mycoxpred

This function amends the function arguments passed to survfit.coxnet
via ... if new data was passed to survfit.coxnet. It's a separate
function as we have to deal with function options like newstrata
and newoffset.

Extremely efficient procedures for fitting the entire lasso or elastic-net regularization path for linear regression, logistic and multinomial regression models, Poisson regression, Cox model, multiple-response Gaussian, and the grouped multinomial regression; see <doi:10.18637/jss.v033.i01> and <doi:10.18637/jss.v039.i05>. There are two new and important additions. The family argument can be a GLM family object, which opens the door to any programmed family (<doi:10.18637/jss.v106.i01>). This comes with a modest computational cost, so when the built-in families suffice, they should be used instead. The other novelty is the relax option, which refits each of the active sets in the path unpenalized. The algorithm uses cyclical coordinate descent in a path-wise fashion, as described in the papers cited.

Trevor Hastie

glmnet

Lasso and Elastic-Net Regularized Generalized Linear Models

Jerome Friedman

Rob Tibshirani

Balasubramanian Narasimhan

Kenneth Tay

Noah Simon

Junyang Qian

James Yang

mycoxpred function

<dl><dt>object</dt>
<dd>A class <code>coxnet</code> object.</dd>
<dt>s</dt>
<dd>The response for the fitted model.</dd>
<dt>...</dt>
<dd>The same ... that was passed to survfit.coxnet.</dd></dl>

Arguments

Helper function to amend ... for new data in survfit.coxnet — mycoxpred

<dl>

<dt>object</dt>
<dd>A class <code>coxnet</code> object.</dd>


<dt>s</dt>
<dd>The response for the fitted model.</dd>


<dt>...</dt>
<dd>The same ... that was passed to survfit.coxnet.</dd>

</dl>

mycoxpred: Helper function to amend ... for new data in survfit.coxnet

Description

Usage

Arguments