View source: R/1_3_model_method.R
predict.hdnom.model | R Documentation |
Predict overall survival probability at certain time points from fitted Cox models.
## S3 method for class 'hdnom.model'
predict(object, x, y, newx, pred.at, ...)
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). |
A nrow(newx) x length(pred.at)
matrix containing
overall survival probablity.
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)
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