coxnet.deviance

pred

a survival response matrix, as produced by <code>Surv</code>

optional <code>x</code> matrix, if <code>pred</code> is <code>NULL</code>

offset

weights

optional coefficient vector/matrix, supplied if <code>pred=NULL</code>

beta

Given a fit or coefficients, compute the deciance (-2 log partial likelihood) for
right-censored survival data

model

Extremely efficient procedures for fitting the entire lasso or elastic-net regularization path for linear regression, logistic and multinomial regression models, Poisson regression and the Cox model. Two recent additions are the multiple-response Gaussian, and the grouped multinomial regression. The algorithm uses cyclical coordinate descent in a path-wise fashion, as described in the papers listed in the URL below.

coxnet.deviance: compute deviance for cox model output

Description

Usage

Arguments

Value

Details

See Also