Draw rectangles on the correlation matrix graph.
Draw rectangles on the correlation matrix graph based on hierarchical cluster
(hclust).
corrRect.hclust(
corr,
k = 2,
col = "black",
lwd = 2,
method = c("complete", "ward", "ward.D", "ward.D2", "single", "average", "mcquitty",
"median", "centroid")
)corr |
Correlation matrix for function |
k |
Integer, the number of rectangles drawn on the graph according to
the hierarchical cluster, for function |
col |
Color of rectangles. |
lwd |
Line width of rectangles. |
method |
Character, the agglomeration method to be used for hierarchical
clustering ( |
Taiyun Wei
data(mtcars) M <- cor(mtcars) corrplot(M, method = "circle", order = "FPC") corrRect(c(5,6)) (order.hc <- corrMatOrder(M, order = "hclust")) (order.hc2 <- corrMatOrder(M, order = "hclust", hclust.method = "ward.D2")) M.hc <- M[order.hc, order.hc] M.hc2 <- M[order.hc2, order.hc2] par(ask = TRUE) # same as: corrplot(M, order = "hclust", addrect = 2) corrplot(M.hc) corrRect.hclust(corr = M.hc, k = 2) # same as: corrplot(M, order = "hclust", addrect = 3) corrplot(M.hc) corrRect.hclust(corr = M.hc, k = 3) # same as: corrplot(M, order = "hclust", hclust.method = "ward.D2", addrect = 2) corrplot(M.hc2) corrRect.hclust(M.hc2, k = 2, method = "ward.D2") # same as: corrplot(M, order = "hclust", hclust.method = "ward.D2", addrect = 3) corrplot(M.hc2) corrRect.hclust(M.hc2, k = 3, method = "ward.D2") # same as: corrplot(M, order = "hclust", hclust.method = "ward.D2", addrect = 4) corrplot(M.hc2) corrRect.hclust(M.hc2, k = 4, method = "ward.D2")
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