performances function

Predictive performance results

Retrieves the predictive performance summaries after running varsel() or cv_varsel(). These summaries are computed by summary.vsel(), so the main method of performances() is performances.vselsummary() (objects of class vselsummary are returned by summary.vsel()). As a shortcut method, performances.vsel() is provided as well (objects of class vsel are returned by varsel() and cv_varsel()). For a graphical representation, see plot.vsel().

performances(object, ...)

## S3 method for class 'vselsummary'
performances(object, ...)

## S3 method for class 'vsel'
performances(object, ...)

Arguments

• object: The object from which to retrieve the predictive performance results. Possible classes may be inferred from the names of the corresponding methods (see also the description).
• ...: For performances.vsel(): arguments passed to summary.vsel(). For performances.vselsummary(): currently ignored.

Returns

An object of class performances which is a list with the following elements:

• submodels: The predictive performance results for the submodels, as a data.frame.
• reference_model: The predictive performance results for the reference model, as a named vector.

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
)

# Run varsel() (here without cross-validation, with L1 search, and with small
# values for `nterms_max` and `nclusters_pred`, but only for the sake of
# speed in this example; this is not recommended in general):
vs <- varsel(fit, method = "L1", nterms_max = 3, nclusters_pred = 10,
             seed = 5555)
print(performances(vs))