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, Leo Guns, R. |
Issue Date: | 2012 | Source: | 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. | Document URI: | http://hdl.handle.net/1942/13693 | ISSN: | 1532-2882 | ISI #: | 000306758600013 | Category: | A1 | Type: | Journal Contribution | Validations: | ecoom 2013 |
Appears in Collections: | Research publications |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Applications of the generalized law of Benford to informetric data.pdf Restricted Access | 107.23 kB | Adobe PDF | View/Open Request a copy |
WEB OF SCIENCETM
Citations
11
checked on Apr 15, 2024
Page view(s)
72
checked on Sep 7, 2022
Download(s)
66
checked on Sep 7, 2022
Google ScholarTM
Check
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.