genfit / guess values

Forum|Forum|11 years ago
December 19, 2014
2 replies
3458 views

Hello All,

I would like to know more about "genfit" algorithm. My main question is:

Why "genfit" routine cannot find a good fit when the guess values are not chosen properly. What is the normal behavior of the genfit outputs with respect to different guess values?

I appreciate if you introduce me some references or articles for further information.

Thank you.

Payman

Statistics_Analysis

R

RichardJ

19-Tanzanite

The algorithm is "Levenberg-Marquardt". Like all non-linear least squares solvers, it is iterative. It starts from the guess value and heads "downhill" on the error surface. If the error surface has only one minimum then it will eventually converge to a solution at that minimum. However, in many cases there are local minima, as well as the global minimum. If that is the case the iterative solver can descend into a local minimum, and determine that is the best solution it can find. Which minimum it finds, local or global, will depend on the guess values at the start of the iterative procedure.

P

payman

Author

1-Visitor

Thank you Richard,

The attached figure is an example of genfit result vs different guess values.

When the guess value is exactly the same as the actual value (in this example 1.5), the genfit returns the best answer.

However slight change in guess value causes abrupt change in the genfit result.

Is it a normal behaviour for genfit? Is there any special information about the system when the convergence is so sharp?

R

RichardJ

19-Tanzanite

Your data happens to be very badly behaved for non-linear least squares fitting. You have very many local minima close to to the global minimum. This is basically telling you that a non-linear least squares fit is not a good way to model your data to find the parameters. At least, not unless unless you first find a way to get very good guesses.

V

ValeryOchkov

24-Ruby IV

genfit works with units in Prime!

One example:

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