statsmodels.tsa.forecasting.theta.ThetaModelResults.prediction_intervals#

ThetaModelResults.prediction_intervals(steps=1, theta=2, alpha=0.05)[source]#

Compute the prediction intervals for the forecast

Parameters:

stepsint, optional: The number of steps ahead to compute the forecast components.
thetafloat, optional: The theta value to use when computing the weight to combine the trend and the SES forecasts.
alphafloat, optional: Significance level for the confidence intervals.

Returns:

DataFrame: DataFrame with columns lower and upper

Notes

The variance of the h-step forecast is assumed to follow from the integrated Moving Average structure of the Theta model, and so is \(\sigma^2(1 + (h-1)(1 + (\alpha-1)^2))\). The prediction interval assumes that innovations are normally distributed.