Hi.
On Mon, 24 Nov 2014 18:47:10 +0000, Michael Howard wrote:
Hello!
I am trying to estimate the parameters of a large number of curves.
They are all instances of the generalized logistic function [...]
I'm trying to do this with what is available in the commons library,
but I can't make sense of how to accomplish it.
First, there is actually already a implementation of the generalized
logistic curve in the commons, under
org.apache.commons.math3.analysis.function.Logistic.Parametric. The
'ParametricUnivariateFunction' class looks like it's intended for use
with curve fitting algorithms, using subclasses of
org.apache.commons.math3.fitting.AbstractCurveFitter. But, there
isn't
an implementation which accepts Logistic. If I understand correctly,
I
would have to code my own implementation of a curve fitting algorithm
and have it extend AbstractCurveFitter.
That would be the simplest way to go, IMHO.
But I think that it is indeed more complicated than it could be for
simple uses (like in your case).
Thus I opened an issue on the bug-tracking system:
https://issues.apache.org/jira/browse/MATH-1172
There you can find the Java code that would let a user to just pass
the "ParametricUnivariateFunction" which he wants to fit.
You could readily use it in your case as follows:
---CUT---
final WeightedObservedPoints obs = new WeightedObservedPoints();
// Add sample data to "obs"...
final ParametricUnivariateFunction logistic = new
Logistic.Parametric();
final double[] guess = new double[] { /* initial values of the
paramters */ };
final BasicCurveFitter fitter = BasicCurveFitter.create(logistic,
guess);
final double[] params = fitter.fit(obs.toList());
---CUT---
[It will be discussed on the "dev" ML whether this code should be added
to Commons Math.]
Best regards,
Gilles
[...]
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