jfa: Bayesian and Classical Audit Sampling

Implements the audit sampling workflow as discussed in Derks et al. (2019) <doi:10.31234/osf.io/9f6ub>. The package makes it easy for an auditor to plan a statistical sample, select the sample from the population, and evaluate the misstatement in the sample using various methods compliant with the International Standards on Auditing. Furthermore, the package implements Bayesian equivalents of these methods.

Version: 0.6.0
Imports: extraDistr, graphics, stats
Suggests: kableExtra, knitr, MUS, rmarkdown, testthat
Published: 2021-09-22
Author: Koen Derks ORCID iD [aut, cre]
Maintainer: Koen Derks <k.derks at nyenrode.nl>
BugReports: https://github.com/koenderks/jfa/issues
License: GPL-3
URL: https://koenderks.github.io/jfa/, https://github.com/koenderks/jfa
NeedsCompilation: no
Language: en-US
Citation: jfa citation info
Materials: README NEWS
CRAN checks: jfa results

Documentation:

Reference manual: jfa.pdf
Vignettes: Get started
Workflow: Classical audit sampling
Workflow: Bayesian audit sampling
Planning: Prior distributions
Selection: Sampling methodology
Evaluation: Estimating misstatement
Evaluation: Testing misstatement
Evaluation: Bayes factors using summary statistics

Downloads:

Package source: jfa_0.6.0.tar.gz
Windows binaries: r-devel: jfa_0.6.0.zip, r-release: jfa_0.6.0.zip, r-oldrel: jfa_0.6.0.zip
macOS binaries: r-release (arm64): jfa_0.6.0.tgz, r-release (x86_64): jfa_0.6.0.tgz, r-oldrel: jfa_0.6.0.tgz
Old sources: jfa archive

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