Extract the prediction performance of one or more (adaptive) PENSE fits.
Usage
prediction_performance(..., alpha = NULL, lambda = "min", se_mult = 1)
# S3 method for class 'pense_pred_perf'
print(x, ...)Arguments
- ...
one or more (adaptive) PENSE fits with cross-validation information.
- alpha
Either a numeric vector or
NULL(default). If given, only fits with the givenalphavalue are considered. Iflambdais a numeric value andobjectwas fit with multiplealphavalues, the parameteralphamust not be missing.- lambda
either a string specifying which penalty level to use (
"min","se","{x}-se") or a single numeric value of the penalty parameter. See details.- se_mult
If
lambda = "se", the multiple of standard errors to tolerate.- x
an object with information on prediction performance created with
prediction_performance().
Value
a data frame with details about the prediction performance of the given PENSE fits. The data frame has a custom print method summarizing the prediction performances.
Details
If lambda = "se" and the cross-validation was performed with multiple replications, use the penalty level whit
prediction performance within se_mult of the best prediction performance.
See also
summary.pense_cvfit() for a summary of the fitted model.
Other functions for plotting and printing:
plot.pense_cvfit(),
plot.pense_fit(),
summary.pense_cvfit()