Run bootstrap on a DEA model to estimate bias corrected efficiency scores and confidence intervals
Arguments
- dea
An object of type pioneer_dea from
compute_dea()- alpha
One minus the confidence level required (defaults to 0.05)
- bw_rule
A string with the type of bandwidth rule to be used, or a number with the bandwidth parameter. See details.
- iterations
The number of bootstrap iterations to be performed
Details
In order to bootstrap a DEA model, you must first create a DEA model object using the
compute_dea() function. Note that you currently can only bootstrap models using
constant or variable returns to scale (RTS). If you try to bootstrap a model using another
RTS, the bootstrap will fail with an error message.
The bandwidth argument can be set to either ucv for unbiased cross validation,
silverman for the Silverman rule, or scott for the Scott rule. If you provide a
number, this will be used directly as the bandwidth parameter h. This can be useful
to replicate results where h is given, such as Simar & Wilson (1998). For most practical
applications of the bootstrap, the default of unbias cross validation is sensible.
Examples
if (FALSE) { # \dontrun{
# Get data
fare89 <- deaR::Electric_plants
# Estimate efficiency
mod <- compute_dea(fare89, 'Plant', c('Labor', 'Fuel', 'Capital'), 'Output', 'vrs', 'in')
# Run bootstrap
boot <- bootstrap_dea(mod, iterations = 2000)
} # }