## 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 dray@biomserv.univ-lyon1.fr

### Examples

```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))```

### Worked out examples

```
> ### Name: dist.quant
> ### Title: Computation of Distance Matrices on Quantitative Variables
> ### Aliases: dist.quant
> ### Keywords: array multivariate
>
> ### ** Examples
>
> 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))
>
>
>
```