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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

  • Czech description

Classification

  • Type

    J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

  • CEP classification

    BA - General mathematics

  • OECD FORD branch

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

  • 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