AIC.glmreg

AIC.zipath

BIC.glmreg

BIC.zipath

Methods for models fitted by coordinate descent algorithms.

methods

Algorithms compute robust estimators for loss functions in the concave convex (CC) family by the iteratively reweighted convex optimization (IRCO), an extension of the iteratively reweighted least squares (IRLS). The IRCO reduces the weight of the observation that leads to a large loss; it also provides weights to help identify outliers. Applications include robust (penalized) generalized linear models and robust support vector machines. The package also contains penalized Poisson, negative binomial, zero-inflated Poisson, zero-inflated negative binomial regression models and robust models with non-convex loss functions. Wang et al. (2014) <doi:10.1002/sim.6314>,
Wang et al. (2015) <doi:10.1002/bimj.201400143>,
Wang et al. (2016) <doi:10.1177/0962280214530608>,
Wang (2021) <doi:10.1007/s11749-021-00770-2>,
Wang (2024) <doi:10.1111/anzs.12409>.

Zhu Wang

mpath

Regularized Linear Models

methods function

<dl> <dt>object</dt>
<dd>objects of class <code>glmreg</code> or <code>zipath</code>.</dd> <dt>...</dt>
<dd>additional arguments passed to calls.</dd> <dt>k</dt>
<dd>numeric, the penalty per parameter to be used; the default
 <code>k = 2</code> is the classical AIC. <code>k</code> has been hard coded in the function and there is no impact to the value of <code>AIC</code> if <code>k</code> is changed</dd></dl>

Arguments

Zhu Wang &lt;zwang145@uthsc.edu&gt;

Author

Methods for mpath Objects — methods

<dl>

 <dt>object</dt>
<dd>objects of class <code>glmreg</code> or <code>zipath</code>.</dd>

 <dt>...</dt>
<dd>additional arguments passed to calls.</dd>

 <dt>k</dt>
<dd>numeric, the penalty per parameter to be used; the default
 <code>k = 2</code> is the classical AIC. <code>k</code> has been hard coded in the function and there is no impact to the value of <code>AIC</code> if <code>k</code> is changed</dd>

</dl>

methods: Methods for mpath Objects

Description

Usage

Arguments

Author

References