATH-784:


Attached a new version of the MC simulation, whith a linear model y = a[0] + a[1] * x, and
only 3 observation points x[0] = 0.333, x[1] = 0.666 and x[2] = 1.0. It looks like in that
case, the two estimator differ quite significantly, and in fact, the simple one (unweighted
square root of the diagonal coefficients) is a much better estimator of the sd on the parameters.

It comes out as a surprise, because it contradicts formulas (34) and (35) in [MathWorld|].
Also, the standard deviation on the parameters in [NIST StRD|]
is computed with the other formula.
> Javadoc of AbstractLeastSquaresOptimizer.guessParametersErrors() is too vague
> -----------------------------------------------------------------------------
>                 Key: MATH-784
>                 URL:
>             Project: Commons Math
>          Issue Type: Improvement
>    Affects Versions: 3.0
>            Reporter: Sébastien Brisard
>            Assignee: Sébastien Brisard
>              Labels: javadoc, optimization
>             Fix For: 3.1
>         Attachments:,
> This bug report follows a recent discussion available [here|].
It is now recognized that the values returned by {{guessParametersErrors()}} are in fact known
as (asymptotic) standard errors. The javadoc should be made more explicit. Besides, the values
returned by this method should be tested. The reference datasets from [NIST|]
are to be used.

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