efficiencyCEAT: Efficiency Scores computed through a Convexified Efficiency...

View source: R/efficiencyCEAT.R

efficiencyCEATR Documentation

Efficiency Scores computed through a Convexified Efficiency Analysis Trees model.

Description

This function computes the efficiency scores for each DMU through a Convexified Efficiency Analysis Trees model.

Usage

efficiencyCEAT(
  data,
  x,
  y,
  object,
  scores_model,
  digits = 3,
  DEA = TRUE,
  print.table = FALSE,
  na.rm = TRUE
)

Arguments

data

data.frame or matrix containing the variables in the model.

x

Column input indexes in data.

y

Column output indexes in data.

object

An EAT object.

scores_model

Mathematical programming model to calculate scores.

  • BCC.OUT BCC model. Output-oriented. Efficiency level at 1.

  • BCC.INP BCC model. Input-oriented. Efficiency level at 1.

  • DDF Directional Distance Function. Efficiency level at 0.

  • RSL.OUT Russell model. Output-oriented. Efficiency level at 1.

  • RSL.INP Russell model. Input-oriented. Efficiency level at 1.

  • WAM.MIP Weighted Additive Model. Measure of Inefficiency Proportions. Efficiency level at 0.

  • WAM.RAM Weighted Additive Model. Range Adjusted Measure of Inefficiency. Efficiency level at 0.

digits

Decimal units for scores.

DEA

logical. If TRUE, the DEA scores are also calculated with the programming model selected in scores_model.

print.table

logical. If TRUE, a summary descriptive table of the efficiency scores is displayed.

na.rm

logical. If TRUE, NA rows are omitted.

Value

A data.frame with the efficiency scores computed through a Convexified Efficiency Analysis Trees model. Optionally, a summary descriptive table of the efficiency scores can be displayed.

Examples



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

efficiencyCEAT(data = simulated, x = c(1, 2), y = c(3, 4), object = EAT_model, 
              scores_model = "BCC.OUT", digits = 2, DEA = TRUE, print.table = TRUE,
              na.rm = TRUE)



eat documentation built on Jan. 10, 2023, 5:13 p.m.