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import pylab as pl | |
from scipy.misc import derivative | |
import inspect | |
def cramer_rao(model, p0, X, noise, show_plot=False): | |
"""Calulate inverse of the Fisher information matrix for model | |
sampled on grid X with parameters p0. Assumes samples are not | |
correlated and have equal variance noise^2. | |
Parameters |