Kolmogorov–Smirnov statistic experiment.

d_stat_experiment.py

# Michael A. Alcorn ([email protected])

import matplotlib.pyplot as plt
import numpy as np
import seaborn as sns

import numpy as np
import statsmodels.api as sm # recommended import according to the docs
import matplotlib.pyplot as plt

sample = np.random.uniform(0, 1, 50)


from scipy.stats import kstest

F = "uniform"
trials = 10000

for samples in [100, 1000]:
    Ds = []
    x_Ds = []
    for i in range(trials):
        G = np.random.uniform(size = samples)
        D = kstest(G, F).statistic
        Ds.append(D)
        
        ecdf = sm.distributions.ECDF(G)
        x = np.linspace(min(G), max(G))
        y = ecdf(x)
        x_D = x[np.abs(y - x).argmax()]
        x_Ds.append(x_D)
        # plt.step(x, y)
        # plt.plot([0, 1], [0, 1], "k-") 
        # plt.show()
    
    sns.distplot(Ds)
    plt.show()
    sns.distplot(x_Ds)
    plt.show()