PLL: Generic function for extracting the predictive partial...

In peperr: Parallelised Estimation of Prediction Error

Generic function for extracting the predictive partial log-likelihood

Description

Generic function for extracting th predictive partial log-likelihood from a fitted survival model.

Usage

PLL(object, newdata, newtime, newstatus, ...)

Arguments

object	fitted model of class class.
newdata	n_new*p matrix of covariates.
newtime	n_new-vector of censored survival times.
newstatus	n_new-vector of event status, coded with 0 for censoring and 1, if an event occurred.
...	additional arguments, for example complexity value, if necessary.

Details

The predictive partial log-likelihood measures the prediction performance of each model fitted in a boostrap sample, using the data not in this sample. Multiplying by (-2) leads to a deviance-like measure, which means that small values indicate good prediction performance.

peperr requires function PLL.class in case of survival response, for each model fit of class class. Available methods include PLL.CoxBoost, PLL.coxph, PLL.penfit, PLL.coxnet, PLL.grpsurv, PLL.ncvsurv, PLL.mboost_coxph, and PLL.SGL_cox.

Value

Numeric predictive partial log-likelihood returned by the method implementation.

peperr documentation built on March 25, 2026, 9:06 a.m.