Pairwise Scatter Plots showing Missing Data Imputations
Creates a scatter plot for each pair of variables in given data, allowing display of imputations for missing values in different colors and symbols than non missing values.
imputePairs(data, dataImp,
symbols = c(1,16), colors = c("black", "red"), labels,
panel = points, ..., lower.panel = panel, upper.panel = panel,
diag.panel = NULL, text.panel = textPanel, label.pos = 0.5 +
has.diag/3, cex.labels = NULL, font.labels = 1, row1attop = TRUE,
gap = 0.2)data |
A numeric vector, matrix, or data frame of observations containing missing values. Categorical variables are not allowed. If a matrix or data frame, rows correspond to observations and columns correspond to variables. |
dataImp |
The dataset |
symbols |
Either an integer or character vector assigning plotting symbols to the nonmissing data and impued values, respectively. The default is a closed circle for the nonmissing data and an open circle for the imputed values. |
colors |
Either an integer or character vector assigning colors to the nonmissing data and impued values, respectively. The default is black for the nonmissing data and red for the imputed values. |
labels |
As in function |
panel |
As in function |
... |
As in function |
lower.panel |
As in function |
upper.panel |
As in function |
diag.panel |
As in function |
text.panel |
As in function |
label.pos |
As in function |
cex.labels |
As in function |
font.labels |
As in function |
row1attop |
As in function |
gap |
As in function |
A pairs plot displaying the location of missing and nonmissing values.
Schafer J. L. (1997). Analysis of Imcomplete Multivariate Data, Chapman and Hall.
# Note that package 'mix' must be installed data(stlouis, package = "mix") # impute the continuos variables in the stlouis data stlimp <- imputeData(stlouis[,-(1:3)]) # plot imputed values imputePairs(stlouis[,-(1:3)], stlimp)
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