On an Iterative Procedure for Estimating Functions When Both Variables Are Subject to Error

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Abstract
An approximate likelihood function has been suggested by Clutton-Brock for fitting a curve to data in the case where both the independent and dependent variables are subject to error. His iterative procedure for maximizing the likelihood is shown to be unsatisfactory in comparison with more conventional methods. It is also shown that this likelihood is a poorly chosen approximation, in that an alternative form is exact for linear functions.

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