R: Distance matrix

Distance matrix {Rfast} | R Documentation

## Distance matrix

### Description

Distance matrix.

### Usage

    Dist(x, method = "euclidean", square = FALSE, p = 0,vector = FALSE)
    vecdist(x)

### Arguments

`x` | A matrix with data. The distances will be calculated between pairs of rows. In the case of vecdist this is a vector.
`method` | This is either "euclidean", "manhattan", "canberra1", "canberra2", "minimum", "maximum", "minkowski", "bhattacharyya", "hellinger", "kullback_leibler" or "jensen_shannon". The last two options are basically the same.
`square` | If you choose "euclidean" or "hellinger" as the method, then you can have the option to return the squared Euclidean distances by setting this argument to TRUE.
`p` | This is for the the Minkowski, the power of the metric.
`vector` | For return a vector instead a matrix.

### Details

The distance matrix is computer with an extra argument for the Euclidean distances. The "kullback_leibler" refers to the symmetric Kullback-Leibler divergence.

### Value

A square matrix with the pairwise distances.

### Author(s)

Manos Papadakis

R implementation and documentation: Manos Papadakis <papadakm95@gmail.com>

### References

Mardia K. V., Kent J. T. and Bibby J. M. (1979). Multivariate Analysis. Academic Press.

### See Also

`dista, colMedians`

### Examples

    x <- matrix(rnorm(50 * 10), ncol = 10)
    a1 <- Dist(x)
    a2 <- as.matrix( dist(x) )

    x<-a1<-a2<-NULL

[Package Rfast version 2.0.0 Index]