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General distributions of number representation elements

Author(s)
Balado, Félix  
Silvestre, Guenole C.  
Uri
http://hdl.handle.net/10197/31588
Date Issued
2024-07-01
Date Available
2026-03-04T12:39:54Z
Abstract
We provide general expressions for the joint distributions of the k most significant b-ary digits and of the k leading continued fraction (CF) coefficients of outcomes of arbitrary continuous random variables. Our analysis highlights the connections between the two problems. In particular, we give the general convergence law of the distribution of the jth significant digit, which is the counterpart of the general convergence law of the distribution of the jth CF coefficient (Gauss-Kuz’min law). We also particularise our general results for Benford and Pareto random variables. The former particularisation allows us to show the central role played by Benford variables in the asymptotics of the general expressions, among several other results, including the analogue of Benford’s law for CFs. The particularisation for Pareto variables—which include Benford variables as a special case—is especially relevant in the context of pervasive scale-invariant phenomena, where Pareto variables occur much more frequently than Benford variables. This suggests that the Pareto expressions that we produce have wider applicability than their Benford counterparts in modelling most significant digits and leading CF coefficients of real data. Our results may find practical application in all areas where Benford’s law has been previously used.
Type of Material
Journal Article
Publisher
Cambridge University Press
Journal
Probability in the Engineering and Informational Sciences
Volume
38
Issue
3
Start Page
594
End Page
616
Copyright (Published Version)
2024 the Authors
Subjects

Benford's Law

Continued fraction co...

Pareto distribution

Significant digits mo...

DOI
10.1017/S0269964823000207
Language
English
Status of Item
Peer reviewed
ISSN
0269-9648
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
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Owning collection
Computer Science Research Collection

Item descriptive metadata is released under a CC-0 (public domain) license: https://creativecommons.org/public-domain/cc0/.
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