An Alternative Proof of the Asymptotic Behavior of GLSE in Polynomial MEM

  • Myung-Sang Moon (Assistant Professor, Department of Statistics, Yonsei University, Wonju-City, Kangwon-Do, 222-701, Korea)
  • Published : 1996.12.01


Polynomial measurement error model(MEM) with one predictor is considered. It is briefly mentioned that Chan and Mak's generalized least squares estimator(GLSE) can be derived more easily if Hermite polynomial concept is applied. It is proved that GLSE derived using new procedure is equivalent to the estimator obtained from corrected score function. Finally, much simpler proof of the asymptotic behavior of GLSE than that of Chan and Mak is provided. Much simpler formula of asymptotic covariance matrix of GLSE is a part of that proof.



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