This function creates a doubledecker plot visualizing a classification rule.
# S3 method for formula
doubledecker(formula, data = NULL, …, main = NULL)
# S3 method for default
doubledecker(x, depvar = length(dim(x)),
margins = c(1,4, length(dim(x)) + 1, 1),
gp = gpar(fill = rev(gray.colors(tail(dim(x), 1)))),
labeling = labeling_doubledecker,
spacing = spacing_highlighting,
main = NULL, keep_aspect_ratio = FALSE, …)
a formula specifying the variables used to create a
contingency table from data
. The dependent variable is used
last for splitting.
either a data frame, or an object of class "table"
or "ftable"
.
a contingency table in array form, with optional category
labels specified in the dimnames(x)
attribute.
dimension index or character string specifying the dependent variable. That will be sorted last in the table.
margins of the plot. Note that by default, all factor names (except the last one) and their levels are visualized as a block under the plot.
object of class "gpar"
used for the tiles of the last variable.
labeling function or corresponding generating
generating function (see strucplot
for details).
spacing object, spacing function or corresponding
generating function (see strucplot
for details).
either a logical, or a character string used for plotting
the main title. If main
is TRUE
, the
name of the data
object is used.
logical indicating whether the aspect ratio should be maintained or not.
Further parameters passed to mosaic
.
The "structable"
visualized is returned invisibly.
Doubledecker plots visualize the the dependence of one categorical (typically binary) variable on further categorical variables. Formally, they are mosaic plots with vertical splits for all dimensions (antecedents) except the last one, which represents the dependent variable (consequent). The last variable is visualized by horizontal splits, no space between the tiles, and separate colors for the levels.
H. Hoffmann (2001), Generalized odds ratios for visual modeling. Journal of Computational and Graphical Statistics, 10, 4, 628--640.
Meyer, D., Zeileis, A., and Hornik, K. (2006),
The strucplot framework: Visualizing multi-way contingency tables with
vcd.
Journal of Statistical Software, 17(3), 1-48.
Available as vignette("strucplot", package = "vcd")
.
10.18637/jss.v017.i03.
# NOT RUN {
data("Titanic")
doubledecker(Titanic)
doubledecker(Titanic, depvar = "Survived")
doubledecker(Survived ~ ., data = Titanic)
# }
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