International Journal of Data Science and Big Data Analytics
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Volume 1, Issue 3, November 2021 | |
Research NoteOpenAccess | |
Generalized Least-Squares Ftting with Procedures for Uncorrelated Data of Constant Variance |
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Joachim W. Walewski1* and Thomas Metz2 |
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1Division of Combustion Physics, Lund University, P.O. Box 118 221 00, Lund, Sweden. E-mail: joachim.walewski@gmail.com
*Corresponding Author | |
Int.J.Data.Sci. & Big Data Anal. 1(3) (2021) 1-5, DOI: https://doi.org/10.51483/IJDSBDA.1.3.2021.1-5 | |
Received: 25/03/2021|Accepted: 21/09/2021|Published: 05/11/2021 |
We show how generalized least-squares fitting, namely, the fitting of correlated data, can be carried out with algorithms for uncorrelated data of constant variance. Doing so requires only a simple linear transformation of the measurement data.
Keywords: Constant variance, Correlated data, Curve fitting, Generalized least-squares fitting, Least squares, Least-squares fitting, Maximum-likelihood estimation, Ordinary leastsquares fitting
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