dist.quant: Computation of Distance Matrices on Quantitative Variables

dist.quantR Documentation

Computation of Distance Matrices on Quantitative Variables

Description

computes on quantitative variables, some distance matrices as canonical, Joreskog and Mahalanobis.

Usage

dist.quant(df, method = NULL, diag = FALSE, upper = FALSE, 
    tol = 1e-07)

Arguments

df

a data frame containing only quantitative variables

method

an integer between 1 and 3. 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’

tol

used in case 3 of method as a tolerance threshold for null eigenvalues

Details

All the distances are of type d = ||x-y||_A = sqrt((x-y)^t A (x-y))

1 = Canonical

A = Identity

2 = Joreskog

A = 1 / diag(cov)

3 = Mahalanobis

A = inv(cov)

Value

an object of class dist

Author(s)

Daniel Chessel
Stéphane Dray stephane.dray@univ-lyon1.fr

Examples

data(ecomor)

if(adegraphicsLoaded()) {
  g1 <- scatter(dudi.pco(dist.quant(ecomor$morpho, 3), scan = FALSE), plot = FALSE)
  g2 <- scatter(dudi.pco(dist.quant(ecomor$morpho, 2), scan = FALSE), plot = FALSE)
  g3 <- scatter(dudi.pco(dist(scalewt(ecomor$morpho)), scan = FALSE), plot = FALSE)
  g4 <- scatter(dudi.pco(dist.quant(ecomor$morpho, 1), scan = FALSE), plot = FALSE)
  G <- ADEgS(list(g1, g2, g3, g4), layout = c(2, 2))
  
} else {
  par(mfrow = c(2, 2))
  scatter(dudi.pco(dist.quant(ecomor$morpho, 3), scan = FALSE))
  scatter(dudi.pco(dist.quant(ecomor$morpho, 2), scan = FALSE))
  scatter(dudi.pco(dist(scalewt(ecomor$morpho)), scan = FALSE))
  scatter(dudi.pco(dist.quant(ecomor$morpho, 1), scan = FALSE))
  par(mfrow = c(1, 1))
}

ade4 documentation built on Nov. 2, 2022, 1:07 a.m.

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