[R] package to fit mixtures of student-t distributions

[Bert Gunter]

Offlist, because this is (a) an opinion and (b) about statistics and
therefore offtopic.

I don't know whether any such package exists, but I would predict that
this is likely to be overdetermined (too many parameters) and
therefore unlikely to be a successful strategy. Fitting a mixture of
Gaussians is already difficult enough.

Feel free to ignore, of course, and no need to reply.

Cheers,
Bert


Bert Gunter

"The trouble with having an open mind is that people keep coming along
and sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )


On Thu, Jun 29, 2017 at 5:41 AM, vare vare via R-help
<r-help at r-project.org> wrote:
> Hello!
>
> I am new to R (before used python exclusively and would actually call the R solution for this issue inside a python notebook, hope that doesn’t disqualify me right of the batch).
>
> Right now I am  looking for a piece of software  to fit a 1D data sample to a mixture of t-distributions.
>
> I searched quite a while already and it seems to be that this is a somehwat obscure endeavor as most search results turn up for mixture of gaussians (what I am not interested here).
>
> The most promising candidates so far are the "AdMit" and "MitSEM" R packages. However I do not know R and find the description of these packages rather comlple and it seems their core objective is not the fitting of mixtures of t’s but instead use this as a step to accomplish something else.
>
> This is in a nutshell what I want the software to accomplish:
>
> Fitting a mixture of t-distributions to some data and estimate the "location" "scale" and "degrees of freedom" for each.
>
> I hope someone can point me to a simple package, I can’t believe that this is such an obscure use case.
>
> Thanks!
>
> ______________________________________________
> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.