最小平方法求回归系数

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--- 最小平方法求回归系数 [2023/04/08 03:44] – zhangruihao
+++ 最小平方法求回归系数 [2024/04/12 04:44] (当前版本) – 2104龚文滕
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   *矩阵形式：b = (X’X)^-1 X’y
+----
+  ***Best fit line**：The goal is to minimize the error, which means that this line is closest to all data points.
+  *The regression line is used to predict the value of Y using the formula (linear equation) given X, a, and b.
+  ***Least squares method**：First, calculate the distance between the actual and predicted values of each Y and square it. Then, calculate the sum of squared errors to determine the total error between the line and the actual data. The line with the smallest sum of squared errors with the actual data points is the best fit line.
+  ***Ordinary least squares, OLS**
+{{:最小二乘法.png?800|}}
+  *SP is the product sum of deviations, SSx is the sum of squared errors of X, Sy and Sx are the standard deviations of Y and X, respectively
+  *Matrix form：b = (X’X)^-1 X’y

最小平方法求回归系数.1680925487.txt.gz · 最后更改: 2023/04/08 03:44 由 zhangruihao