metric.dist

Distance Matrix Computation

This function computes the distances between the rows of a data matrix by using the specified distance measure.

Keywords
cluster
Usage
metric.dist(x, y = NULL, method = "euclidean", p = 2, dscale = 1, ...)
Arguments
x

Data frame 1. The dimension is (n1 x m).

y

Data frame 2. The dimension is (n2 x m).

method

The distance measure to be used. This must be one of "euclidean", "maximum", "manhattan", "canberra", "binary" or "minkowski".

p

The power of the Minkowski distance.

dscale

If scale is a numeric, the distance matrix is divided by the scale value. If scale is a function (as the mean for example) the distance matrix is divided by the corresponding value from the output of the function.

Further arguments passed to dist function.

Details

This function returns a distance matrix by using dist function. The matrix dimension is (n1 x n1) if y=NULL, (n1 x n2) otherwise.

See Also

See also dist for multivariate date case and metric.lp for functional data case

Aliases
  • metric.dist
Examples
# NOT RUN {
data(iris)
d<-metric.dist(iris[,1:4])
matplot(d,type="l",col=as.numeric(iris[,5]))
# }
Documentation reproduced from package fda.usc, version 2.0.1, License: GPL-2

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