Comments (4)
Thanks for the suggestion, this makes sense. This is feasible as it would not change the projection part, just the criterion for whether the model is good enough.
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Checking if you would like to collaborate on this?
from projpred.
In which sense?
from projpred.
In sense of developing theory, running experiments, or implementing code? Have you already done experiments on this?
from projpred.
Related Issues (20)
- 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
- negbin latent projection in latent vignette fails with parallel HOT 1
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