ICGE (version 0.4.2)

dgower: Gower Distance for Mixed Variables

Description

dgower computes and returns the Gower distance matrix for mixed variables.

Usage

dgower(x, type = list())

Value

A dist object with distance information.

Arguments

x

data matrix.

type

it is a list with components cuant, bin, nom. Each component indicates the column position of the quantitative, binary or nominal variables, respectively.

Author

Itziar Irigoien ; Konputazio Zientziak eta Adimen Artifiziala, Euskal Herriko Unibertsitatea (UPV/EHU), Donostia, Spain.

Conchita Arenas ; Departament d'Estadistica, Universitat de Barcelona, Barcelona, Spain.

Details

The distance between two pairs of objects i and j is obtained as \(\sqrt{2(1-s_{ij})}\) where \(s_{ij}\) is the Gower's similarity coefficient for mixed data. This function allows to include missing values (as NA) and therefore calculates distances based on Gower's weighted similarity coefficient.

References

Gower, J.C. (1971). A general coefficient of similarity and some of its properties. Biometrics, 27, 857--871.

See Also

dist, dmahal, dbhatta, dcor, dproc2

Examples

#Generate 10 objects in dimension 6
# Quantitative variables
mu <- sample(1:10, 2, replace=TRUE)
xc <- matrix(rnorm(10*2, mean = mu, sd = 1), ncol=2, byrow=TRUE)

# Binary variables
xb <- cbind(rbinom(10, 1, 0.1), rbinom(10, 1, 0.5), rbinom(10, 1, 0.9))

# Nominal variables
xn <- matrix(sample(1:3, 10, replace=TRUE), ncol=1)

x <- cbind(xc, xb, xn)

# Distances
d <- dgower(x, type=list(cuant=1:2, bin=3:5, nom=6))