Discrete lognormal distributions with application to insurance data
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DOI: 10.1007/s13198-021-01443-x
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- 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.
- 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.
- 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.
- 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).
- 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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