Description Usage Arguments Details Value Author(s) References See Also

Object of the `penalty`

class to handle the lasso penalty (Tibshirani, 1996).

1 |

`lambda` |
regularization parameter. This must be a nonnegative real number. |

`...` |
further arguments |

The ‘classic’ penalty that incorporates variables selection. As introduced in Tibshirani (1996) the lasso penalty is defined as

*
P_λ^r (\boldsymbol{β}) = λ ∑_{i=1}^p |β_j|.
*

An object of the class `penalty`

. This is a list with elements

`penalty` |
character: the penalty name. |

`lambda` |
double: the (nonnegative) regularization parameter. |

`getpenmat` |
function: computes the diagonal penalty matrix. |

Jan Ulbricht

Tibshirani, R. (1996) Regression shrinkage and selection via the lasso. *Journal of the Royal Statistical Society B* **58**, 267–288.

lqa documentation built on May 30, 2017, 3:41 a.m.

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.