force_search_terms: Force search terms

In paasim/glmproj: Projection Predictive Feature Selection

Force search terms

Description

A helper function to construct the input for argument search_terms of varsel() or cv_varsel() if certain predictor terms should be forced to be selected first whereas other predictor terms are optional (i.e., they are subject to the variable selection, but only after the inclusion of the "forced" terms).

Usage

force_search_terms(forced_terms, optional_terms)

Arguments

forced_terms	A character vector of predictor terms that should be selected first.
optional_terms	A character vector of predictor terms that should be subject to the variable selection after the inclusion of the "forced" terms.

Value

A character vector that may be used as input for argument search_terms of varsel() or cv_varsel().

See Also

varsel(), cv_varsel()

Examples

# Data:
dat_gauss <- data.frame(y = df_gaussian$y, df_gaussian$x)

# The `stanreg` fit which will be used as the reference model (with small
# values for `chains` and `iter`, but only for technical reasons in this
# example; this is not recommended in general):
fit <- rstanarm::stan_glm(
  y ~ X1 + X2 + X3 + X4 + X5, family = gaussian(), data = dat_gauss,
  QR = TRUE, chains = 2, iter = 500, refresh = 0, seed = 9876
)

# We will force X1 and X2 to be selected first:
search_terms_forced <- force_search_terms(
  forced_terms = paste0("X", 1:2),
  optional_terms = paste0("X", 3:5)
)

# Run varsel() (here without cross-validation and with small values for
# `nterms_max`, `nclusters`, and `nclusters_pred`, but only for the sake of
# speed in this example; this is not recommended in general):
vs <- varsel(fit, nclusters = 5, nclusters_pred = 10,
             search_terms = search_terms_forced, seed = 5555)
# Now see, for example, `?print.vsel`, `?plot.vsel`, `?suggest_size.vsel`,
# and `?ranking` for possible post-processing functions.

paasim/glmproj documentation built on April 14, 2024, 5:30 p.m.