Plot the cross-validation curve from a cv.biglasso() object, along with standard error bars.

# S3 method for cv.biglasso
plot(
  x,
  log.l = TRUE,
  type = c("cve", "rsq", "scale", "snr", "pred", "all"),
  selected = TRUE,
  vertical.line = TRUE,
  col = "red",
  ...
)

Arguments

x

A "cv.biglasso" object.

log.l

Should horizontal axis be on the log scale? Default is TRUE.

type

What to plot on the vertical axis. cve plots the cross-validation error (deviance); rsq plots an estimate of the fraction of the deviance explained by the model (R-squared); snr plots an estimate of the signal-to-noise ratio; scale plots, for family="gaussian", an estimate of the scale parameter (standard deviation); pred plots, for family="binomial", the estimated prediction error; all produces all of the above.

selected

If TRUE (the default), places an axis on top of the plot denoting the number of variables in the model (i.e., that have a nonzero regression coefficient) at that value of lambda.

vertical.line

If TRUE (the default), draws a vertical line at the value where cross-validaton error is minimized.

col

Controls the color of the dots (CV estimates).

...

Other graphical parameters to plot

Details

Error bars representing approximate 68\ along with the estimates at value of lambda. For rsq and snr, these confidence intervals are quite crude, especially near.

Author

Yaohui Zeng and Patrick Breheny

Examples

## See examples in "cv.biglasso"