Skip to contents

Biweight Midcorrelation

Source: R/biweight_midcorrelation.R
biweight_midcorrelation.Rd

This function computes the biweight midcorrelation between two numeric vectors. The biweight midcorrelation is a robust measure of correlation that is less sensitive to outliers than the traditional Pearson's correlation coefficient.

Usage

biweight_midcorrelation(x, y)

Arguments

x

A numeric vector.

y

A numeric vector of the same length as x.

Value

The biweight midcorrelation between x and y.

Details

The biweight midcorrelation is calculated using the biweight midvariances and biweight midcovariance, as described by Wilcox (1994). It is bounded between -1 and 1.

References

  • Wilcox, R. R. (1994). The Biweight Midcorrelation: A Robust Correlation Technique for Two Samples. Journal of Statistical Computation and Simulation, 48(2):103-110.

Author

Christian L. Goueguel

Examples

data(forageLIBS)
ok <- !is.na(forageLIBS$Fe)
c(pearson = stats::cor(forageLIBS$Fe[ok], forageLIBS$Mn[ok]),
  biweight = biweight_midcorrelation(forageLIBS$Fe[ok], forageLIBS$Mn[ok]))
#>   pearson  biweight 
#> 0.2186135 0.2112649