predict.KMforCSD: Kernel Machine for Current Status Data - Prediction
In Yael-Travis-Lumer/KMforCSD: Kernel Machine Regression for Current Status Data

Description Usage Arguments Value Examples

predict.KMforCSD returns the KM decision function, together with the test data (which can be equivalent to the training data).

1 2	## S3 method for class 'KMforCSD' predict(object, newdata)

`object`	A KMforCSD fitted model. This is the output of `KMforCSD`.
`newdata`	A data frame consisting of the p-dimensional covariates Z, the current status indicator vector delta, and the censoring times C.

The function returns a data frame consisting of newdata, and the kernel machine predictions.

d <- exp_data(n=100) #training set
sol <- KMforCSD(data=d[[1]]) #training
d_test <- exp_data(n=50) #test set
new_data <- predict(sol,d_test[[1]]) #prediction
decision_function <- new_data$prediction