projsel: Forward selection minimizing KL-divergence in projection

In hsstan: Hierarchical Shrinkage Stan Models for Biomarker Selection

Description

Forward selection minimizing KL-divergence in projection

Usage

projsel(obj, max.iters = 30, start.from = NULL, out.csv = NULL)

Arguments

obj	Object of class hsstan.
max.iters	Maximum number of iterations (number of predictors selected) after which the selection procedure should stop.
start.from	Vector of variable names to be used in the starting submodel. If NULL (default), selection starts from the set of unpenalized covariates if the model contains penalized predictors, otherwise selection starts from the intercept-only model.
out.csv	If not NULL, the name of a CSV file to save the output to.

Value

A data frame of class projsel where each row corresponds to a forward-selected submodel that contains all variables listed up to that row. Attribute start.from reports the predictors in the initial model. The data frame contains the following columns:

var	names of the variables selected.
kl	KL-divergence from the full model to the submodel.
rel.kl.null	relative explanatory power of predictors starting from the intercept-only model.
rel.kl	relative explanatory power of predictors starting from the initial submodel.
elpd	the expected log predictive density of the submodels.
delta.elpd	the difference in elpd from the full model.

Examples

# continued from ?hsstan
sel <- projsel(hs.biom, max.iters=3)
plot(sel)

hsstan documentation built on Sept. 16, 2021, 9:11 a.m.