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Autor
Erciulescu AnL. (National Institute of Statistical Sciences and USDA NASS, Washington), Fuller Wayne A. (Iowa State University)
Tytuł
Small Area Prediction Under Alternative Model Specifications
Źródło
Statistics in Transition, 2016, vol. 17, nr 1, s. 9-24, tab., bibliogr. s. 23-24
Słowa kluczowe
Metody samowsporne, Statystyka małych obszarów, Metody statystyczne
Bootstrap, Small area estimates, Statistical methods
Uwagi
Materiały z międzynarodowej konferencji Small Area Estimation (SAE 2014), Poznań.
summ.
The work of Erciulescu was conducted while she was a student in the Departments of Statistics at Iowa State University. This research was partially supported by USDA NRCS CESU agreement 68-7482-11-534.
Abstrakt
Construction of small area predictors and estimation of the prediction mean squared error, given different types of auxiliary information are illustrated for a unit level model. Of interest are situations where the mean and variance of an auxiliary variable are subject to estimation error. Fixed and random specifications for the auxiliary variables are considered. The efficiency gains associated with the random specification for the auxiliary variable measured with error are demonstrated. A parametric bootstrap procedure is proposed for the mean squared error of the predictor based on a logit model. The proposed bootstrap procedure has smaller bootstrap error than a classical double bootstrap procedure with the same number of samples. (original abstract)
Dostępne w
Biblioteka Główna Uniwersytetu Ekonomicznego w Krakowie
Biblioteka SGH im. Profesora Andrzeja Grodka
Biblioteka Główna Uniwersytetu Ekonomicznego w Katowicach
Biblioteka Główna Uniwersytetu Ekonomicznego we Wrocławiu
Pełny tekst
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Bibliografia
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  1. DATTA, G. S., RAO, J. N. K., SMITH, D., (2005). On measuring the variability of small area estimators under a basic area level model, Biometrika, 92, 183-196.
  2. DATTA, G. S., RAO, J. N. K., SMITH, D., (2012). Amendments and Corrections: On measuring the variability of small area estimators under a basic area level model, Biometrika, 99, 2, 509.
  3. DATTA, G. S., RAO, J. N. K., TORABI, M., (2010). Pseudo-empirical Bayes estimation of small area means under a nested error linear regression model with functional measurements errors, Journal of Statistical Planning and Inference, 140, 2952-2962.
  4. DAVIDSON, R., MACKINNON, J. G., (2007). Improving the reliability of bootstrap tests with the fast double bootstrap, Computational Statistics and Data Analysis, 51, 3259-3281.
  5. FULLER, W. A., HARTER, R. M., (1987). The multivariate components of variance model for small area estimation, Small Area Statistics: An International Symposium, Platek, R., Rao, J. N. K., Sarndal, C.E. and Singh, M.P. (Eds.), John Wiley, New York, 103-123.
  6. GHOSH, M., KIM, D., SINHA, K., MAITI, T., KATZOFF, M., PARSONS, V. L., (2009). Hierarchical and Empirical Bayes small domain estimation and proportion of persons without health insurance for minority subpopulations, Survey Methodology, 35, 53-66.
  7. GHOSH, M., SINHA, K., (2007). Empirical Bayes estimation in finite population sampling under functional measurement error models, Journal of Statistical Planning and Inference, 137, 2759-2773.
  8. HALL, P., MAITI, T., (2006). On parametric bootstrap methods for small area prediction, J R. Statist. Soc. B, 68, 2, 221-238.
  9. PFEFFERMANN, D., CORREA, S., (2012). Empirical bootstrap bias correction and estimation of prediction mean square error in small area estimation, Biometrika, 99, 457-472.
  10. TORABI, M., DATTA, G., RAO, J. N. K., (2009). Empirical Bayes Estimation of Small Area Means under a Nested Error Linear Regression Model with Measurement Errors in the Covariates, Scandinavian Journal of Statistics, 36, 355-368.
  11. WANG, J., FULLER, W. A., (2003). The mean squared error of small area spedictors constructed with estimated area variances, Journal of the American Statistical Association, 98, 716-723.
  12. YBARRA, L. M. R., LOHR, S. L., (2008). Small area estimation when auxiliary information is measured with error, Biometrika, 95, 919 -931.
Cytowane przez
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ISSN
1234-7655
Język
eng
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