marginmatrix {VIM} | R Documentation |
Create a scatterplot matrix with information about missing/imputed values in the plot margins of each panel.
marginmatrix(x, delimiter = NULL, col = c("skyblue","red","red4", "orange","orange4"), alpha = NULL, ...) TKRmarginmatrix(x, delimiter = NULL, col = c("skyblue","red","red4", "orange","orange4"), alpha = NULL, ..., hscale = NULL, vscale = NULL, TKRpar = list())
x |
a matrix or |
delimiter |
a character-vector to distinguish between variables
and imputation-indices for imputed variables (therefore, |
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 |
... |
further arguments and graphical parameters to be
passed to |
hscale |
horizontal scale factor for plot to be embedded in a Tcl/Tk window (see ‘Details’). The default value depends on the number of variables. |
vscale |
vertical scale factor for the plot to be embedded in a Tcl/Tk window (see ‘Details’). The default value depends on the number of variables. |
TKRpar |
a list of graphical parameters to be set for the plot
to be embedded in a Tcl/Tk window (see ‘Details’ and
|
marginmatrix
uses pairsVIM
with a panel function
based on marginplot
.
The graphical parameter oma
will be set unless supplied as an
argument.
TKRmarginmatrix
behaves like marginmatrix
, but uses
tkrplot
to embed the plot in a Tcl/Tk
window. This is useful if the number of variables is large, because
scrollbars allow to move from one part of the plot to another.
Andreas Alfons, modifications by Bernd Prantner
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.
marginplot
, pairsVIM
,
scattmatrixMiss
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")