Computes the coefficients or returns a list of the indices of the nonzero
coefficients at the requested values for lambda
from a fitted
gcdnet
object.
# S3 method for gcdnet
coef(object, s = NULL, type = c("coefficients", "nonzero"), ...)
The object returned depends on type.
fitted gcdnet
model object.
value(s) of the penalty parameter lambda
at which
predictions are required. Default is the entire sequence used to create
the model.
type "coefficients"
computes the coefficients at the
requested values for s
. Type "nonzero"
returns a list of the
indices of the nonzero coefficients for each value of s
. Default is
"coefficients"
.
not used. Other arguments to predict.
Yi Yang, Yuwen Gu and Hui Zou
Maintainer: Yi Yang <yi.yang6@mcgill.ca>
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.
Yang, Y. and Zou, H. (2012).
"An Efficient Algorithm for Computing The HHSVM and Its Generalizations."
Journal of Computational and Graphical Statistics, 22, 396-415.
BugReport: https://github.com/emeryyi/gcdnet
Gu, Y., and Zou, H. (2016).
"High-dimensional generalizations of asymmetric least squares regression and their applications."
The Annals of Statistics, 44(6), 2661–2694.
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/
predict.gcdnet
method
data(FHT)
fit1 <- gcdnet(x = FHT$x,y = FHT$y)
coef(fit1, type = "coef", s = c(0.1,0.005))
coef(fit1, type = "nonzero")
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