Empirical bayes estimation of small area means under a nested error linear regression model with measurement errors in the covariates

Scandinavian Journal of Statistics

Volumn 36, Issue 2, 2009, Pages 355-369

  Torabi, Mahmoud ^b   Datta, Gauri S ^c   Rao, J N K ^a  

^a CARLETON UNIVERSITY   (Canada)

^b UNIVERSITY OF ALBERTA   (Canada)

^c UNIVERSITY OF GEORGIA   (United States)

Author keywords

Bayes risk; Empirical Bayes; Jackknife method; Mean squared prediction error; Nested error model

Indexed keywords

EID: 67949108052     PISSN: 03036898     EISSN: 14679469     Source Type: Journal    
DOI: 10.1111/j.1467-9469.2008.00623.x     Document Type: Article

References (14)

1. Battese, G. E., Harter, R. M. & Fuller, W. A. (1988). An error components model for prediction of county crop area using survey and satellite data. J. Amer. Statist. Assoc. 83, 28-36.
2. Bolfarine, H., Zacks, S. & Sandoval, M. C. (1996). On predicting the population total under regression models with measurement errors. J. Statist. Plann. Inference 55, 63-76.
3. Chen, S. & Lahiri, P. (2002). On mean squared prediction error estimation in small area estimation problems. In Proceedings of the survey research methods section, 473-477. American Statistical Association, Washington.
4. Cochran, W. G. (1977). Sampling techniques, 3rd edn. Wiley, New York.
5. Datta, G. S. (2008). Model-based approach to small area estimation. In Handbook No. 29 sample surveys: theory, methods and inference (eds D. Pfeffermann & C. R. Rao), Elsevier B.V., New York, (in press).
6. Fuller, W. A. (1987). Measurement error models. Wiley, New York.
7. Ghosh, M., Sinha, K. & Kim, D. (2006). Empirical and hierarchical Bayesian estimation in finite population sampling under structural measurement error models. Scand. J. Statist. 33, 591-608.
8. Jiang, J. & Lahiri, P. (2006). Mixed model prediction and small area estimation. Test 15, 1-96.
9. Jiang, J., Lahiri, P. & Wan, S.-M. (2002). A unified Jackknife theory for empirical best prediction with M-estimation. Ann, Statist. 30, 1782-1810.
10. Lohr, S. L. (1999). Sampling: design and analysis. Duxbury, Pacific Grove, California.
11. Prasad, N. G. N. & Rao, J. N. K. (1990). The estimation of mean squared error of small area estimators. J. Amer. Statist. Assoc. 85, 163-171.
12. Rao, J. N. K. (2003). Small area estimation. Wiley, Hoboken, New Jersey.
13. Resnick, S. I. (1999). A probability path. Birkhäuser, Boston.
14. Thompson, M. E. (1997). Theory of sample surveys. Chapman & Hall, London.