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 (Pandas.DataFrame) – 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).

• **kwargs – Additional keyword arguments are passed to the ml.get_contribution() method. For example, tmin and tmax can be passed as keyword arguments to compute the confidence interval of a contribution for a specific period.

Parameters

• name (str) –

• n (int) –

• alpha (float) –

• max_iter (int) –

Return type

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.