Automatic model selection for high-dimensional Cox models with adaptive lasso penalty, evaluated by penalized partial-likelihood.
Response matrix made by
Fold numbers of cross-validation.
Model selection criterion,
Two random seeds for cross-validation fold division in two estimation steps.
data("smart") x <- as.matrix(smart[, -c(1, 2)]) time <- smart$TEVENT event <- smart$EVENT y <- survival::Surv(time, event) fit <- fit_alasso(x, y, nfolds = 3, rule = "lambda.1se", seed = c(7, 11)) nom <- as_nomogram( fit, x, time, event, pred.at = 365 * 2, funlabel = "2-Year Overall Survival Probability" ) plot(nom)