make_deadata function

make_deadata

This function creates, from a data frame, a deadata structure, which is as list with fields input, output, dmunames, nc_inputs, nc_outputs, nd_inputs, nd_outputs.

make_deadata(datadea = NULL,
          ni = NULL,
          no = NULL,
          dmus = 1,
          inputs = NULL,
          outputs = NULL,
          nc_inputs = NULL,
          nc_outputs = NULL,
          nd_inputs = NULL,
          nd_outputs = NULL,
          ud_inputs = NULL, 
          ud_outputs = NULL)

Arguments

• datadea: Data frame with DEA data.
• ni: Number of inputs, if inputs are in columns 2:(ni + 1) (if DMUs are in the first column) or 1:ni (no DMUs column).
• no: Number of outputs, if outputs are in columns (ni + 2):(ni + no + 1) (if DMUs are in the first column) or (ni + 1):(ni + no) (no DMUs column). If not specified, DMUs are in the first column.
• dmus: Column (number or name) of DMUs (optional). By default, it is the first column. If there is not any DMU column, then it must be NULL.
• inputs: Columns (numbers or names) of inputs (optional). It prevails over ni. Alternatively to datadea, it can be a matrix with the inputs (DMUs in columns). In this case, DMUs names are taken from the columns names.
• outputs: Columns (numbers or names) of outputs (optional). It prevails over no. Alternatively to datadea, it can be a matrix with the outputs (DMUs in columns).
• nc_inputs: A numeric vector containing the indices of non-controllable inputs.
• nc_outputs: A numeric vector containing the indices of non-controllable outputs.
• nd_inputs: A numeric vector containing the indices of non-discretionary inputs.
• nd_outputs: A numeric vector containing the indices of non-discretionary outputs.
• ud_inputs: A numeric vector containing the indices of undesirable (good) inputs.
• ud_outputs: A numeric vector containing the indices of undesirable (bad) outputs.

Returns

An object of class deadata

Examples

data("Coll_Blasco_2006")
data_example <- make_deadata(datadea = Coll_Blasco_2006,
                             ni = 2, 
                             no = 2)
# This is the same as:
data_example <- make_deadata(Coll_Blasco_2006,
                             inputs = 2:3, 
                             outputs = 4:5)
# And the same as:
dmunames <- c("A", "B", "C", "D", "E", "F")
nd <- length(dmunames) # Number of DMUs
inputnames <- c("Employees", "Capital")
ni <- length(inputnames) # Number of Inputs
outputnames <- c("Vehicles", "Orders")
no <- length(outputnames) # Number of Outputs
inputs <- matrix(c(8, 8, 11, 15, 14, 12, 12, 13, 11, 18, 18, 20),
                 nrow = ni, ncol = nd, dimnames = list(inputnames, dmunames))
outputs <- matrix(c(14, 20, 25, 42, 8, 30, 25, 8, 40, 22, 24, 30),
                  nrow = no, ncol = nd, dimnames = list(outputnames, dmunames))
data_example <- make_deadata(inputs = inputs,
                             outputs = outputs)                
# If the first input is a non-controllable input:
data_example <- make_deadata(Coll_Blasco_2006,
                             inputs = 2:3,
                             outputs = 4:5, 
                             nc_inputs = 1)
# If the second output is a non-discretionary output:
data_example <- make_deadata(Coll_Blasco_2006,
                             inputs = 2:3, 
                             outputs = 4:5, 
                             nd_outputs = 2)
# If the second input is a non-discretionary input and the second output is an undesirable:
data_example <- make_deadata(Coll_Blasco_2006,
                             inputs = 2:3, 
                             outputs = 4:5, 
                             nd_inputs = 2, 
                             ud_outputs = 2)

Author(s)

Vicente Coll-Serrano (vicente.coll@uv.es ). Quantitative Methods for Measuring Culture (MC2). Applied Economics.

Vicente Bolós (vicente.bolos@uv.es ). Department of Business Mathematics

Rafael Benítez (rafael.suarez@uv.es ). Department of Business Mathematics

University of Valencia (Spain)