The discretised lognormal and hooked power law distributions for complete citation data: Best options for modelling and regression

作者：

Highlights：

• The hooked power law fits citation data from a single subject better than the discretised lognormal distribution in science.

• The discretised lognormal distribution fits citation from a single subject better than the hooked power law outside science.

• After a transformation, normal distribution parameters are more stable than discrete distribution parameters for citation data.

摘要

•The hooked power law fits citation data from a single subject better than the discretised lognormal distribution in science.•The discretised lognormal distribution fits citation from a single subject better than the hooked power law outside science.•After a transformation, normal distribution parameters are more stable than discrete distribution parameters for citation data.

论文关键词：Scientometrics,Hooked power law,Shifted power law,Discretised lognormal distribution,Citation analysis,Citation distributions

论文评审过程：Received 22 September 2015, Revised 22 December 2015, Accepted 22 December 2015, Available online 3 March 2016, Version of Record 3 March 2016.

论文官网地址：https://doi.org/10.1016/j.joi.2015.12.007