Add Mahalanobis distance
add_mahalanobis.RdAdd a mahalanobis distance to the end of a data frame.
Usage
add_mahalanobis(
df,
...,
.inverted = FALSE,
.name = "md",
.p = "p_value",
tolerance = .Machine$double.eps
)Arguments
- df
A data.frame
- ...
Columns to select
- .inverted
Logical. If TRUE, covariance matrix (p x p) of the distribution is supposed to contain the inverse of the covariance matrix.
- .name
The name of the new column for the distance value
- .p
The name for the new column for the p-value calculation
- tolerance
`tol` in [base::solve()]
Examples
df <- head(iris)
add_mahalanobis(df, Sepal.Length, Sepal.Width, Petal.Length, Petal.Width)
#> Sepal.Length Sepal.Width Petal.Length Petal.Width Species md p_value
#> 1 5.1 3.5 1.4 0.2 setosa 1.901692 0.7538342
#> 2 4.9 3.0 1.4 0.2 setosa 3.634221 0.4577653
#> 3 4.7 3.2 1.3 0.2 setosa 4.064753 0.3973134
#> 4 4.6 3.1 1.5 0.2 setosa 4.064753 0.3973134
#> 5 5.0 3.6 1.4 0.2 setosa 2.167915 0.7049075
#> 6 5.4 3.9 1.7 0.4 setosa 4.166667 0.3839196
df[1, ] <- NA_real_
add_mahalanobis(df, Sepal.Length, Sepal.Width, Petal.Length, Petal.Width)
#> Sepal.Length Sepal.Width Petal.Length Petal.Width Species md p_value
#> 1 NA NA NA NA <NA> NA NA
#> 2 4.9 3.0 1.4 0.2 setosa 3.2 0.5249309
#> 3 4.7 3.2 1.3 0.2 setosa 3.2 0.5249309
#> 4 4.6 3.1 1.5 0.2 setosa 3.2 0.5249309
#> 5 5.0 3.6 1.4 0.2 setosa 3.2 0.5249309
#> 6 5.4 3.9 1.7 0.4 setosa 3.2 0.5249309