Empirical validation of Lotka's law
Information Processing and Management: an International Journal
The Gini index and the Leimkuhler curve for bibliometric processes
Information Processing and Management: an International Journal - Special issue on Informetrics
Informetric distributions. III. ambiguity and randomness
Journal of the American Society for Information Science
Heavy-tailed probability distributions in the World Wide Web
A practical guide to heavy tails
Implications of ambiguity for scientometric measurement
Journal of the American Society for Information Science and Technology - Special issue on the still the frontier: Information Science at the Millenium
"Ambiguity" and scientometric measurement: a dissenting view
Journal of the American Society for Information Science and Technology
Zipfian and Lotkaian continuous concentration theory: Research Articles
Journal of the American Society for Information Science and Technology
Symmetry and other transformation features of Lorenz/Leimkuhler representations of informetric data
Information Processing and Management: an International Journal - Special issue: Infometrics
On Egghe's version of continuous concentration theory: Brief Communication
Journal of the American Society for Information Science and Technology
On Egghe's construction of Lorenz curves: Brief Communication
Journal of the American Society for Information Science and Technology
Egghe's construction of Lorenz curves resolved
Journal of the American Society for Information Science and Technology
Hirsch index rankings require scaling and higher moment
Journal of the American Society for Information Science and Technology
Theory and practice of the shifted Lotka function
Scientometrics
The Hirsch index of a shifted Lotka function and its relation with the impact factor
Journal of the American Society for Information Science and Technology
The Hirsch index and related impact measures
Annual Review of Information Science and Technology
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The continuous version of the Lotka distribution, more generally referred to outside of informetrics as the Pareto distribution, has long enjoyed a central position in the theoretical development of informetrics despite several reported drawbacks in modelling empirical data distributions, most particularly that the inverse power form seems mainly to be evident only in the upper tails. We give a number of published examples graphically illustrating this shortcoming. In seeking to overcome this, we here draw attention to an intuitively reasonable generalization of the Pareto distribution, namely the Pareto type II distribution, of which we consider two versions. We describe its basic properties and some statistical features together with concentration aspects and argue that, at least in qualitative terms, it is better able to describe many observed informetric phenomena over the full range of the distribution. Suggestions for further investigations, including truncated and time-dependent versions, are also given.