Compute fitted values and prediction error for a model fitted by lple
## S3 method for class 'lple'
# S3 method for lple
predict(object, newdata, newy=NULL, ...)
# S3 method for lple
residuals(object, type=c("martingale", "deviance"), ...)
predict.lple returns a list of predicted values, prediction error and residuals.
linear predictor of beta(w)*Z, where beta(w) is the fitted regression coefficient and Z is covariance matrix.
risk score, exp(lp). When new y is provided, both lp and risk will be ordered by survival time of the new y.
martingale residuals of the prediction, if available.
prediction error based on martingale residual, if both new data and new y is provided.
cumulative hzard function.
time for cumulative hazard function. Time from new y will be used is provided
a model object from the lple fit
optional new data at which to do predictions. If absent, predictions are for the dataframe used in the original fit
optional new response data. Default is NULL
type of residuals, the default is a martingale residual
additional arguments affecting the predictions produced
Bingshu E. Chen
predict.lple is called to predict object from the lple model lple.
The default method, predict has its own help page. Use methods("predict") to get all the methods for the predict generic.
The default method for predict predict,
For the Cox model prediction: predict.coxph.
#survfit.lple