Nothing
recluster.cons <- function(mat,phylo=NULL,tr=100,p=0.5,dist="simpson", method="average", blenghts=TRUE, select=FALSE) {
if(data.class(mat)=="dist")
{distance<-mat}
else
{distance<-recluster.dist(mat,phylo,dist)}
sampl<-cbind((1:nrow(as.matrix(distance)))+10,rownames(as.matrix(distance)))
res<-NULL
trees<-NULL
RSS<-NULL
for (i in 1 : tr){
dist1<-as.matrix(distance)
sampl[,1]<-sample(1:nrow(sampl))+10
rownames(dist1)<-sampl[,1]
colnames(dist1)<-sampl[,1]
dist1<-dist1[order(rownames(dist1)), order(colnames(dist1))]
nam<-sampl[order(sampl[,1]),]
rownames(dist1)<-nam[,2]
tree<-as.phylo(hclust(as.dist(dist1),method=method))
if (select){RSS[[i]]<-attr(nnls.tree(as.dist(dist1), tree, rooted=T),"RSS")}
trees[[i]]<-tree
}
if (select){trees[which(RSS<median(RSS))]}
cons<-compute.brlen(consensus(trees[1:i],p=p, check.labels=T), method="Grafen")
if(blenghts){cons<-nnls.tree(distance,cons, rooted=T,trace=F)}
res$cons<-multi2di(cons, random=T)
res$trees<-trees
res$RSS<-RSS
return(res)
}
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