CategoricalProximities: Proximities among individuals using nominal variables.

In MultBiplotR: Multivariate Analysis Using Biplots in R

Proximities among individuals using nominal variables.

Description

Proximities among individuals using nominal variables.

Usage

CategoricalProximities(Data, SUP = NULL, coefficient = "GOW", transformation = 3, ...)

Arguments

Data	A data frame containing categorical (nominal) variables
SUP	Supplementary data (Used to project supplementary individuals onto the PCoA configuration, for example)
coefficient	Similarity coefficient to use (see details)
transformation	Transformation of the similarity into a distance
...	Extra parameters

Details

The function calculates similarities and dissimilarities among a set ob ogjects characterized by a set of nominal variables. The function uses similarities and converts into dissimilarities using a variety of transformations controled by the user.

Value

A list of Values

Author(s)

Jose Luis Vicente Villardon

References

dos Santos, T. R., & Zarate, L. E. (2015). Categorical data clustering: What similarity measure to recommend?. Expert Systems with Applications, 42(3), 1247-1260.

Boriah, S., Chandola, V., & Kumar, V. (2008). Similarity measures for categorical data: A comparative evaluation. red, 30(2), 3.

Examples

data(Doctors)
Dis=CategoricalProximities(Doctors, SUP=NULL, coefficient="GOW" , transformation=3)
pco=PrincipalCoordinates(Dis)
plot(pco, RowCex=0.7, RowColors=as.integer(Doctors[[1]]), RowLabels=as.character(Doctors[[1]]))

MultBiplotR documentation built on Nov. 21, 2023, 5:08 p.m.