Mishra, SK (2010): A note on empirical sample distribution of journal impact factors in major discipline groups.

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Abstract
What type of statistical distribution do the Journal Impact Factors follow? In the past, researchers have hypothesized various types of statistical distributions underlying the generation mechanism of journal impact factors. These are: lognormal, normal, approximately normal, Weibull, negative exponential, combination of exponentials, Poisson, Generalized inverse GaussianPoisson, negative binomial, generalized Waring, gamma, etc. It is pertinent to note that the major characteristics of JIF data lay in the asymmetry and nonmesokurticity. The present study, frequently encounters BurrXII, inverse BurrIII (Dagum), Johnson SU, and a few other distributions closely related to Burr distributions to best fit the JIF data in subject groups such as biology, chemistry, economics, engineering, physics, psychology and social sciences.
Item Type:  MPRA Paper 

Original Title:  A note on empirical sample distribution of journal impact factors in major discipline groups 
Language:  English 
Keywords:  Journal impact factor; JIF; theoretical probability distribution; Burr; Dagum; Generalized extreme value; generalized gamma; Inverse Gaussian; Johnson SU; Johnson SB; Kumaraswamy; Loglogistic; lognonmal; logPearson; Weibull; Generalized normal; Hypersecant; Beta; empirical distribution; sample 
Subjects:  C  Mathematical and Quantitative Methods > C1  Econometric and Statistical Methods and Methodology: General > C16  Specific Distributions 
Item ID:  20747 
Depositing User:  Sudhanshu Kumar Mishra 
Date Deposited:  17. Feb 2010 07:24 
Last Modified:  12. Feb 2013 01:06 
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URI:  http://mpra.ub.unimuenchen.de/id/eprint/20747 