dist.prop {ade4}

Computation of Distance Matrices of Percentage Data

Description

computes for percentage data some distance matrices.

Usage

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

Arguments

df

a data frame containing only positive or null values, used as row percentages

method

an integer between 1 and 5. 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

1 = Manly

d_1=\frac{1}{2} \sum_{i=1}^{K}{|{p_i-q_i}|}

2 = Overlap index Manly

d_2=1-\frac{\sum_{i=1}^{K}{p_i q_i}}{\sqrt{\sum_{i=1}^{K}{p_i^2}}{\sqrt{\sum_{i=1}^{K}{q_i^2}}}}

3 = Rogers 1972 (one locus)

d_3=\sqrt{\frac{1}{2} \sum_{i=1}^{K}{(p_i-q_i)^2}}

4 = Nei 1972 (one locus)

d_4=\ln{\frac{\sum_{i=1}^{K}{p_i q_i}}{\sqrt{\sum_{i=1}^{K}{p_i^2}}{\sqrt{\sum_{i=1}^{K}{q_i^2}}}}}

5 = Edwards 1971 (one locus)

d_5=\sqrt{1-\sum_{i=1}^{K}{\sqrt{p_1 q_i}}}

Value

returns a distance matrix, object of class dist

Author(s)

Daniel Chessel
Stéphane Dray [e-mail]

References

Edwards, A. W. F. (1971) Distance between populations on the basis of gene frequencies. Biometrics, 27, 873–881.

Manly, B. F. (1994) Multivariate Statistical Methods. A primer., Second edition. Chapman & Hall, London.

Nei, M. (1972) Genetic distances between populations. The American Naturalist, 106, 283–292.

Examples

data(microsatt)
w <- microsatt$tab[1:microsatt$loci.eff[1]]

if(adegraphicsLoaded()) {
  g1 <- scatter(dudi.pco(lingoes(dist.prop(w, 1)), scann = FALSE), plot = FALSE)
  g2 <- scatter(dudi.pco(lingoes(dist.prop(w, 2)), scann = FALSE), plot = FALSE)
  g3 <- scatter(dudi.pco(dist.prop(w, 3), scann = FALSE), plot = FALSE)
  g4 <- scatter(dudi.pco(lingoes(dist.prop(w, 4)), scann = FALSE), plot = FALSE)
  G <- ADEgS(list(g1, g2, g3, g4), layout = c(2, 2))
  
} else {
  par(mfrow = c(2, 2))
  scatter(dudi.pco(lingoes(dist.prop(w, 1)), scann = FALSE))
  scatter(dudi.pco(lingoes(dist.prop(w, 2)), scann = FALSE))
  scatter(dudi.pco(dist.prop(w, 3), scann = FALSE))
  scatter(dudi.pco(lingoes(dist.prop(w, 4)), scann = FALSE))
  par(mfrow = c(1, 1))
}