coef.gglasso {gglasso} | R Documentation |
Computes the coefficients at the requested values for lambda
from a fitted gglasso
object.
## S3 method for class 'gglasso' coef(object, s = NULL, ...)
object |
fitted |
s |
value(s) of the penalty parameter |
... |
not used. Other arguments to predict. |
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.
The coefficients at the requested values for lambda
.
Yi Yang and Hui Zou
Maintainer: Yi Yang <yi.yang6@mcgill.ca>
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
predict.gglasso
method
# 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))