compute_dea {pioneeR} | R Documentation |
Compute DEA
Description
Solve an input or output oriented DEA model under constant (crs
), variable (vrs
),
non-increasing (drs
), or non-decreasing (irs
) returns to scale.
Usage
compute_dea(
data,
input,
output,
id = NULL,
rts = c("crs", "vrs", "drs", "irs"),
orientation = c("in", "out"),
super = FALSE,
slack = FALSE,
peers = FALSE
)
Arguments
data |
Dataset to analyse. | ||||||||||||||||
input |
A character vector with input variables. | ||||||||||||||||
output |
A character vector with output variables. | ||||||||||||||||
id |
Optional. A string with the DMU id or name variable. Defaults to the rownames of the dataset. | ||||||||||||||||
rts |
Returns to scale.
| ||||||||||||||||
orientation |
Model orientation. | ||||||||||||||||
super |
If | ||||||||||||||||
slack |
If | ||||||||||||||||
peers |
If |
Value
A list of class pioneer_dea
.
Examples
# Load example data
fare89 <- deaR::Electric_plants
# Estimate efficiency
mod <- compute_dea(
data = fare89,
input = c("Labor", "Fuel", "Capital"),
output = "Output",
id = "Plant",
rts = "vrs",
orientation = "in"
)
# Print results
print(mod)
# Get summary
summary(mod)
# Convert to data frame
df <- as.data.frame(mod)
[Package pioneeR version 0.5.0 Index]