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

Details

A plot is produced.

Author(s)

Wei Qian, Yi Yang and Hui Zou
Maintainer: Wei Qian <weiqian@stat.umn.edu>

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/

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)

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(HDtweedie)
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/HDtweedie/plot.cv.HDtweedie.Rd_%03d_medium.png", width=480, height=480)
> ### Name: plot.cv.HDtweedie
> ### Title: plot the cross-validation curve produced by cv.HDtweedie
> ### Aliases: plot.cv.HDtweedie
> ### Keywords: models regression
> 
> ### ** 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)
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>