pastas.solver.LeastSquares.ci_contribution#

LeastSquares.ci_contribution(name, n=1000, alpha=0.05, max_iter=10, **kwargs)#

Method to calculate the confidence interval for the contribution.

Returns

data – DataFrame of length number of observations and two columns labeled 0.025 and 0.975 (numerical values) containing the 2.5% and 97.5% interval (for alpha=0.05)

Return type

Pandas.DataFrame

Notes

The confidence interval shows the uncertainty in the simulation due to parameter uncertainty. In other words, there is a 95% probability that the true best-fit line for the observed data lies within the 95% confidence interval.