Kurva Rasio Variansi Spasial Hierarchical Bayes Small Area Estimation untuk Berbagai Ukuran Sampel

Abstract

Area level models such as Fay-Herriot have been widely used to obtain reliable model-based estimators in small area estimation. However, in the model, two strong assumptions are made. One is that the sampling error variances are customarily assumed to be known, and the other is that the area-specific random effect are assumed to be independent and identically distributed. In this paper, we propose full hierarchical Bayes (HB) models which relax these two strong assumptions by constructing Gaussian conditional autoregressive (CAR) models on the area-specific effects to induce spatial correlation, and assuming the sampling variances unknown. Curve relationship between success proportion to the variances ration showed a quadratic relationship.