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maximum likelihood sensitivity to outliers [message #67124]

Tue, 07 July 2009 15:56

Jeremy Bailin
Messages: 618
Registered: April 2008

Senior Member

This is much more a numerical analysis question than an IDL question,
but I suspect that some people here can point me in the right
direction...

I am a big fan of using maximum likelihood estimation to fit
distributions without binning (and therefore wrote ML_DISTFIT, which
you can find in JBIU). But one problem is that the method is quite
sensitive to outliers. Does anyone know (or even better, have an IDL
implementation of) a more outlier-robust version of the basic maximum
likelihood estimator?

Thanks,
-Jeremy.

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