Nonmetric MDS with isotonic regression

Kruskal-style nonmetric MDS using pool-adjacent-violators monotone regression on dissimilarity ranks.

Usage

morie_spatial_voting_nonmetric_mds(
  D,
  n_dims = 2L,
  max_iter = 300L,
  tol = 1e-06
)

Arguments

D

Symmetric dissimilarity matrix.

n_dims

Number of dimensions.

max_iter

Maximum iterations.

tol

Convergence tolerance.

Value

A list with coordinates, stress, iterations, converged.

References

Kruskal, J. B. (1964). "Nonmetric Multidimensional Scaling: A Numerical Method." Psychometrika, 29(2), 115-129.

Examples

D <- as.matrix(dist(matrix(rnorm(40), 10)))
morie_spatial_voting_nonmetric_mds(D)
#> $coordinates
#>                [,1]          [,2]
#>  [1,]  7.585202e+12 -6.559505e+10
#>  [2,] -2.138871e+11  2.899097e+12
#>  [3,]  9.863559e+11 -1.030154e+12
#>  [4,]  2.969107e+12  6.010167e+12
#>  [5,] -4.244429e+12  4.485912e+12
#>  [6,]  9.328051e+11 -5.983424e+12
#>  [7,]  1.189021e+13 -8.063686e+11
#>  [8,] -6.584392e+12 -9.598533e+12
#>  [9,] -5.351187e+12  1.592718e+12
#> [10,] -7.969790e+12  2.496180e+12
#> 
#> $stress
#> [1] 0.04433834
#> 
#> $iterations
#> [1] 300
#> 
#> $converged
#> [1] FALSE
#>