Abstract

Indonesian’s data are obtained from BPS from census, but census are designed for large area. Now, local goverments need to have reliable and detailed information in small area. Direct estimation are unreliable to be applied in small area because produced high mean square error (MSE). To overcome this problem, we use the indirect estimation Small Area Estimation Hierarchical Bayesian (SAE HB) with Logit Normal as the model. From this study founded that HB produced a smaller MSE than direct estimation

Details

Title
Hierarchical Bayesian Modelling in Small Area for Estimating Binary Data
Author
Sari, A D 1 ; Yanuar, F 1 

 Mathematics and Science Department, Andalas University, Padang, Indonesia 
Publication year
2020
Publication date
May 2020
Publisher
IOP Publishing
ISSN
17426588
e-ISSN
17426596
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2557324207
Copyright
© 2020. This work is published under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.