dimensio (version 0.9.0)

pcoa: Principal Coordinates Analysis

Description

Computes classical (metric) multidimensional scaling.

Usage

pcoa(object, ...)
# S4 method for dist
pcoa(object, rank = 2)

Value

A PCOA object.

Arguments

object

A distance structure.

...

Currently not used.

rank

An integer value specifying the maximal number dimension of the space which the data are to be represented in.

Author

N. Frerebeau

References

Gower, J. C. (1966). Some Distance Properties of Latent Root and Vector Methods Used in Multivariate Analysis. Biometrika, 53(3‑4): 325-338. tools:::Rd_expr_doi("10.1093/biomet/53.3-4.325").

See Also

stats::cmdscale()

Other multivariate analysis: ca(), mca(), pca(), predict()

Examples

## Load data
data("iris")

## Compute euclidean distances
d <- dist(iris[, 1:4], method = "euclidean")

## Compute principal coordinates analysis
X <- pcoa(d)

## Screeplot
screeplot(X)

## Plot results
plot(X, extra_quali = iris$Species)