Thank you for your hints, now the goodness of fit test provides me
good results, but surprisingly for me the three-component model turns
out to be worse than the two-component one (indeed, I focused on the
three-component mixture because the two-component one exhibits a low
p-value).
In
I tried the function flexmix() with the driver FLXMRnegbin() with two
components first, in order to compare its results with those provided
by my function mixnbinom(). In particular, I ran the following code:
fm0 <- flexmix(y ~ 1, data = data.frame(y), k = 2, model = FLXMRnegbin())
I need a function for R software which computes a mixture of Negative
Binomial distributions with at least three components.
I found on another site the following function "mixnbinom". It works very
well, but it computes a mixture of only two components:
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