gglasso (version 1.5.1)

coef.gglasso: get coefficients or make coefficient predictions from an "gglasso" object.

Description

Computes the coefficients at the requested values for lambda from a fitted gglasso object.

Usage

# S3 method for gglasso
coef(object, s = NULL, ...)

Value

The coefficients at the requested values for lambda.

Arguments

object

fitted gglasso model object.

s

value(s) of the penalty parameter lambda at which predictions are required. Default is the entire sequence used to create the model.

...

not used. Other arguments to predict.

Author

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

Details

s is the new vector at which predictions are requested. If s is not in the lambda sequence used for fitting the model, the coef function will use linear interpolation to make predictions. The new values are interpolated using a fraction of coefficients from both left and right lambda indices.

References

Yang, Y. and Zou, H. (2015), ``A Fast Unified Algorithm for Computing Group-Lasso Penalized Learning Problems,'' Statistics and Computing. 25(6), 1129-1141.
BugReport: https://github.com/emeryyi/gglasso

See Also

predict.gglasso method

Examples

# load gglasso library
library(gglasso)

# load data set
data(colon)

# define group index
group <- rep(1:20,each=5)

# fit group lasso
m1 <- gglasso(x=colon$x,y=colon$y,group=group,loss="logit")

# the coefficients at lambda = 0.01 and 0.02
coef(m1,s=c(0.01,0.02))