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WeightedPCoA

Weighted Principal Coordinates Analysis


Description

Weighted Principal Coordinates Analysis

Usage

WeightedPCoA(Proximities, 
  weigths = matrix(1,dim(Proximities$Proximities)[1],1), 
  dimension = 2, tolerance=0.0001)

Arguments

Proximities

A matrix containing the proximities among a set of objetcs

weigths

Weigths

dimension

Dimension of the solution

tolerance

Tolerance for the eigenvalues

Details

Weighted Principal Coordinates Analysis

Value

data(spiders) dist=BinaryProximities(spiders) pco=WeightedPCoA(dist) An object of class Principal.Coordinates

Author(s)

Jose Luis Vicente-Villardon

References

Gower, J. C. (2006) Similarity dissimilarity and Distance, measures of. Encyclopedia of Statistical Sciences. 2nd. ed. Volume 12. Wiley

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

J.R. Demey, J.L. Vicente-Villardon, M.P. Galindo, A.Y. Zambrano, Identifying molecular markers associated with classifications of genotypes by external logistic biplot, Bioinformatics 24 (2008) 2832.

Cuadras, C. M., Fortiana, J. Metric scaling graphical representation of Categorical Data. Proceedings of Statistics Day, The Center for Multivariate Analysis, Pennsylvania State University, Part 2, pp.1-27, 1995.

See Also

Examples

data(spiders)
dist=BinaryProximities(spiders)
pco=WeightedPCoA(dist)

MultBiplotR

Multivariate Analysis Using Biplots in R

v1.3.30
GPL (>= 2)
Authors
Jose Luis Vicente-Villardon
Initial release
2021-03-30

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