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Regression analysis
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==Other methods== Although the parameters of a regression model are usually estimated using the method of least squares, other methods which have been used include: * [[Bayesian method]]s, e.g. [[Bayesian linear regression]] * Percentage regression, for situations where reducing ''percentage'' errors is deemed more appropriate.<ref>{{cite journal| ssrn=1406472 |title=Least Squares Percentage Regression |last=Tofallis |first=C. |journal=Journal of Modern Applied Statistical Methods |volume=7 |year=2009 |pages=526β534| doi=10.2139/ssrn.1406472|url=https://digitalcommons.wayne.edu/cgi/viewcontent.cgi?article=1466&context=jmasm |hdl=2299/965 |hdl-access=free }}</ref> * [[Least absolute deviations]], which is more robust in the presence of outliers, leading to [[quantile regression]] * [[Nonparametric regression]], requires a large number of observations and is computationally intensive * [[Scenario optimization]], leading to [[interval predictor model]]s
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