An Algorithm For Least Squares Analysis Of Spectroscopic Data
Abstract
This paper describes a variant of the Gauss-Newton-Hartley algorithm for nonlinear least squares, in which a QR implementation is used to solve the linear least squares problem. We follow Grey's idea of updating variables at intermediate stages of the orthogonalization. This technique, applied in partitions identified with known or suspected spectral lines, appears to be especially suited to the analysis of spectroscopic data. We suggest that this algorithm is an attractive candidate for the optimization role in Ekenberg's interactive computer graphics curve fitting program. © 1979 BIT Foundations.
Recommended Citation
D. C. St. Clair and A. K. Rigler, "An Algorithm For Least Squares Analysis Of Spectroscopic Data," BIT, vol. 19, no. 4, pp. 448 - 456, Springer, Jan 1979.
The definitive version is available at https://doi.org/10.1007/BF01931260
Department(s)
Mathematics and Statistics
Keywords and Phrases
Curve fitting; least squares; orthogonalization; spectroscopic analysis
International Standard Serial Number (ISSN)
1572-9125; 0006-3835
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2023 Springer, All rights reserved.
Publication Date
01 Jan 1979
