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Characterisation of some generalised continuous distributions by doubly truncated moments

Author

Listed:
  • Haseeb Athar
  • Mohammad Ahsanullah
  • Mohd. Almech Ali

Abstract

The characterisation of probability distribution plays an important role in statistical studies. There are various methods of characterisation available in the literature. The characterisation using truncated moments limits the observations; hence, researchers may save time and cost. In this paper, the characterisation of three general forms of continuous distributions based on doubly truncated moments has been studied. The results are given simply and explicitly. Further, the results have been applied to some well-known continuous distributions.

Suggested Citation

  • Haseeb Athar & Mohammad Ahsanullah & Mohd. Almech Ali, 2023. "Characterisation of some generalised continuous distributions by doubly truncated moments," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 33(1), pages 1-19.
    • Handle: RePEc:wut:journl:v:33:y:2023:i:1:p:1-19:id:1
    DOI: 10.37190/ord230101
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    References listed on IDEAS

    as
    1. K. Balasubramanian & Aloke Dey, 1997. "Distributions characterized through conditional expectations," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 45(1), pages 189-196, January.
    2. Farouk Metiri & Halim Zeghdoudi & Abdelali Ezzebsa, 2022. "On the characterisation of X-Lindley distribution by truncated moments. Properties and application," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 32(1), pages 97-109.
    3. Manuel Franco & Jose Ruiz, 1997. "On characterizations of distributions by expected values of order statistics and record values with gap," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 45(1), pages 107-119, January.
    4. K. Balasubramanian & M. Beg, 1992. "Distributions determined by conditioning on a pair of order statistics," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 39(1), pages 107-112, December.
    Full references (including those not matched with items on IDEAS)

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