`projpred.Rd`

Description

projpred is an R package to perform projection predictive variable selection for generalized
linear models. The package is aimed to be compatible with rstanarm but also other
reference models can be used (see function `init_refmodel`

).

Currently, the supported models (family objects in R) include Gaussian, Binomial and Poisson families, but more will be implemented later. See the quickstart-vignette for examples.

- varsel, cv_varsel, init_refmodel, suggest_size
Perform and cross-validate the variable selection. init_refmodel can be used to initialize a reference model other than rstanarm-fit.

- project
Get the projected posteriors of the reduced models.

- proj_predict, proj_linpred
Make predictions with reduced number of features.

- varsel_plot, varsel_stats
Visualize and get some key statistics about the variable selection.

Dupuis, J. A. and Robert, C. P. (2003). Variable selection in qualitative models via
an entropic explanatory power. *Journal of Statistical Planning and Inference*, 111(1-2):77–94.

Goutis, C. and Robert, C. P. (1998). Model choice in generalised linear models: a Bayesian
approach via Kullback–Leibler projections. *Biometrika*, 85(1):29–37.

Juho Piironen and Aki Vehtari (2017). Comparison of Bayesian predictive methods for model selection.
*Statistics and Computing*, 27(3):711-735. doi:10.1007/s11222-016-9649-y. (Online).