Plot solution paths from a "HDtweedie" object

Description

Produces a coefficient profile plot of the coefficient paths for a fitted HDtweedie object.

Usage

## S3 method for class 'HDtweedie'
plot(x, group = FALSE, log.l = TRUE, ...)

Arguments

Details

A coefficient profile 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.

Examples

# load HDtweedie library
library(HDtweedie)

# load data set
data(auto)

# fit the lasso
m0 <- HDtweedie(x=auto$x,y=auto$y,p=1.5)

# make plot
plot(m0) # plots the coefficients against the log-lambda sequence

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

# fit group lasso
m1 <- HDtweedie(x=auto$x,y=auto$y,group=group1,p=1.5)

# make plots
par(mfrow=c(1,3))
plot(m1) # plots the coefficients against the log-lambda sequence 
plot(m1,group=TRUE) # plots group norm against the log-lambda sequence 
plot(m1,log.l=FALSE) # plots against the lambda sequence

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.HDtweedie.Rd_%03d_medium.png", width=480, height=480)
> ### Name: plot.HDtweedie
> ### Title: Plot solution paths from a "HDtweedie" object
> ### Aliases: plot.HDtweedie
> ### Keywords: models regression
> 
> ### ** Examples
> 
> # load HDtweedie library
> library(HDtweedie)
> 
> # load data set
> data(auto)
> 
> # fit the lasso
> m0 <- HDtweedie(x=auto$x,y=auto$y,p=1.5)
> 
> # make plot
> plot(m0) # plots the coefficients against the log-lambda sequence
> 
> # define group index
> group1 <- c(rep(1,5),rep(2,7),rep(3,4),rep(4:14,each=3),15:21)
> 
> # fit group lasso
> m1 <- HDtweedie(x=auto$x,y=auto$y,group=group1,p=1.5)
> 
> # make plots
> par(mfrow=c(1,3))
> plot(m1) # plots the coefficients against the log-lambda sequence 
> plot(m1,group=TRUE) # plots group norm against the log-lambda sequence 
> plot(m1,log.l=FALSE) # plots against the lambda sequence
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>