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Fitting nature's basic functions. I. Polynomials and linear least squares

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1 Author(s)
Rust, B.W. ; Nat. Inst. of Stand. & Technol., Gaithersburg, MD, USA

The problem of fitting a mathematical model which depends on an n-vector of unknown parameters, to a measured data set is ubiquitous in science and engineering. This paper is the first installment of a series that will demonstrate modern techniques for fitting combinations of basic mathematical functions to measured real-world data. Fitting a straight line, linear least squares and the best linear unbiased estimate are discussed.

Published in:

Computing in Science & Engineering  (Volume:3 ,  Issue: 5 )