plot.sdwd: plot coefficients for the sparse DWD

Description

Plots the solution paths for a fitted sdwd object.

Usage

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

Arguments

A fitted sdwd model.

xvar

Specifies the X-axis. If xvar == "norm", plots against the L1-norm of the coefficients; if xvar == "lambda" against the log-lambda sequence.

color

If TRUE, plots the curves with rainbow colors; otherwise, with gray colors (default).

label

If TRUE, labels the curves with variable sequence numbers. Default is FALSE.

…

Other graphical parameters to plot.

Details

Plots the solution paths as a coefficient profile plot. This function is modified based on the plot function from the gcdnet and the glmnet packages.

References

Wang, B. and Zou, H. (2016) ``Sparse Distance Weighted Discrimination", Journal of Computational and Graphical Statistics, 25(3), 826--838. https://www.tandfonline.com/doi/full/10.1080/10618600.2015.1049700

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. https://www.tandfonline.com/doi/full/10.1080/10618600.2012.680324

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. https://www.jstatsoft.org/v33/i01/paper

Examples

Run this code

# NOT RUN {
data(colon)
fit = sdwd(colon$x, colon$y)
par(mfrow=c(1,3))
# plots against the L1-norm of the coefficients
plot(fit) 
# plots against the log-lambda sequence
plot(fit, xvar="lambda", label=TRUE)
# plots with colors
plot(fit, color=TRUE)
# }