WeightedPCoA function

Weighted Principal Coordinates Analysis

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

Returns

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

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.

Author(s)

Jose Luis Vicente-Villardon

See Also

BinaryProximities

Examples

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