Least Squares for Practitioners

Blais, J. A. Rod

Least Squares for Practitioners

dc.contributor.author	Blais, J. A. Rod
dc.date.accessioned	2018-09-27T12:02:17Z
dc.date.available	2018-09-27T12:02:17Z
dc.date.issued	2010-09-23
dc.date.updated	2018-09-27T12:02:17Z
dc.description.abstract	In experimental science and engineering, least squares are ubiquitous in analysis and digital data processing applications. Minimizing sums of squares of some quantities can be interpreted in very different ways and confusion can arise in practice, especially concerning the optimality and reliability of the results. Interpretations of least squares in terms of norms and likelihoods need to be considered to provide guidelines for general users. Assuming minimal prerequisites, the following expository discussion is intended to elaborate on some of the mathematical characteristics of the least-squares methodology and some closely related questions in the analysis of the results, model identification, and reliability for practical applications. Examples of simple applications are included to illustrate some of the advantages, disadvantages, and limitations of least squares in practice. Concluding remarks summarize the situation and provide some indications of practical areas of current research and development.
dc.description.version	Peer Reviewed
dc.identifier.citation	J. A. Rod Blais, “Least Squares for Practitioners,” Mathematical Problems in Engineering, vol. 2010, Article ID 508092, 19 pages, 2010. doi:10.1155/2010/508092
dc.identifier.doi	https://doi.org/10.1155/2010/508092
dc.identifier.uri	http://hdl.handle.net/1880/108444
dc.language.rfc3066	en
dc.rights.holder	Copyright © 2010 J. A. Rod Blais. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
dc.title	Least Squares for Practitioners
dc.type	Journal Article