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Application of Generalized Maximum Entropy Estimator to the Two-way Nested Error Component Model with Ill-Posed DataApplication of Generalized Maximum Entropy Estimator to the Two-way Nested Error Component Model with Ill-Posed Data
- Other Titles
- Application of Generalized Maximum Entropy Estimator to the Two-way Nested Error Component Model with Ill-Posed Data
- Authors
- 전수영
- Issue Date
- 2009
- Publisher
- 한국통계학회
- Keywords
- Two way nested error component; Ill-posed; GME estimation
- Citation
- Communications for Statistical Applications and Methods, v.16, no.4, pp.659 - 667
- Indexed
- KCI
- Volume
- 16
- Number
- 4
- Start Page
- 659
- End Page
- 667
- ISSN
- 2287-7843
- Abstract
- Recently Song and Cheon (2006) and Cheon and Lim (2009) developed the generalized maximum entropy(GME) estimator to solve ill-posed problems for the regression coefficients in the simple panel model. The models discussed consider the individual and a spatial autoregressive disturbance effects. However, in many application in economics the data may contain nested groupings. This paper considers a two-way error component model with nested groupings for the ill-posed data and proposes the GME estimator of the unknown parameters. The performance of this estimator is compared with the existing methods on the simulated dataset. The results indicate that the GME method performs the best in estimating the unknown parameters 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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