pastas.solver.LeastSquares.prediction_interval

LeastSquares.prediction_interval(n=1000, alpha=0.05, max_iter=10, **kwargs)

Method to calculate the prediction interval for the simulation.

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% prediction interval (for alpha=0.05)

Return type:

Pandas.DataFrame

Parameters:

• n (int) –

• alpha (float) –

• max_iter (int) –

Notes

Add residuals assuming a Normal distribution with standard deviation equal to the standard deviation of the residuals.