代码:
# -*- coding: utf-8 -*- ''' Created on 2018年5月15日 @author: user @attention: beta distribution ''' from scipy.stats import beta import matplotlib.pyplot as plt import numpy as np def 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:
0.7865168539325842 0.04264874077027537 -1.124071486322822 0.5654574834055228 0.30981296354477267