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. 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.
The most recent jfa release can be installed from CRAN via:
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")
jfa is an open-source project that aims to be useful for the audit community. Your help in benchmarking and extending the package is therefore greatly appreciated. Contributing does not have to take much time or knowledge, and there is extensive information available about it on the Wiki of this repository.
If you are willing to contribute to the improvement of the package by adding a benchmark, please check out the Wiki page on how to contribute a benchmark to jfa. If you are willing to contribute to the improvement of the package by adding a new statistical method, please check the Wiki page on how to contribute a new method to jfa.
If you use jfa, please cite the software as follows:
Derks, K. (2022). jfa: Statistical methods for auditing. https://cran.r-project.org/package=jfa