plot.cv.HDtweedie {HDtweedie}

plot the cross-validation curve produced by cv.HDtweedie

Description

Plots the cross-validation curve, and upper and lower standard deviation curves, as a function of the lambda values used. This function is modified based on the plot.cv function from the glmnet package.

Usage

## S3 method for class 'cv.HDtweedie'
plot(x, sign.lambda, ...)

Arguments

x

fitted cv.HDtweedie object

sign.lambda

either plot against log(lambda) (default) or its negative if sign.lambda=-1.

...

other graphical parameters to plot

Details

A plot is produced.

Author(s)

Wei Qian, Yi Yang and Hui Zou
Maintainer: Wei Qian <[e-mail]>

References

Qian, W., Yang, Y., Yang, Y. and Zou, H. (2016), “Tweedie's Compound Poisson Model With Grouped Elastic Net,” Journal of Computational and Graphical Statistics, 25, 606-625.

Friedman, J., Hastie, T., and Tibshirani, R. (2010), “Regularization paths for generalized linear models via coordinate descent,” Journal of Statistical Software, 33, 1.

See Also

cv.HDtweedie.

Examples

# load HDtweedie library
library(HDtweedie)

# load data set
data(auto)

# 5-fold cross validation using the lasso
cv0 <- cv.HDtweedie(x=auto$x,y=auto$y,p=1.5,nfolds=5,lambda.factor=.0005)

# make a CV plot
plot(cv0)

# define group index
group1 <- c(rep(1,5),rep(2,7),rep(3,4),rep(4:14,each=3),15:21)

# 5-fold cross validation using the grouped lasso 
cv1 <- cv.HDtweedie(x=auto$x,y=auto$y,group=group1,p=1.5,nfolds=5,lambda.factor=.0005)

# make a CV plot
plot(cv1)