Dist: Distance matrix

Description Usage Arguments Details Value Author(s) References See Also Examples

View source: R/Dist.R

Description

Distance matrix.

Usage

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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

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

x<-a1<-a2<-NULL

Example output

Loading required package: Rcpp
Loading required package: RcppZiggurat

Rfast documentation built on May 18, 2021, 1:07 a.m.