MUS-package {MUS} | R Documentation |
Monetary Unit Sampling and Estimation Methods, Widely Used in Auditing
Description
Sampling and evaluation methods to apply Monetary Unit Sampling (or in older literature Dollar Unit Sampling) during an audit of financial statements.
Details
Monetary Unit Sampling (MUS), also known as Dollar Unit Sampling (DUS) or Probability-Proportional-to-Size Sampling (PPS), is a sampling approach that is widely used in auditing.
This package was written mainly for a research project. However, it should be possible to use the methods for practical auditing, too. Furthermore, the package comes with ABSOLUTELY NO WARRANTY. Use it at your own risk!
You have to walk through four steps: 1. Plan a sample and determine the sample size, use function: MUS.planning 2. Extract the sample, use function: MUS.extract 3. Audit the extracted sample (e.g. by asking for debtor confirmations). 4. Evaluate the audited sample, use function: MUS.evaluation
Author(s)
Henning Prömpers, André Guimarães Maintainer: Henning Prömpers <henning@proempers.net>
See Also
MUS.planning
for planning a sample,
MUS.extraction
for extraction of the planned sample and
MUS.evaluation
for evaluation of the extracted and
audited sample.
Examples
## Simple Example
library(MUS)
# Assume 500 invoices, each between 1 and 1000 monetary units
example.data.1 <- data.frame(book.value=round(runif(n=500, min=1,
max=1000)))
# Plan a sample and cache it
plan.results.simple <- MUS.planning(data=example.data.1,
tolerable.error=100000, expected.error=20000)
# Extract a sample and cache it (no high values exist in this example)
extract.results.simple <- MUS.extraction(plan.results.simple)
# Copy book values into a new column audit values
audited.sample.simple <- extract.results.simple$sample
audited.sample.simple <- cbind(audited.sample.simple,
audit.value=audited.sample.simple$book.value)
# Edit manually (if any audit difference occur)
#audited.sample.simple <- edit(audited.sample.simple)
# Evaluate the sample, cache and print it
evaluation.results.simple <- MUS.evaluation(extract.results.simple,
audited.sample.simple)
print(evaluation.results.simple)