Title :
Least-squares fitting of data by polynomials
Author :
Dyer, Stephen A. ; He, Xin
fDate :
12/1/2001 12:00:00 AM
Abstract :
In the last two columns, we looked at one approach to approximation, interpolating a set of points by piecewise-cubic polynomials forming a cubic spline. We now look at another approach - one that involves fitting a curve to a set of data without restricting that curve to coincide with the data points. Our focus is on least-squares approximation, and, in particular, least-square fitting of polynomials to data
Keywords :
curve fitting; least squares approximations; polynomial approximation; Fourier representation; curve fitting; error function; higher-degree polynomials; least-square fitting; least-squares approximation; natural spline; normal equations; orthogonal-polynomial functions; polynomials to data; straight line; Curve fitting; Helium; Instruments; Linear approximation; Noise level; Nonlinear equations; Polynomials; Spline;
Journal_Title :
Instrumentation & Measurement Magazine, IEEE
DOI :
10.1109/5289.975465
