期刊名称：International Journal of Computer Science and Network
印刷版ISSN：2277-5420
出版年度：2017
卷号：6
期号：6
页码：812-819
出版社：IJCSN publisher
摘要：Village level poverty rates are needed as a consideration for allocating village funds. The national socio economic survey
samples are designed to estimate poverty rates in province and distric level. Direct estimate for calculating estimates of village level
poverty rates does not have a good precision due to small sample sizes. Small Area Estimation (SAE) technique is used to produce a
good precision with small sample sizes. The estimates of poverty rates should also be produced for non sampled area and when no poor
are included in the sample. We propose zero inflated beta model because poverty rates takes value in the intervals [0,1). Clustering
technique is used to acommodate random effect area for non sampled area. The purpose of this research is to estimate poverty rates on
village level in Langsa Municipality. The result showed that estimates poverty rates on village level with zero inflated beta model is
better than direct estimates.
关键词：Clustering; Poverty Rates; Small Area Estimation; Zero Inflated Beta Model
