least-squares method

"Least-squares method" is a method to determine unknown parameters so that the sum of squares of the residuals between the experimental and calculated values is minimized. It is used for crystal structure analysis and spectral curve fitting. When the sum of the squares of the residuals is minimized by a liner combination of unknown parameters (∑a_i・x_i + b), the method is called linear least-squares method. When a nonlinear function is used for fitting, it is called nonlinear least-squares method. Nonlinear least-squares method includes cases where fitting of unknown parameters is executed by numerical calculations without assuming a specific nonlinear function. For example, nonlinear least-squares fitting is effectively used to obtain structural parameters (atom positions, Debye-Waller factors) by minimizing the sum of the squares of the residuals between the experimental intensities of CBED patterns and the calculated intensities for crystal structure models. That is, the sum of the squares of the residuals for a set of certain structural parameters is obtained. Then, a set of structural parameters is generated so that the differential of the sum is negative with respect to each parameter. Then the sum of the squares of the residuals is calculated for the set of the generated parameters. Repeating the calculation procedure reaches the minimum sum of the squares of the residuals, determining the unknown parameters.