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``` r
library(nlme) ## mixed models with more advanced covariance structures
library(lme4) ## mixed models for glm
library(mlogit) ## multinomial (mixed) logistic regression
library(mnlogit) ## multi…
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This week we applied binomial regression on the the train dataset, using only the "true" and "false" labeled data. Furthermore, we made a brief start with implementing multinomial logistic regression …
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As a suggestion, would it be possible to extend `rms` to also support polytomous (multinomial) logistic regression models?
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Multinomial regression is possible in brms using the multinomial family and it works very well (thank you)! However there is currently no way to account for 0 count across all possible choices. This h…
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I can't get it to run quickly enough: https://discourse.mc-stan.org/t/troubleshooting-a-maxdiff-hierarchical-multinomial-regression/11235
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Look into stability of `brglm2`, then add as an option (replacing `glm.fit` with `brglm.fit` as needed) for running glm to adding Firth penalty functionality. This will require a bit of craftiness to …
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It would be very useful to be able to perform variable selection with competing risks. It would seem that it should be straightforward, since `glmnet` has a `multinomial` family. But as we've discover…
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More as a feature request: do you think it might be possible to allow some form of regularisation in `mblogit` multinomial fits?
When one is dealing with sparse data, one now often encounters problem…
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Add cross-validation tests for XGBoost.
* Weights column taken into account
* Test custom weights column
* Test binomial/regression/multinomial.
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Could look at including some fixed / random effects only in certain categories. Correspondence also discussed in [On the "Poisson Trick" and its Extensions for Fitting Multinomial Regression Models](h…