PCOA-class: PCoA Results

In dimensio: Multivariate Data Analysis

PCoA Results

Description

An S4 class to store the results of a principal coordinates analysis.

Slots

points

A numeric matrix whose rows give the coordinates of the points chosen to represent the dissimilarities.

eigenvalues

A numeric vector giving the eigenvalues computed during the scaling process.

method

A character string giving the distance that has been used to create the distance structure.

GOF

A length-two numeric vector.

groups

A character vector specifying the class for each observation.

Author(s)

N. Frerebeau

See Also

Other class: BootstrapCA-class, BootstrapPCA-class, CA-class, MCA-class, MultivariateAnalysis, MultivariateBootstrap, MultivariateResults, MultivariateSummary, PCA-class

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)

## Add convex hulls
plot(
  x = X,
  extra_quali = iris$Species,
  hull = TRUE
)

## Add tolerance ellipses
plot(
  x = X,
  extra_quali = iris$Species,
  ellipse = list(type = "tolerance", level = 0.95)
)

dimensio documentation built on April 3, 2025, 10:36 p.m.