if (FALSE) { # requireNamespace("rstanarm", quietly = TRUE)
# 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.
}
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