imputePairs: Pairwise Scatter Plots showing Missing Data Imputations

In mclust: Gaussian Mixture Modelling for Model-Based Clustering, Classification, and Density Estimation

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 non missing values.

Usage

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) 

Arguments

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 data 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.

Value

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

References

Schafer J. L. (1997). Analysis of Imcomplete Multivariate Data, Chapman and Hall.

See Also

pairs, imputeData

Examples

# 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)

mclust documentation built on May 29, 2024, 8:06 a.m.