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georgebv avatar georgebv commented on July 1, 2024

@DamienIrving confidence intervals are computed using the Monte Carlo method (for both MLE and MCMC). Documentation takes a lot of time which I currently don't have. I would appreciate any contributions though and would give full credit to the author.

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oceanywalker avatar oceanywalker commented on July 1, 2024

It's really excellent work! While I have the same problem with the confident interval. Can you show me the exact position the confident interval calculated in your code?

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georgebv avatar georgebv commented on July 1, 2024

@oceanywalker here you go:

  • MLE:
    # Calculate confidence intervals
    rv_sample = self.distribution.distribution.isf(
    ep, *np.transpose(self.fit_parameter_cache[:n_samples])
    )
    cil, ciu = np.quantile(
    a=rv_sample, q=[(1 - alpha) / 2, (1 + alpha) / 2]
    )
  • MCMC:
    # Calculate confidence intervals
    rv_sample = self.distribution.get_prop(
    prop="isf",
    x=ep,
    free_parameters=np.vstack(self.trace[:, burn_in:, :]),
    )
    cil, ciu = np.quantile(
    a=rv_sample, q=[(1 - alpha) / 2, (1 + alpha) / 2]
    )

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