predict.hdnom.model: Make predictions from high-dimensional Cox models

In hdnom: Benchmarking and Visualization Toolkit for Penalized Cox Models

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 Surv.
newx	Matrix (with named columns) of new values for x at which predictions are to be made.
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)

hdnom documentation built on April 24, 2023, 9:09 a.m.