R: Computation of Distance Matrices on Quantitative Variables

dist.quant {ade4} | R 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))
    }

[Package ade4 version 1.7-17 Index]