最小二乘法(Least Squares Fitting)

least squares fitting proceeds by finding the sum of the squares of the vertical deviations R2R^2 of a set of n data points:



The condition for R2R^2 to be a minimum is that



for i=1, …, n. For a linear fit,



so



These lead to the equations



In matrix form,



so



The 2×2 matrix inverse is



so



原文链接：Least Squares Fitting