TY - JOUR
T1 - Model-based small area estimation with application to unemployment estimates
AU - Omrani, Hichem
AU - Gerber, Philippe
AU - Bousch, Patrick
PY - 2009
Y1 - 2009
N2 - The problem of Small Area Estimation (SAE) is complex because of various information sources and insufficient data. In this paper, an approach for SAE is presented for decision-making at national, regional and local level. We propose an Empirical Best Linear Unbiased Predictor (EBLUP) as an estimator in order to combine several information sources to evaluate various indicators. First, we present the urban audit project and its environmental, social and economic indicators. Secondly, we propose an approach for decision making in order to estimate indicators. An application is used to validate the theoretical proposal. Finally, a decision support system is presented based on open-source environment.
AB - The problem of Small Area Estimation (SAE) is complex because of various information sources and insufficient data. In this paper, an approach for SAE is presented for decision-making at national, regional and local level. We propose an Empirical Best Linear Unbiased Predictor (EBLUP) as an estimator in order to combine several information sources to evaluate various indicators. First, we present the urban audit project and its environmental, social and economic indicators. Secondly, we propose an approach for decision making in order to estimate indicators. An application is used to validate the theoretical proposal. Finally, a decision support system is presented based on open-source environment.
KW - decision-making
KW - sampling
KW - Small area estimation
KW - statistical method
KW - empirical best linear unbiased predictor (EBLUP)
UR - http://www.scopus.com/inward/record.url?eid=2-s2.0-78651567347&partnerID=MN8TOARS
M3 - Article
VL - 3
SP - 10
EP - 17
JO - World Academy of Science, Engineering and Technology
JF - World Academy of Science, Engineering and Technology
IS - 1
ER -