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On the median residual lifetime and its aging properties: A characterization theorem and applications

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  • Rosa E. Lillo

Abstract

This paper is devoted to study several aspects of the median residual life function (MERLF). In reliability studies, it is well known that, although the MERLF have several advantages over the mean residual life function (MRLF), the MRLF has the good property of uniquely determine a life distribution whereas either the median residual life function (MERLF) or an α‐percentile residual life do not have such good property. We shall give a characterization result where knowledge of both the MERLF and the survival function on an interval does uniquely determine the distribution. Moreover, in order to apply this characterization in practical situations, we propose a method to estimate the necessary information of the survival function. Relationships between analytical properties of the survival function and its associated MERLF are also obtained. Bryson and Siddiqui [J Am Statist Assoc 64 (1969), 1472–1483] proved relationships among seven criteria for aging, out of which two contained the MRLF (decreasing MRLF and net decreasing MRLF). In this paper, we prove that the same pattern of relationships holds if the MRLF is replaced by the MERLF. We also examine the aging criteria corresponding to an increasing MERLF and show that there is no relation between the behavior (increasing or decreasing) of the MERLF and of the MRLF. © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2005

Suggested Citation

  • Rosa E. Lillo, 2005. "On the median residual lifetime and its aging properties: A characterization theorem and applications," Naval Research Logistics (NRL), John Wiley & Sons, vol. 52(4), pages 370-380, June.
    • Handle: RePEc:wly:navres:v:52:y:2005:i:4:p:370-380
    DOI: 10.1002/nav.20082
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    References listed on IDEAS

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    1. Barry C. Arnold & Patrick L. Brockett, 1983. "Technical Note—When Does the βth Percentile Residual Life Function Determine the Distribution?," Operations Research, INFORMS, vol. 31(2), pages 391-396, April.
    2. Harry Joe & Frank Proschan, 1984. "Percentile Residual Life Functions," Operations Research, INFORMS, vol. 32(3), pages 668-678, June.
    3. Kottas A. & Gelfand A.E., 2001. "Bayesian Semiparametric Median Regression Modeling," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 1458-1468, December.
    4. David C. Schmittlein & Donald G. Morrison, 1981. "The Median Residual Lifetime: A Characterization Theorem and an Application," Operations Research, INFORMS, vol. 29(2), pages 392-399, April.
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    Cited by:

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    2. M. Kayid & M. Shafaei Noughabi & A. M. Abouammoh, 2020. "A Nonparametric Estimator of Bivariate Quantile Residual Life Model with Application to Tumor Recurrence Data Set," Journal of Classification, Springer;The Classification Society, vol. 37(1), pages 237-253, April.

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