| Distance matrix {Rfast} | R Documentation |
Distance matrix.
Dist(x, method = "euclidean", square = FALSE, p = 0,vector = FALSE) vecdist(x)
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. |
The distance matrix is computer with an extra argument for the Euclidean distances. The "kullback_leibler" refers to the symmetric Kullback-Leibler divergence.
A square matrix with the pairwise distances.
Manos Papadakis
R implementation and documentation: Manos Papadakis <papadakm95@gmail.com>
Mardia K. V., Kent J. T. and Bibby J. M. (1979). Multivariate Analysis. Academic Press.
x <- matrix(rnorm(50 * 10), ncol = 10) a1 <- Dist(x) a2 <- as.matrix( dist(x) ) x<-a1<-a2<-NULL