conv2glmreg

convert glm object to class glmreg, which then can be used for other purposes

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

conv2glmreg function

<dl> <dt>object</dt>
<dd>an object of class glm</dd> <dt>family</dt>
<dd>one of families in glm class</dd></dl>

Arguments

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

Author

convert glm object to class glmreg — conv2glmreg

<dl>

 <dt>object</dt>
<dd>an object of class glm</dd>

 <dt>family</dt>
<dd>one of families in glm class</dd>

</dl>

conv2glmreg: convert glm object to class glmreg

Description

Usage

Value

Arguments

Author