I have a complete graph from a 6 by 6 correlation matrix. Naturally, it has 15 edges. I'm looking for a way to make R identify which edges need to be eliminated in order to make the graph a planar maximally filtered graph. I have a graph which comes from the matrix "corr.214"

```corformelt <- corr.214 corformelt[upper.tri(corformelt)] <- 42 corformelt <- melt(corformelt) corformelt <- filter(corformelt, value != 42) %>% filter(Var1 != Var2) corformelt <- arrange(corformelt,desc(value)) corformelt corf.g <- graph_from_data_frame(corformelt,directed = FALSE)

``corf.g.nel <- as_graphnel(corf.g) require(RBGL) corf.plan.try <- makeMaximalPlanar(corf.g.nel) try.again <- as.data.frame(t(corf.plan.try$new graph`)) try.again.plot <- graph_from_data_frame(try.again,directed = FALSE)

I make it a graphnel object, and then use the makeMaximalPlanar function. I don't understand the output of the makeMaximalPlanar function. The matrix it returns under $new graph creates a graph that has 15 edges. This doesn't make sense to me, as I thought a PMFG with 6 veritces should have 3(n-2) = 12 edges. Can someone help me interpret what makeMaximalPlanar does?