SVForecastResult#

class impulso.results.SVForecastResult(*, idata, series_name, steps, index=None)[source]#

Bases: VARResultBase

Density forecast from a univariate SV model.

Parameters:

idata (InferenceData)
series_name (str)
steps (int)
index (Index | None)

idata#: InferenceData-schema container with ‘forecast’ in posterior_predictive.

series_name#

Name of the forecast series.

Type:: str

steps#

Number of forecast steps.

Type:: int

index#

Forecast axis, normally supplied by FittedSV.forecast — a DatetimeIndex continuing the observed calendar when the data’s frequency is detectable. None (the default) falls back to a step-numbered RangeIndex.

Type:: pandas.Index | None

hdi(prob=0.89)[source]#

Highest-density interval for the density forecast.

Parameters:: prob (float) – Probability mass for the HDI. Default 0.89.
Returns:: HDIResult with lower/upper DataFrames sharing the index of median().
Return type:: HDIResult

median()[source]#

Posterior median of the density forecast.

Returns:: DataFrame of median forecasts indexed by the forecast axis — calendar dates when available, otherwise step number.
Return type:: DataFrame

model_config = {'arbitrary_types_allowed': True, 'frozen': True}#: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

plot()[source]#

Plot the density forecast with HDI bands.

Returns:: Matplotlib Figure of the density forecast.
Return type:: Figure

to_dataframe()[source]#

Density forecast posterior median as a DataFrame.

Returns:: DataFrame of median forecasts indexed by the forecast axis.
Return type:: DataFrame