Nothing

```
# Part of the R package, http://www.R-project.org
#
# Copyright (C) 1995-2012 The R Core Team
#
# This program is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 2 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# A copy of the GNU General Public License is available at
# http://www.r-project.org/Licenses/
thresholdAbsSPath <- function(expdata){
## function that take data
## and provide the clustering output
## based on the threshold sample covariance matrix
## input expdata (matrix): data to compute the sample covariance matrix S
## output partitionList (list): list of resulting partitions from thresolding S
## output lambdaPath (list): list of threshold parameters
## require
## library(igraph)
if(is.matrix(expdata) == FALSE & is.data.frame(expdata) == FALSE)
stop(paste(sQuote("expdata"), "must be a matrix"))
labelsPath <- list()
Sabs <- abs(cor(expdata))
valThres <- Sabs[upper.tri(Sabs)]
orderValue <- valThres[order(valThres)]
for( lam in 1:length(orderValue)){
lambdaR <- orderValue[lam]
E <- Sabs
E[Sabs>lambdaR] <- 1
E[Sabs<lambdaR] <- 0
E[Sabs==lambdaR] <- 0
goutput <- graph.adjacency(E,mode="undirected",weighted=NULL)
labelsPath[[lam]] <- clusters(goutput)$membership
}
return(list(partitionList=unique(labelsPath), lambdaPath=unique(orderValue)))
}
```

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