Plot Cross-Validation Results vs Eta

Plots cross-validated performance across eta for cv.coxkl, cv.coxkl_ridge, or cv.coxkl_enet results. The main CV curve is drawn as a solid purple line; a green dotted horizontal reference line is placed at the value corresponding to eta = 0 (or the closest available eta), with a solid green point marking that reference level.

Usage

cv.plot(object, line_color = "#7570B3", baseline_color = "#1B9E77", ...)

Arguments

object: A fitted cross-validation result of class "cv.coxkl", "cv.coxkl_ridge", or "cv.coxkl_enet".
line_color: Color for the CV performance curve. Default "#7570B3".
baseline_color: Color for the horizontal reference line and point. Default "#1B9E77".
...: Additional arguments (currently ignored).

Value

A ggplot object showing cross-validation performance versus eta.

Details

The function reads the performance metric from the object:

For "cv.coxkl": uses object$internal_stat (one row per eta).
For "cv.coxkl_ridge" and "cv.coxkl_enet": uses object$integrated_stat.best_per_eta (best lambda per eta).

The y-axis label is set to “Loss” if criteria in the object is “V&VH” or “LinPred”; otherwise it is “C Index”. The horizontal reference (“baseline”) is taken from the plotted series at eta = 0 (or the nearest eta present in the results).

Examples

data(Exampledata_lowdim)
#> Warning: data set 'Exampledata_lowdim' not found

train_dat_lowdim <- ExampleData_lowdim$train
beta_external_good_lowdim <- ExampleData_lowdim$beta_external_good

etas <- generate_eta(method = "exponential", n = 100, max_eta = 30)
cv_res <- cv.coxkl(z = train_dat_lowdim$z,
                   delta = train_dat_lowdim$status,
                   time = train_dat_lowdim$time,
                   stratrum = train_dat_lowdim$stratum,
                   beta = beta_external_good_lowdim,
                   etas = etas,
                   nfolds = 5,
                   criteria = c("V&VH"),
                   seed = 1)
#> Warning: Stratum not provided. Treating all data as one stratum.
cv.plot(cv_res)