Least-squares fitting of data by polynomials

Autor:	S.A. Dyer, Xin He
Rok vydání:	2001
Předmět:	Classical orthogonal polynomials Set (abstract data type) Smoothing spline Data point Polynomial and rational function modeling Difference polynomials Mathematical analysis Curve fitting Electrical and Electronic Engineering Focus (optics) Instrumentation Mathematics
Zdroj:	IEEE Instrumentation & Measurement Magazine. 4:46-51
ISSN:	1094-6969
DOI:	10.1109/5289.975465
Popis:	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.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::c9c8ef507b37f50fce890d7b9eeb0603 https://doi.org/10.1109/5289.975465 Zobrazit plný text záznamu