Increasing convex order on generalized aggregation of SAI random variables with applications

Xiaoqing Pan, Xiaohu Li

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

In this paper we study general aggregation of stochastic arrangement increasing random variables, including both the generalized linear combination and the standard aggregation as special cases. In terms of monotonicity, supermodularity, and convexity of the kernel function, we develop several sufficient conditions for the increasing convex order on the generalized aggregations. Some applications in reliability and risks are also presented.

Original languageEnglish
Pages (from-to)685-700
Number of pages16
JournalJournal of Applied Probability
Volume54
Issue number3
DOIs
StatePublished - 1 Sep 2017

Keywords

  • Arrangement increasing
  • coverage limit
  • deductible
  • generalized linear combination
  • majorization
  • submodular
  • weighted k-out-of-n system

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