Covariance and correlation
Contents
Covariance and correlation¶
The Fortran Standard library stdlib provides several procedures to compute covariances and Pearson correlations of the elements of an array along a dimension.
This guide shows examples to compute covariances and Pearson correlations from an array. All the functions described in this tutorial can be accessed via the stdlib_stats module.
Covariance¶
The Fortran Standard library stdlib provides the function cov for computing the
covariance of the elements of an array along a dimension:
program cov
use stdlib_stats, only: cov
implicit none
real :: y(1:2, 1:3) = reshape([1., 2., 3., 4., 5., 6.], [2, 3])
print*, cov(y, 1)
print*, cov(y, 2)
end program cov
Note
The default scaling of the covariance is n-1. However, it can be scaled with
n by setting the optional argument corrected to .false..
Pearson correlation¶
The Fortran Standard library stdlib provides the function corr for computing the
Pearson correlation of the elements of an array along a dimension:
program corr
use stdlib_stats, only: corr
implicit none
real :: y(1:2, 1:3) = reshape([1., 2., 3., 4., 5., 6.], [2, 3])
print*, corr(y, 1)
print*, corr(y, 2)
end program corr
Note
Like other procedures in the stdlib_stats module, the functions for computing covariances and correlations of array elements support an optional mask to ignore some elements of the array.