model_mcp

Function to model mcp selection process on a given dataframe

internal

A stable approach to variable selection through stability selection and the use of a permutation-based objective stability threshold. Lima et al (2021) <doi:10.1038/s41598-020-79317-8>, Meinshausen and Buhlmann (2010) <doi:10.1111/j.1467-9868.2010.00740.x>.

Robert Hyde

stabiliser

Stabilising Variable Selection

Martin Green

Eliana Lima

model_mcp function

<dl><dt>data</dt>
<dd>a dataframe containing an outcome variable to be permuted (usually coming from nested bootstrap data)</dd>
<dt>outcome</dt>
<dd>the outcome as a string (i.e. "y")</dd>
<dt>type</dt>
<dd>model type, either "linear" or "logistic"</dd></dl>

Arguments

model_mcp — model_mcp

<dl>

<dt>data</dt>
<dd>a dataframe containing an outcome variable to be permuted (usually coming from nested bootstrap data)</dd>


<dt>outcome</dt>
<dd>the outcome as a string (i.e. "y")</dd>


<dt>type</dt>
<dd>model type, either "linear" or "logistic"</dd>

</dl>

model_mcp: model_mcp

Description

Arguments