View source: R/make_deadata_fuzzy.R
make_deadata_fuzzy | R Documentation |
This function creates, from a data frame, a deadata_fuzzy
structure, which is as list with fields input
, output
and
dmunames
. At the same time, input
and output
are lists with fields
mL
, mR
, dL
and dR
.
make_deadata_fuzzy(datadea,
dmus = 1,
inputs.mL = NULL,
inputs.mR = NULL,
inputs.dL = NULL,
inputs.dR = NULL,
outputs.mL = NULL,
outputs.mR = NULL,
outputs.dL = NULL,
outputs.dR = NULL,
nc_inputs = NULL,
nc_outputs = NULL,
nd_inputs = NULL,
nd_outputs = NULL,
ud_inputs = NULL,
ud_outputs = NULL)
datadea |
Data frame with DEA data. |
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 |
inputs.mL |
Where are (columns) the Alternatively to |
inputs.mR |
Where are (columns) the Alternatively to |
inputs.dL |
Where are (columns) the Alternatively to |
inputs.dR |
Where are (columns) the Alternatively to |
outputs.mL |
Analogous to |
outputs.mR |
Analogous to |
outputs.dL |
Analogous to |
outputs.dR |
Analogous to |
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. |
An object of class deadata_fuzzy
.
# Example 1. If inputs and/or outputs are symmetric triangular fuzzy numbers
data("Leon2003")
data_example <- make_deadata_fuzzy(datadea = Leon2003,
inputs.mL = 2,
inputs.dL = 3,
outputs.mL = 4,
outputs.dL = 5)
# Example 2. If inputs and/or outputs are non-symmetric triangular fuzzy numbers
data("Kao_Liu_2003")
data_example <- make_deadata_fuzzy(Kao_Liu_2003,
inputs.mL = 2,
outputs.mL = 3:7,
outputs.dL = c(NA, NA, 8, NA, 10),
outputs.dR = c(NA, NA, 9, NA, 11))
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