minkowski: Minkowski distance

In SBCK: Statistical Bias Correction Kit

Minkowski distance

Description

Compute Minkowski distance between two dataset or SparseHist X and Y. If p = 2, it is the Euclidean distance, for p = 1, it is the manhattan distance, if p = Inf, chebyshev distance is called.

Usage

minkowski(X, Y, p = 2)

Arguments

X	[matrix or SparseHist] If matrix, dim = ( nrow = n_samples, ncol = n_features)
Y	[matrix or SparseHist] If matrix, dim = ( nrow = n_samples, ncol = n_features)
p	[float] power of distance

Value

[float] value of distance

Examples

X = base::cbind( stats::rnorm(2000) , stats::rnorm(2000)  )
Y = base::cbind( stats::rnorm(2000,mean=2)  , stats::rnorm(2000) )
bw = base::c(0.1,0.1)
muX = SBCK::SparseHist( X , bw )
muY = SBCK::SparseHist( Y , bw )

## The four are equals
d = SBCK::minkowski(  X ,   Y , p = 3 )
d = SBCK::minkowski(muX ,   Y , p = 3 )
d = SBCK::minkowski(  X , muY , p = 3 )
d = SBCK::minkowski(muX , muY , p = 3 )

SBCK documentation built on Sept. 11, 2023, 5:10 p.m.