dist {mva}R Documentation

Distance Matrix Computation

Description

This function computes and returns the distance matrix computed by using the specified distance measure to compute the distances between the rows of a data matrix.

Usage

dist(x, method = "euclidean", diag = FALSE, upper = FALSE)

print.dist(x, diag = NULL, upper = NULL, ...)
as.matrix.dist(x)
as.dist(m, diag = NULL, upper = NULL)

Arguments

x A matrix or (data frame). Distances between the rows of x will be computed.
method The distance measure to be used. This must be one of "euclidean", "maximum", "manhattan", "canberra" or "binary". Any unambiguous substring can be given.
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.
m A matrix of distances to be converted to a "dist" object (only the lower triangle is used, the rest is ignored).
... further arguments, passed to the (next) print method.

Details

Available distance measures are (written for two vectors x and y):

euclidean:
Usual square distance between the two vectors (2 norm).
maximum:
Maximum distance between two components of x and y (supremum norm)
manhattan:
Absolute distance between the two vectors (1 norm).
canberra:
sum(|x_i - y_i| / |x_i + y_i|)
binary:
(aka asymmetric binary): Count the number of different bits in x and y where at least one of the two bits is 1, i.e., components where both bits are zero are ignored.

The functions as.matrix.dist() and as.dist() can be used for conversion between objects of class "dist" and conventional distance matrices and vice versa.

Value

An object of class "dist".
The lower triangle of the distance matrix stored by columns in a single vector. The vector has the attributes "Size", "Diag", "Upper", "Labels" and "class" equal to "dist".

References

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

See Also

hclust.

Examples

x <- matrix(rnorm(100), nrow=5)
dist(x)
dist(x, diag = TRUE)
dist(x, upper = TRUE)
m <- as.matrix(dist(x))
d <- as.dist(m)
print(d, digits = 3)