Repeat linear regression and store the estimator

Question

x = np.random.uniform(0,1,100)
y = 5 + 3 * x + np.random.normal(loc=0,scale=1,size=100)
b, m = polyfit(x, y, 1)

I am using least-squares linear regression to get the estimator b,m. How can I repeat above calculations by 10000 times and then store 10000 different values of b,m to a list?

Answer 1

You can use a dictionary:

vals = {}
for i in range(10**4):
    x = np.random.uniform(0,1,100)
    y = 5 + 3 * x + np.random.normal(loc=0,scale=1,size=100)
    b, m = polyfit(x, y, 1)

    vals[f'Regression {i+1}'] = (b, m)