plot.gcdnet: Plot coefficients from a "gcdnet" object

In gcdnet: The (Adaptive) LASSO and Elastic Net Penalized Least Squares, Logistic Regression, Hybrid Huberized Support Vector Machines, Squared Hinge Loss Support Vector Machines and Expectile Regression using a Fast Generalized Coordinate Descent Algorithm

Plot coefficients from a "gcdnet" object

Description

Produces a coefficient profile plot of the coefficient paths for a fitted gcdnet object. This function is modified based on the plot function from the glmnet package.

Usage

## S3 method for class 'gcdnet'
plot(x, xvar = c("norm", "lambda"), color = FALSE, label = FALSE, ...)

Arguments

x	fitted gcdnet model
xvar	what is on the X-axis. "norm" plots against the L1-norm of the coefficients, "lambda" against the log-lambda sequence.
color	if TRUE, plot the curves with rainbow colors. FALSE is gray colors. Default is FALSE
label	if TRUE, label the curves with variable sequence numbers. Default is FALSE
...	other graphical parameters to plot

Details

A coefficient profile plot is produced.

Author(s)

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

References

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/

Examples

data(FHT)
m1 <- gcdnet(x = FHT$x,y = FHT$y)
par(mfrow = c(1,3))
plot(m1) # plots against the L1-norm of the coefficients
plot(m1,xvar = "lambda",label = TRUE) # plots against the log-lambda sequence
plot(m1,color = TRUE)

gcdnet documentation built on Aug. 14, 2022, 9:05 a.m.