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Discrete lognormal distributions with application to insurance data

Author

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  • Jiahang Lyu

    (University of Manchester)

  • Saralees Nadarajah

    (University of Manchester)

Abstract

The continuous lognormal distribution has been used to model discrete count data, which is clearly not appropriate. In this paper, we introduce two discrete versions of the continuous lognormal distribution. We study their mathematical properties and estimation issues. Two real data applications show superior performance of the discrete versions over the continuous counter parts.

Suggested Citation

  • Jiahang Lyu & Saralees Nadarajah, 2022. "Discrete lognormal distributions with application to insurance data," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(3), pages 1268-1282, June.
  • Handle: RePEc:spr:ijsaem:v:13:y:2022:i:3:d:10.1007_s13198-021-01443-x
    DOI: 10.1007/s13198-021-01443-x
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    References listed on IDEAS

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    1. Michael J. Stringer & Marta Sales‐Pardo & Luís A. Nunes Amaral, 2010. "Statistical validation of a global model for the distribution of the ultimate number of citations accrued by papers published in a scientific journal," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 61(7), pages 1377-1385, July.
    2. Luckstead, Jeff & Devadoss, Stephen, 2017. "Pareto tails and lognormal body of US cities size distribution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 573-578.
    3. Michael J. Stringer & Marta Sales-Pardo & Luís A. Nunes Amaral, 2010. "Statistical validation of a global model for the distribution of the ultimate number of citations accrued by papers published in a scientific journal," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 61(7), pages 1377-1385, July.
    4. Pigeon, Mathieu & Denuit, Michel, 2011. "Composite Lognormal-Pareto model with random threshold," LIDAM Reprints ISBA 2011020, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    5. Thelwall, Mike & Wilson, Paul, 2014. "Regression for citation data: An evaluation of different methods," Journal of Informetrics, Elsevier, vol. 8(4), pages 963-971.
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