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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
전수영진서훈
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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