AIC.fcrr

Similar functional utility to <code>coef</code> methods.

In competing risks regression, the proportional subdistribution hazards (PSH) model is popular for its direct assessment of covariate effects on the cumulative incidence function. This package allows for both penalized and unpenalized PSH regression in linear time using a novel forward-backward scan. Penalties include Ridge, Lease Absolute Shrinkage and Selection Operator (LASSO), Smoothly Clipped Absolute Deviation (SCAD), Minimax Concave Plus (MCP), and elastic net <doi: 10.32614/RJ-2021-010>.

Eric Kawaguchi

fastcmprsk

Fine-Gray Regression via Forward-Backward Scan

AIC.fcrr function

<dl><dt>object</dt>
<dd><code>fcrr</code> object</dd>
<dt>...</dt>
<dd>Additional arguments. Not implemented.</dd>
<dt>k</dt>
<dd>Numeric, the penalty per parameter to be used; the default k = 2 is the classical AIC.</dd></dl>

Arguments

Akaike's An Information Criterion — AIC.fcrr

<dl>

<dt>object</dt>
<dd><code>fcrr</code> object</dd>


<dt>...</dt>
<dd>Additional arguments. Not implemented.</dd>


<dt>k</dt>
<dd>Numeric, the penalty per parameter to be used; the default k = 2 is the classical AIC.</dd>

</dl>

AIC.fcrr: Akaike's An Information Criterion

Description

Usage

Value

Arguments