plot.coxpath: Plots the regularization path computed from coxpath

In glmpath: L1 Regularization Path for Generalized Linear Models and Cox Proportional Hazards Model

Description

This function takes a coxpath object and visualizes the regularization path. The horizontal axis can be norm, lambda or step. The vertical axis can be coefficients, aic or bic.

Usage

  ## S3 method for class 'coxpath'
plot(x, xvar = c("norm", "lambda", "step"),
     type = c("coefficients", "aic", "bic"),
     plot.all.steps = FALSE, xlimit = NULL, predictor = FALSE,
     omit.zero = TRUE, breaks = TRUE, mar = NULL, main = NULL,
     eps = .Machine$double.eps, ...)

Arguments

x	a coxpath object
xvar	horizontal axis. xvar=norm plots against the L1 norm of the coefficients (to which L1 norm penalty was applied); xvar=lambda plots against λ; and xvar=step plots against the number of steps taken. Default is norm.
type	type of the plot, or the vertical axis. Default is coefficients.
plot.all.steps	If TRUE, all the steps taken along the path are marked on the plot. If FALSE, which is the default, only the steps at which the active set changed are shown on the plot.
xlimit	When the user wants to visualize a (beginning) sub-part of the plot, xlimit sets an upper limit to the L1 norm or the number of steps, or a lower limit to λ.
predictor	If TRUE and type=coefficients, the predictor step estimates are connected with dotted lines. If FALSE, only the corrector step estimates are connected with solid lines.
omit.zero	If TRUE, the predictors that were never in the active set are omitted.
breaks	If TRUE, vertical lines are drawn at the points where the active set changes and numbered with the degrees of freedom.
mar	margin relative to the current font size
main	title of the plot
eps	an effective zero
...	other options for the plot

Author(s)

Mee Young Park and Trevor Hastie

References

Mee Young Park and Trevor Hastie (2007) L1 regularization path algorithm for generalized linear models. J. R. Statist. Soc. B, 69, 659-677.

See Also

cv.coxpath, coxpath, predict.coxpath

Examples

data(lung.data)
attach(lung.data)
fit <- coxpath(lung.data)
par(mfrow=c(3, 2))
plot(fit)
plot(fit, xvar="lambda")
plot(fit, xvar="step")
plot(fit, xvar="step", xlimit=8)
plot(fit, type="aic")
plot(fit, type="bic")
detach(lung.data)

Example output

Loading required package: survival

glmpath documentation built on May 2, 2019, 4 p.m.