nomclust (version 2.1.6)

morlini: Morlini and Zani's (MZ) Measure

Description

A function for calculation of a proximity (dissimilarity) matrix based on the MZ similarity measure.

Usage

morlini(data)

Arguments

data

A data.frame or a matrix with cases in rows and variables in colums.

Value

The function returns a dissimilarity matrix of the size n x n, where n is the number of objects in the original dataset in the argument data.

Details

The MZ measure was originally introduced by Morlini and Zani (2012) under the name S2. The S2 measure was proposed. It is based on a binary-transformed dataset, so the morlini function must first create dummy-coded variables. The measure uses relative frequencies of categories of binary-coded variables, and it assigns higher weights to infrequent categories.

References

Morlini I., Zani S. (2012). A new class of weighted similarity indices using polytomous variables. Journal of Classification, 29(2), p. 199-226.

See Also

eskin, good1, good2, good3, good4, iof, lin, lin1, of, sm, ve, vm.

Examples

# NOT RUN {
# sample data
data(data20)

# dissimilarity matrix calculation
prox.morlini <- morlini(data20)

# }