cv.biglasso object,
along with standard error bars.
"plot"(x, log.l = TRUE, type = c("cve", "rsq", "scale", "snr", "pred", "all"), selected = TRUE, vertical.line = TRUE, col = "red", ...)"cv.biglasso" object.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.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.TRUE (the default), draws a vertical
line at the value where cross-validaton error is minimized.plotlambda. For
rsq and snr, these confidence intervals are quite crude,
especially near.biglasso, cv.biglasso## See examples in "cv.biglasso"
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