Generic function for computing standard errors of non-zero regularized estimators

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`x` |
a fitted model object. |

`which` |
which penalty parameter(s)? |

`log` |
if TRUE, the computed standard error is for log(theta) for negative binomial regression, otherwise, for theta. |

`...` |
arguments passed to methods. |

A vector containing standard errors of non-zero regularized estimators.

Zhu Wang <zwang@connecticutchildrens.org>

Zhu Wang, Shuangge Ma and Ching-Yun Wang (2015) *Variable selection for zero-inflated and overdispersed data with application to health care demand in Germany*, *Biometrical Journal*. 57(5):867-84.

`zipath`

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