# print.HDtweedie: print a HDtweedie object In HDtweedie: The Lasso for the Tweedie's Compound Poisson Model Using an IRLS-BMD Algorithm

## Description

Print the nonzero group counts at each lambda along the HDtweedie path.

## Usage

 ```1 2``` ```## S3 method for class 'HDtweedie' print(x, digits = max(3, getOption("digits") - 3), ...) ```

## Arguments

 `x` fitted `HDtweedie` object `digits` significant digits in printout `...` additional print arguments

## Details

Print the information about the nonzero group counts at each lambda step in the `HDtweedie` object. The result is a two-column matrix with columns `Df` and `Lambda`. The `Df` column is the number of the groups that have nonzero within-group coefficients, the `Lambda` column is the the corresponding lambda.

## Value

a two-column matrix, the first columns is the number of nonzero group counts and the second column is `Lambda`.

## 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.

## Examples

 ``` 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 auto data set data(auto) # fit the lasso m0 <- HDtweedie(x=auto\$x,y=auto\$y,p=1.5) # print out results print(m0) # define group index group1 <- c(rep(1,5),rep(2,7),rep(3,4),rep(4:14,each=3),15:21) # fit the grouped lasso m1 <- HDtweedie(x=auto\$x,y=auto\$y,group=group1,p=1.5) # print out results print(m1) ```

HDtweedie documentation built on May 29, 2017, 6:32 p.m.