plot.cv.HDtweedie: plot the cross-validation curve produced by cv.HDtweedie In emeryyi/hdtweedie: The Lasso for the Tweedie's Compound Poisson Model Using an IRLS-BMD Algorithm

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

 ```1 2``` ```## 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 <[email protected]>

References

Qian, W., Yang, Y., Yang, Y. and Zou, H. (2013), “Tweedie's Compound Poisson Model With Grouped Elastic Net,” submitted to Journal of Computational and Graphical Statistics.

Friedman, J., Hastie, T., and Tibshirani, R. (2010), “Regularization paths for generalized linear models via coordinate descent,” Journal of Statistical Software, 33, 1.
http://www.jstatsoft.org/v33/i01/

`cv.HDtweedie`.
 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20``` ```# 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) ```