def test_geometric(rnd, p, loc=0):
# geometric random variate generator
geometric_dist = RVGs.Geometric(p, loc)
# obtain samples
samples = get_samples(geometric_dist, rnd)
# report mean and variance
print_test_results('Geometric',
samples,
expectation=1 / p + loc,
variance=(1 - p) / (p**2))
def test_fitting_geometric():
print("\nTesting Geometric with p=0.3, loc=1")
dist = RVGs.Geometric(p=0.3, loc=1)
print(' percentile interval: ', dist.get_percentile_interval(alpha=0.05))
data = np.array(get_samples(dist, np.random))
dict_mm_results = RVGs.Geometric.fit_mm(mean=np.average(data),
fixed_location=1)
dict_ml_results = RVGs.Geometric.fit_ml(data=data, fixed_location=1)
print(" Fit:")
print(" MM:", dict_mm_results)
print(" ML:", dict_ml_results)
# plot the fitted distributions
Plot.plot_geometric_fit(data=data,
fit_results=dict_mm_results,
title='Method of Moment')
Plot.plot_geometric_fit(data=data,
fit_results=dict_ml_results,
title='Maximum Likelihood')