Small area estimation of poverty proportions under random regression coefficient models

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21340%2F11%3A00187398" target="_blank" >RIV/68407700:21340/11:00187398 - isvavai.cz</a>
Alternative codes found
RIV/67985556:_____/11:00366043
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-642-20853-9_22" target="_blank" >http://dx.doi.org/10.1007/978-3-642-20853-9_22</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-642-20853-9_22" target="_blank" >10.1007/978-3-642-20853-9_22</a>

Result language
angličtina
Original language name
Small area estimation of poverty proportions under random regression coefficient models
Original language description
In 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 aggregatedto 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 arereported as well as an application to real data.
Czech name
—
Czech description
—

Project
<a href="/en/project/1M0572" target="_blank" >1M0572: Data, algorithms, decision making</a><br>
Continuities
Z - Vyzkumny zamer (s odkazem do CEZ)<br>S - Specificky vyzkum na vysokych skolach

Publication year
2011
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Book/collection name
Modern Mathematical Tools and Techniques in Capturing Complexity
ISBN
978-3-642-20852-2
Number of pages of the result
14
Pages from-to
315-328
Number of pages of the book
511
Publisher name
Springer-Verlag
Place of publication
Berlin
UT code for WoS chapter
—

Similar results(10)