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November 10, 2025 20:16
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Benchmarking do DEA para o Juarez
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| # Install the Benchmarking package if you haven't already | |
| # install.packages("Benchmarking") | |
| # Load the library | |
| library(Benchmarking) | |
| # Sample data: inputs (x) and outputs (y) for a set of DMUs | |
| # Example from the package documentation | |
| x <- matrix(c(100, 200, 300, 500, 100, 200, 600), ncol = 1) | |
| y <- matrix(c(75, 100, 300, 400, 25, 50, 400), ncol = 1) | |
| # Run the DEA model (e.g., input-oriented, VRS or CRS) | |
| # The 'dea' function returns an object of class 'Farrell' | |
| # We'll use VRS (Variable Returns to Scale) as an example | |
| e <- Benchmarking::dea(x, y, RTS = "VRS", ORIENTATION = "in") | |
| e$eff | |
| # Get the peers for each DMU | |
| # The 'peers' function returns a matrix where each row corresponds to a DMU, | |
| # and the columns list the indices (or names, if specified) of its peers. | |
| # Efficient DMUs are their own peers. | |
| peers_list <- peers(e, NAMES = TRUE) | |
| # Print the peers | |
| print(peers_list) | |
| # To get the contribution (lambda values) of each peer, you can use the 'get.peers.lambda' function | |
| lambda_list <- get.peers.lambda(e) | |
| # Print the lambda values | |
| print(lambda_list) |
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install.packages("farrell")
https://cran.r-project.org/web/packages/farrell/vignettes/Intro.html
library(farrell)
farrell()
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The peers(e) function will return the indices (or names) of the efficient DMUs that form the benchmark for each evaluated DMU.
The get.peers.lambda(e) function provides a list where each element corresponds to a DMU, listing its peers and the associated (\lambda ) weight. The (\lambda ) values represent the intensity variables indicating the contribution of each peer to the inefficient DMU's performance target.
This approach allows you to identify exactly which efficient units a specific inefficient DMU should emulate to become efficient.