import scipy.stats
import numpy as np
import matplotlib.pyplot as plt
# sample from multivariate normal
x = scipy.stats.multivariate_normal(mean=[0,1], cov=[[1,0.5],[0.5,2]]).rvs(10000)
z = 1 / (x[0] - x[1])
print(z.mean())
print(z.var())
# Create kde of the distribution
kde = scipy.stats.gaussian_kde(z)
grid = np.linspace(z.min(), z.max(), 1000)
plt.plot(grid, kde.evaluate(grid))
plt.show()
假定
y
和x
服从正态分布,导出的量一般不会服从正态分布。您可以用数字来估计误差分布:相关问题 更多 >
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