Research Article
Mean Square Error of Non-Sampled Area in Small Area Estimation
@INPROCEEDINGS{10.4108/eai.2-8-2019.2290339, author={Faisal Haris and Azka Ubaidillah}, title={Mean Square Error of Non-Sampled Area in 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={clustering non sampled area mean square error small area estimation}, doi={10.4108/eai.2-8-2019.2290339} }- Faisal Haris
Azka Ubaidillah
Year: 2020
Mean Square Error of Non-Sampled Area in Small Area Estimation
ICSA
EAI
DOI: 10.4108/eai.2-8-2019.2290339
Abstract
Small area estimation (SAE) is a statistical technique to predict the parameter of subpopulation with small or even zero sample size. An area with zero sample size can be estimated with the support of cluster information. The area random effect assumed has a similarity between region and can be analyzed by clustering the auxiliary variables. In SAE, Mean square error (MSE) is used to compare the precision of parameter estimates. But, there is no study that discuss the MSE of non-sampled area in SAE. The main idea of this research is to modify the existing statistical method by adding the cluster information with the assumption that there are similar characteristics of similar areas. The new method was evaluated by data simulation and case study to check the performance. The data simulation show that all modified methods produce a relatively similar MSE of non-sampled area..
