Small area prediction of proportions and counts under a spatial Poisson mixed model

Author:

Boubeta Miguel,Lombardía María JoséORCID,Morales Domingo

Abstract

AbstractThis paper introduces an area-level Poisson mixed model with SAR(1) spatially correlated random effects. Small area predictors of proportions and counts are derived from the new model and the corresponding mean squared errors are estimated by parametric bootstrap. The behaviour of the introduced predictors is empirically investigated by running model-based simulation experiments. An application to real data from the Spanish living conditions survey of Galicia (Spain) is given. The target is the estimation of domain proportions of women under the poverty line.

Funder

Ministerio de Economía, Industria y Competitividad, Gobierno de España

Generalitat Valenciana

Xunta de Galicia

GAIN (Galician Innovation Agency) and the Regional Ministry of Economy, Employment and Industry

Centro de Investigacion del Sistema universitario de Galicia

Universidade da Coruña

Publisher

Springer Science and Business Media LLC

Subject

Statistics, Probability and Uncertainty,Statistics and Probability

Reference47 articles.

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4. Banerjee S, Carlin BP, Gelfand AE (2015) Hierarchical modeling and analysis for spatial data. CRC Press

5. Boubeta M, Lombardía MJ, Morales D (2016) Empirical best prediction under area-level Poisson mixed models. TEST 25:548–569

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