adea: ADEA analysis to variable selection in DEA

In adea: Alternate DEA Package

ADEA analysis to variable selection in DEA

Description

ADEA analysis, computes a score for each DMU and load ratio for each variable.

Usage

adea(
  input,
  output,
  orientation = c("input", "output"),
  load.orientation = c("inoutput", "input", "output"),
  name = "",
  eff.tolerance = 0.001
)

Arguments

input	A matrix or a data frame with the inputs of units to be evaluated, one row for each DMU and one column for each input.
output	A matrix or a data frame with the outputs of units to be evaluated, one row for each DMU and one column for each output.
orientation	Use "input" for input orientation or use "output" for output orientation in DEA model.
load.orientation	It allows the selection of variables to be included in load analysis. Its default value is "inoutput" which means that all input and all output variables will be included. Use "input" or "output" to include only input or output variables in load analysis.
name	An optional descriptive name for the model. It will be shown in print and summary results.
eff.tolerance	A value between 0 and 1 to tolerance when considering a DMU as efficient in reports.

Details

This function computes an efficiency score for each DMU, the same as in standard DEA model.

Then a load ratio for each variable is computed searching two new set of weights while keeping DMU's scores.

The load ratio of a variable is a number between 0 and 1. Where 0 means that the contribution of that variable to the efficiency computations is negligible. In an ideal case, each input or output variable will have a load of 1 divide by the number of them.

As it is usually done in DEA this load ratio has been computed as its maximum allowable value. But because the sum of all of them is 1, when one increases its load ratio any other decreases its value. So only the lowest value of all load ratios, this is load model, has a real meaning. This lowest value can be taken as a significance measure of the entire model.

Value

The function return an adea class object with the following named members:

• eff is a vector with DMU's scores

• neff is the number of efficient DMU with eff.tolerance. It means DMUs with efficiencies between 1 - eff.tolerance and 1 + eff.tolerance.

• load.orientation is the load orientation, one of 'input', 'output' or 'inoutput'. The last is the default value.

• name: A label of the model

• orientation: DEA model orientation 'input' or 'output'

• ux: A set of weights for inputs

• vy: A set of weights for output

• load: A list with all information about loads:

  • ratios$input: A vector with load ratios of input variables

  • ratios$output: A vector with load ratios of output variables

  • load: The lowest load ratio, which is the load of the ADEA model

  • lp: A pointer to the linear programming program of the model. Mainly for research purpose

  • iinput: A vector of index of inputs that almost reach the load level

  • ioutput: A vector of index of outputs that almost reach the load level

  • vinput: Standardized virtual input dividing by the sum of the weights, see [Costa2006] in adea-package.

  • voutput: Standardized virtual output dividing by the sum of the weights, see [Costa2006] in adea-package.

See Also

adea-package.

Examples

data('cardealers4')
input <- cardealers4[, 1:2]
output <- cardealers4[, 3:4]

# Compute adea model
model <- adea(input, output)
model
# Dealer A  Dealer B  Dealer C  Dealer D  Dealer E  Dealer F
# 0.9915929 1.0000000 0.8928571 0.8653846 1.0000000 0.6515044

# Get model's load
model$load$load
# [1] 0.6666667

# Get model's load ratios
model$load$ratios
# $input
# Employees Depreciation
# 0.6666667    1.3333333
# $output
# CarsSold WorkOrders
# 1.2663476  0.7336524 

adea documentation built on March 18, 2022, 7:24 p.m.