[R] MLE Estimation of Gamma Distribution Parameters for data with 'zeros'

[Ken Kleinman]

There's at least one package that can do zero-inflated gamma regression
(Rfast2::zigamma).  I'm not sure it's ML, though.


On Thu, Jan 19, 2023 at 10:17 AM Jeff Newmiller <jdnewmil using dcn.davis.ca.us>
wrote:

> Beware of adding a constant... the magnitude of the constant used can have
> an outsized impact on the answer obtained. See e.g.
> https://gist.github.com/jdnewmil/99301a88de702ad2fcbaef33326b08b4
>
> On January 19, 2023 3:49:29 AM PST, peter dalgaard <pdalgd using gmail.com>
> wrote:
> >Not necessarily homework, Bert. There's a generic issue with MLE and
> rounded data, in that gamma densities may be 0 at the boundary but small
> numbers are represented as 0, making the log-likelihood -Inf.
> >
> >The cleanest way out is to switch to a discretized distribution in the
> likelihood, so that instead of log(dgamma(0,...)) you use
> log(pgamma(.005,..) - pgamma(0,...)) == pgamma(.005,..., log=TRUE). (For
> data rounded to nearest .01, that is). Cruder techniques would be to just
> add, like, .0025 to all the zeros.
> >
> >-pd
> >
> >> On 10 Jan 2023, at 18:42 , Bert Gunter <bgunter.4567 using gmail.com> wrote:
> >>
> >> Is this homework? This list has a no-homework policy.
> >>
> >>
> >> -- Bert
> >>
> >> On Tue, Jan 10, 2023 at 8:13 AM Nyasha <kahuninyasha13296 using gmail.com>
> wrote:
> >>>
> >>> Please how can one go about this one? I don't know how to go about it.
> >>>
> >>>        [[alternative HTML version deleted]]
> >>>
> >>> ______________________________________________
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> >>
> >> ______________________________________________
> >> R-help using r-project.org mailing list -- To UNSUBSCRIBE and more, see
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> >> and provide commented, minimal, self-contained, reproducible code.
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>
> --
> Sent from my phone. Please excuse my brevity.
>
> ______________________________________________
> R-help using r-project.org mailing list -- To UNSUBSCRIBE and more, see
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> PLEASE do read the posting guide
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> and provide commented, minimal, self-contained, reproducible code.
>

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