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Fixed bugs for combined fits with multiple independent variables (#211)

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s-kuberski 2023-10-24 19:30:52 +02:00 • committed by GitHub
parent 0ef8649031
commit dc63142f8e
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2 changed files with 49 additions and 2 deletions
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pyerrors/fits.py
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@ -365,7 +365,7 @@ def least_squares(x, y, func, priors=None, silent=False, **kwargs):
raise Exception('The minimization procedure did not converge.')
output.chisquare = chisquare
output.dof = x_all.shape[-1] - n_parms + len(loc_priors)
output.dof = y_all.shape[-1] - n_parms + len(loc_priors)
output.p_value = 1 - scipy.stats.chi2.cdf(output.chisquare, output.dof)
if output.dof > 0:
output.chisquare_by_dof = output.chisquare / output.dof
@ -393,7 +393,7 @@ def least_squares(x, y, func, priors=None, silent=False, **kwargs):
hat_vector = prepare_hat_matrix()
A = W @ hat_vector
P_phi = A @ np.linalg.pinv(A.T @ A) @ A.T
expected_chisquare = np.trace((np.identity(x_all.shape[-1]) - P_phi) @ W @ cov @ W)
expected_chisquare = np.trace((np.identity(y_all.shape[-1]) - P_phi) @ W @ cov @ W)
output.chisquare_by_expected_chisquare = output.chisquare / expected_chisquare
if not silent:
print('chisquare/expected_chisquare:', output.chisquare_by_expected_chisquare)