predictSGL {SGL} | R Documentation |
Outputs Predicted Responses from an SGL Model for New Observations
Description
Outputs predicted response values for new user input observations at a specified lambda
value
Usage
predictSGL(x, newX, lam)
Arguments
x |
fitted |
newX |
covariate matrix for new observations whose responses we wish to predict |
lam |
the index of the lambda value for the model with which we desire to predict |
Details
Predicted outcomes are given
Author(s)
Noah Simon, Jerome Friedman, Trevor Hastie, and Rob Tibshirani
Maintainer: Noah Simon <nrsimon@uw.edu>
References
Simon, N., Friedman, J., Hastie T., and Tibshirani, R. (2011)
A Sparse-Group Lasso,
http://faculty.washington.edu/nrsimon/SGLpaper.pdf
See Also
SGL
and cvSGL
.
Examples
n = 50; p = 100; size.groups = 10
index <- ceiling(1:p / size.groups)
X = matrix(rnorm(n * p), ncol = p, nrow = n)
beta = (-2:2)
y = X[,1:5] %*% beta + 0.1*rnorm(n)
data = list(x = X, y = y)
Fit = SGL(data, index, type = "linear")
X.new = matrix(rnorm(n * p), ncol = p, nrow = n)
predictSGL(Fit, X.new, 5)
[Package SGL version 1.3 Index]