geo_median | R Documentation |
Compute the “geometric median” of points in n-dimensional space, that is the point with the least sum of (Euclidean) distances to all these points.
geo_median(P, tol = 1e-07, maxiter = 200)
P |
matrix of points, |
tol |
relative tolerance. |
maxiter |
maximum number of iterations. |
The task is solved applying an iterative process, known as Weiszfeld's algorithm. The solution is unique whenever the points are not collinear.
If the dimension is 1 (one column), the median will be returned.
Returns a list with components p
the coordinates of the solution
point, d
the sum of distances to all the sample points, reltol
the relative tolerance of the iterative process, and niter
the
number of iterations.
This is also known as the “1-median problem” and can be generalized to the
“k-median problem” for k cluster centers;
see kcca
in the ‘flexclust’ package.
See Wikipedia's entry on “Geometric median”.
L1linreg
# Generate 100 points on the unit sphere in the 10-dim. space
set.seed(1001)
P <- rands(n=100, N=9)
( sol <- geo_median(P) )
# $p
# [1] -0.009481361 -0.007643410 -0.001252910 0.006437703 -0.019982885 -0.045337987
# [7] 0.036249563 0.003232175 0.035040592 0.046713023
# $d
# [1] 99.6638
# $reltol
# [1] 3.069063e-08
# $niter
# [1] 10
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.