TuneCStatisticLogit

Computes the difference in absolute value between the desired and expected C
statistic given the vector of true probabilities.

internal

This R package can be used to generate artificial data conditionally on pre-specified (simulated or user-defined) relationships between the variables and/or observations. Each observation is drawn from a multivariate Normal distribution where the mean vector and covariance matrix reflect the desired relationships. Outputs can be used to evaluate the performances of variable selection, graphical modelling, or clustering approaches by comparing the true and estimated structures (B Bodinier et al (2021) <arXiv:2106.02521>).

Barbara Bodinier

fake

Flexible Data Simulation Using the Multivariate Normal
Distribution

TuneCStatisticLogit function

<dl><dt>scaling_factor</dt>
<dd>constant by which log-odds (or beta coefficients when
there is no intercept) are multiplied.</dd>
<dt>crude_log_odds</dt>
<dd>vector of log-odds to be multiplied by the
<code>scaling_factor</code>.</dd>
<dt>auc</dt>
<dd>desired concordance statistic (area under the ROC curve). If
<code>auc=NULL</code>, the obtained concordance statistic is returned.</dd></dl>

Arguments

Tuning function (logistic regression) — TuneCStatisticLogit

<dl>

<dt>scaling_factor</dt>
<dd>constant by which log-odds (or beta coefficients when
there is no intercept) are multiplied.</dd>


<dt>crude_log_odds</dt>
<dd>vector of log-odds to be multiplied by the
<code>scaling_factor</code>.</dd>


<dt>auc</dt>
<dd>desired concordance statistic (area under the ROC curve). If
<code>auc=NULL</code>, the obtained concordance statistic is returned.</dd>

</dl>

TuneCStatisticLogit: Tuning function (logistic regression)

Description

Usage

Value

Arguments