plot.spikeslab: Plots for Spike and Slab Analysis

In spikeslab: Prediction and Variable Selection Using Spike and Slab Regression

Plots for Spike and Slab Analysis

Description

Plots either the gnet solution path or the cross-validated mean-squared-error (the latter only applies when cross-validation is used).

Usage

## S3 method for class 'spikeslab'
plot(x, plot.type = c("path", "cv"), breaks = FALSE, ...)

Arguments

x	An object of class spikeslab.
plot.type	Choosing "path" produces a plot of the gnet solution path. The choice "cv" produces the mean-squared error plot. The latter applies only to objects from a cv.spikeslab call.
breaks	If TRUE, then vertical lines are drawn at each break point in the gnet solution path.
...	Further arguments passed to or from other methods.

Author(s)

Hemant Ishwaran ([e-mail])

J. Sunil Rao ([e-mail])

Udaya B. Kogalur ([e-mail])

References

Efron B., Hastie T., Johnstone I., and Tibshirani R. (2004). Least angle regression (with discussion). Ann. Statist., 32:407-499.

Ishwaran H. and Rao J.S. (2010). Generalized ridge regression: geometry and computational solutions when p is larger than n.

See Also

spikeslab, cv.spikeslab.

Examples

## Not run: 
#------------------------------------------------------------
# Example 1: diabetes data
#------------------------------------------------------------

data(diabetesI, package = "spikeslab")
obj <- spikeslab(Y ~ . , diabetesI, verbose = TRUE)
plot(obj, plot.type = "path")

## End(Not run)

spikeslab documentation built on April 27, 2022, 1:05 a.m.