On approximate Monetary Unit Sampling
AbstractMonetary Unit Sampling (MUS), also known as Dollar-Unit Sampling, is a popular sampling strategy in Auditing, in which all units are to be randomly selected with probabilities proportional to the book value. However, if units sizes have very large variability, no vector of probabilities exists fulfilling the requirement that all probabilities are proportional to the associated book values. In this note we propose a Mathematical Optimization approach to address this issue. An optimization program is posed, structural properties of the optimal solution are analyzed, and an algorithm yielding the optimal solution in time and space linear to the number of population units is given.
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Bibliographic InfoArticle provided by Elsevier in its journal European Journal of Operational Research.
Volume (Year): 217 (2012)
Issue (Month): 2 ()
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Web page: http://www.elsevier.com/locate/eor
Nonlinear programming; Monetary Unit Sampling; Statistical sampling; Karush–Kuhn–Tucker conditions;
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- R. Blanquero & E. Carrizosa & E. Conde, 2006. "Inferring Efficient Weights from Pairwise Comparison Matrices," Computational Statistics, Springer, vol. 64(2), pages 271-284, October.
- Carrizosa, Emilio, 2010. "Unequal probability sampling from a finite population: A multicriteria approach," European Journal of Operational Research, Elsevier, vol. 201(2), pages 500-504, March.
- S. Illeris & G. Akehurst, 2002. "Introduction," The Service Industries Journal, Taylor & Francis Journals, vol. 22(1), pages 1-3, January.
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