summary.dea: Summary conventional DEA models.
In deaR: Conventional and Fuzzy Data Envelopment Analysis

summary.dea

R Documentation

Summary conventional DEA models.

Description

Summary of the results obtained by a conventional DEA model.

Usage

## S3 method for class 'dea'
summary(object, exportExcel = FALSE, filename = NULL, returnList = FALSE, ...)

Arguments

`object`	An object of class `"dea"` obtained by a DEA model function.
`exportExcel`	Logical value. If TRUE (FALSE by default) the results are also exported to an Excel file.
`filename`	Character string. Absolute file name (including path) of the exported Excel file. If NULL, then the file name will be "ResultsDEA" + timestamp.xlsx.
`returnList`	Logical value. If TRUE then the results are given as a list of data frames. If FALSE (default) all the data frames are merged into a single data frame.
`...`	Ignored. Used for compatibility issues.

Value

Depending on the model it returns a single data.frame containing: efficiencies, slacks, lambdas, targets, references or a list of data.frames with the cross-efficiencies computed with different methods (Arbitrary, Method II or Method III (see CITA)) or, in case the model is a Malmquist index, a single data.frame with the coefficients for the different periods.

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)

References

Charnes, A.; Cooper, W.W.; Rhodes, E. (1981). "Evaluating Program and Managerial Efficiency: An Application of Data Envelopment Analysis to Program Follow Through", Management Science, 27(6), 668-697. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1287/mnsc.27.6.668")}

Examples

data("PFT1981") 
# Selecting DMUs in Program Follow Through (PFT)
PFT <- PFT1981[1:49, ] 
PFT <- make_deadata(PFT, 
                    inputs = 2:6, 
                    outputs = 7:9 )
eval_pft <- model_basic(PFT, 
                        orientation = "io", 
                        rts = "crs")
summary(eval_pft)

deaR documentation built on May 2, 2023, 5:13 p.m.