imgCor | R Documentation |
Display two-dimensional visualizations (image maps) of the correlation matrices within and between two data sets.
imgCor(
X,
Y,
type = "combine",
X.var.names = TRUE,
Y.var.names = TRUE,
sideColors = TRUE,
interactive.dev = TRUE,
title = TRUE,
color,
row.cex,
col.cex,
symkey,
keysize,
xlab,
ylab,
margins,
lhei,
lwid
)
X |
numeric matrix or data frame |
Y |
numeric matrix or data frame |
type |
character string, (partially) maching one of |
X.var.names , Y.var.names |
logical, should the name of |
sideColors |
character vector of length two. The color name for
horizontal and vertical side bars that may be used to annotate the |
interactive.dev |
Logical. The current graphics device that will be opened is interactive? |
title |
logical, should the main titles be shown? |
color , xlab , ylab |
arguments passed to |
row.cex , col.cex |
positive numbers, used as |
symkey |
Logical indicating whether the color key should be made
symmetric about 0. Defaults to |
keysize |
positive numeric value indicating the size of the color key. |
margins |
numeric vector of length two containing the margins (see
|
lhei , lwid |
arguments passed to |
If 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
.
NULL (invisibly)
Ignacio González, Kim-Anh Lê Cao, Florian Rohart, Al J Abadi
cor
, image
, color.jet
.
data(nutrimouse)
X <- nutrimouse$lipid
Y <- nutrimouse$gene
## 'combine' type plot (default)
imgCor(X, Y)
## Not run:
## 'separate' type plot
imgCor(X, Y, type = "separate")
## 'separate' type plot without the name of datas
imgCor(X, Y, X.var.names = FALSE, Y.var.names = FALSE, type = "separate")
## End(Not run)
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