Stochastic orders in time transformed exponential models with applications

Xiaohu Li; Jianhua Lin

doi:10.1016/j.insmatheco.2011.02.002

Stochastic orders in time transformed exponential models with applications

Xiaohu Li
, Jianhua Lin

Department of Mathematical Sciences

Xiamen University

Research output: Contribution to journal › Article › peer-review

3 Scopus citations

Abstract

This paper studies expectations of a supermodular function of bivariate random risks following TTE models. Comparison of such expectations are conducted based on some stochastic orders of the involved univariate survival functions in the models, and also the upper orthant-convex order between two bivariate random risks in TTE models is built. This corrects Theorem 2.3 of Mulero et al. (2010) and invalidates some results there. Some applications in actuarial science are presented as well.

Original language	English
Pages (from-to)	47-52
Number of pages	6
Journal	Insurance: Mathematics and Economics
Volume	49
Issue number	1
DOIs	https://doi.org/10.1016/j.insmatheco.2011.02.002
State	Published - Jul 2011

Keywords

Concave
Stop loss transform order
Supermodular
Upper orthant-convex order

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10.1016/j.insmatheco.2011.02.002

Cite this

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title = "Stochastic orders in time transformed exponential models with applications",

abstract = "This paper studies expectations of a supermodular function of bivariate random risks following TTE models. Comparison of such expectations are conducted based on some stochastic orders of the involved univariate survival functions in the models, and also the upper orthant-convex order between two bivariate random risks in TTE models is built. This corrects Theorem 2.3 of Mulero et al. (2010) and invalidates some results there. Some applications in actuarial science are presented as well.",

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AU - Lin, Jianhua

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AB - This paper studies expectations of a supermodular function of bivariate random risks following TTE models. Comparison of such expectations are conducted based on some stochastic orders of the involved univariate survival functions in the models, and also the upper orthant-convex order between two bivariate random risks in TTE models is built. This corrects Theorem 2.3 of Mulero et al. (2010) and invalidates some results there. Some applications in actuarial science are presented as well.

KW - Concave

KW - Stop loss transform order

KW - Supermodular

KW - Upper orthant-convex order

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VL - 49

SP - 47

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JO - Insurance: Mathematics and Economics

JF - Insurance: Mathematics and Economics

IS - 1

ER -

Stochastic orders in time transformed exponential models with applications

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Keywords

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