python最小二乘法误差分析

在Python中，最小二乘法误差分析是通过使用SciPy库中的leastsq函数来实现的。该函数可以用于拟合回归模型并估计回归系数。下面是一个使用最小二乘法进行误差分析的示例代码：

import random
import numpy as np
from scipy.optimize import leastsq

def orbit_fitting(t, m):
    def func(p, x):
        w3, w2, w1, w0 = p
        return w3*x**3 + w2*x**2 + w1 * x + w0

    def error(p, x, y):
        return func(p, x) - y

    orbital_paras = []
    p0 = [1, 2, 3, 4]
    x = np.array(t)
    y = np.array(m)
    Para = leastsq(error, p0, args=(x, y))
    orbital_paras.append(Para<span class="em">1</span><span class="em">2</span><span class="em">3</span>
#### 引用[.reference_title]
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