Calculates a Mahalanobis distance for every row of a set of outcome variables (Mahalanobis, 1936 <doi:10.1007/s13171-019-00164-5>). The conditional Mahalanobis distance is calculated using a conditional covariance matrix (i.e., a covariance matrix of the outcome variables after controlling for a set of predictors). Plotting the output of the cond_maha() function can help identify which elements of a profile are unusual after controlling for the predictors.

Calculates Conditional Mahalanobis Distances

package-ubuntu-20.04-r-4.0.5#cran#unusualprofile-0.1.0

<p>Rounds proportions to significant digits both near 0 and 1
</p>

<table summary="R argblock">
<tr valign="top">
<td><code>p</code></td>
<td>
<p>probability</p>
</td>
</tr>
<tr valign="top">
<td><code>digits</code></td>
<td>
<p>rounding digits</p>
</td>
</tr>
</table>

package-ubuntu-20.04-r-4.0.5#cran#unusualprofile-0.1.0#docs#proportion_round

proportion_round

Description

Usage

Arguments

Value

Examples

unusualprofile

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`p`	probability
`digits`	rounding digits