Monte Carlo, Markov Chains, Metropolis Hastings.
from N(x1,1) ... Iteration N: Sample xn from N(xn-1, 1) The simulation in python: import numpy as np import matplotlib.pyplot as plt # Markov Chain Monte Carlo sample_t1 = np.random.normal(0, 1, 1) samples = [sample_t1] for t in range(1,10000): samples_t = np.random.normal(samples[t-1], 1, 1)