| corrMatOrder {corrplot} | R Documentation |
Draw rectangle(s) around the chart of corrrlation matrix based on the number of each cluster's members.
corrMatOrder(corr, order=c("AOE", "FPC", "hclust", "alphabet"),
hclust.method = c("complete", "ward", "single", "average",
"mcquitty", "median", "centroid"))
corr |
Correlation matrix to reorder. |
order |
Character, the ordering method for the correlation matrix.
|
hclust.method |
Character, the agglomeration method to be used when |
Returns a single permutation vector.
Taiyun Wei
Package seriation offers more methods to reorder matrices, such as
ARSA, BBURCG, BBWRCG, MDS, TSP, Chen and so forth.
M <- cor(mtcars) (order.AOE <- corrMatOrder(M, order="AOE")) (order.FPC <- corrMatOrder(M, order="FPC")) (order.hc <- corrMatOrder(M, order="hclust")) (order.hc2 <- corrMatOrder(M, order="hclust", hclust.method="ward")) M.AOE <- M[order.AOE,order.AOE ] M.FPC <- M[order.FPC,order.FPC ] M.hc <- M[order.hc, order.hc ] M.hc2 <- M[order.hc2,order.hc2] par(ask=TRUE) corrplot(M) corrplot(M.AOE) corrplot(M.FPC) corrplot(M.hc) corrplot(M.hc) corrRect.hclust(corr=M.hc, k=2) corrplot(M.hc) corrRect.hclust(corr=M.hc, k=3) corrplot(M.hc2) corrRect.hclust(M.hc2, k=2, method="ward")