Comments (4)
AlejandroCatalina
commented on June 4, 2024
Sorry I took some time to get back to this because of my Christmas holidays!
We are pursuing this direction as we speak and already have a prototype to deal with models outside of the exponential family. I hope I can bring more news soon for you to test it.
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StaffanBetner
commented on June 4, 2024
In the meanwhile I can suggest that you fit a Poisson model with a random intercept per observation, which also models the overdispersion. The difference to a negative binomial model is that the additional variation is assumed to be normally distributed instead of Gamma distributed (since the negative binomial distribution is a Poisson-Gamma mixture).
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fweber144
commented on June 4, 2024
See also #361.
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fweber144
commented on June 4, 2024
Forgot to mention here that the latent projection can be used for negative binomial models, see the latent vignette. Otherwise, #361 tentatively describes how the projection problem could be solved exactly in case of the negative binomial family, so closing this issue here now.
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Related Issues (20)
- Test Suite Crashes HOT 5
- variable selection for uncorrelated random variables HOT 3
- Incompatible with brms when random effects are specified with || syntax HOT 2
- Error from multivariate brms models HOT 6
- Memory issues in multilevel models HOT 2
- Predictive performance gap / jumpy behavior at full size in Gaussian multilevel model HOT 1
- For a stan_glm model cv_varsel with loo works, but kfold gives an error HOT 4
- plot.vsel shows extra xtick label HOT 1
- brmsfit cumulative model & Latent projection predictive feature selection HOT 3
- Convergence checks for additive submodels HOT 4
- Allow dispersion parameter to be observation-specific HOT 1
- Smoothing of cross-validated predictive performance HOT 1
- Add R2 as performance statistic HOT 4
- Error when getting reference model with k-fold cross validation for cv_varsel HOT 9
- Truncated response distributions
- Clarify doc for refit_prj HOT 2
- Don't warn about slightly large khats HOT 1
- Remove QR=TRUE from the vignette
- Guide on latent_ll_oscale for other families e.g. zero-inflated negative binomial, hurdle negbinom HOT 5
- Using projpred in multi-response models with group correlated hierarchical effects HOT 3
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