On the uniform random upper bound family of first significant digit distributions
作者：
Highlights：
• The mixture of uniform distributions with a random upper bound is considered.
• A closed-form formula for its first significant digit distribution is obtained.
• Fitting capabilities for Benford like data sets from scientific research including scientometrics.
• Best fit (compared to generalized Benford law) for Erlang/gamma mixing distributions.
• Introduction of a finite structure index for Benford like data sets.
摘要
•The mixture of uniform distributions with a random upper bound is considered.•A closed-form formula for its first significant digit distribution is obtained.•Fitting capabilities for Benford like data sets from scientific research including scientometrics.•Best fit (compared to generalized Benford law) for Erlang/gamma mixing distributions.•Introduction of a finite structure index for Benford like data sets.
论文关键词：62E15,62P05,62P10,Benford's law,Stigler's law,Uniform distribution,Simulation algorithm,Extended truncated Pareto,Erlang distribution
论文评审过程：Received 16 December 2014, Revised 23 January 2015, Accepted 20 February 2015, Available online 13 March 2015.
论文官网地址：https://doi.org/10.1016/j.joi.2015.02.007
