Technical Note: Review of methods for linear least-squares fitting of data and application to atmospheric chemistry problems C. A. Cantrell National Center for Atmospheric Research, Atmospheric Chemistry Division, 1850 Table Mesa Drive, Boulder, CO 80305, USA Received: 13 February 2008 – Accepted: 21 February 2008 – Published: 1 April 2008 Correspondence to: C. A. Cantrell ([email protected]) P...

Least-squares fitting, first developed by Carl Friedrich Gauss, is arguably the most widely used technique in statistical data analysis. It provides a method through which the parameters of a model can be optimised in order to obtain the best fit to a data set through the minimisation of the squared differences between the model and the data. This tutorial document describes the closely associa...

Along with the science research field is more and more wide, solve large-scale over determined system of linear equations has become an important problem , and the parallel processing technology also become the trend of the research. Firstly, this paper introduces the basic principle of the curve fitting least squares serial algorithm, based on the least square principle we found an parallel le...

A Singular value decomposition (SVD)-enhanced Least-square fitting technique is discussed. By automatic identifying, ordering, and selecting dominant SVD modes of the derivative matrix that responds to the variations of the variables, the converging process of the Least Square fitting is significantly enhanced. Thus the fitting speed can be fast enough for a fairly large system. This technique ...

5 QR Decomposition 7 5.1 Householder Reflections and Givens Rotations . . . . . . . . . . . . . . . . . . . . . . . 8 5.2 Gram-Schmidt orthonormalization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 5.3 QR Decomposition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 5.4 Least Square Fitting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ....