| import numpy as np | |
| import numpy.random as nr | |
| def gen(N): | |
| X = nr.choice([0,1],size=N,p=[0.6,0.4]) | |
| D = nr.choice([0,1],size=N,p=[0.6,0.4]) | |
| epsi = nr.uniform(0,2,N) | |
| Y = X+D*epsi | |
| return X,D,epsi,Y | |
| def estim(D,Y): | |
| Y0 = np.average(Y[D==0]) | |
| Y1 = np.average(Y[D==1]) | |
| return Y1-Y0 | |
| X,D,epsi,Y = gen(10000) | |
| estim(D,Y) |
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