plot.cv.cocktail: plot the cross-validation curve produced by cv.cocktail

In fastcox: Lasso and Elastic-Net Penalized Cox's Regression in High Dimensions Models using the Cocktail Algorithm

plot the cross-validation curve produced by cv.cocktail

Description

Plots the cross-validation curve, and upper and lower standard deviation curves, as a function of the lambda values used. This function is modified based on the plot.cv function from the glmnet package.

Usage

## S3 method for class 'cv.cocktail'
plot(x, sign.lambda, ...)

Arguments

x	fitted cv.cocktail object
sign.lambda	either plot against log(lambda) (default) or its negative if sign.lambda=-1.
...	other graphical parameters to plot

Details

A plot is produced.

Author(s)

Yi Yang and Hui Zou
Maintainer: Yi Yang <[e-mail]>

References

Yang, Y. and Zou, H. (2013), "A Cocktail Algorithm for Solving The Elastic Net Penalized Cox's Regression in High Dimensions", Statistics and Its Interface, 6:2, 167-173.
https://github.com/archer-yang-lab/fastcox

Friedman, J., Hastie, T., and Tibshirani, R. (2010), "Regularization paths for generalized linear models via coordinate descent," Journal of Statistical Software, 33, 1.
https://www.jstatsoft.org/v33/i01/

See Also

cv.cocktail.

fastcox documentation built on June 8, 2025, 10:47 a.m.