Statistical Indicators for the Optimal Prediction of Failure Times of Reliability Stochastic Systems: A Rational Expectations-Like Approach

37 Pages Posted: 14 Sep 2022

See all articles by Jorgen Vitting Andersen

Jorgen Vitting Andersen

CES, Université Paris 1 Panthéon-Sorbonne

Roy Cerqueti

University Sapienza Rome

Jessica Riccioni

University of Rome I - Sapienza University of Rome, Department of Earth Sciences and Forecasting Research Center, Prevention and Control of Geological Risks

Date Written: June 23, 2022

Abstract

The estimation of the optimal failure time of stochastic systems is the aim of this paper. We are in the field of reliability theory, and we merge the Bayesian-like method of estimating the failure time of the so-called k-out-of-n systems with rational expectations-like expectations, thus obtaining a new forecasting method and innovative and original results. To do this, we simulate the path of two sets of systems from zero time to failure time, using a series of statistical measures that allow us to compare the simulation procedures and understand which is the best predictive combination.

Keywords: Reliability theory, rational expectations, optimal failure time prediction

JEL Classification: C02, C13, C15

Suggested Citation

Vitting Andersen, Jorgen and Cerqueti, Roy and Riccioni, Jessica, Statistical Indicators for the Optimal Prediction of Failure Times of Reliability Stochastic Systems: A Rational Expectations-Like Approach (June 23, 2022). Available at SSRN: https://ssrn.com/abstract=4201520 or http://dx.doi.org/10.2139/ssrn.4201520

Jorgen Vitting Andersen

CES, Université Paris 1 Panthéon-Sorbonne ( email )

Maison des Sciences Economiques
106-112 Boulevard de l'Hôpital 75647 Paris Cedex
Paris, 75647
France

Roy Cerqueti

University Sapienza Rome ( email )

Piazzale Aldo Moro 5
Roma, Rome 00185
Italy

Jessica Riccioni (Contact Author)

University of Rome I - Sapienza University of Rome, Department of Earth Sciences and Forecasting Research Center, Prevention and Control of Geological Risks ( email )

Rome
Italy

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