CalculatePref: Calculate Performance Metrics

In IOBR: Immune Oncology Biological Research

Calculate Performance Metrics

Description

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))
}

IOBR documentation built on May 30, 2026, 5:07 p.m.