plot.msgps: plot the solution path from a "msgps" object.

In msgps: Degrees of Freedom of Elastic Net, Adaptive Lasso and Generalized Elastic Net

plot the solution path from a "msgps" object.

Description

This functions predicts fitted values from a "msgps" object.

Usage

## S3 method for class 'msgps'
plot(x, criterion="cp", xvar="norm", yvar="coef", yvar.dflasso=TRUE, 
stand.coef=TRUE, plot.step = 1000, col=TRUE,...)

Arguments

x	Fitted "msgps" model object.

criterion	The code criterion plots the value of tuning parameter of each criterion ("cp", "aicc", "gcv", "bic"). The code "none" does not depict the tuning parameter.
xvar	The type of x variable. "xvar=norm" is max|beta|/|beta|, "xvar=sum" is max|beta|, "xvar=step" is the number of steps, and "xvar=t" is tuning parameter.
yvar	The type of y variable. "yvar=coef" is the standardized coefficients, and "tvar=df" is the degrees of freedom.
yvar.dflasso	For lasso penalty, the degrees of freedom of the lasso (the number of non-zero parameters) is given when "yvar=df" and "yvar.dflasso=TRUE".
stand.coef	The standardized coefficients and tuning parameters are dipicted if "stand.coef=TRUE".
plot.step	The number of steps to plot the solution of df. As plot.step increases, the picture will be well-looking whereas the file size of the picture will increase.
col	The color option.
...	Other graphical parameters to plot

Value

The object returned depends on type.

Author(s)

Kei Hirose
[e-mail]

See Also

coef.msgps, predict.msgps and summary.msgps objects.

Examples

#data
X <- matrix(rnorm(100*8),100,8)
beta0 <- c(3,1.5,0,0,2,0,0,0)
epsilon <- rnorm(100,sd=3)
y <- X %*% beta0 + epsilon
y <- c(y)

#fit
fit <- msgps(X,y)
plot(fit,criterion="cp") #plot the solution path with a model selected by Cp criterion

msgps documentation built on Oct. 21, 2022, 1:06 a.m.