print {grpnet}

S3 'print' Methods for grpnet

Description

Prints some basic information about the coefficients (for coef.grpnet objects), observed cross-validation error (for cv.grpnet objects), or the computed regularization path (for grpnet objects).

Usage

## S3 method for class 'coef.grpnet'
print(x, ...)

## S3 method for class 'cv.grpnet'
print(x, digits = max(3, getOption("digits") - 3), ...)

## S3 method for class 'grpnet'
print(x, ...)

Arguments

x

an object of class coef.grpnet, cv.grpnet, or grpnet

digits

the number of digits to print (must be a positive integer)

...

additional arguments for print (currently ignored)

Details

For coef.grpnet objects, prints the non-zero coefficients and uses "." for coefficients shrunk to zero.

For cv.grpnet objects, prints the function call, the cross-validation type.measure, and a two-row table with information about the min and 1se solutions.

For grpnet objects, prints a data frame with columns
* nGrp: number of non-zero groups for each lambda
* Df: effective degrees of freedom for each lambda
* %Dev: percentage of null deviance explained for each lambda
* Lambda: the values of lambda

Value

No return value (produces a printout)

Note

Some syntax and functionality were modeled after the print functions in the glmnet package (Friedman, Hastie, & Tibshirani, 2010).

Author(s)

Nathaniel E. Helwig <[e-mail]>

References

Friedman, J., Hastie, T., & Tibshirani, R. (2010). Regularization paths for generalized linear models via coordinate descent. Journal of Statistical Software, 33(1), 1-22. doi:10.18637/jss.v033.i01

See Also

coef.grpnet for extracting coefficients

cv.grpnet for k-fold cross-validation of lambda

grpnet for fitting grpnet regularization paths

Examples

# see 'coef.grpnet' for coefficient printing examples
?coef.grpnet

# see 'cv.grpnet' for cross-validation error printing examples
?cv.grpnet

# see 'grpnet' for regularization path printing examples
?grpnet