代码：
# -*- coding: utf-8 -*-'''Created on 5月15日@author: user@attention: beta distribution'''from scipy.stats import betaimport matplotlib.pyplot as pltimport numpy as npdef test_beta_distribution():fig, ax = plt.subplots(1, 1)a, b = 2.31, 0.627#Mean(‘m’), variance(‘v’), skew(‘s’), and/or kurtosis(‘k’).mean, var, skew, kurt = beta.stats(a, b, moments='mvsk')print (mean)print (var)print (skew)print (kurt)print (beta.pdf(0.333, a, b))x = np.linspace(beta.ppf(0.01, a, b),beta.ppf(0.99, a, b), 100)ax.plot(x, beta.pdf(x, a, b), 'r-', lw=5, alpha=0.6, label='beta pdf')rv = beta(a, b)ax.plot(x, rv.pdf(x), 'k-', lw=2, label='frozen pdf')vals = beta.ppf([0.001, 0.5, 0.999], a, b)np.allclose([0.001, 0.5, 0.999], beta.cdf(vals, a, b))r = beta.rvs(a, b, size=1000)ax.hist(r, density=True, histtype='stepfilled', alpha=0.2)ax.legend(loc='best', frameon=False)plt.show()if __name__ == '__main__': test_beta_distribution()#beta分布
结果：
0.78651685393258420.04264874077027537-1.1240714863228220.56545748340552280.30981296354477267
