R: Marginplot Matrix

marginmatrix {VIM} | R Documentation

## Marginplot Matrix

### Description

Create a scatterplot matrix with information about missing/imputed values in the plot margins of each panel.

### Usage

    marginmatrix(x, delimiter = NULL, col = c("skyblue", "red", "red4",
      "orange", "orange4"), alpha = NULL, ...)

### Arguments

`x` | a matrix or `data.frame`.
`delimiter` | a character-vector to distinguish between variables and imputation-indices for imputed variables (therefore, `x` needs to have `colnames`). If given, it is used to determine the corresponding imputation-index for any imputed variable (a logical-vector indicating which values of the variable have been imputed). If such imputation-indices are found, they are used for highlighting and the colors are adjusted according to the given colors for imputed variables (see `col`).
`col` | a vector of length five giving the colors to be used in the marginplots in the off-diagonal panels. The first color is used for the scatterplot and the boxplots for the available data, the second/fourth color for the univariate scatterplots and boxplots for the missing/imputed values in one variable, and the third/fifth color for the frequency of missing/imputed values in both variables (see ‘Details’). If only one color is supplied, it is used for the bivariate and univariate scatterplots and the boxplots for missing/imputed values in one variable, whereas the boxplots for the available data are transparent. Else if two colors are supplied, the second one is recycled.
`alpha` | a numeric value between 0 and 1 giving the level of transparency of the colors, or `NULL`. This can be used to prevent overplotting.
`...` | further arguments and graphical parameters to be passed to `pairsVIM` and `marginplot`. `par("oma")` will be set appropriately unless supplied (see `par`).

### Details

`marginmatrix` uses `pairsVIM` with a panel function based on `marginplot`.

The graphical parameter `oma` will be set unless supplied as an argument.

### Author(s)

Andreas Alfons, modifications by Bernd Prantner

### References

M. Templ, A. Alfons, P. Filzmoser (2012) Exploring incomplete data using visualization tools. Journal of Advances in Data Analysis and Classification, Online first. DOI: 10.1007/s11634-011-0102-y.

### See Also

`marginplot`, `pairsVIM`, `scattmatrixMiss`

### Examples

    data(sleep, package = "VIM")
    ## for missing values
    x <- sleep[, 1:5]
    x[,c(1,2,4)] <- log10(x[,c(1,2,4)])
    marginmatrix(x)

    ## for imputed values
    x_imp <- kNN(sleep[, 1:5])
    x_imp[,c(1,2,4)] <- log10(x_imp[,c(1,2,4)])
    marginmatrix(x_imp, delimiter = "_imp")

[Package VIM version 4.8.0 Index]