The Minkowski metric is a generalized form of Euclidean (p=2) and Manhattan (p=1) distance.
minkowski(x, y, p = 1)Numeric vectors.
Exponent parameter, a single number greater than zero.
The Minkowski distance between x and y.
For vectors x and y, the Minkowski distance is defined as
$$d(x, y) = \left( \sum_i |x_i - y_i|^p \right)^{1/p}.$$ Relation to
other definitions:
Equivalent to R's built-in dist() function with
method = "minkowski".
Equivalent to the minkowski() function in
scipy.spatial.distance.
Equivalent to \(D_6\) in Legendre & Legendre.
The default value of p = 1 makes this distance equal to the Manhattan
distance.