legends: Legend Functions for Strucplots

Description

These functions generate legend functions for residual-based shadings.

Usage

legend_resbased(fontsize = 12,
  x = unit(1, "lines"), y = unit(0.1,"npc"),
  height = unit(0.8, "npc"),
  width = unit(0.7, "lines"),
  digits = 3, check_overlap = TRUE, text = NULL,
  steps = 200, ticks = 10, pvalue = TRUE)
legend_fixed(fontsize = 12, x = unit(1, "lines"), y = NULL,
  height = NULL, width = unit(1.5, "lines"), steps = 200,
  digits = 1, space = 0.05, text = NULL)

Arguments

fontsize

fontsize of title and p-value text.

x, y

objects of class "unit" indicating the coordinates of the title. For legend_fixed, the default for y is computed as to leave enough space for the specified text.

height, width

object of class "unit" indicating the height/width of the legend. For legend_fixed, the default for y is computed as to align upper margins of legend and actual plot.

digits

number of digits for the scale labels.

check_overlap

logical indicating whether overlap of scale labels should be inhibited or not.

space

For legend_fixed only: proportion of space between the tiles.

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.

Value

A function with arguments:
residualsresiduals from the fitted independence model to be visualized.
shadingshading function computing colors from residuals (see details).
autotextcharacter vector indicating the title to be used when no text argument is specified. Allows strucplot to generate sensible defaults depending on the residuals type.

Details

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.

References

D. Meyer, A. Zeileis, K. Hornik (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. http://www.ci.tuwien.ac.at/Conferences/DSC-2003/Proceedings/

Examples

Run this code

data("Titanic")

mosaic(Titanic, shade = TRUE, legend = legend_resbased)
mosaic(Titanic, shade = TRUE, legend = legend_fixed, gp = shading_Friendly)

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