unusualprofile

unusualprofile-package

<img src="figures/logo.png?package=unusualprofile&version=0.1.4" style="float: right" alt="logo" width="120">
Calculates a Mahalanobis distance for every row of a set of outcome variables (Mahalanobis, 1936 tools:::Rd_expr_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.

internal

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.

W. Joel Schneider

Calculates Conditional Mahalanobis Distances

Feng Ji

unusualprofile-package function

Maintainer: W. Joel Schneider <a href="/link/w.joel.schneider%40gmail.com?package=unusualprofile&version=0.1.4" data-mini-rdoc="unusualprofile::w.joel.schneider@gmail.com">w.joel.schneider@gmail.com</a> (<a href="https://orcid.org/0000-0002-8393-5316">ORCID</a>)
Authors:<ul>
<li>Feng Ji <a href="/link/fengji%40berkeley.edu?package=unusualprofile&version=0.1.4" data-mini-rdoc="unusualprofile::fengji@berkeley.edu">fengji@berkeley.edu</a></li>
</ul>

Author

<img src='figures/logo.png' style='float: right' alt='logo' width='120' />
Calculates a Mahalanobis distance for every row of a set of outcome variables (Mahalanobis, 1936 tools:::Rd_expr_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.

unusualprofile: Calculates Conditional Mahalanobis Distances — unusualprofile-package

Maintainer: W. Joel Schneider <a href='mailto:w.joel.schneider@gmail.com'>w.joel.schneider@gmail.com</a> (<a href='https://orcid.org/0000-0002-8393-5316'>ORCID</a>)
Authors:<ul>
<li>Feng Ji <a href='mailto:fengji@berkeley.edu'>fengji@berkeley.edu</a></li>
</ul>

unusualprofile-package: unusualprofile: Calculates Conditional Mahalanobis Distances

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