Numerous statistical models do not have explicitly known distribution functions. Because of this, the study of properties of the cumulative residual (past) inaccuracy measures using distribution function-based approach are difficult. Further, it is well-known that in modeling and analyzing statistical data, an equivalent alternative to distribution function is quantile function. The objective of this paper is to introduce and study quantile versions of the cumulative residual (past) inaccuracy measures and their dynamic forms. We obtain some bounds, relations with other quantile-based reliability measures, monotonicity results and characterizations. Various examples are provided to show the importance of the proposed quantile-based measures and the associated results. (C) 2018 Elsevier B.V. All rights reserved.
机构:
Virginia Commonwealth Univ, Stat Sci & Operat Res, Med Coll Virginia Campus, Richmond, VA 23284 USAVirginia Commonwealth Univ, Stat Sci & Operat Res, Med Coll Virginia Campus, Richmond, VA 23284 USA
Chen, Xi
Kim, Kyoung-Kuk
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Korea Adv Inst Sci & Technol, Ind & Syst Engn, Daejeon 305701, South KoreaVirginia Commonwealth Univ, Stat Sci & Operat Res, Med Coll Virginia Campus, Richmond, VA 23284 USA