Abstract
The aim of a least-squares approach is to estimate the parameters that define a known, or hypothetical, physical law. The estimated parameters are those that make the law fit a given set of data points in the least-squares sense. Probably the reader has carried through a least-squares curve fit more than once during his career. But, there is actually a great deal more to this problem than accomplishing the fit.
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Chapter 14
L. Breiman: Statistics: With a View Toward Applications (Houghton Mifflin, Boston 1973) Chap. 10
M. G. Kendall, A. Stuart: The Advanced Theory of Statistics, Vol. 1 (Charles Griffin London 1969)
Additional Reading
Bjerhammar, A.: Theory of Errors and Generalized Matrix Inverses (Elsevier Scientific, Amsterdam 1973)
Mendenhall, W., R. L. Scheaffer: Mathematical Statistics with Applications (Duxbury, North Scituate, MA 1973)
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© 1983 Springer-Verlag Berlin Heidelberg
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Frieden, B.R. (1983). Least-Squares Curve Fitting — Regression Analysis. In: Probability, Statistical Optics, and Data Testing. Springer Series in Information Sciences, vol 10. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-96732-0_14
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DOI: https://doi.org/10.1007/978-3-642-96732-0_14
Publisher Name: Springer, Berlin, Heidelberg
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