Number of the records: 1  

Modern Mathematical Tools and Techniques in Capturing Complexity

  1. 1.
    SYSNO ASEP0366043
    Document TypeM - Monograph Chapter
    R&D Document TypeMonograph Chapter
    TitleSmall Area Estimation of Poverty Proportions under Random Regression Coefficient Models
    Author(s) Hobza, Tomáš (UTIA-B)
    Morales, D. (ES)
    Number of authors2
    Source TitleModern Mathematical Tools and Techniques in Capturing Complexity. - Berlin : Springer, 2011 / Pardo L. ; Balakrishnan N. ; Gil M. A. - ISSN 1860-0832 - ISBN 978-3-642-20852-2
    Pagess. 315-328
    Number of pages14 s.
    Number of pages512
    Languageeng - English
    CountryDE - Germany
    Keywordssmall area estimation ; random regression coefficient model ; EBLUP estimates
    Subject RIVBB - Applied Statistics, Operational Research
    R&D Projects1M0572 GA MŠMT - Ministry of Education, Youth and Sports (MEYS)
    CEZAV0Z10750506 - UTIA-B (2005-2011)
    DOI10.1007/978-3-642-20853-9_22
    AnnotationIn this paper a random regression coefficient model is used to provide estimates of small area poverty proportions. As poverty variable is dichotomic at the individual level, the sample data from Spanish Living Conditions Survey is previously aggregated to the level of census sections. EBLUP estimates based on the proposed model are obtained. A closed-formula procedure to estimate the mean squared error of the EBLUP estimators is given and empirically studied. Results of several simulations studies are reported as well as an application to real data.
    WorkplaceInstitute of Information Theory and Automation
    ContactMarkéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201.
    Year of Publishing2012
Number of the records: 1  

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