fda.usc (version 2.0.1)

metric.dist: Distance Matrix Computation

Description

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

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

Examples

# NOT RUN {
data(iris)
d<-metric.dist(iris[,1:4])
matplot(d,type="l",col=as.numeric(iris[,5]))
# }

Run the code above in your browser using DataCamp Workspace