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proper propagation of variance through the Gaussian likelihood
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1 changed files with 2 additions and 2 deletions
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@ -42,8 +42,8 @@ class Gaussian(likelihood):
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"""
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mean = mu*self._std + self._mean
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true_var = (var + self._variance)*self._std**2
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_5pc = mean + - 2.*np.sqrt(var)
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_95pc = mean + 2.*np.sqrt(var)
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_5pc = mean + - 2.*np.sqrt(true_var)
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_95pc = mean + 2.*np.sqrt(true_var)
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return mean, _5pc, _95pc
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def fit_full(self):
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