On multiply monotone distributions, continuous or discrete, with applications
This paper is concerned with the class of distributions, continuous or discrete, whose shape is monotone of finite integer order t. A characterization is presented as a mixture of a minimum of t independent uniform distributions. Then, a comparison of t-monotone distributions is made using the s-convex stochastic orders. A link is also pointed out with an alternative approach to monotonicity based on a stationary-excess operator. Finally, the monotonicity property is exploited to reinforce the classical Markov and Lyapunov inequalities. The results are illustrated by several applications to insurance.
|Date of creation:||2013|
|Date of revision:|
|Publication status:||Published, Journal of Applied Probability, 2013, 50, 3, 603-907|
|Note:||View the original document on HAL open archive server: http://hal.archives-ouvertes.fr/hal-00750562|
|Contact details of provider:|| Web page: https://hal.archives-ouvertes.fr/|
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Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Lefèvre, Claude & Loisel, Stéphane, 2010.
"Stationary-excess operator and convex stochastic orders,"
Insurance: Mathematics and Economics,
Elsevier, vol. 47(1), pages 64-75, August.
- Claude Lefèvre & Stéphane Loisel, 2010. "Stationary-excess operator and convex stochastic orders," Post-Print hal-00442047, HAL.
- Denuit, Michel & Lefevre, Claude & Mesfioui, M'hamed, 1999. "On s-convex stochastic extrema for arithmetic risks," Insurance: Mathematics and Economics, Elsevier, vol. 25(2), pages 143-155, November.
- Denuit, Michel & Vylder, Etienne De & Lefevre, Claude, 1999. "Extremal generators and extremal distributions for the continuous s-convex stochastic orderings," Insurance: Mathematics and Economics, Elsevier, vol. 24(3), pages 201-217, May.
- Denuit, Michel & Lefevre, Claude, 1997. "Some new classes of stochastic order relations among arithmetic random variables, with applications in actuarial sciences," Insurance: Mathematics and Economics, Elsevier, vol. 20(3), pages 197-213, October.
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