Logit-Normal Spatial Model for Small Area Estimation: Case Study of Poverty in Bengkulu

The main objective of this research is to develop a Logit-Normal model with spatial effects. Spatial effects are characterized by a spatial weighted matrix. The weighted matrix used is the distance of the amount of auxiliary variables of area. It was used to estimate the proportion/parameters using...

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Bibliographic Details
Published in:IOP conference series. Earth and environmental science 2018-11, Vol.187 (1), p.12051
Main Author: Sunandi, E
Format: Article
Language:English
Subjects:
Bayesian analysis
Case studies
Parameter estimation
Poverty
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Summary:The main objective of this research is to develop a Logit-Normal model with spatial effects. Spatial effects are characterized by a spatial weighted matrix. The weighted matrix used is the distance of the amount of auxiliary variables of area. It was used to estimate the proportion/parameters using Hierarchical Bayesian method. The design of the research is a case study. Data used in the case study is poverty data in Bengkulu Province. The results show that the spatial effect can improve the value of the Root Mean Square Error.
ISSN:1755-1307
1755-1315
1755-1315
DOI:10.1088/1755-1315/187/1/012051