用(python)Scipy拟合帕累托分布

import numpy as np
import matplotlib.pyplot as plt
from scipy import stats
from scipy.optimize import curve_fit

# 生成模拟数据
data = stats.pareto.rvs(5, scale=10, size=1000)

# 拟合帕累托分布
def pareto_fit(x, a, b):
    return stats.pareto.pdf(x, a, scale=b)

params, _ = curve_fit(pareto_fit, data, np.histogram(data, bins=50)[0])

# 绘制拟合结果
plt.hist(data, bins=50, density=True, alpha=0.6, color='b')
xmin, xmax = plt.xlim()
x = np.linspace(xmin, xmax, 100)
p = stats.pareto.pdf(x, params[0], scale=params[1])
plt.plot(x, p, 'k-', linewidth=2)
plt.xlabel('x')
plt.ylabel('Probability Density')
plt.title('Pareto Distribution')
plt.show()