eat (version 0.1.4)

efficiencyJitter: Efficiency Scores Jitter Plot

Description

This function returns a jitter plot from ggplot2. This graphic shows how DMUs are grouped into leaf nodes in a model built using the EAT function. Each leaf node groups DMUs with the same level of resources. The dot and the black line represent, respectively, the mean value and the standard deviation of the scores of its node. Additionally, efficient DMU labels always are displayed based on the model entered in the scores_model argument. Finally, the user can specify an upper bound upn and a lower bound lwb in order to show, in addition, the labels whose efficiency score lies between them.

Usage

efficiencyJitter(object, df_scores, scores_model, upb = NULL, lwb = NULL)

Value

Jitter plot with DMUs and scores.

Arguments

object

An EAT object.

df_scores

data.frame with efficiency scores (from efficiencyEAT or efficiencyCEAT).

scores_model

Mathematical programming model to calculate scores.

• BCC.OUT BCC model. Output-oriented.

• BCC.INP BCC model. Input-oriented.

• DDF Directional Distance Function.

• RSL.OUT Russell model. Output-oriented.

• RSL.INP Russell model. Input-oriented.

• WAM.MIP Weighted Additive Model. Measure of Inefficiency Proportions.

• WAM.RAM Weighted Additive Model. Range Adjusted Measure of Inefficiency.

upb

Numeric. Upper bound for labeling.

lwb

Numeric. Lower bound for labeling.

Examples

# \donttest{
simulated <- X2Y2.sim(N = 50, border = 0.2)
EAT_model <- EAT(data = simulated, x = c(1,2), y = c(3, 4))

EAT_scores <- efficiencyEAT(data = simulated, x = c(1, 2), y = c(3, 4), object = EAT_model,
                            scores_model = "BCC.OUT", digits = 2, na.rm = TRUE)

efficiencyJitter(object = EAT_model, df_scores = EAT_scores, scores_model = "BCC.OUT")
# }