CrossEfficiency | R Documentation |
Cross Efficiency uses DEA to do peer evaluation of DMUs. Single-phase cross efficiency approach.
CrossEfficiency(x = x, y = y, rts = "crs", orientation = "input", weightRestriction)
x |
Inputs or resources used by each decision making unit. |
y |
Outputs or resources used by each decision making unit. |
rts |
Returns to scale for the application, or industry studied. Note the default rts is crs. vrs Variable returns to scale. crs Constant returns to scale. |
orientation |
Orientation of the DEA model - primary emphasis on input-reduction input or output-augmentation output. Note that unlike the DEA functions, the default is input orientation. |
weightRestriction |
Weight restriction for the model. Optional parameter. |
The function returns a number of values per DMU.
$ceva_matrix |
Returns the cross efficiency matrix. Row is the Rating DMU and Column is the Rated DMU. |
$ce_ave |
Returns the cross efficiency score for the DMU. |
$ceva_max |
Returns the maximum cross efficiency score for the DMU. |
$ceva_min |
Returns the minimum cross efficiency score for the DMU. |
$vx |
Input weights from the model. |
$uy |
Output weights from the model. |
$Model_Status |
Returns the status of the LP model. |
ceva_matrix - cross-evaluation matrix. ceva_max - cross-evaluation maximum. ceva_min - cross-evaluation minimum. ce_ave - cross-efficiency scores.
#Example from Kenneth R. Baker: Optimization Modeling with Spreadsheets, Third Edition,p. 176, #John Wiley and Sons, Inc. dmu <- c("A", "B", "C", "D", "E", "F") x <- data.frame(c(150,400,320,520,350,320),c(0.2,0.7,1.2,2.0,1.2,0.7)) rownames(x) <- dmu colnames(x)[1] <- c("StartHours") colnames(x)[2] <- c("Supplies") y <- data.frame(c(14,14,42,28,19,14),c(3.5,21,10.5,42,25,15)) rownames(y) <- dmu colnames(y)[1] <- c("Reimbursed") colnames(y)[2] <- c("Private") # Calculate the efficiency score result <- CrossEfficiency(x,y,"crs", "input") # Examine the cross efficiency score for DMUs print(result$ce_ave)
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