def create_moments(self, _n_moments):
self.n_moments = _n_moments
self.true_moments = []
for i in range(0, self.n_moments):
self.true_moments.append(
beta.moment(i + 1, self.p_beta, self.q_beta))
def beta_example_gender():
'''
Plot example beta distribution for males and females
'''
a_f, b_f = 3 * 1, 2 * 1
a_m, b_m = a_f * 2, b_f * 2
# Mean and sample size
mu_m = beta.moment(1, a_m, b_m)
mu_f = beta.moment(1, a_f, b_f)
n_m, n_f = a_m + b_m, a_f + b_f
x = np.linspace(0, 1, 1000)
fig, ax = plt.subplots()
# Function to create label
def label_str(g, mu, n):
label_str = g + ' \\\\ ' \
+ r'($\mu = $' + str(round(mu, 2)) + r', $n = $' + str(n) + ')'
return label_str
ax.plot(x,
beta.pdf(x, a_m, b_m),
label=label_str('Men', mu_m, n_m),
color=color_list[0])
ax.plot(x,
beta.pdf(x, a_f, b_f),
label=label_str('Women', mu_f, n_f),
color=color_list[1])
ax.legend(loc='upper left', handlelength=0.5, frameon=False, borderpad=0)
# get the current limit of y-axis
_, y_max = ax.get_ylim()
# Dotted line at mean
ax.plot([mu_f, mu_f], [0, y_max], ':', color='#BBBBBB')
# set y-limit
ax.set_ylim(0, y_max)
def generate_moments(self, max_moment):
'''
Calculate & store moments to retrieve more efficiently later
'''
self._moments = np.zeros((max_moment, 1))
#Rely on scipy.stats to return non-central moment
for i in range(max_moment):
self._moments[i] = scipybeta.moment(i+1, self._alpha, self._beta,
self._shift, self._scale)