View source: R/ContinuousDistances.R
ContinuousDistances | R Documentation |
Calculates distances among rows of a continuous data matrix or among the rows of two continuous matrices.
ContinuousDistances(x, y = NULL, coef = "Pythagorean", r = 1)
x |
Main data matrix. Distances among rows are calculated if y=NULL. |
y |
Supplementary data matrix. If not NULL the distances among the rows of x and y are calculated |
coef |
Distance coefficient. Use the name or the number(see details) |
r |
Exponent for the Minkowsky |
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))
A list with:
Data |
A matrix with the initial data (x matrix). |
SupData |
A matrix with the supplementary data (y matrix). |
D |
The matrix of distances |
Coefficient |
The coefficient used. |
Jose Luis Vicente-Villardon
Gower, J. C. (2006) Similarity dissimilarity and Distance, measures of. Encyclopedia of Statistical Sciences. 2nd. ed. Volume 12. Wiley
PrincipalCoordinates
data(wine)
dis=ContinuousDistances(wine[,4:21])
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