Overall Percentage Error (OPE). For the true series :math:`y` and predicted series :math:`\\hat{y}` of length :math:`T`, it is computed as a

Number of time steps predicted at once by the model, not defined for statistical models.

Number of time steps predicted at once by the model.

Number of time steps that the output/prediction starts after the end of the input.

Returns the likelihood parameter names.

Returns the past covariates component names generated by `SequentialEncoder.past_encoders`. Only available after calling `SequentialEncoder.en

Returns the past covariates encoders

Returns the past transformer object

Plot the warp path. Parameters ---------- new_plot Boolean value indicating whether to spawn a new figure. show_series

Plot a TimeSeries using Matplotlib. Parameters ---------- series The TimeSeries to plot. new_plot Whether to spawn a

Plots the uni-variate component of each series, with lines between them indicating the alignment selected by the DTW algorithm. Paramete

Plot a TimeSeries using Plotly. Parameters ---------- series The TimeSeries to plot. fig Optionally, a Plotly `go.Fig

Precision Score [1]_. For the true series :math:`y` and predicted series :math:`\\hat{y}` of length :math:`T`, it is computed per component/c

Generates sampled or direct likelihood parameter predictions. Parameters ---------- model_output The out

Forecasts values for `n` time steps after the end of the series. If :func:`fit()` has been called with only one ``TimeSeries`` as argument, t

Forecasts values for `n` time steps after the end of the training series. If some future covariates were specified during the training, they

If the `series` parameter is not set, forecasts values for `n` time steps after the end of the training series. If some future covariates were

Forecasts calibrated quantile intervals (or samples from calibrated intervals) for `n` time steps after the end of the `series`. It i

Returns the distribution parameters as a array, extracted from the raw model outputs.

Overwrite the parent since the parameters are extracted in two steps.

Overwrite parent method since QuantileRegression is not a Likelihood per-se and parameters must be extracted differently.

Process package RST files to replace titles and add docstring content. This is connected to the 'source-read' event in Sphinx. Args:

Quantile Loss (QL). Also known as Pinball Loss. QL is a metric that quantifies the accuracy of a specific quantile :math:`q` from the predict

Quantile Risk (QR) QR is a metric that quantifies the accuracy of a specific quantile :math:`q` from the predicted value distribution of a st

Decorator usable on any method within a class that will provide a random context. The decorator will store a `_random_instance` property on the o

Decorator usable on any method within a class that will provide an isolated torch random context. The decorator will store a `_random_instance` p

List of all continuous variables in model

Recall Score [1]_. For the true series :math:`y` and predicted series :math:`\\hat{y}` of length :math:`T`, it is computed per component/colu

Whether the `Encoder` sub class must be fit with `Encoder.encode_train()` before inference with `Encoder.encode_inference()`.

Restores default config after each test.

Compute the residuals that the model produced for historical forecasts on (potentially multiple) `series`. This function computes the differe

Root Mean Squared Log Error (RMSLE). For the true series :math:`y` and predicted series :math:`\\hat{y}` of length :math:`T`, it is computed per

Root Mean Squared Scaled Error (RMSSE) (see [1]_ for more information on scaled forecasting errors). It is the Root Mean Squared Error (RMSE) sca

Samples a prediction from the likelihood distribution and the predicted parameters.

Samples a prediction from the likelihood distribution and the predicted parameters.