DeaMultiplierModel {MultiplierDEA}

DEA Multiplier Model

Description

DEA multiplier model calculates the efficieny and reference sets for each DMUs.

Usage

DeaMultiplierModel(x = x, y = y, rts = "crs", orientation = "input", weightRestriction)

Arguments

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. Available option: crs, vrs

orientation

Orientation of the DEA model - primary emphasis on input-reduction or output-augmentation output. Note that unlike the DEA functions, the default is input orientation. Available option: input, output.

weightRestriction

Weight restriction for the model. Optional parameter.

Value

The function returns a number of values per DMU. The standardized efficiency (all inefficiencies are between 0 and 1, for input and output orientation). Efficiency, and lambda values are returned.

$rts

Returns to scale of the model.

$Orientation

Orientation of the model.

$InputValues

Input Values (x) passed to the model.

$OutputValues

Output Values (y) passed to the model.

$Efficiency

Efficiency of each DMU in the model.

$Lambda

Lambdas per DMU in the model.

$HCU_Input

HCU data for inputs.

$HCU_Output

HCU data for outputs.

$vx

Input weights from the model.

$uy

Output weights from the model.

$Free_Weights

Free weights from the model. Applies only to vrs returns-to-scale.

$Model_Status

Returns the status of the LP model.

Examples

#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")

#Creating the weight restriction data frame with Upper bound

weightRestriction<-data.frame(lower = c(1), numerator = c("StartHours"),
denominator = c("Supplies"), upper = c(2))

#Creating the weight restriction data frame without Upper bound
weightRestriction<-data.frame(lower = c(1), numerator = c("StartHours"),
denominator = c("Supplies"))

#Creating the weight restriction data frame with Upper bound and Na, Inf or NaN
weightRestriction<-data.frame(lower = c(1,2), numerator = c("StartHours","Reimbursed"),
denominator = c("Supplies","Private"), upper = c(2,Inf))

# Calculate the efficiency score without weight Restriction
result <- DeaMultiplierModel(x,y,"crs", "input")
# Examine the efficiency score for DMUs
print(result$Efficiency)


# Calculate the efficiency score with weight Restriction
result <- DeaMultiplierModel(x,y,"crs", "input", weightRestriction)
  # Examine the efficiency score for DMUs
print(result$Efficiency)