2019
DOI: 10.1103/physreve.100.062106
|View full text |Cite
|
Sign up to set email alerts
|

Universality of power-law exponents by means of maximum-likelihood estimation

Abstract: Power-law type distributions are extensively found when studying the behaviour of many complex systems. However, due to limitations in data acquisition, empirical datasets often only cover a narrow range of observation, making it difficult to establish power-law behaviour unambiguously. In this work we present a statistical procedure to merge different datasets with the aim of obtaining a broader fitting range for the statistics of different experiments or observations of the same system or the same universali… Show more

Help me understand this report
View preprint versions

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1

Citation Types

0
2
0

Year Published

2020
2020
2024
2024

Publication Types

Select...
5
2

Relationship

0
7

Authors

Journals

citations
Cited by 11 publications
(2 citation statements)
references
References 54 publications
0
2
0
Order By: Relevance
“…In addition, the determination of the functional form of the degree distribution of nodes has gained notoriety for establishing the behavior of connectivities and structural analysis of networks [ 47 ]. In the case of the distributions corresponding to the orthographic and phonological layer, it is observed that they correspond to distributions with a broad degree distribution, also known as fat-tailed distribution [ 48 ] (See Fig 3 ). For each degree distribution in our study, we performed fits to the data by considering the following distributions: Gumbel, Exponential, Loglogistic, Lognormal, Weibull and Power-law (see Supplementary Material [ 44 ]).…”
Section: Resultsmentioning
confidence: 99%
“…In addition, the determination of the functional form of the degree distribution of nodes has gained notoriety for establishing the behavior of connectivities and structural analysis of networks [ 47 ]. In the case of the distributions corresponding to the orthographic and phonological layer, it is observed that they correspond to distributions with a broad degree distribution, also known as fat-tailed distribution [ 48 ] (See Fig 3 ). For each degree distribution in our study, we performed fits to the data by considering the following distributions: Gumbel, Exponential, Loglogistic, Lognormal, Weibull and Power-law (see Supplementary Material [ 44 ]).…”
Section: Resultsmentioning
confidence: 99%
“…have been used to observe the jumps and their distributions. Considerable theoretical work has also been performed in order to provide the tools to analyse these distributions, many of which are based on the maximum-likelihood method [31][32][33].…”
Section: Introductionmentioning
confidence: 99%