fit_lasso | R Documentation |
Automatic model selection for high-dimensional Cox models with lasso penalty, evaluated by penalized partial-likelihood.
fit_lasso(x, y, nfolds = 5L, rule = c("lambda.min", "lambda.1se"), seed = 1001)
x |
Data matrix. |
y |
Response matrix made by |
nfolds |
Fold numbers of cross-validation. |
rule |
Model selection criterion, |
seed |
A random seed for cross-validation fold division. |
data("smart")
x <- as.matrix(smart[, -c(1, 2)])
time <- smart$TEVENT
event <- smart$EVENT
y <- survival::Surv(time, event)
fit <- fit_lasso(x, y, nfolds = 5, rule = "lambda.1se", seed = 11)
nom <- as_nomogram(
fit, x, time, event,
pred.at = 365 * 2,
funlabel = "2-Year Overall Survival Probability"
)
plot(nom)
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