plot.data_descr {MSmix}

Plot descriptive statistics for partial rankings

Description

plot method for class "data_descr".

Usage

## S3 method for class 'data_descr'
plot(
  x,
  cex_text_mean = 1,
  cex_symb_mean = 12,
  cex_text_pc = 3,
  cex_range_pc = c(8, 20),
  ...
)

Arguments

x

An object of class "data_descr" returned by data_description.

cex_text_mean

Positive scalar: the magnification to be used for all the labels in the plot for the mean rank vector. Defaults to 1.

cex_symb_mean

Positive scalar: the magnification to be used for the symbols in the pictogram of the mean rank vector. Defaults to 12.

cex_text_pc

Positive scalar: the magnification to be used for all the labels in the bubble plot of the paired comparison frequencies. Defaults to 3.

cex_range_pc

Numeric vector indicating the range of values to be used on each axis in the bubble plot of the paired comparison frequencies. Defaults to c(8,20).

...

Further arguments passed to or from other methods (not used).

Value

Produce 5 plots to display descriptive summaries of the partial ranking dataset, namely: i) a barplot of the frequency distribution (%) of the number of ranked items (i.e., the length of the partial sequences), ii) a basic pictogram of the mean rank vector, iii) a heatmap of the first-order marginals, iv) the ecdf of the marginal rank distributions and v) a bubble plot of the pairwise comparison matrix.

References

Wickham H (2016). ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York. ISBN 978-3-319-24277-4, https://ggplot2.tidyverse.org.

See Also

data_description

Examples

## Example 1. Plot sample statistics for the Antifragility dataset.
desc <- data_description(ranks_antifragility)
plot(desc)

## Example 2. Plot sample statistics for the Sports dataset.
r_sports <- ranks_sports[, 1:8]
desc <- data_description(rankings = r_sports, borda_ord = TRUE)
plot(desc, cex_text_mean = 1.2)

## Example 3. Plot sample statistics for the Sports dataset by gender.
r_sports <- ranks_sports[, 1:8]
desc_f <- data_description(rankings = r_sports, subset = (ranks_sports$Gender == "Female"))
plot(desc_f, cex_text_mean = 1.2)
desc_m <- data_description(rankings = r_sports, subset = (ranks_sports$Gender == "Male"))
plot(desc_m, cex_text_mean = 1.2)