Plot Model Performance vs Lambda for coxkl_ridge

Plots model performance across the lambda sequence. Performance is loss (-2 times partial log-likelihood) or concordance index (C-index). If no test data are provided, the curve uses the training data stored in object$data.

Usage

# S3 method for class 'coxkl_ridge'
plot(
  object,
  test_z = NULL,
  test_time = NULL,
  test_delta = NULL,
  test_stratum = NULL,
  criteria = c("loss", "CIndex"),
  ...
)

Arguments

object: A fitted model object of class "coxkl_ridge".
test_z: Optional numeric matrix of test covariates.
test_time: Optional numeric vector of test survival times.
test_delta: Optional numeric vector of test event indicators.
test_stratum: Optional vector of test stratum membership.
criteria: Character string: "loss" or "CIndex".
...: Additional arguments (ignored).

Value

A ggplot object showing the performance curve.

Details

When criteria = "loss" and no test data are supplied, the plotted values are -2 * object$likelihood (no normalization). When test data are provided, performance is computed via test_eval(..., criteria). The x-axis is shown in decreasing lambda with a reversed log10 scale.

Examples

data(ExampleData_highdim) 

train_dat_highdim <- ExampleData_highdim$train
test_dat_highdim <- ExampleData_highdim$test
beta_external_highdim <- ExampleData_highdim$beta_external


model_ridge <- coxkl_ridge(z = train_dat_highdim$z,
                           delta = train_dat_highdim$status,
                           time = train_dat_highdim$time,
                           beta = beta_external_highdim,
                           eta = 1)
#> Warning: Stratum information not provided. All data is assumed to originate from a single stratum!

plot(
  model_ridge,
  test_z       = test_dat_highdim$z,
  test_time    = test_dat_highdim$time,
  test_delta   = test_dat_highdim$status,
  test_stratum = test_dat_highdim$stratum,
  criteria     = "CIndex"
)