Abstract
Our summary of least squares given in Sections 1.3–1.5 shows that the core problem is one of solving the set of linear equations (1.3). In some accounts of regression, therefore, we are led directly to this algebraic problem.
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Further reading
Clarke, M. R. B. (1981) Algorithm AS163. A Gauss algorithm for moving from one linear model to another without going back to the data. Appl. Statist., 30, 198–203.
Clarke, M. R. B. (1982) The Gauss-Jordan SWEEP operator with detection of collinearity. Appl. Statist., 31, 166–168.
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© 1986 G. Barrie Wetherill
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Barrie Wetherill, G., Duncombe, P., Kenward, M., Köllerström, J., Paul, S.R., Vowden, B.J. (1986). Obtaining least squares solutions. In: Regression Analysis with Applications. Monographs on Statistics and Applied Probability. Springer, Dordrecht. https://doi.org/10.1007/978-94-009-4105-2_3
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DOI: https://doi.org/10.1007/978-94-009-4105-2_3
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