Empirical modeling of the impact factor distribution
The distribution of impact factors has been modeled in the recent informetric literature using two-exponent law proposed by Mansilla et al. (2007). This paper shows that two distributions widely-used in economics, namely the Dagum and Singh-Maddala models, possess several advantages over the two-exponent model. Compared to the latter, the former give as good as or slightly better fit to data on impact factors in eight important scientific fields. In contrast to the two-exponent model, both proposed distributions have closed-from probability density functions and cumulative distribution functions, which facilitates fitting these distributions to data and deriving their statistical properties.
|Date of creation:||2014|
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- Mansilla, R. & Köppen, E. & Cocho, G. & Miramontes, P., 2007. "On the behavior of journal impact factor rank-order distribution," Journal of Informetrics, Elsevier, vol. 1(2), pages 155-160.
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- Sarabia, José María & Prieto, Faustino & Trueba, Carmen, 2012. "Modeling the probabilistic distribution of the impact factor," Journal of Informetrics, Elsevier, vol. 6(1), pages 66-79.
- Egghe, L., 2009. "Mathematical derivation of the impact factor distribution," Journal of Informetrics, Elsevier, vol. 3(4), pages 290-295.
- Samuel Dastrup & Rachel Hartshorn & James McDonald, 2007. "The impact of taxes and transfer payments on the distribution of income: A parametric comparison," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 5(3), pages 353-369, December.
- Waltman, Ludo & van Eck, Nees Jan, 2009. "Some comments on Egghe's derivation of the impact factor distribution," Journal of Informetrics, Elsevier, vol. 3(4), pages 363-366.
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