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Annals of Operations Research

, Volume 274, Issue 1–2, pp 291–308 | Cite as

How adding new information modifies the estimation of the mean and the variance in PERT: a maximum entropy distribution approach

  • A. Hernández-Bastida
  • M. P. Fernández-SánchezEmail author
Original Research
  • 105 Downloads

Abstract

This paper presents an alternative method to estimate the mean and the variance when using the program evaluation and review technique (PERT). Different levels of information, provided by an expert, are considered in the PERT scenario to obtain the values of the mean and the variance by means of a maximum entropy distribution approach. In our opinion, the information to be taken into account should be only that supplied by the expert. We also perform a numerical analysis to examine how the estimates vary if new information is added. From this, we conclude that the inclusion of new information (even for analytic purposes) produces significant changes in the estimates proposed.

Keywords

PERT Unimodality Maximum entropy Beta distribution 

Notes

Acknowledgements

AHB thanks to the Project ECO2017-85577-P. The authors gratefully acknowledge the helpful comments of the anonymous reviewers and the editor-in-chief.

Compliance with ethical standards

Conflict of interest

The authors report no conflicts of interest. The authors are solely responsible for the content and writing of this paper.

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Quantitative Methods in Economics, Faculty of EconomicsUniversity of GranadaGranadaSpain

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