[FEATURE] Dirichlet-multinomial likelihood for composition data #112
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kind: feature
New feature or request
status: wishlist
this will be moved to a later milestone
theme: more features
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Is your feature request related to a problem? Please describe.
A Dirichlet multinomial distribution for composition data can help capture error more accurately
Describe the solution you'd like
A clear and concise description of what you want to happen.
Describe alternatives you've considered
Plain ol multinomial or multinomial robust (with small constant added)
Describe a reference describing the statistical validity of this approach
Thorson et al. 2017. Model-based estimates of effective sample size in stock assessment models using the Dirichlet-multinomial distribution.
Describe if this is needed for a management application
???
Additional context
@iantaylor-NOAA noted in issue 136 that measures of uncertainty specified in the input data might change based on what distribution is being used. For the Dirichlet-multinomial there still needs to be an input sample size but it is unclear if we should be using the same input sample size for the Dirichlet-multinomial as we do the multinomial. Something to think about when coding and advocating for a non-standard distribution. [Moved from #136 to this issue by @kellijohnson-NOAA].
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