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- W175027653 abstract "The reduced major axis (RMA) method is widely used in many disciplines as a solution to errors in variables model, although it lacks efficiency. This paper provides an alternative view on RMA estimator. Moreover, it introduces a new estimator to fit regression line when both variables are subject to measurement errors. The proposed weighted reduced major axis (WR) estimator is derived based on the mathematical relationship between the vertical and orthogonal distances of the observed points and the regression line. Compared to the RMA and OLS-bisector estimators the proposed WR estimator is less sensitive to the variation of the ratio of error variances. The simulation results show that the WR estimator is more consistent and efficient than the RMA and OLS-bisector estimators." @default.
- W175027653 created "2016-06-24" @default.
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- W175027653 date "2012-12-19" @default.
- W175027653 modified "2023-09-27" @default.
- W175027653 title "Weighted reduced major axis method for regression model" @default.
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