R: Image Maps of Correlation Matrices between two Data Sets

imgCor {mixOmics} | R Documentation

## Image Maps of Correlation Matrices between two Data Sets

### Description

Display two-dimensional visualizations (image maps) of the correlation matrices within and between two data sets.

### Usage

    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)

### Arguments

`X` | numeric matrix or data frame (n x p), the observations on the X variables. `NA`s are allowed.
`Y` | numeric matrix or data frame (n x q), the observations on the Y variables. `NA`s are allowed.
`type` | character string, (partially) maching one of `"combine"` or `"separated"`, determining the kind of plots to be produced. See Details.
`X.var.names, Y.var.names` | logical, should the name of X- and/or Y-variables be shown? If `TRUE` (defaults) `object$names$X` and/or `object$names$Y` are used. Possible character vector with X- and/or Y-variable labels to use.
`sideColors` | character vector of length two. The color name for horizontal and vertical side bars that may be used to annotate the X and Y correlation matrices.
`interactive.dev` | boolean. The current graphics device that will be opened is interactive?
`title` | logical, should the main titles be shown?
`color,xlab, ylab` | arguments passed to `cim`.
`row.cex, col.cex` | positive numbers, used as `cex.axis` in for the row or column axis labeling. The defaults currently only use number of rows or columns, respectively.
`symkey` | boolean indicating whether the color key should be made symmetric about 0. Defaults to `TRUE`.
`keysize` | positive numeric value indicating the size of the color key.
`margins` | numeric vector of length two containing the margins (see `par(mar)`) for column and row names respectively.
`lhei, lwid` | arguments passed to `layout` to divide the device up into two rows and two columns, with the row-heights `lhei` and the column-widths `lwid`.

### Details

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`.

### Author(s)

Ignacio González.

### See Also

`cor`, `image`, `color.jet`.

### Examples

    data(nutrimouse)
    X <- nutrimouse$lipid
    Y <- nutrimouse$gene

    ## 'combine' type plot (default)
    imgCor(X, Y)

    ## 'separate' type plot
    ## Not run:
    imgCor(X, Y, type = "separate")

    ## 'separate' type plot without the name of datas
    imgCor(X, Y, X.names = FALSE, Y.names = FALSE, type = "separate")

    ## End(Not run)

[Package mixOmics version 6.3.2 Index]