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Dos and don'ts of reduced chi-squared
[article]
2010
arXiv
pre-print
Reduced chi-squared is a very popular method for model assessment, model comparison, convergence diagnostic, and error estimation in astronomy. In this manuscript, we discuss the pitfalls involved in using reduced chi-squared. There are two independent problems: (a) The number of degrees of freedom can only be estimated for linear models. Concerning nonlinear models, the number of degrees of freedom is unknown, i.e., it is not possible to compute the value of reduced chi-squared. (b) Due to
arXiv:1012.3754v1
fatcat:525edsb73jexvdeedvm6rx3fv4