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Modeling compositional time series with vector autoregressive models

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15310%2F15%3A33155233" target="_blank" >RIV/61989592:15310/15:33155233 - isvavai.cz</a>

  • Result on the web

    <a href="http://onlinelibrary.wiley.com/doi/10.1002/for.2336/epdf" target="_blank" >http://onlinelibrary.wiley.com/doi/10.1002/for.2336/epdf</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1002/for.2336" target="_blank" >10.1002/for.2336</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Modeling compositional time series with vector autoregressive models

  • Original language description

    Multivariate time series describing relative contributions to a total (like proportional data) are called compositional time series. They need to be transformed first to the usual Euclidean geometry before a time series model is fitted. It is shown how an appropriate transformation can be chosen, resulting in coordinates with respect to the Aitchison geometry of compositional data. Using vector autoregressive models, the standard approach based on raw data is compared with the compositional approach based on transformed data. The results from the compositional approach are consistent with the relative nature of the observations, while the analysis of the raw data leads to several inconsistencies and artifacts. The compositional approach is extended tothe case when also the total of the compositional parts is of interest. Moreover, a concise methodology for an interpretation of the coordinates in the transformed space together with the corresponding statistical inference (like hypothes

  • 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/EE2.3.20.0170" target="_blank" >EE2.3.20.0170: Building of Research Team in the Field of Environmental Modeling and the Use of Geoinformation Systems with the Consequence in Participation in International Networks and Programs</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2015

  • 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 Forecasting

  • ISSN

    0277-6693

  • e-ISSN

  • Volume of the periodical

    34

  • Issue of the periodical within the volume

    4

  • Country of publishing house

    GB - UNITED KINGDOM

  • Number of pages

    12

  • Pages from-to

    303-314

  • UT code for WoS article

    000357816400005

  • EID of the result in the Scopus database