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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/13693

Title: Applications of the generalized law of Benford to informetric data
Authors: Egghe, L.
Guns, R.
Issue Date: 2012
Citation: JOURNAL OF THE AMERICAN SOCIETY FOR INFORMATION SCIENCE AND TECHNOLOGY, 63(8), p. 1662-1665
Abstract: In a previous work (Egghe, 2011), the first author showed that Benford's law (describing the logarithmic distribution of the numbers 1, 2,..., 9 as first digits of data in decimal form) is related to the classical law of Zipf with exponent 1. The work of Campanario and Coslado (2011), however, shows that Benford's law does not always fit practical data in a statistical sense. In this article, we use a generalization of Benford's law related to the general law of Zipf with exponent β > 0. Using data from Campanario and Coslado, we apply nonlinear least squares to determine the optimal β and show that this generalized law of Benford fits the data better than the classical law of Benford.
URI: http://hdl.handle.net/1942/13693
ISI #: 000306758600013
ISSN: 1532-2882
Category: A1
Type: Journal Contribution
Validation: ecoom, 2013
Appears in Collections: Research publications

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