An Investigation of Hierarchical and Empirical Bayesian Small Area Predictors Under Measurement Error
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Publisher
Springer International Publishing
Link
http://link.springer.com/content/pdf/10.1007/978-3-030-21158-5_17
Reference14 articles.
1. Alvares, D., Armero, C., Forte, A.: What does objective mean in a Dirichlet multinomial process? Int. Stat. Rev. 106–118 (2017)
2. Arima, S., Polettini, S.: A unit-level small area model with misclassified covariates. J. R. Stat. Soc. A. (2019). https://doi.org/10.1111/rssa.12468
3. Arima, S., Datta, G.S., Liseo, B.: Objective Bayesian analysis of a measurement error small area model. Bayesian Anal. 72(2), 363–384 (2012)
4. Arima, S., Datta, G.S., Liseo, B.: Models in small area estimation when covariates are measured with error. In: Pratesi, M. (ed.) Analysis of Poverty Data by Small Area Estimation, pp. 151–170. Wiley, New York (2016)
5. Carroll, R.J., Ruppert, D., Stefanski, L., Crainiceanu, C.: Measurement Error in Nonlinear Models: A Modern Perspective, 2nd edn. Chapman & Hall, CRC, Boca Raton (2006)
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