Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10358391 | Journal of Informetrics | 2014 | 7 Pages |
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.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science Applications
Authors
Michal Brzezinski,