Poisson gamma model in empirical Bayes of small area estimation (SAE)

Yanuar, Ferra Poisson gamma model in empirical Bayes of small area estimation (SAE). IOP Conf. Series: Journal of Physics: Conf. Series.

	Text ICOMSET 2019..pdf Download (644kB)
	Text ICOMSET 2019..pdf Download (644kB)

Abstract

This study aims to describe the empirical Bayes estimator for small area estimation which use Poisson Gamma as prior distribution. The method then apply to generated data and model it with and without indicator variable. Parameter model estimated uses direct method and indirect method (known as empirical Bayes approach; with and without indicator variable). The choice of better estimator is based on MSE with Jackknife method. The criteria of acceptable proposed model are based on Deviance, Scaled Deviance, Pearson ChiSquare and Scaled Pearson Chi-square. This study proves that empirical Bayes in SAE with indicator variable result better estimated values than two other methods. All criteria of acceptable model indicate that proposed model could be accepted. Based on plot between the estimated residual versus predicted values of response variable informed that proposed model is plausible enough.

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