A Comparative Study of Generalized Maximum Entropy Estimator for the Two-way Error Component Regression ModelA Comparative Study of Generalized Maximum Entropy Estimator for the Two-way Error Component Regression Model
- Other Titles
- A Comparative Study of Generalized Maximum Entropy Estimator for the Two-way Error Component Regression Model
- Authors
- 전수영; 진서훈
- Issue Date
- 2009
- Publisher
- 한국자료분석학회
- Keywords
- Panel regression model; Two way error component; Information recovery; GME estimation.
- Citation
- Journal of The Korean Data Analysis Society, v.11, no.2, pp.617 - 627
- Indexed
- KCI
- Journal Title
- Journal of The Korean Data Analysis Society
- Volume
- 11
- Number
- 2
- Start Page
- 617
- End Page
- 627
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/121826
- ISSN
- 1229-2354
- Abstract
- 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.
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Collections - Graduate School > Department of Applied Statistics > 1. Journal Articles
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