uniscale: Unidimensional Scaling

In smacof: Multidimensional Scaling

Unidimensional Scaling

Description

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.

Usage

uniscale(delta, weightmat = NULL, verbose = TRUE)

Arguments

delta	Either a symmetric dissimilarity matrix or an object of class "dist"
weightmat	Optional matrix with dissimilarity weights
verbose	Permutation printout

Value

delta	Observed dissimilarities, not normalized
confdist	Configuration distances
conf	Vector with fitted configurations
stress	Stress-1 value
weightmat	Weight matrix
nobj	Number of objects
npermtot	Total number of permutations (factorial)
npermscale	Number of accepted permutations (monotonicity check)

References

Mair P., De Leeuw J. (2015). Unidimensional scaling. In Wiley StatsRef: Statistics Reference Online, Wiley, New York.

See Also

mds

Examples

## unidimensional scaling of Plato's 7 works
PlatoD <- dist(t(Plato7))
fit.uni <- uniscale(PlatoD)
fit.uni
plot(fit.uni)

smacof documentation built on May 6, 2022, 9:05 a.m.