imgCor(
X,
Y,
type = c("combine", "separate"),
col = color.jet(25),
X.var.names = TRUE,
Y.var.names = TRUE,
x.sideColors = "blue",
y.sideColors = "red",
symkey = TRUE,
keysize = c(1,1),
interactive.dev = TRUE,
row.cex = NULL,
col.cex = NULL,
margins = c(5, 5),
lhei = NULL,
lwid = NULL
)
NA
s are allowed.NA
s are allowed."combine"
or "separated"
,
determining the kind of plots to be produced. See Details.heat.colors
, topo.colors
, rainbow
or similar functTRUE
(defaults) object$names$X
and/or object$names$Y
are used. Possible character
vector with $X$- and/or $Y$-variable labels to use.ncol(object$X)
and
ncol(object$Y)
containing the color names for horizontal and vertical side bars that may
be used to annotate the $X$- and/or $Y$-variables.cex.axis
in for the row or column
axis labeling. The defaults currently only use number of rows or columns, respectively.TRUE
.par(mar)
)
for column and row names respectively.layout
to divide the device up into two
rows and two columns, with the row-heights lhei
and the column-widths lwid
.type="combine"
, the correlation matrix is computed of the combined
matrices cbind(X, Y)
and then plotted. If type="separate"
,
three correlation matrices are computed, cor(X)
, cor(Y)
and
cor(X,Y)
and plotted separately on a device. In both cases,
a color correlation scales strip is plotted.The correlation matrices are pre-processed before calling the image
function in order to get, as in the numerical representation, the diagonal
from upper-left corner to bottom-right one.
Missing values are handled by casewise deletion in the imgCor
function.
If X.names = FALSE
, the name of each X-variable is hidden.
Default value is TRUE
.
If Y.names = FALSE
, the name of each Y-variable is hidden.
Default value is TRUE
.
cor
, image
, color.jet
.data(nutrimouse)
X <- nutrimouse$lipid
Y <- nutrimouse$gene
## 'combine' type plot (default)
imgCor(X, Y)
## 'separate' type plot
imgCor(X, Y, type = "separate")
## 'separate' type plot without the name of datas
imgCor(X, Y, X.names = FALSE, Y.names = FALSE, type = "separate")
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