Adding prediction interval to forecast

Is your feature request related to a current problem? Please describe. Most algorithms have a prediction interval also associated with the forecast. This could be implemented in an algorithm agnostic way also.

https://otexts.com/fpp2/prediction-intervals.html

Describe proposed solution In predict have an optional parameter, prediction_interval which when set True. returns not just forecast (yhat) , but also yhat_upper and yhat_lower based on the prediction interal.

Can use the sample Naive forecast logic mentioned here to implement this.

Describe potential alternatives Prophet, auto arima etc provides these prediction interval values.

Additional context This could also be used in plots for the forecast.

[hrzn]

Thanks for the suggestion. We have this (or at least something similar) on our roadmap.

[hrzn]

This has been released in v0.9.0.

Some models support specifying num_samples to predict(), in which case they will return a “stochastic” TimeSeries containing num_samples samples, which describe the distribution of the time series’ values. Some of the neural networks (at the moment RNNModel and TCNModel) are able to produce such stochastic forecasts if they are built specifying a certain likelihood parameter (e.g., darts.utils.likelihood_models.GaussianLikelihoodModel() to train the model with a negative Gaussian log likelihood loss).

We went for such a sampling-based representation (instead, for instance, of returning fixed confidence intervals), because it allows (i) to compute arbitrary quantiles (using e.g. TimeSeries.quantiles_df() or TimeSeries.quantile_timeseries() and (ii) for multivariate series it allows to capture the joint distribution over all components without assuming a specific parametric form.