R/plot-cv-ncvreg.R
plot.cv.ncvreg.RdPlots the cross-validation curve from a cv.ncvreg or
cv.ncvsurv object, along with standard error bars.
A cv.ncvreg or cv.ncvsurv object.
Should horizontal axis be on the log scale? Default is TRUE.
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.
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.
If TRUE (the default), draws a vertical line at
the value where cross-validaton error is minimized.
Controls the color of the dots (CV estimates).
Other graphical parameters to plot
Error bars representing approximate 68\
along with the estimates at value of lambda. For rsq and
snr applied to models other than linear regression, the Cox-Snell
R-squared is used.
Breheny P and Huang J. (2011) Coordinate descentalgorithms for nonconvex penalized regression, with applications to biological feature selection. Annals of Applied Statistics, 5: 232-253. c("\Sexpr[results=rd]tools:::Rd_expr_doi(\"#1\")", "10.1214/10-AOAS388")doi:10.1214/10-AOAS388
# Linear regression --------------------------------------------------
data(Prostate)
cvfit <- cv.ncvreg(Prostate$X, Prostate$y)
plot(cvfit)
op <- par(mfrow=c(2,2))
plot(cvfit, type="all")
par(op)
# Logistic regression ------------------------------------------------
data(Heart)
cvfit <- cv.ncvreg(Heart$X, Heart$y, family="binomial")
plot(cvfit)
op <- par(mfrow=c(2,2))
plot(cvfit, type="all")
par(op)
# Cox regression -----------------------------------------------------
data(Lung)
cvfit <- cv.ncvsurv(Lung$X, Lung$y)
op <- par(mfrow=c(1,2))
plot(cvfit)
plot(cvfit, type="rsq")
par(op)