Empirical and Hierarchical Bayesian Estimation in Finite Population Sampling under Structural Measurement Error Models
By Malay Ghosh, Karabi Sinha, D. Kim. 2006
55 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/9538eda6a0c68e36339acd6be2bd1c1b4e67f58a
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Brunero Liseo
- Serena Arima
- Gauri Sankar Datta
- J. Rao
- Mahmoud Torabi
- Malay Ghosh
- Laura Ventura
- Walter Racugno
In Statistics and Probability
- Brunero Liseo
- Serena Arima
- Gauri Sankar Datta
- J. Rao
- Mahmoud Torabi
- Liugen Xue
- Jae Kwang Kim
- Adelchi Azzalini
Citations in the corpus
- Empirical Bayes Estimation of Small Area Means under a Nested Error Linear Regression Model with Measurement Errors in the Covariates (2009, methodology): “In a pioneering paper, Ghosh et al. (2006), henceforth abbreviated GSK, proposed a nested error linear regression population model with an area-level covariate, x, subject to measurement error.”
- Bayesian Estimators for Small Area Models when Auxiliary Information is Measured with Error (2015, methodology): “We note that a Bayesian approach to unit-level model with measurement error in the covariates has been considered in Ghosh et al. (2006), Ghosh & Sinha (2007), Torabi et al. (2009), Datta et al. (2010) and Arima et al. (2012).”