Small area estimation has received enormous attention in recent years due to its wide range of application, particularly in policy making decisions. The variance based on direct sample size of small area estimator is unduly large and there is a need of constructing model based estimator with low mean squared prediction error (MSPE). Estimation of MSPE and in particular the bias correction of MS...

It is now widely recognized that small area estimation (SAE) needs to be model-based. Global-local (GL) shrinkage priors for random effects are important in sparse situations where many areas’ level do not have a significant impact on the response beyond what offered by covariates. We propose this paper hierarchical multivariate model with GL priors. prove propriety of posterior density when re...

The USDA National Agricultural Statistics Service (NASS) and other federal statistical agencies have used probability-based surveys as the foundation for official statistics over half a century. Non-survey data that can be to improve accuracy precision of estimates such administrative, remotely sensed, retail become increasingly available. Both frequentist Bayesian models are combine survey non...