maximal_friends {deaR}

Maximal friends of a set of DMUs.

Description

Finds the maximal friends subsets of a given set of DMUs, according to Tone (2010). It uses an ascending algorithm in order to find directly maximal subsets.

Usage

maximal_friends(datadea,
             dmu_ref = NULL,
             rts = c("crs", "vrs", "nirs", "ndrs"),
             tol = 1e-6,
             silent = FALSE)

Arguments

datadea

A deadata object with n DMUs, m inputs and s outputs.

dmu_ref

A numeric vector containing which DMUs are the evaluation reference set, i.e. the cluster of DMUs from which we want to find maximal friends. If NULL (default), all DMUs are considered.

rts

A string, determining the type of returns to scale, equal to "crs" (constant), "vrs" (variable), "nirs" (non-increasing) or "ndrs" (non-decreasing).

tol

Numeric, a tolerance margin for checking efficiency. It is 1e-6 by default.

silent

Logical, if FALSE (default) steps are printed.

Value

A list with numeric vectors representing maximal friends subsets of DMUs.

Author(s)

Vicente Coll-Serrano ([e-mail]). Quantitative Methods for Measuring Culture (MC2). Applied Economics.

Vicente Bolós ([e-mail]). Department of Business Mathematics

Rafael Benítez ([e-mail]). Department of Business Mathematics

University of Valencia (Spain)

References

Tone, K. (2010). "Variations on the theme of slacks-based measure of efficiency in DEA", European Journal of Operational Research, 200, 901-907. doi:10.1016/j.ejor.2009.01.027

See Also

is.friends, model_sbmeff

Examples

## Not run: 
data("PFT1981")
datadea <- make_deadata(PFT1981,
                        ni = 5,
                        no = 3)
# We find maximal friends of a cluster formed by the first 20 DMUs
result <- maximal_friends(datadea = datadea,
                          dmu_ref = 1:20)

## End(Not run)