summary.fmm

Provide the summary for the model fitting

The penalized and non-penalized Minorize-Maximization (MM) method for frailty models to fit the clustered data, multi-event data and recurrent data. Least absolute shrinkage and selection operator (LASSO), minimax concave penalty (MCP) and smoothly clipped absolute deviation (SCAD) penalized functions are implemented. All the methods are computationally efficient. These general methods are proposed based on the following papers,
Huang, Xu and Zhou (2022) <doi:10.3390/math10040538>,
Huang, Xu and Zhou (2023) <doi:10.1177/09622802221133554>.

Yunpeng Zhou

frailtyMMpen

Efficient Algorithm for High-Dimensional Frailty Model

Xifen Huang

Jinfeng Xu

summary.fmm function

<dl><dt>object</dt>
<dd>Object with class "fmm", generated from <code>frailtyMM</code>.</dd>
<dt>...</dt>
<dd>Ignored</dd></dl>

Arguments

Provide the summary for the model fitting — summary.fmm

<dl>

<dt>object</dt>
<dd>Object with class "fmm", generated from <code>frailtyMM</code>.</dd>


<dt>...</dt>
<dd>Ignored</dd>

</dl>

summary.fmm: Provide the summary for the model fitting

Description

Usage

Arguments

Details