fit.glmnet {c060}R Documentation

Interface function for fitting a penalized regression model with glmnet


Interface for fitting penalized regression models for binary of survival endpoint using glmnet, conforming to the requirements for argument in peperr call.


fit.glmnet(response, x, cplx, ...)



a survival object (with Surv(time, status), or a binary vector with entries 0 and 1).


n*p matrix of covariates.


lambda penalty value.


additional arguments passed to glmnet call such as family.


Function is basically a wrapper for glmnet of package glmnet. Note that only penalized Cox PH (family="cox") and logistic regression models (family="binomial") are sensible for prediction error evaluation with package peperr.


glmnet object


Thomas Hielscher \


Friedman, J., Hastie, T. and Tibshirani, R. (2008) Regularization Paths for Generalized Linear Models via Coordinate Descent,
Journal of Statistical Software, Vol. 33(1), 1-22 Feb 2010
Simon, N., Friedman, J., Hastie, T., Tibshirani, R. (2011) Regularization Paths for Cox's Proportional Hazards Model via Coordinate Descent, Journal of Statistical Software, Vol. 39(5) 1-13
Porzelius, C., Binder, H., and Schumacher, M. (2009) Parallelized prediction error estimation for evaluation of high-dimensional models, Bioinformatics, Vol. 25(6), 827-829.
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. doi:10.18637/jss.v062.i05

See Also

peperr, glmnet

[Package c060 version 0.3-0 Index]