coef.cv.sdwd {sdwd} | R Documentation |
Computes coefficients at chosen values of lambda
from the cv.sdwd
object.
## S3 method for class 'cv.sdwd' coef(object, s=c("lambda.1se", "lambda.min"),...)
object |
A fitted |
s |
Value(s) of the L1 tuning parameter |
... |
Other arguments that can be passed to |
This function computes the coefficients at the values of lambda
suggested by the cross-validation. This function is modified based on the coef.cv
function from the glmnet
and the gcdnet
packages.
The object returned depends the choice of s
and the ... argument passed on to the sdwd
method.
Boxiang Wang and Hui Zou
Maintainer: Boxiang Wang boxiang@umn.edu
Wang, B. and Zou, H. (2015)
“Sparse Distance Weighted Discrimination", Journal of Computational and Graphical Statistics, forthcoming.
http://arxiv.org/abs/1501.06066
Yang, Y. and Zou, H. (2013)
“An Efficient Algorithm for Computing the HHSVM and Its Generalizations",
Journal of Computational and Graphical Statistics, 22(2), 396–415
http://users.stat.umn.edu/~yiyang/resources/papers/JCGS_gcdnet.pdf
Friedman, J., Hastie, T., and Tibshirani, R. (2010), "Regularization paths for generalized
linear models via coordinate descent," Journal of Statistical Software, 33(1), 1–22
http://www.jstatsoft.org/v33/i01/paper
cv.sdwd
and predict.cv.sdwd
methods.
data(colon) colon$x = colon$x[ ,1:100] # this example only uses the first 100 columns set.seed(1) cv = cv.sdwd(colon$x, colon$y, lambda2=1, nfolds=5) c1 = coef(cv, s="lambda.1se")