A Comparative Study of Generalized Maximum Entropy Estimator for the Two-way Error Component Regression Model

• 발행기관: 한국자료분석학회
• 저자명: Sooyoung Cheon Seohoon Jin
• 간행물 정보: 『Journal of The Korean Data Analysis Society (JKDAS)』Vol.11 No.2, 617~627쪽, 전체 11쪽
• 주제분류: 자연과학 > 통계학
• 파일형태: PDF
• 발행일자: 2009.04.30

영문 초록

Recently the study of the panel data has received attention in the literature of the regression model. The model has been usually dealing with the complete data. However, in a practical manner it is rare for data to be complete. For ill-posed problems, Song and Cheon(2006) proposed a robust generalized maximum entropy estimator less sensitive to the assumption and limited situation in a panel regression model with the only individual effect. However, the time effect needs to be considered in panel data. This paper considers a two-way error component model with both individual and time effects in ill-posed problems and proposes the generalized maximum entropy(GME) estimator for the unknown parameters. This estimator is compared with a variety of existing estimators on the simulated dataset. The numerical results are in favor of the new estimator in terms of its quality when the data are ill-posed.

목차

1. Introduction

2. The model

3. Comparison of estimators

4. Numerical results

5. Conclusion

Reference

키워드

Panel regression model Two way error component Information recovery GME estimation