--- title: Get started with the jfa package author: Koen Derks output: rmarkdown::html_vignette: toc: true toc_depth: 3 vignette: > %\VignetteIndexEntry{Get started with the jfa package} %\VignetteEngine{knitr::rmarkdown} %\VignetteDepends{jfa} %\VignetteKeywords{audit, jfa} %\VignettePackage{jfa} %\VignetteEncoding{UTF-8} --- ## Introduction Welcome to the 'Get started' page of the **jfa** package. **jfa** is an R package that provides Bayesian and classical statistical methods for audit sampling, data auditing, and algorithm auditing. This page points you to the vignettes accompanying each of these three subjects. ## Audit sampling Firstly, **jfa** facilitates statistical audit sampling. That is, the package provides functions for planning, performing, and evaluating an audit sample compliant with international standards on auditing. - [Audit sampling: Get started](https://koenderks.github.io/jfa/articles/audit-sampling.html) - [Creating a prior distribution for audit sampling](https://koenderks.github.io/jfa/articles/creating-prior.html) - [Planning statistical audit samples](https://koenderks.github.io/jfa/articles/sample-planning.html) - [Selecting statistical audit samples](https://koenderks.github.io/jfa/articles/sample-selection.html) - [Evaluating statistical audit samples](https://koenderks.github.io/jfa/articles/sample-evaluation.html) - [Evaluating audit samples with partial misstatements](https://koenderks.github.io/jfa/articles/sample-evaluation-partial.html) - [Walkthrough of the classical audit sampling workflow](https://koenderks.github.io/jfa/articles/sampling-workflow.html) - [Walkthrough of the Bayesian audit sampling workflow](https://koenderks.github.io/jfa/articles/bayesian-sampling-workflow.html) ## Data auditing Secondly, **jfa** facilitates statistical data auditing. That is, the package includes functions for auditing data, such as testing the distribution of first digits of a data set against Benford's law, or assessing whether a data set includes an unusual amount of repeated values. - [Data auditing: Get started](https://koenderks.github.io/jfa/articles/data-auditing.html) - [Digit analysis](https://koenderks.github.io/jfa/articles/digit-analysis.html) ## Algorithm auditing Finally, **jfa** facilitates statistical algorithm auditing. That is, the package implements functions for auditing algorithms, such as computing fairness metrics and testing the equality of parity metrics across protected groups. - [Algorithm auditing: Get started](https://koenderks.github.io/jfa/articles/algorithm-auditing.html) - [Algorithmic fairness](https://koenderks.github.io/jfa/articles/model-fairness.html)