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Exploring the Regional Czech Household Income Dynamics Regression Mixtures

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14310%2F11%3A00056752" target="_blank" >RIV/00216224:14310/11:00056752 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Exploring the Regional Czech Household Income Dynamics Regression Mixtures

  • Original language description

    Model-based cluster analysis is popular methods for grouping observations into unobserved segments. The article deals with cluster analysis of household income dynamics based on the results of statistical survey EU SILC 2005-2008. In this paper we address the problem of clustering sets of trajectory data generated by households in different regions. The focus is to model curve data directly using a set of model-based curve clustering algorithms referred to as mixtures of regressions or regression mixtures. The R environment (R Development Core Team, 2010) is used for mixture model analysis.

  • Czech name

  • Czech description

Classification

  • Type

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

  • CEP classification

    BB - Applied statistics, operational research

  • OECD FORD branch

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2011

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Aplimat - Journal of Applied Mathematics

  • ISSN

    1337-6365

  • e-ISSN

  • Volume of the periodical

    4(2011)

  • Issue of the periodical within the volume

    3

  • Country of publishing house

    SK - SLOVAKIA

  • Number of pages

    11

  • Pages from-to

    261-271

  • UT code for WoS article

  • EID of the result in the Scopus database