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unusualprofile  

Calculates Conditional Mahalanobis Distances
View on CRAN: Click here


Download and install unusualprofile package within the R console
Install from CRAN:
install.packages("unusualprofile")

Install from Github:
library("remotes")
install_github("cran/unusualprofile")

Install by package version:
library("remotes")
install_version("unusualprofile", "0.1.4")



Attach the package and use:
library("unusualprofile")
Maintained by
W. Joel Schneider
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-05-13
Latest Update: 2024-02-14
Description:
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.
How to cite:
W. Joel Schneider (2021). unusualprofile: Calculates Conditional Mahalanobis Distances. R package version 0.1.4, https://cran.r-project.org/web/packages/unusualprofile
Previous versions and publish date:
0.1.0 (2021-05-13 12:10), 0.1.1 (2022-11-30 01:40), 0.1.2 (2022-12-14 00:00)
Other packages that cited unusualprofile R package
View unusualprofile citation profile
Other R packages that unusualprofile depends, imports, suggests or enhances
Functions, R codes and Examples using the unusualprofile R package
Some associated functions: R_example . cond_maha . d_example . is_singular . p2label . plot.cond_maha . plot.maha . proportion2percentile . proportion_round . unusualprofile . 
Some associated R codes: data.R . main.R . unusualprofile-package.R .  Full unusualprofile package functions and examples
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