PLL.coxnet: Predictive partial log-likelihood for glmnet Cox PH model fit

In c060: Extended Inference for Lasso and Elastic-Net Regularized Cox and Generalized Linear Models

Predictive partial log-likelihood for glmnet Cox PH model fit

Description

Extracts the predictive partial log-likelihood from a glmnet Cox PH model fit.

Usage

## S3 method for class 'coxnet'
PLL(object, newdata, newtime, newstatus, complexity, ...)

Arguments

object	fitted model of class coxnet.
newdata	n_new*p matrix of covariates.
newtime	n_new-vector of censored survival times.
newstatus	n_new-vector of survival status, coded with 0 and .1
complexity	lambda penalty value.
...	additional arguments, not used.

Details

Used by function peperr, if function fit.glmnet and family="cox" is used for model fit, which gives a class coxnet object. This is basically a wrapper based on the coxnet.deviance function from package glmnet.

Value

Vector of length n_new

Author(s)

Thomas Hielscher [e-mail]

References

Sill M., Hielscher T., Becker N. and Zucknick M. (2014), c060: Extended Inference with Lasso and Elastic-Net Regularized Cox and Generalized Linear Models, Journal of Statistical Software, Volume 62(5), pages 1–22. https://doi.org/10.18637/jss.v062.i05.

c060 documentation built on Nov. 5, 2025, 7:21 p.m.