SOLVED: from scipy.optimize import fmin import numpy as np from scipy.stats import norm mu = 10000 sigma = np.round(norm.rvs(loc=mu, scale=sigma, size=M)) def likelihood(x, mu, sigma): # Likelihood of one sample # YOUR
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In [1]: from scipy.optimize import curve_fit from | Chegg.com
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1. Use scipy optimize.root to locate 2 solutions | Chegg.com
1c) (10 points) Use the function scipy.optimize. | Chegg.com