Research Article
Implementation of the Beta Distribution Parameter Estimation Method on Empirical Bayes of Small Area Estimation
@INPROCEEDINGS{10.4108/eai.2-8-2019.2290335, author={Siti Rafika Fiandasari and Margaretha Ari Anggorowati}, title={Implementation of the Beta Distribution Parameter Estimation Method on Empirical Bayes of Small Area Estimation}, proceedings={Proceedings of the 1st International Conference on Statistics and Analytics, ICSA 2019, 2-3 August 2019, Bogor, Indonesia}, publisher={EAI}, proceedings_a={ICSA}, year={2020}, month={1}, keywords={claire empirical bayes rao small area estimation}, doi={10.4108/eai.2-8-2019.2290335} }- Siti Rafika Fiandasari
Margaretha Ari Anggorowati
Year: 2020
Implementation of the Beta Distribution Parameter Estimation Method on Empirical Bayes of Small Area Estimation
ICSA
EAI
DOI: 10.4108/eai.2-8-2019.2290335
Abstract
There is a problem when the amount of available sample is not sufficient for estimating a parameter in sampel survey. Small Area Estimation can handle the problem with use additional variable, but there is a problem when the additional variable hard to get or not strong enough to correlate with the response variable. Empirical Bayes method can handle that because it does not need an additional variable, but there are α and β in that method which needs to be estimated. This research uses four methods for estimating α and β that is Moment and Newton Raphson by Rao, Moment and Newton Raphson by Claire. Moment by Claire, Moment and Newton Raphson by Rao are more effective than Newton Raphson by Claire while Empirical Bayes estimator are more effective than direct estimator.