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mclust (version 3.4.7)

imputePairs: Pairwise Scatter Plots showing Missing Data Imputations

Description

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 nonmissing values.

Usage

imputePairs(x, impx, symbols = c(16,1), 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 = 1)

Arguments

x
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.
impx
The dataset x with missing values imputed.
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 pairs.
panel
As in function pairs.
...
As in function pairs.
lower.panel
As in function pairs.
upper.panel
As in function pairs.
diag.panel
As in function pairs.
text.panel
As in function pairs.
label.pos
As in function pairs.
cex.labels
As in function pairs.
font.labels
As in function pairs.
row1attop
As in function pairs.
gap
As in function pairs.

Side Effects

A pairs plot displaying the location of missing and nonmissing values.

References

C. Fraley and A. E. Raftery (2006). MCLUST Version 3 for R: Normal Mixture Modeling and Model-Based Clustering, Technical Report no. 504, Department of Statistics, University of Washington.

See Also

pairs, imputeData

Examples

Run this code
library(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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