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Re: maximum likelihood sensitivity to outliers [message #67121] Tue, 07 July 2009 21:24 Go to previous message
maurya is currently offline  maurya
Messages: 16
Registered: February 2009
Junior Member
On 8 July, 03:56, Jeremy Bailin <astroco...@gmail.com> wrote:
> 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.

A maximum-likelihood routine "MLEfit.pro" given at VIRGO web page may
be helpful for you.

http://www.ias.u-psud.fr/virgo/html/IDLpro/MLEfit.pro

Cheers
Maurya
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