Abstract
Small area estimation is defined as a statistical technique to estimate small sub population of a certain area. There are several method of small area including Empirical Bayes (EB), Hierarchical Bayes (HB) and Empirical Best Linear Unbiassed Prediction (EBLUP). EB method is one of methods in small area estimation for count or binary data. Estimation with EB method is based on posterior which its parameter is estimated by data. One application of EB method for binary data is Beta-Bernoulli Model. In this study, Mean Squared Error (MSE) of the EB estimator was evaluated by Bootstrap method by theory and empirical though simulation by using Ri386 3.4.3 software. The results of this study showed that EB estimator is biased, and the Bootstrap MSE becomes smaller when the amount of areas get greater.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
