Journal of the Korean Data and Information Science Society

The Korean Data and Information Science Society (한국데이터정보과학회)
권호 표지

A Comparative Study of Small Area Estimation Methods

소지역 추정법에 관한 비교연구

  • Park, Jong-Tae (Department of Information Science, Pyongtaek University) ;
  • Lee, Sang-Eun (Department of Applied Information Statistics, Kyonggi University)
  • 박종태 (평택대학교 정보과학과) ;
  • 이상은 (경기대학교 응용정보통계학과)
  • Published : 2001.10.30
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Abstract

Usually estimating the means is used for statistical inference. However depending the purpose of survey, sometimes totals will give the better and more meaningful in statistical inference than the means. Here in this study, we dealt with the unemployment population of small areas with using 4 different small area estimation methods: Direct, Synthetic, Composite, Bayes estimation. For all the estimates considered in this study, the average of absolute bias and men square error were obtained in the Monte Carlo Study which was simulated using data from 1998 Economic Active Population Survey in Korea.

직접(direct) 추정법, 합성(synthetic) 추정법, 복합(composite) 추정법, 베이즈(Bayes) 추정법 등 소지역 추정법들의 효율성을 비교, 분석하고자 '98 경제활동 인구조사에서 경기도의 실제 자료를 이용하여 각 시부지역의 실업자수 추정값의 편의(bias)와 평균제곱 오차(MSE)를 모의실험을 통해 계산하였다.

Keywords

References

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