Quasi Score is more Efficient than Corrected Score in a Polynomial Measurement Error Model
نویسندگان
چکیده
منابع مشابه
Quasi Score is more efficient than Corrected Score in a polynomial measurement error model
We consider a polynomial regression model, where the covariate is measured with Gaussian errors. The measurement error variance is supposed to be known. The covariate is normally distributed with known mean and variance. Quasi Score (QS) and Corrected Score (CS) are two consistent estimation methods, where the first makes use of the distribution of the covariate (structural method), while the l...
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We compare two consistent estimators of the parameter vector β of a general exponential family measurement error model with respect to their relative efficiency. The quasi score (QS) estimator uses the distribution of the regressor, the corrected score (CS) estimator does not make use of this distribution and is therefore more robust. However, if the regressor distribution is known, QS is asymp...
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The asymptotic covariance matrices of the corrected score, the quasi score, and the simple score estimators of a polynomial measurement error model have been derived in the literature. Here some alternative formulas are presented, which might lead to an easier computation of these matrices. In particular, new properties of the variables tr and μr that constitute the estimators are derived. In a...
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Corrected score (Nakamura, 1990; Stefanski, 1989) is an important consistent functional modeling method for covariate measurement error in nonlinear regression. Although its pathological behaviors are known to exacerbate with increasing error contamination, neither their nature nor severity is well understood. In this article, we conduct a detailed investigation with the log-linear model for co...
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ژورنال
عنوان ژورنال: Metrika
سال: 2006
ISSN: 0026-1335,1435-926X
DOI: 10.1007/s00184-006-0076-5