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On a new NBUE property in multivariate sense: An application


  • Fernández-Ponce, J.M.
  • Pellerey, F.
  • Rodríguez-Griñolo, M.R.


Since multivariate lifetime data frequently occur in applications, various properties of multivariate distributions have been previously considered to model and describe the main concepts of aging commonly considered in the univariate setting. The generalization of univariate aging notions to the multivariate case involves, among other factors, appropriate definitions of multivariate quantiles and related notions, which are able to correctly describe the intrinsic characteristics of the concepts of aging that should be generalized, and which provide useful tools in the applications. A new multivariate version of the well-known New Better than Used in Expectation univariate aging notion is provided, by means of the concepts of the upper corrected orthant and multivariate excess-wealth function. Some of its properties are described, with particular attention paid to those that can be useful in the analysis of real data sets. Finally, through an example it is illustrated how the new multivariate aging notion influences the final results in the analysis of data on tumor growth from the Comprehensive Cohort Study performed by the German Breast Cancer Study Group.

Suggested Citation

  • Fernández-Ponce, J.M. & Pellerey, F. & Rodríguez-Griñolo, M.R., 2011. "On a new NBUE property in multivariate sense: An application," Computational Statistics & Data Analysis, Elsevier, vol. 55(12), pages 3283-3294, December.
  • Handle: RePEc:eee:csdana:v:55:y:2011:i:12:p:3283-3294

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    References listed on IDEAS

    1. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    2. Fernandez-Ponce, J. M. & Infante-Macias, R. & Munoz-Perez, J., 1996. "Characterization of lifetime distributions based on a quantile dispersion measure," Computational Statistics & Data Analysis, Elsevier, vol. 21(5), pages 547-561, May.
    3. Shaked, Moshe & Shanthikumar, J. George, 1991. "Dynamic multivariate aging notions in reliability theory," Stochastic Processes and their Applications, Elsevier, vol. 38(1), pages 85-97, June.
    4. Gupta, Ramesh C. & Peng, Cheng, 2009. "Estimating reliability in proportional odds ratio models," Computational Statistics & Data Analysis, Elsevier, vol. 53(4), pages 1495-1510, February.
    5. Wang, You-Gan & Shao, Quanxi & Zhu, Min, 2009. "Quantile regression without the curse of unsmoothness," Computational Statistics & Data Analysis, Elsevier, vol. 53(10), pages 3696-3705, August.
    6. Johnson, N. L. & Kotz, Samuel, 1975. "A vector multivariate hazard rate," Journal of Multivariate Analysis, Elsevier, vol. 5(1), pages 53-66, March.
    7. Belzunce, F. & Castano, A. & Olvera-Cervantes, A. & Suarez-Llorens, A., 2007. "Quantile curves and dependence structure for bivariate distributions," Computational Statistics & Data Analysis, Elsevier, vol. 51(10), pages 5112-5129, June.
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