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NominalLogisticBiplot (version 0.2)

PCoA: Principal Coordinates Analysis

Description

This function calculates principal coordinates analysis using a distante matrix among a set of objets.

Usage

PCoA(dis, r = 2)

Arguments

dis
Distance matrix between a set ob objects.
r
Number of dimensions for the solution.

Value

An object with has some components:
EigenValues
Eigenvalues of the inner products matrix
Inertia
Variance (Inertia) accounted for each dimension
RowCoordinates
Coordinates for the rows in the reduced space
RowQualities
Qualities of representation of the objects. Squared cosines between the points (vectors) in the full space and the points in the reduced space. Values near 1 indicate good quality

References

Gower,J.C. (1966) Some distance properties of latent root and vector methods used in multivariate analysis. Biometrika, 53, 325--338.

See Also

NominalDistances

Examples

Run this code
  
  data(HairColor)
  dis = NominalDistances(data.matrix(HairColor))
  PCoA(dis,2)
  

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