predict.hdnom.model {hdnom} | R Documentation |
Make predictions from high-dimensional Cox models
Description
Predict overall survival probability at certain time points from fitted Cox models.
Usage
## S3 method for class 'hdnom.model'
predict(object, x, y, newx, pred.at, ...)
Arguments
object |
Model object. |
x |
Data matrix used to fit the model. |
y |
Response matrix made with |
newx |
Matrix (with named columns) of new values for |
pred.at |
Time point at which prediction should take place. |
... |
Other parameters (not used). |
Value
A nrow(newx) x length(pred.at)
matrix containing
overall survival probablity.
Examples
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)
predict(fit, x, y, newx = x[101:105, ], pred.at = 1:10 * 365)
[Package hdnom version 6.0.3 Index]