Empirical modeling of the impact factor distribution |
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| Institution: | 1. CNRS (LAMSADE, UMR 7243) & Université Paris Dauphine, Place du Maréchal de Lattre de Tassigny, F-75775 Paris Cedex 16, France;2. Ghent University, Department of Data Analysis, H. Dunantlaan, 1, B-9000 Gent, Belgium;1. Instituto de Turismo y Desarrollo Económico Sostenible Tides, Universidad de Las Palmas de Gran Canaria, Spain;2. Departamento de Estadística, Investigación Operativa y Computación, Universidad de La Laguna, Spain |
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| Abstract: | The distribution of impact factors has been modeled in the recent informetric literature using two-exponent law proposed by Mansilla, Köppen, Cocho, and Miramontes (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 models 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. |
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| Keywords: | Impact factor Two-exponent law Dagum model Singh-Maddala model Maximum likelihood estimation Model selection |
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