MLE Estimation of Gamma Distribution Parameters for data with 'zeros'

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 at 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 at 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 at gmail.com>

wrote:

Please how can one go about this one? I don't know how to go about it.

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