import numpy as np from scipy.stats import laplace import matplotlib.pyplot as plt fig, ax = plt.subplots(1, 1) mean, var, skew, kurt = laplace.stats(moments='mvsk') x = np.linspace(laplace.ppf(0.01), laplace.ppf(0.99), 100) ax.plot(x, laplace.pdf(x), 'r-', lw=5, alpha=0.6, label='laplace pdf') rv = laplace() ax.plot(x, rv.pdf(x), 'k-', lw=2, label='frozen pdf') vals = laplace.ppf([0.001, 0.5, 0.999]) np.allclose([0.001, 0.5, 0.999], laplace.cdf(vals)) r = laplace.rvs(size=1000) #ax.hist(r, normed=True, histtype='stepfilled', alpha=0.2) #ax.legend(loc='best', frameon=False) plt.show()
def laplace_central_moment(loc, scale, moment):
if moment < 1 or moment > 4:
print 'Unable to compute moment of laplace distribution ):'
assert(False)
moments_arr = laplace.stats(loc=loc, scale=scale, moments='mvsk')
return moments_arr[moment - 1]