# corrRect.hclust

0th

Percentile

##### Draw rectangles on the correlation matrix graph.

Draw rectangles on the correlation matrix graph based on hierarchical cluster (hclust).

Keywords
hplot
##### Usage
corrRect.hclust(corr, k = 2, col = "black", lwd = 2,
method = c("complete", "ward", "ward.D", "ward.D2", "single", "average",
"mcquitty", "median", "centroid"))
##### Arguments
corr

Correlation matrix for function corrRect.hclust. It use 1-corr as dist in hierarchical clustering (hclust).

k

Integer, the number of rectangles drawn on the graph according to the hierarchical cluster, for function corrRect.hclust.

col

Color of rectangles.

lwd

Line width of rectangles.

method

Character, the agglomeration method to be used for hierarchical clustering (hclust). This should be (an unambiguous abbreviation of) one of "ward", "ward.D", "ward.D2", "single", "complete", "average", "mcquitty", "median" or "centroid".

##### Aliases
• corrRect.hclust
##### Examples
# NOT RUN {
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"))
M.hc  <- M[order.hc, order.hc]
M.hc2 <- M[order.hc2, order.hc2]

# 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", addrect = 2)
corrplot(M.hc2)
corrRect.hclust(M.hc2, k = 2, method = "ward")

# same as: corrplot(M, order = "hclust", hclust.method = "ward", addrect = 3)
corrplot(M.hc2)
corrRect.hclust(M.hc2, k = 3, method = "ward")

# same as: corrplot(M, order = "hclust", hclust.method = "ward", addrect = 4)
corrplot(M.hc2)
corrRect.hclust(M.hc2, k = 4, method = "ward")
# }

Documentation reproduced from package corrplot, version 0.84, License: GPL

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