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Precise Large Deviations of Aggregate Claims with Dominated Variation in Dependent Multi‐Risk Models

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  • Shijie Wang
  • Xuejun Wang
  • Wensheng Wang

Abstract

We consider a dependent multirisk model in insurance, where all the claims constitute a linearly extended negatively orthant dependent (LENOD) random array, and then upper and lower bounds for precise large deviations of nonrandom and random sums of random variables with dominated variation are investigated. The obtained results extend some related existing ones.

Suggested Citation

  • Shijie Wang & Xuejun Wang & Wensheng Wang, 2014. "Precise Large Deviations of Aggregate Claims with Dominated Variation in Dependent Multi‐Risk Models," Abstract and Applied Analysis, John Wiley & Sons, vol. 2014(1).
    • Handle: RePEc:wly:jnlaaa:v:2014:y:2014:i:1:n:972029
    DOI: 10.1155/2014/972029
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    References listed on IDEAS

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    1. Liu, Yan, 2007. "Precise large deviations for negatively associated random variables with consistently varying tails," Statistics & Probability Letters, Elsevier, vol. 77(2), pages 181-189, January.
    2. Shen, Xinmei & Lin, Zhengyan, 2008. "Precise large deviations for randomly weighted sums of negatively dependent random variables with consistently varying tails," Statistics & Probability Letters, Elsevier, vol. 78(18), pages 3222-3229, December.
    3. Chen, Yu & Zhang, Weiping, 2007. "Large deviations for random sums of negatively dependent random variables with consistently varying tails," Statistics & Probability Letters, Elsevier, vol. 77(5), pages 530-538, March.
    4. Liu, Li, 2009. "Precise large deviations for dependent random variables with heavy tails," Statistics & Probability Letters, Elsevier, vol. 79(9), pages 1290-1298, May.
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