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On Estimating Linear Relationships When Both Variables Are Subject to Heteroscedastic Measurement Errors

Summary: [This abstract is based on the authors' abstract.]Point estimation of the parameters in a linear measurement error model is considered when the variances in the measurement errors on both axes vary between observations. Application of existing and new regression methods to real data cases shows that the coefficients of the regression lines depend on the method chosen. Guidelines for choosing a suitable regression method are provided.

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  • Topics: Sampling
  • Keywords: Heteroscedasticity,Least squares,Maximum likelihood estimate (MLE),Measurement error,Moment estimation,Sample size
  • Author: Cheng, Chi-Lun; Riu, Jordi
  • Journal: Technometrics