Function reference • projpred

All functions
`as.matrix(<projection>)`	Extract projected parameter draws and coerce to matrix
`as_draws_matrix(<projection>)` `as_draws(<projection>)`	Extract projected parameter draws and coerce to `draws_matrix` (see package posterior)
`augdat_ilink_binom()`	Inverse-link function for augmented-data projection with binomial family
`augdat_link_binom()`	Link function for augmented-data projection with binomial family
`break_up_matrix_term()`	Break up matrix terms
`cl_agg()`	Weighted averaging within clusters of parameter draws
`cv_folds()` `cvfolds()` `cv_ids()`	Create cross-validation folds
`cv_proportions()`	Ranking proportions from fold-wise predictor rankings
`cv_varsel()`	Run search and performance evaluation with cross-validation
`df_binom`	Binomial toy example
`df_gaussian`	Gaussian toy example
`extend_family()`	Extend a family
`Student_t()`	Extra family objects
`force_search_terms()`	Force search terms
`mesquite`	Mesquite data set
`performances()`	Predictive performance results
`plot(<cv_proportions>)` `plot(<ranking>)`	Plot ranking proportions from fold-wise predictor rankings
`plot(<vsel>)`	Plot predictive performance
`proj_linpred()` `proj_predict()`	Predictions from a submodel (after projection)
`predict(<refmodel>)`	Predictions or log posterior predictive densities from a reference model
`predictor_terms()`	Predictor terms used in a `project()` run
`print(<projection>)`	Print information about `project()` output
`print(<refmodel>)`	Print information about a reference model object
`print(<vsel>)`	Print results (summary) of a `varsel()` or `cv_varsel()` run
`print(<vselsummary>)`	Print summary of a `varsel()` or `cv_varsel()` run
`project()`	Projection onto submodel(s)
`projpred` `projpred-package`	Projection predictive feature selection
`ranking()`	Predictor ranking(s)
`get_refmodel()` `init_refmodel()`	Reference model and more general information
`run_cvfun()`	Create `cvfits` from `cvfun`
`solution_terms()`	Retrieve the full-data solution path from a `varsel()` or `cv_varsel()` run or the predictor combination from a `project()` run
`suggest_size()`	Suggest submodel size
`summary(<vsel>)`	Summary of a `varsel()` or `cv_varsel()` run
`varsel()`	Run search and performance evaluation without cross-validation
`y_wobs_offs()`	Extract response values, observation weights, and offsets

Reference

All functions