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 chessel@biomserv.univ-lyon1.fr

### Examples

    library(mva)
    data(ecomor)
    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 Contents]