r - exctract correlated elements of a correlation matrix -

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i have correlation matrix in r , want know how many groups (and put these groups vectors) of elements correlate between them in more 95%.

x <- matrix(0,3,5)  x[,1] <- c(1,2,3) x[,2] <- c(1,2.2,3)*2 x[,3] <- c(1,2,3.3)*3 x[,4] <- c(6,5,1) x[,5] <- c(6.1,5,1.2)*4  cor.matrix <- cor(x) cor.matrix <- cor.matrix*lower.tri(cor.matrix) cor.vector <- which(cor.matrix>0.95, arr.ind=true)

cor.vector contains:

     row col  [1,]   2   1  [2,]   3   1  [3,]   3   2  [4,]   5   4

that means, expected, vectors 1,2 , 3 correlate between them, , 4 , 5.

what need 2 vectors c(1,2,3) , c(4,5) final result.

this simple example, processing large matrices though.

here's approach using igraph package:

require(igraph) g <- graph.data.frame(cor.vector, directed = false) split(unique(as.vector(cor.vector)), clusters(g)$membership) # $`1` # [1] 2 3 1  # $`2` # [1] 5 4

what find clusters in graph g (disconnected sets), illustrated in figure below. since vertices used create graph in order entered (from cor.vector), clustering order comes in same order. is: vertices c(2,3,5,1,4) clusters c(1,1,2,1,2) total of 2 clusters (cluster 1 , cluster 2). so, use split using cluster group.

enter image description here


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