plot.kerndwd: plot coefficients

In kerndwd: Distance Weighted Discrimination (DWD) and Kernel Methods

Description

Plot the solution paths for a fitted kerndwd object.

Usage

## S3 method for class 'kerndwd'
plot(x, color=FALSE, ...)

Arguments

x	A fitted “kerndwd"" model.
color	If TRUE, plots the curves with rainbow colors; otherwise, with gray colors (default).
...	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 glmnet package.

Author(s)

Boxiang Wang and Hui Zou
Maintainer: Boxiang Wang [e-mail]

References

Wang, B. and Zou, H. (2018) “Another Look at Distance Weighted Discrimination," Journal of Royal Statistical Society, Series B, 80(1), 177–198.
https://rss.onlinelibrary.wiley.com/doi/10.1111/rssb.12244
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

See Also

kerndwd, predict.kerndwd, coef.kerndwd, plot.kerndwd, and cv.kerndwd.

Examples

data(BUPA)
BUPA$X = scale(BUPA$X, center=TRUE, scale=TRUE)
lambda = 10^(seq(-3, 3, length.out=10))
kern = rbfdot(sigma=sigest(BUPA$X))
m1 = kerndwd(BUPA$X, BUPA$y, kern, qval=1, 
  lambda=lambda, eps=1e-5, maxit=1e5)
plot(m1, color=TRUE)

Example output

kerndwd documentation built on Sept. 4, 2020, 1:08 a.m.