Simple implementation where all dissimilarity permutations are subject to a 1D MDS fit and the one which leads to a minimal stress values is returned.
uniscale(delta, weightmat = NULL, verbose = TRUE)
Observed dissimilarities, not normalized
Configuration distances
Vector with fitted configurations
Stress-1 value
Weight matrix
Number of objects
Total number of permutations (factorial)
Number of accepted permutations (monotonicity check)
Either a symmetric dissimilarity matrix or an object of class "dist"
"dist"
Optional matrix with dissimilarity weights
Permutation printout
Mair P., De Leeuw J. (2015). Unidimensional scaling. In Wiley StatsRef: Statistics Reference Online, Wiley, New York.
mds
## unidimensional scaling of Plato's 7 works PlatoD <- dist(t(Plato7)) fit.uni <- uniscale(PlatoD) fit.uni plot(fit.uni)
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