[R] package to fit mixtures of student-t distributions
varevare at googlemail.com
Thu Jun 29 19:02:12 CEST 2017
I don’t see how neither a) or b) applies to this question nor the technical merit of the remark about mixture models.
Do you have a suggestion for a more appropriate forum for this issue/question? (stackoverflow basically sent me here).
> On 29. Jun 2017, at 16:58, Bert Gunter <bgunter.4567 at gmail.com> wrote:
> 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.
> 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:
>> 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.
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