Gloria

Constructor

Gloria(*args[, model, sampling_period, ...])

The Gloria forecaster object is the central hub for the entire modeling workflow.

Attributes

Gloria.is_fitted

Determines whether the present Gloria model is fitted.

Methods

Gloria.add_event(name, regressor_type, profile)	Adds an event to the Gloria object.
Gloria.add_external_regressor(name, prior_scale)	Add an external regressor to the Gloria object.
Gloria.add_protocol(protocol)	Add a protocol to the Gloria object.
Gloria.add_seasonality(name, period, ...[, ...])	Adds a seasonality to the Gloria object.
Gloria.fit(data[, toml_path])	Fits the Gloria object.
Gloria.from_dict(model_dict)	Restores a fitted Gloria model from a dictionary.
Gloria.from_json(model_json[, return_as])	Restores a fitted Gloria model from a json string or file.
Gloria.from_toml(toml_path[, ignore])	Instantiate and configure a Gloria object from a TOML configuration file.
Gloria.load_data([toml_path])	Load and configure the time-series input data for fit method.
Gloria.make_future_dataframe([periods, ...])	Build a timestamp skeleton that extends the training horizon.
Gloria.plot(fcst[, ax, uncertainty, ...])	Plot the forecast, trend, and observed data with extensive customization options.
Gloria.plot_components(fcst[, uncertainty, ...])	Plot forecast components of a Gloria model using a modern Seaborn style, with global kwargs applied to all subplots.
Gloria.predict([data, toml_path])	Generate forecasts from a fitted Gloria model.
Gloria.to_dict()	Converts Gloria object to a dictionary of JSON serializable types.
Gloria.to_json([filepath])	Converts Gloria object to a JSON string.