Stochastic comparisons for time transformed exponential models
Different sufficient conditions for stochastic comparisons between random vectors have been described in the literature. In particular, conditions for the comparison of random vectors having the same copula, i.e., the same dependence structure, may be found in Müller and Scarsini (2001). Here we provide conditions for the comparison, in the usual stochastic order sense and in other weaker stochastic orders, of two time transformed exponential bivariate lifetimes having different copulas. Some examples of applications are provided too.
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- Müller, Alfred & Scarsini, Marco, 2005.
"Archimedean copulæ and positive dependence,"
Journal of Multivariate Analysis,
Elsevier, vol. 93(2), pages 434-445, April.
- Alfred Müller & Marco Scarsini, 2003. "Archimedean Copulae and Positive Dependence," ICER Working Papers - Applied Mathematics Series 25-2003, ICER - International Centre for Economic Research.
- Marco Scarsini & Alfred Muller, 2005. "Archimedean copulae and positive dependence," Post-Print hal-00539618, HAL.
- Bassan, Bruno & Spizzichino, Fabio, 2005. "Bivariate survival models with Clayton aging functions," Insurance: Mathematics and Economics, Elsevier, vol. 37(1), pages 6-12, August.
- Bassan, Bruno & Spizzichino, Fabio, 2005. "Relations among univariate aging, bivariate aging and dependence for exchangeable lifetimes," Journal of Multivariate Analysis, Elsevier, vol. 93(2), pages 313-339, April.
- Pellerey, Franco, 2000. "Random vectors with HNBUE-type marginal distributions," Statistics & Probability Letters, Elsevier, vol. 50(3), pages 265-271, November.
- An, Mark Yuying, 1998.
"Logconcavity versus Logconvexity: A Complete Characterization,"
Journal of Economic Theory,
Elsevier, vol. 80(2), pages 350-369, June.
- An, Mark Yuying, 1995. "Logconcavity versus Logconvexity: A Complete Characterization," Working Papers 95-03, Duke University, Department of Economics.
- Nelsen, Roger B., 1997. "Dependence and Order in Families of Archimedean Copulas," Journal of Multivariate Analysis, Elsevier, vol. 60(1), pages 111-122, January.
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