Generalized Additive Mixed Models In Small Area Estimation

Abstract

Small Area Estimation (SA E) is a statistical technique to estimate parameters of sub-population containing small size of samples with adequate precision. This technique ;s very important to be developed due to the increaSing needs of statistic for small domains, such as districts or villages. Some SA E techniques have been developed in Canada, USA. and UE based all real data. We adapted this technique to produce small area statistic in Indonesia based on national data collected by the Statistics Indonesia (Badon Pusat Statistik), We Jound that the linear model applied to auxiliary data produced estimates with low precision. In this paper we propose a class of generalized additive mixed model to improve the model of auxiliary data in small area estimation.