Draw rectangle(s) after the correlation matrix plotted. SUGGESTION: It's more convenient to draw rectangle(s) by using pipe operator `|>` since R 4.1.0.
corrRect(
corrRes = NULL,
index = NULL,
name = NULL,
namesMat = NULL,
col = "black",
lwd = 2,
...
)
List of the corrplot()
returns.
Vector, variable index of diag rect c(Rect1from, Rect2from,
Rect3from, ..., RectNto)
on the correlation matrix graph.
It works when the colnames are the same as rownames, or both of them is NULL.
It needs corrRes
inputted.
Vector, variable name of diag rect c(Rect1from, Rect2from,
Rect3from, ..., RectNto)
on the correlation matrix graph.
OIt works when the colnames are the same as rownames.
It needs corrRes
inputted.
4-length character vector or 4-columns character matrix,
represents the names of xleft, ybottom, xright, ytop correspondingly.
It needs corrRes
inputted.
Color of rectangles.
Line width of rectangles.
Additional arguments passing to function rect()
.
(Invisibly) returns input parameter corrRes
,
usually list(corr, corrTrans, arg)
.
corrRect
needs one of index
, name
and namesMat
inputted.
While corrRect.hclust
can get the members in each cluster
based on hierarchical clustering (hclust
).
data(mtcars)
M = cor(mtcars)
r = rbind(c('gear', 'wt', 'qsec', 'carb'),
c('wt', 'gear', 'carb', 'qsec'))
corrplot(M, order = 'AOE') -> p
corrRect(p, namesMat = r)
# same as using pipe operator `|>` if R version >= 4.1.0:
# corrplot(M, order = 'AOE') |> corrRect(namesMat = r)
r = c('gear', 'carb', 'qsec', 'wt')
corrplot(M, order = 'AOE', type='lower') -> p
corrRect(p, namesMat = r)
# same as using pipe operator `|>` if R version >= 4.1.0:
# corrplot(M, order = 'AOE', type='lower') |> corrRect(namesMat = r)
corrplot(M, order = 'hclust', type = 'upper') -> p
corrRect(p, index = c(1, 6, 11))
# same as using pipe operator `|>` if R version >= 4.1.0:
# corrplot(M, order = 'AOE', type='lower') |> corrRect(index = c(1, 6, 11))
corrplot(M, order = 'hclust') -> p
corrRect(p, name = c('carb', 'qsec', 'gear'))
# same as using pipe operator `|>` if R version >= 4.1.0:
# corrplot(M, order = 'hclust') |> corrRect(name = c('carb', 'qsec', 'gear'))
(order.hc = corrMatOrder(M, order = 'hclust'))
#> [1] 11 6 4 2 3 7 8 1 5 9 10
(order.hc2 = corrMatOrder(M, order = 'hclust', hclust.method = 'ward.D'))
#> [1] 6 2 3 4 11 7 8 9 10 1 5
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.D', addrect = 2)
corrplot(M.hc2)
corrRect.hclust(M.hc2, k = 2, method = 'ward.D')
# same as: corrplot(M, order = 'hclust', hclust.method = 'ward.D', addrect = 3)
corrplot(M.hc2)
corrRect.hclust(M.hc2, k = 3, method = 'ward.D')
# same as: corrplot(M, order = 'hclust', hclust.method = 'ward.D', addrect = 4)
corrplot(M.hc2)
corrRect.hclust(M.hc2, k = 4, method = 'ward.D')