R Under development (unstable) (2025-06-25 r88360 ucrt) -- "Unsuffered Consequences"
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> require(symbolicDA)
Loading required package: symbolicDA
Loading required package: clusterSim
Loading required package: cluster
Loading required package: MASS
Loading required package: XML
> # Example 1
> library(stats)
> data("cars",package="symbolicDA")
> x<-cars
> d<-dist_SDA(x, type="U_2")
> wynik<-hclust(d, method="ward", members=NULL)
The "ward" method has been renamed to "ward.D"; note new "ward.D2"
> clusters<-cutree(wynik, 4)
> G1d<-index.G1d(d, clusters)
> print(G1d)
[1] 334.1739
> 
> # Example 2
> 
> 
> data("cars",package="symbolicDA")
> md <- dist_SDA(cars, type="U_3", gamma=0.5, power=2)
> min_nc=2
> max_nc=10
> res <- array(0,c(max_nc-min_nc+1,2))
> res[,1] <- min_nc:max_nc
> clusters <- NULL
> for (nc in min_nc:max_nc)
+ {
+ cl2 <- pam(md, nc, diss=TRUE)
+ res[nc-min_nc+1,2] <- G1d <- index.G1d(md,cl2$clustering)   
+ clusters <- rbind(clusters, cl2$clustering)
+ }
> print(sprintf("max G1d for %f clusters=%.3f",max(res[,2]),(min_nc:max_nc)[which.max(res[,2])]))
[1] "max G1d for 101.360663 clusters=9.000"
> print("clustering for max G1d")
[1] "clustering for max G1d"
> print(clusters[which.max(res[,2]),])
 [1] 1 2 3 4 5 5 6 3 7 7 3 7 8 6 4 5 1 9 6 4 4 2 1 9 6 4 2 6 4 2
> write.table(res,file="G1d_res.csv",sep=";",dec=",",row.names=TRUE,col.names=FALSE)
> plot(res, type="p", pch=0, xlab="Number of clusters", ylab="G1d", xaxt="n")
> axis(1, c(min_nc:max_nc))
> 
> proc.time()
   user  system elapsed 
  23.85    1.29   25.21