Generalized Nonlinear Yule Models
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14310%2F16%3A00088377" target="_blank" >RIV/00216224:14310/16:00088377 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/s10955-016-1630-9" target="_blank" >http://dx.doi.org/10.1007/s10955-016-1630-9</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/s10955-016-1630-9" target="_blank" >10.1007/s10955-016-1630-9</a>
Alternative languages
Result language
angličtina
Original language name
Generalized Nonlinear Yule Models
Original language description
With the aim of considering models related to random graphs growth exhibiting persistent memory, we propose a fractional nonlinear modification of the classical Yule model often studied in the context of macroevolution. Here the model is analyzed and interpreted in the framework of the development of networks such as the World Wide Web. Nonlinearity is introduced by replacing the linear birth process governing the growth of the in-links of each specific webpage with a fractional nonlinear birth process with completely general birth rates. Among the main results we derive the explicit distribution of the number of in-links of a webpage chosen uniformly at random recognizing the contribution to the asymptotics and the finite time correction. The mean value of the latter distribution is also calculated explicitly in the most general case.
Czech name
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Czech description
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Classification
Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
BA - General mathematics
OECD FORD branch
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Result continuities
Project
<a href="/en/project/GA15-06991S" target="_blank" >GA15-06991S: Functional data analysis and related topics</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2016
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
JOURNAL OF STATISTICAL PHYSICS
ISSN
0022-4715
e-ISSN
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Volume of the periodical
165
Issue of the periodical within the volume
3
Country of publishing house
US - UNITED STATES
Number of pages
19
Pages from-to
661-679
UT code for WoS article
000386681800008
EID of the result in the Scopus database
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