cholesky分解是用于将一个对称正定的矩阵分解为一个上三角与一个下三角矩阵乘积的形式，可运用于回归系数求解，线性方程组求解中
逐步回归是在回归分析的建模过程中用于变量筛选的有效方法，这里同时进行了向前和向后回归，效果更加显著(Cholesky decomposition is used to decompose a symmetric positive definite matrix into an upper triangle and a lower triangular matrix product, which can be used to solve the regression coefficients and solve the linear equations.
Stepwise regression is an effective method for variable selection in the modeling process of regression analysis. The effect of both forward and backward regression is more significant at the same time.)