print.cocktail: print a cocktail object

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

print a cocktail object

Description

Print a summary of the cocktail path at each step along the path. This function is modified based on the print function from the glmnet package.

Usage

## S3 method for class 'cocktail'
print(x, digits = max(3, getOption("digits") - 3), ...)

Arguments

x	fitted cocktail object
digits	significant digits in printout
...	additional print arguments

Details

The call that produced the cocktail object is printed, followed by a two-column matrix with columns Df and Lambda. The Df column is the number of nonzero coefficients.

Value

a two-column matrix, the first columns is the number of nonzero coefficients and the second column is Lambda.

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. (2008) "Regularization Paths for Generalized Linear Models via Coordinate Descent", https://web.stanford.edu/~hastie/Papers/glmnet.pdf
Journal of Statistical Software, Vol. 33(1), 1-22 Feb 2010
https://www.jstatsoft.org/v33/i01/

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
https://www.jstatsoft.org/v39/i05/

Examples

data(FHT)
m1<-cocktail(x=FHT$x,y=FHT$y,d=FHT$status,alpha=0.5)
print(m1)

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