For statsmodels for the methods I am familiar with you can pass in frequency weights, https://www.statsmodels.org/stable/generated/statsmodels.genmod.generalize

For statsmodels for the methods I am familiar with you can pass in frequency weights, https://www.statsmodels.org/stable/generated/statsmodels.genmod.generalized_linear_model.GLM.html#statsmodels.genmod.generalized_linear_model.GLM https://www.statsmodels.org/stable/generated/statsmodels.gen... So that will be a bit different than r style formula's using cbind, but yes if you only have a few categories of data using weights makes sense. (Even many of sklearn's functions allow you to pass in weights.) I have not worked out closed form for logit regression, but for Poisson regression you can get closed form for the incident rate ratio, https://andrewpwheeler.com/2024/03/18/poisson-designs-and-minimum-detectable-effects/ https://andrewpwheeler.com/2024/03/18/poisson-designs-and-mi.... So no need to use maximum likelihood at all in that scenario.