Extract the prediction performance of one or more (adaptive) PENSE fits.
prediction_performance(..., alpha = NULL, lambda = "min", se_mult = 1)
# S3 method for pense_pred_perf
print(x, ...)one or more (adaptive) PENSE fits with cross-validation information.
Either a numeric vector or NULL (default).
If given, only fits with the given alpha value are considered.
If lambda is a numeric value and object was fit with multiple alpha
values, the parameter alpha must not be missing.
either a string specifying which penalty level to use
("min", "se", "{x}-se")
or a single numeric value of the penalty parameter. See details.
If lambda = "se", the multiple of standard errors to tolerate.
an object with information on prediction performance created with prediction_performance().
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.
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.
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()