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Total least squares regression (TLS) fits a line to data where errors may occur in both the dependent and independent variables. In higher dimensions, TLS fits a hyperplane to such data. The elementary algorithm presented here fits readily in a first course in numerical linear algebra.
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Yves Nievergelt (1994) studied this question.
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