performances | R Documentation |
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, ...)
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 |
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.
# 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))
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