Data validity and statistical conformity with Benford's Law
Journal article
Cerqueti, R and Maggi, M (2021). Data validity and statistical conformity with Benford's Law. Chaos, Solitons & Fractals. 144, pp. 110740-110740. https://doi.org/10.1016/j.chaos.2021.110740
Authors | Cerqueti, R and Maggi, M |
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Abstract | Benford's Law is a statistical regularity of a large number of datasets; assessing the compliance of a large dataset with the Benford's Law is a theme of remarkable relevance, mainly for its practical consequences. Such a task can be faced by introducing a statistical distance concept between the empirical distribution of the data and the random variable associated with Benford's Law. This paper deals with the problem of measuring the compliance of a random variable – which can be seen as describing the empirical distribution of a collection of data – with the Benford's Law. It proposes a statistical methodology for detecting the critical values related to conformity/nonconformity with Benford's Law in some well-established cases of statistical distance. The followed approach is grounded on the proper selection of a family of parametric random variables – the lognormal distribution, in our case – and of a reference statistical distance concept – mean absolute deviation. A discussion of the obtained results is carried out on the ground of the existing literature. Moreover, some open problems are also presented. |
Year | 2021 |
Journal | Chaos, Solitons & Fractals |
Journal citation | 144, pp. 110740-110740 |
Publisher | Elsevier BV |
ISSN | 0960-0779 |
Digital Object Identifier (DOI) | https://doi.org/10.1016/j.chaos.2021.110740 |
Publication dates | |
01 Mar 2021 | |
Online | 24 Feb 2021 |
Publication process dates | |
Accepted | 26 Jan 2021 |
Deposited | 21 Apr 2021 |
Accepted author manuscript | License File Access Level Open |
https://openresearch.lsbu.ac.uk/item/8w8w7
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Accepted author manuscript
BL - CSF - R1 -- 17122020.pdf | ||
License: CC BY-NC-ND 4.0 | ||
File access level: Open |
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