Dispersion Parameter of Poisson-Gamma Model in the Small Area Estimation

• 발행기관: 한국자료분석학회
• 저자명: Kwang Mo Jeong Hye Ryung Yang
• 간행물 정보: 『Journal of The Korean Data Analysis Society (JKDAS)』Vol.11 No.1, 23~32쪽, 전체 10쪽
• 주제분류: 자연과학 > 통계학
• 파일형태: PDF
• 발행일자: 2009.02.28

영문 초록

The Poisson-gamma model is useful as a population model for estimating the means of small areas. We consider the Empirical Bayes estimator and the confidence interval for small area mean. When sample sizes are small we frequently encounter the inaccuracy in estimating the dispersion parameters provided the inverse dispersion parameter is small. We investigate the statistical properties of mean squared error and the confidence interval in terms of coverage probability through a Monte Carlo simulation study. In this paper we are restricted to the gamma prior with fixed parameters but it would be more reasonable to assume hierachical prior distributions for the parameters. Furthermore we may consider a Poisson loglinear model for the Poisson mean θ d if auxiliary information of covariates is available.

목차

1. Introduction

2. Bayes Estimator for Small Area Mean

3. Confidence Intervals for Small Area Means

4. Monte Carlo Study

5. Summary

References

키워드

Poisson-gamma model small area estimation Empirical Bayes dispersion parameter coverages