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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.

Versions across snapshots

VersionRepositoryFileSize
0.1.4 rolling linux/jammy R-4.5 unusualprofile_0.1.4.tar.gz 353.5 KiB
0.1.4 rolling linux/noble R-4.5 unusualprofile_0.1.4.tar.gz 353.3 KiB
0.1.4 rolling source/ R- unusualprofile_0.1.4.tar.gz 475.2 KiB
0.1.4 latest linux/jammy R-4.5 unusualprofile_0.1.4.tar.gz 353.5 KiB
0.1.4 latest linux/noble R-4.5 unusualprofile_0.1.4.tar.gz 353.3 KiB
0.1.4 latest source/ R- unusualprofile_0.1.4.tar.gz 475.2 KiB
0.1.4 2026-04-26 source/ R- unusualprofile_0.1.4.tar.gz 475.2 KiB
0.1.4 2026-04-23 source/ R- unusualprofile_0.1.4.tar.gz 475.2 KiB
0.1.4 2026-04-09 windows/windows R-4.5 unusualprofile_0.1.4.zip 359.0 KiB
0.1.4 2025-04-20 source/ R- unusualprofile_0.1.4.tar.gz 475.2 KiB

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