---
title: "Intro"
output: rmarkdown::html_vignette
vignette: >
%\VignetteIndexEntry{Intro}
%\VignetteEngine{knitr::rmarkdown}
%\VignetteEncoding{UTF-8}
---
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>"
)
```
The goal of farrell is to provide an interactive interface to Data Envelopment Analysis modeling in R. The farrell package is built upon [Benchmarking](https://CRAN.R-project.org/package=Benchmarking).
## Installation
You can install the farrell package from CRAN with:
```{r, eval = FALSE}
install.packages("farrell")
```
## Example
You can run:
```{r, eval=FALSE}
library(farrell)
farrell()
```
or if you're working on RStudio, just click on __Addins__ then __farrell__.
## Data Loading:
Hit __Browse...__ to upload your data frame in a csv format. All the inputs and outputs must be contained within the data frame (each column for each input/output). Further, the data frame needs to contain an identification column in order to identify Decision Making Units. It can be a numeric or a character column.
![](fig1.png)
In the following examples, we use the mtcars data frame which has been exported in a csv format with an additional column: __cars name__.
![](fig2.png)
## Model Tuning
![](fig3.png)
Within the Model Tuning tab, you will select the input and output variables, then you determine your identification column. Then you choose the Returns to Scale assumption between: crs, vrs, irs, drs, add and fdh. After that, you determine the orientation of the model, whether input or output. Finally, hit __Calculate Efficiency__ to get the results.
Let's for example consider __mpg__ and __disp__ as the output variables and __wt__ as input. We choose __cars name__ as the identification column and model an input-oriented model with crs assumption.
![](fig4.png)
## Efficiency Results
The Efficiency Results tab displays the efficiency scores along with the peers for each unit in a descending order. You have the ability to download the result in a csv format. The tab also provides a summary of the distribution of the efficiency scores.
![](fig5.png)
## Lambdas
In the Lambdas tab, you get the contribution of the peers to the inefficient units' score.
![](fig6.png)
## Scale Efficiency
The SE tab provides the Scale Efficiency score of each DMU under consideration.
![](fig7.png)
## Slacks
The Slacks tab displays a data frame containing the sum of the slacks and the slacks for each input/output variables.
![](fig8.png)
## Citation
If you use the farrell package in your publications or teaching activities, please cite it as follows:
Mohamed El Fodil Ihaddaden (2020). farrell: Interactive
Interface to Data Envelopment Analysis Modeling. R package version 0.2.0.
https://github.com/feddelegrand7/farrell
A BibTeX entry for LaTeX users is
@Manual{,
title = {farrell: Interactive Interface to Data Envelopment Analysis Modeling},
author = {Mohamed El Fodil Ihaddaden},
note = {R package version 0.2.0},
year={2020},
url = {https://github.com/feddelegrand7/farrell},
}
## Code of Conduct
Please note that the farrell project is released with a [Contributor Code of Conduct](https://contributor-covenant.org/version/2/0/CODE_OF_CONDUCT.html). By contributing to this project, you agree to abide by its terms.