Calculates proximities among rows of a continuous data matrix or among the rows of two continuous matrices.
ContinuousProximities(x, y = NULL, ysup = FALSE,
transpose = FALSE, coef = "Pythagorean", r = 1)
A matrix with the initial data (x matrix).
A matrix with the supplementary data (y matrix).
The matrix of distances
The coefficient used.
Main data matrix. Distances among rows are calculated if y=NULL.
Supplementary data matrix. If not NULL the distances among the rows of x and y are calculated
Supplementary Y data
Transpose rows and columns
Distance coefficient. Use the name or the number(see details)
Exponent for the Minkowsky
Jose Luis Vicente-Villardon
The following coefficients are calculated
1.- Pythagorean = sqrt(sum((y[i, ] - x[j, ])^2)/p)
2.- Taxonomic = sqrt(sum(((y[i,]-x[j,])^2)/r^2)/p)
3.- City = sum(abs(y[i,]-x[j,])/r)/p
4.- Minkowski = (sum((abs(y[i,]-x[j,])/r)^t)/p)^(1/t)
5.- Divergence = sqrt(sum((y[i,]-x[j,])^2/(y[i,]+x[j,])^2)/p)
6.- dif_sum = sum(abs(y[i,]-x[j,])/abs(y[i,]+x[j,]))/p
7.- Camberra = sum(abs(y[i,]-x[j,])/(abs(y[i,])+abs(x[j,])))
8.- Bray_Curtis = sum(abs(y[i,]-x[j,]))/sum(y[i,]+x[j,])
9.- Soergel = sum(abs(y[i,]-x[j,]))/sum(apply(rbind(y[i,],x[j,]),2,max))
10.- Ware_hedges = sum(abs(y[i,]-x[j,]))/sum(apply(rbind(y[i,],x[j,]),2,max))
Gower, J. C. (2006) Similarity dissimilarity and Distance, measures of. Encyclopedia of Statistical Sciences. 2nd. ed. Volume 12. Wiley
data(wine)
dis=ContinuousProximities(wine[,4:21])
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