smacof (version 2.1-7)

uniscale: 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)

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)

Arguments

delta

Either a symmetric dissimilarity matrix or an object of class "dist"

weightmat

Optional matrix with dissimilarity weights

verbose

Permutation printout

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)