Reexamining Discrete Approximations to Continuous Distributions

Robert K. Hammond () and J. Eric Bickel ()
Additional contact information
Robert K. Hammond: Graduate Program in Operations Research and Industrial Engineering, University of Texas at Austin, Austin, Texas 78712
J. Eric Bickel: Graduate Program in Operations Research and Industrial Engineering, University of Texas at Austin, Austin, Texas 78712

Decision Analysis, 2013, vol. 10, issue 1, 6-25

Abstract: Discretization is a common decision analysis technique for which many methods are described in the literature and employed in practice. The accuracy of these methods is typically judged by how well they match the mean, variance, and possibly higher moments of the underlying continuous probability distribution. Previous authors have analyzed the accuracy of differing discretization methods across a limited set of distributions drawn from particular families (e.g., the bell-shaped beta distributions). In this paper, we extend this area of research by (i) using the Pearson distribution system to consider a wide range of distribution shapes and (ii) including common, but previously unexplored, discretization methods. In addition, we propose new three-point discretizations tailored to specific distribution types that improve upon existing methods.

Keywords: probability discretization; subjective probability; decision analysis; Pearson distribution; Swanson--Megill; practice (search for similar items in EconPapers)
Date: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (14)

Downloads: (external link)
http://dx.doi.org/10.1287/deca.1120.0260 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:inm:ordeca:v:10:y:2013:i:1:p:6-25

Access Statistics for this article

More articles in Decision Analysis from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().