Implementasi Model Poisson Bayes Berhirarki Dua-Level untuk Memodelkan Data Cacahan pada Masalah Pendugaan Area Kecil - Nusar Hajarisman; Aceng Komarudin Mutaqin; Anneke Iswani Ahmad (Program Studi Statistika Unisba, 2012)
In this paper, we address the issue of estimation of the hierarchical Bayesian models, especially forcount data in small area estimation problem. This model was developed by combining the existingterminology in generalized linear models with the concept of Bayes methods, especially hierarchicalBayes methods, such that it can be implemented to address the problem of small area estimation forsurvey data in the form of the count data. Development of this model starts by assuming that theobserved random variable is a member of the exponential family conditional on a certain parameter.The main objective of the development of this model is to make inference on these parameters are alsoconsidered as random variables. Then these parameters are modeled with the Fay-Herriot model asthe basic model of the small area estimation. Furthermore, the combination of both models will bestandardized in such a way as to represent a model within the framework of Bayes methods that willeventually form a two-level hierarchical Bayes Poisson model to solve problems in small areaestimation.