Audit sampling with jfa

jfa implements the standard audit sampling workflow in R, supporting both classical and Bayesian inference. The package provides five main functions that map to the sequential steps of an audit: specifying a prior, calculating sample size, selecting items, evaluating misstatement, and generating a report.

What’s covered#

• Basics – installation, workflow overview, and example dataset (BuildIt)
• Construct a prior distribution – auditPrior() with likelihood and method arguments
• Calculate the minimum sample size – planning() with materiality, expected errors, and likelihood
• Select items from the population – selection() with random, cell, or fixed-interval sampling
• Evaluate the misstatement – evaluation() with classical or Bayesian methods
• Create a report – report() generating an HTML summary of results