Calculate Performance Metrics

Computes True Positive Rate (TPR) and False Positive Rate (FPR) for ROC analysis using the ROCR package. Used internally for ROC curve generation.

Usage

CalculatePref(model, newx, s, acture.y)

Arguments

model

Fitted glmnet model.

newx

New data matrix for prediction.

s

Lambda value for prediction.

acture.y

Actual binary outcomes.

Value

ROCR performance object containing TPR and FPR values.

Examples

if (requireNamespace("glmnet", quietly = TRUE) &&
  requireNamespace("ROCR", quietly = TRUE)) {
  fitted_model <- glmnet::cv.glmnet(matrix(rnorm(100), ncol = 2), rbinom(50, 1, 0.5), nfolds = 3)
  perf <- CalculatePref(fitted_model, matrix(rnorm(20), ncol = 2), "lambda.min", rbinom(10, 1, 0.5))
}