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Multivariate Convex Orderings, Dependence, and Stochastic Equality

Published online by Cambridge University Press:  14 July 2016

Marco Scarsini*
Affiliation:
Università D'Annunzio
*
Postal address: Dipartimento di Scienze, Università D'Annunzio, Viale Pindaro 42, I-65127 Pescara, Italy. e-mail address: [email protected]

Abstract

We consider the convex ordering for random vectors and some weaker versions of it, like the convex ordering for linear combinations of random variables. First we establish conditions of stochastic equality for random vectors that are ordered by one of the convex orderings. Then we establish necessary and sufficient conditions for the convex ordering to hold in the case of multivariate normal distributions and sufficient conditions for the positive linear convex ordering (without the restriction to multi-normality).

Type
Research Papers
Copyright
Copyright © Applied Probability Trust 1998 

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References

Arnold, B.C. (1987). Majorization and the Lorenz Order: A Brief Introduction. (Lecture Notes in Statistics.) Springer, New York.CrossRefGoogle Scholar
Baccelli, F., and Makowski, A.M. (1989). Multidimensional stochastic ordering and associated random variables. Operat. Res. 37, 478487.CrossRefGoogle Scholar
Bhandari, S.K. (1988). Multivariate majorization and directional majorization; positive results. Sankhyā A 50, 199204.Google Scholar
Bhattacharjee, M.C. (1991). Some generalized variability orderings among life distributions with reliability applications. J. Appl. Prob. 28, 374383.CrossRefGoogle Scholar
Bhattacharjee, M.C., and Sethuraman, J. (1990). Families of life distributions characterized by two moments. J. Appl. Prob. 27, 720725.CrossRefGoogle Scholar
Chang, C.-S., Chao, X.L., Pinedo, M., and Shantikumar, J. G. (1991). Stochastic convexity for multi-dimensional processes and its applications. IEEE Trans. Automatic Control 36, 13471355.CrossRefGoogle Scholar
Fishburn, P.C. (1980). Stochastic dominance and moments of distributions. Math. Operat. Res. 5, 94100.CrossRefGoogle Scholar
Fishburn, P.C., and Lavalle, I.H. (1995). Stochastic dominance on unidimensional grids. Math. Operat. Res. 20, 513525.CrossRefGoogle Scholar
Joe, H., and Verducci, J. (1993). Multivariate majorization by positive combinations. In Stochastic Inequalities. ed. Shaked, M. and Tong, Y. L. IMS Lecture Notes/Monograph Series, Hayward, CA. pp. 159181.Google Scholar
Johansen, S. (1972). A representation theorem for a convex cone of quasi convex functions. Math. Scand. 30, 297312.CrossRefGoogle Scholar
Johansen, S. (1974). The extremal convex functions. Math. Scand. 34, 6168.CrossRefGoogle Scholar
Koshevoy, G. (1995). Multivariate Lorenz majorization. Social Choice and Welfare 12, 93102.CrossRefGoogle Scholar
Koshevoy, G. (1996). Lorenz zonotope and multivariate majorization. To appear in Social Choice and Welfare CrossRefGoogle Scholar
Koshevoy, G., and Mosler, K. (1995). A geometrical approach to compare the variability of random vectors. Preprint. Universität der Bundeswehr Hamburg.Google Scholar
Koshevoy, G., and Mosler, K. (1996). The Lorenz zonoid of a multivariate distribution. J. Amer. Statist. Assoc. 91, 873882.CrossRefGoogle Scholar
Li, H., and Zhu, H. (1994). Stochastic equivalence of ordered random variables with applications in reliability theory. Statist. Prob. Lett. 20, 383393.CrossRefGoogle Scholar
Marshall, A.W., and Olkin, I. (1979). Inequalities: Theory of Majorization and Its Applications. Academic Press, New York.Google Scholar
Meester, L.E., and Shanthikumar, J.G. (1993). Regularity of stochastic processes: A theory based on directional convexity. Prob. Eng. Inf. Sci. 7, 343360.CrossRefGoogle Scholar
Mosler, K., and Scarsini, M. (1991). Some theory of stochastic dominance. In Stochastic Orderings and Decision under Risk. ed. Mosler, K. and Scarsini, M. IMS Lecture Notes/Monograph Series, Hayward, CA. pp. 261284.CrossRefGoogle Scholar
Mosler, K., and Scarsini, M. (1993). Stochastic Orders and Applications: A Classified Bibliography. (Lecture Notes in Economics and Mathematical Systems.) Springer, Berlin.CrossRefGoogle Scholar
O'Brien, G.L. (1984). Stochastic dominance and moment inequalities. Math. Operat. Res. 9, 475477.CrossRefGoogle Scholar
O'Brien, G.L., and Scarsini, M. (1991). Multivariate stochastic dominance and moments. Math. Operat. Res. 16, 382389.CrossRefGoogle Scholar
Rüschendorf, L. (1980). Inequalities for the expectation of Δ-monotone functions. Z. Wahrscheinlichkeitsth. 54, 341349.CrossRefGoogle Scholar
Sampson, A.R., and Whitaker, L.R. (1988). Positive dependence, upper sets, and multi-dimensional partitions. Math. Operat. Res. 13, 254264.CrossRefGoogle Scholar
Scarsini, M. (1988). Multivariate stochastic dominance with fixed dependence structure. Operat. Res. Lett. 7, 237240.CrossRefGoogle Scholar
Scarsini, M., and Shaked, M. (1990). Some conditions for stochastic equality. Nav. Res. Logist. 37, 617625.3.0.CO;2-L>CrossRefGoogle Scholar
Shaked, M., and Shanthikumar, J.G. (1994). Stochastic Orders and Their Applications. Academic Press, New York.Google Scholar
Tong, Y.L. (1990). The Multivariate Normal Distribution. Springer, New York.CrossRefGoogle Scholar