New maximum entropy methods for modeling lifetime distributions |
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| Authors: | Majid Asadi Nader Ebrahimi Ehsan S. Soofi Somayeh Zarezadeh |
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| Affiliation: | 1. Department of Statistics, University of Isfahan, , Isfahan, 81744 Iran;2. Division of Statistics, Northern Illinois University, , DeKalb, Illinois, 60155;3. Lubar School of Business, University of Wisconsin‐Milwaukee, , Milwaukee, Wisconsin, 53201;4. Department of Statistics, Shiraz University, , Shiraz, 71454 Iran |
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| Abstract: | This article introduces two new maximum entropy (ME) methods for modeling the distribution of time to an event. One method is within the classical ME framework and provides characterizations of change point models such as the piecewise exponential distribution. The second method uses the entropy of the equilibrium distribution (ED) for the objective function and provides new characterizations of the exponential, Weibull, Pareto, and uniform distributions. With the same moment constraints, the classical ME and the maximum ED entropy algorithms generate different models for the interarrival time. © 2014 Wiley Periodicals, Inc. Naval Research Logistics 61: 427–434, 2014 |
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| Keywords: | change point distribution entropy equilibrium distribution Kullback– Leibler information mean residual |
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