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unusualprofile: Calculates Conditional Mahalanobis Distances
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.
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Package details |
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| Author | W. Joel Schneider [aut, cre] (<https://orcid.org/0000-0002-8393-5316>), Feng Ji [aut] |
| Maintainer | W. Joel Schneider <w.joel.schneider@gmail.com> |
| License | GPL (>= 3) |
| Version | 0.1.4 |
| URL | https://github.com/wjschne/unusualprofile https://wjschne.github.io/unusualprofile/ |
| Package repository | View on CRAN |
| Installation |
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