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Generalized Maximum Entropy Estimator for the Linear Regression Model with a Spatial Autoregressive Disturbance

오차항이 SAR(1)을 따르는 공간선형회귀모형에서 일반화 최대엔트로피 추정량에 관한 연구

  • Cheon, Soo-Young (KU Industry-Academy Cooperation Group Team of Economics and Statistics, Korea Univ.) ;
  • Lim, Seong-Seop (Personal Risk Management Team, Hana Bank)
  • 전수영 (고려대학교 세종캠퍼스 경제통계 산학협력단) ;
  • 임성섭 (하나은행)
  • Published : 2009.03.30

Abstract

This paper considers a linear regression model with a spatial autoregressive disturbance with ill-posed data and proposes the generalized maximum entropy(GME) estimator of regression coefficients. The performance of this estimator is investigated via Monte Carlo experiments. The results show that the GME estimator provides efficient and robust estimate for the unknown parameter.

References

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Cited by

  1. A Comparative Study on Spatial Lattice Data Analysis - A Case Where Outlier Exists - vol.17, pp.2, 2010, https://doi.org/10.5351/CKSS.2010.17.2.193