Legend Functions for Strucplots
These functions generate legend functions for residual-based shadings.
legend_resbased(fontsize = 12, fontfamily = "", x = unit(1, "lines"), y = unit(0.1,"npc"), height = unit(0.8, "npc"), width = unit(0.7, "lines"), digits = 2, pdigits = max(1, getOption("digits") - 2), check_overlap = TRUE, text = NULL, steps = 200, ticks = 10, pvalue = TRUE, range = NULL) legend_fixed(fontsize = 12, fontfamily = "", x = unit(1, "lines"), y = NULL, height = NULL, width = unit(1.5, "lines"), steps = 200, digits = 1, space = 0.05, text = NULL, range = NULL)
fontsize |
fontsize of title and p-value text. |
fontfamily |
fontfamily of all text. |
x, y |
objects of class |
height, width |
object of class |
digits |
number of digits for the scale labels. |
pdigits |
number of digits for the p-value. |
check_overlap |
logical indicating whether overlap of scale labels should be inhibited or not. |
space |
For |
text |
character string indicating the title of the legend. |
steps |
granularity of the color gradient. |
ticks |
number of scale ticks. |
pvalue |
logical indicating whether the p-value should be visualized under the scale or not. |
range |
Numeric vector of length 2 for setting the legend
range. Computed from the residuals if omitted. |
These functions generate legend functions for residual-based shadings,
visualizing deviations from expected values of an hypothesized
independence model. Therefore, the legend uses a supplied shading
function to visualize the color gradient for the residuals range.
legend_fixed
is inspired by the legend used in
mosaicplot
. For
more details on the shading functions and their return values, see
shadings
.
A function with arguments:
residuals |
residuals from the fitted independence model to be visualized. |
shading |
shading function computing colors from residuals (see details). |
autotext |
character vector indicating the title to be used when
no |
David Meyer David.Meyer@R-project.org
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.
doi: 10.18637/jss.v017.i03 and available as
vignette("strucplot")
.
Meyer, D., Zeileis, A., Hornik, K. (2003), Visualizing independence using extended association plots. Proceedings of the 3rd International Workshop on Distributed Statistical Computing, K. Hornik, F. Leisch, A. Zeileis (eds.), ISSN 1609-395X. https://www.R-project.org/conferences/DSC-2003/Proceedings/
data("Titanic") mosaic(Titanic, shade = TRUE, legend = legend_resbased) mosaic(Titanic, shade = TRUE, legend = legend_fixed, gp = shading_Friendly)
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