https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.jarque_bera.html

import numpy as np
import xlrd
import pandas as pd
import matplotlib.pyplot as plt
from scipy import interpolate#插值, __version__
from scipy import stats#统计
from scipy.optimize import leastsq  ##引入最小二乘法算法
plt.rcParams['font.sans-serif']=['SimHei'] #用来正常显示中文标签
plt.rcParams['axes.unicode_minus']=False #用来正常显示负号
def JarqueBera():
    '''雅克-贝拉'''
    '''https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.jarque_bera.html官网'''

    rng = np.random.default_rng()
    x = rng.normal(0, 1, 100000)
    jarque_bera_test = stats.jarque_bera(x)
    print(jarque_bera_test)
    '''一般p显著水平要大于0.05'''
    # Jarque_beraResult(statistic（JB值）=3.3415184718131554, pvalue（显著水平）=0.18810419594996775)

JarqueBera()

Ctrl键点开函数可得，其内部公式

 	mu = x.mean()
    diffx = x - mu
    skewness = (1 / n * np.sum(diffx**3)) / (1 / n * np.sum(diffx**2))**(3 / 2.)
    kurtosis = (1 / n * np.sum(diffx**4)) / (1 / n * np.sum(diffx**2))**2
    jb_value = n / 6 * (skewness**2 + (kurtosis - 3)**2 / 4)
    p = 1 - distributions.chi2.cdf(jb_value, 2)