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jfa: Statistical Methods for Auditing

jfa is an R package that provides statistical methods for auditing. The package includes functions for planning, performing, evaluating, and reporting audit samples compliant with international auditing standards, as well as functions for auditing data, such as testing the distribution of leading digits against Benford’s law, and functions for auditing algorithms with respect to fairness. In addition to offering classical (frequentist) methods, jfa also provides a straightforward implementation of their Bayesian counterparts.

The functionality of the jfa package and its intended workflow are implemented with a graphical user interface in the Audit module of JASP, a free and open-source software program for statistical analyses.



Latest Release

The most recent jfa release can be installed from CRAN via:


Development Version

To install the development version from GitHub, first make sure that you can install the rstan package and C++ toolchain by following these instructions. Once rstan is successfully installed, you can install jfa from GitHub using the remotes package by executing the following in R:

# install.packages("remotes")
remotes::install_github("koenderks/jfa", INSTALL_opts = "--no-multiarch")


The jfa project is an open-source initiative with the objective of providing value to the audit community. Therefore, the collaboration and support of the community in benchmarking and expanding the package is greatly appreciated. Participating in this endeavor does not require extensive time or expertise, as comprehensive information can be found on the repository’s Wiki page.

Individuals who are interested in contributing to the validation of the package through the addition of a benchmark are encouraged to consult the Wiki page on how to contribute a benchmark to jfa. Similarly, individuals who wish to contribute to the improvement of the package by incorporating a statistical method are advised to review the Wiki page on how to contribute a method to jfa.


To obtain the preferred citation for jfa, run the following code in the R console:


#>  To cite jfa in publications, please use:
#>    Derks, K. (2023). jfa: Statistical methods for auditing. R package version 0.7.0.
#>  A BibTeX entry for LaTeX users is
#>    @Manual{jfa,
#>      title = {jfa: Statistical methods for auditing},
#>      author = {Koen Derks},
#>      year = {2023},
#>      note = {R package version 0.7.0},
#>      url = {},
#>    }