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On Structure, Family and Parameter Estimation of Hierarchical Archimedean Copulas

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F17%3A00478633" target="_blank" >RIV/67985807:_____/17:00478633 - isvavai.cz</a>

  • Alternative codes found

    RIV/47813059:19520/17:00010847

  • Result on the web

    <a href="http://dx.doi.org/10.1080/00949655.2017.1365148" target="_blank" >http://dx.doi.org/10.1080/00949655.2017.1365148</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1080/00949655.2017.1365148" target="_blank" >10.1080/00949655.2017.1365148</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    On Structure, Family and Parameter Estimation of Hierarchical Archimedean Copulas

  • Original language description

    Research on structure determination and parameter estimation of hierarchical Archimedean copulas (HACs) has so far mostly focused on the case in which all appearing Archimedean copulas belong to the same Archimedean family. The present work addresses this issue and proposes a new approach for estimating HACs that involve different Archimedean families. It is based on employing goodness-of-fit test statistics directly into HAC estimation. The approach is summarized in a simple algorithm, its theoretical justification is given and its applicability is illustrated by several experiments, which include estimation of HACs involving up to five different Archimedean families.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    10103 - Statistics and probability

Result continuities

  • Project

    <a href="/en/project/GA17-01251S" target="_blank" >GA17-01251S: Metalearning for Extraction of Rules with Numerical Consequents</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2017

  • 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 Computation and Simulation

  • ISSN

    0094-9655

  • e-ISSN

  • Volume of the periodical

    87

  • Issue of the periodical within the volume

    17

  • Country of publishing house

    GB - UNITED KINGDOM

  • Number of pages

    64

  • Pages from-to

    3261-3324

  • UT code for WoS article

    000417048000002

  • EID of the result in the Scopus database

    2-s2.0-85028562700