[jira] Updated: (MATH-177) Provide a general minimizing package with a classical Gauss-Newton algorithm

["Gilles (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/MATH-177?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Gilles updated MATH-177:
------------------------

    Attachment: UnivariateRealSolverImpl.java
                UnivariateRealSolver.java
                BrentMinimizer.java

Here are the files discussed on the ML under subject: "[math] Brent Minimization".
[Although Luc said I should attach them to this issue, they are probably meant to be included in (or below) the "analysis" package.]


> Provide a general minimizing package with a classical Gauss-Newton algorithm
> ----------------------------------------------------------------------------
>
>                 Key: MATH-177
>                 URL: https://issues.apache.org/jira/browse/MATH-177
>             Project: Commons Math
>          Issue Type: Improvement
>    Affects Versions: 2.0
>            Reporter: Mick
>            Assignee: Luc Maisonobe
>             Fix For: 2.0
>
>         Attachments: BrentMinimizer.java, UnivariateRealSolver.java, UnivariateRealSolverImpl.java
>
>
> Currently the math API provides least squares only method for minimizing (solving). The limitation to least-squares problems comes from the Levenberg-Marquardt algorithm. A more general minimizer (not for quadratic forms) could be implemented by refactoring this with a classical GN, steepest descent and also conjugate gradient. We could use them as a basis for some least-squares solvers (and also keep the very efficient and specialized Levenberg-Marquardt too).
> Based on email exchange with Luc Maisonobe entitled [math] Minimizer on 1/15/08.

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