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Stability of L-statistics from weakly dependent observations

Author

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  • Kaluszka, Marek
  • Okolewski, Andrzej

Abstract

We study the stability of moments of L-estimates with respect to several types of weak dependencies motivated by different mixing concepts. An actuarial interpretation of the presented results is indicated.

Suggested Citation

  • Kaluszka, Marek & Okolewski, Andrzej, 2011. "Stability of L-statistics from weakly dependent observations," Statistics & Probability Letters, Elsevier, vol. 81(5), pages 618-625, May.
    • Handle: RePEc:eee:stapro:v:81:y:2011:i:5:p:618-625
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    References listed on IDEAS

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    1. Wang, Shaun, 1996. "Premium Calculation by Transforming the Layer Premium Density," ASTIN Bulletin, Cambridge University Press, vol. 26(1), pages 71-92, May.
    2. Kevin Dowd & John Cotter & Ghulam Sorwar, 2008. "Spectral Risk Measures: Properties and Limitations," Journal of Financial Services Research, Springer;Western Finance Association, vol. 34(1), pages 61-75, August.
    3. Acerbi, Carlo, 2002. "Spectral measures of risk: A coherent representation of subjective risk aversion," Journal of Banking & Finance, Elsevier, vol. 26(7), pages 1505-1518, July.
    4. Kaluszka, M. & Okolewski, A., 2001. "An extension of the Erdös-Neveu-Rényi theorem with applications to order statistics," Statistics & Probability Letters, Elsevier, vol. 55(2), pages 181-186, November.
    5. Denuit, Michel & Dhaene, Jan & Ribas, Carmen, 2001. "Does positive dependence between individual risks increase stop-loss premiums?," Insurance: Mathematics and Economics, Elsevier, vol. 28(3), pages 305-308, June.
    6. Birkel, Thomas, 1992. "Laws of large numbers under dependence assumptions," Statistics & Probability Letters, Elsevier, vol. 14(5), pages 355-362, July.
    7. Kremer, Erhard, 1998. "Largest Claims Reinsurance Premiums under Possible Claims Dependence," ASTIN Bulletin, Cambridge University Press, vol. 28(2), pages 257-267, November.
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    Cited by:

    1. Okolewski, A. & Kaluszka, M., 2015. "Stability of expected L-statistics against weak dependence of observations," Statistics & Probability Letters, Elsevier, vol. 106(C), pages 157-164.

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