dist.binary {ade4}R Documentation

Computation of Distance Matrices for Binary Data

Description

computes for binary data some distance matrice.

Usage

dist.binary(df, method = NULL, diag = FALSE, upper = FALSE)

Arguments

df a data frame with positive or zero values. Used with as.matrix(1 * (df > 0))
method an integer between 1 and 10 . If NULL the choice is made with a console message. See details
diag a logical value indicating whether the diagonal of the distance matrix should be printed by `print.dist'
upper a logical value indicating whether the upper triangle of the distance matrix should be printed by `print.dist'

Details

All these distances are of type d = sqrt(1 - s) with s a similarity coefficient.

1 = Jaccard index (1901)
S3 coefficient of Gower & Legendre s1 = a / (a+b+c)
2 = Sockal & Michener index (1958)
S4 coefficient of Gower & Legendre s2 = (a+d) / (a+b+c+d)
3 = Sockal & Sneath(1963)
S5 coefficient of Gower & Legendre s3 = a / (a + 2(b + c))
4 = Rogers & Tanimoto (1960)
S6 coefficient of Gower & Legendre s4 = (a + d) / (a + 2(b + c) +d)
5 = Czekanowski (1913) or Sorensen (1948)
S7 coefficient of Gower & Legendre s5 = 2a / (2a + b + c)
6 = S9 index of Gower & Legendre (1986)
s6 = (a - (b + c) + d) / (a + b + c + d)
7 = Ochiai (1957)
S12 coefficient of Gower & Legendre s7 = a / sqrt((a + b)(a + c))
8 = Sockal & Sneath (1963)
S13 coefficient of Gower & Legendre s8 = ad / sqrt((a + b)(a + c)(d + b)(d + c))
9 = Phi of Pearson
S14 coefficient of Gower & Legendre s9 = (ad - bc) / sqrt((a + b)(a + c)(d + b)(d + c))
10 = S2 coefficient of Gower & Legendre
s10 = a / (a + b + c + d)

Value

returns a distance matrix of class dist between the rows of the data frame

References

Gower, J.C. and Legendre, P. (1986) Metric and Euclidean properties of dissimilarity coefficients. Journal of Classification, 3, 5–48.

Examples

data(aviurba)
for (i in 1:10) {
        d <- dist.binary(aviurba$fau, method = i)
        cat(attr(d, "method"), is.euclid(d), "\n")}

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