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Unfolding map of a cross-efficiency matrix

Source: R/plot-cem-unfolding.R
plot_cem_unfolding.Rd

Applies multidimensional unfolding (Ashkiani and Mar-Molinero, 2017) to a cross-efficiency matrix, placing each DMU twice – once as a "rating" unit (the weights it applies) and once as a "rated" unit – so that a rating unit sits close to the units it scores highly. Dissimilarities are taken as 1 - CEM.

Usage

plot_cem_unfolding(
  x,
  labels = "none",
  max.overlaps.value = 10,
  transparency = 0.7,
  fade = TRUE,
  subtitle = NULL,
  title = NULL,
  interactive = FALSE,
  ...
)

Arguments

x

A cross-efficiency matrix from compute_cross_efficiency, or a dea_data object / data frame from which one is computed.

labels

Which DMUs to label: "none" (default), "all" (label every DMU; ggrepel with max.overlaps = Inf), "max.overlaps" (ggrepel using max.overlaps.value), or the name/id of a single DMU to highlight just that one. Use "id" to print each DMU's row number inside its own marker.

max.overlaps.value

Passed to ggrepel when labels = "max.overlaps" (default 10); larger values keep more crowded labels.

transparency

Opacity of the markers/areas, a single number in [0, 1] (default 0.7).

fade

Controls the single-DMU focus view. When one DMU is given to labels, all other marks (and, for the network plots, everything outside that DMU's sub-network; for the panel biplot, the other trajectories) are faded so the chosen DMU stands out. TRUE (default) uses a sensible fade level; FALSE disables it; a single number in [0, 1] sets the alpha of the faded marks directly, where larger values fade them less (e.g. 0.4 leaves them more visible).

subtitle

Optional subtitle shown beneath the title.

title

Optional plot title.

interactive

Logical; static ggplot2 (default) or interactive plotly.

...

When x is data rather than a matrix, further arguments (e.g. approach, epsilon) passed to compute_cross_efficiency.

Value

A ggplot2 object, or a plotly object when interactive = TRUE.

References

Ashkiani, S., & Mar-Molinero, C. (2017). Visualization of cross-efficiency matrices using multidimensional unfolding. In Recent Applications of Data Envelopment Analysis.

See also

compute_cross_efficiency, unfolding

Examples

df <- data.frame(
  dmu  = paste0("D", 1:6),
  i_x1 = c(4, 7, 8, 4, 2, 5),
  i_x2 = c(3, 3, 1, 2, 4, 2),
  o_y  = c(5, 8, 6, 7, 3, 9)
)
ce <- compute_cross_efficiency(df)
plot_cem_unfolding(ce)