chi^2 and Linear Fits

Andrew Gould (Ohio State)

chi^2 and Linear Fits

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arxiv astro-ph/0310577 v1 pith:HMUO5DRX submitted 2003-10-20 astro-ph

Andrew Gould (Ohio State) This is my paper · ORCID

classification astro-ph

keywords fitsdataformlinearpresentedtheyamplifiedappear

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The mathematics of linear fits is presented in covariant form. Topics include: correlated data, covariance matrices, joint fits to multiple data sets, constraints, and extension of the formalism to non-linear fits. A brief summary at the end provides a convenient crib sheet. These are somewhat amplified notes from a 90 minute lecture in a first-year graduate course. None of the results are new. They are presented here because they do not appear to be elsewhere available in compact form.

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An Alternate Method for Minimizing $\chi^2$
astro-ph.IM 2025-02 conditional novelty 3.0 of 10

SFit implements the Gauss-Newton approximation for chi-square minimization and, in KMTNet point-lens fits, reports fewer false success and failure flags than BFGS while using fewer evaluations than Nelder-Mead.

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