statsmodels.tsa.statespace.structural.UnobservedComponentsResults.plot_components
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UnobservedComponentsResults.plot_components(which=None, alpha=0.05, observed=True, level=True, trend=True, seasonal=True, freq_seasonal=True, cycle=True, autoregressive=True, legend_loc='upper right', fig=None, figsize=None)
[source]
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Plot the estimated components of the model.
Parameters: |
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which ({'filtered', 'smoothed'}, or None, optional) – Type of state estimate to plot. Default is ‘smoothed’ if smoothed results are available otherwise ‘filtered’.
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alpha (float, optional) – The confidence intervals for the components are (1 - alpha) %
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level (boolean, optional) – Whether or not to plot the level component, if applicable. Default is True.
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trend (boolean, optional) – Whether or not to plot the trend component, if applicable. Default is True.
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seasonal (boolean, optional) – Whether or not to plot the seasonal component, if applicable. Default is True.
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freq_seasonal (boolean, optional) – Whether or not to plot the frequency domain seasonal component(s), if applicable. Default is True.
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cycle (boolean, optional) – Whether or not to plot the cyclical component, if applicable. Default is True.
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autoregressive (boolean, optional) – Whether or not to plot the autoregressive state, if applicable. Default is True.
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fig (Matplotlib Figure instance, optional) – If given, subplots are created in this figure instead of in a new figure. Note that the grid will be created in the provided figure using
fig.add_subplot() . -
figsize (tuple, optional) – If a figure is created, this argument allows specifying a size. The tuple is (width, height).
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Notes
If all options are included in the model and selected, this produces a 6x1 plot grid with the following plots (ordered top-to-bottom):
- Observed series against predicted series
- Level
- Trend
- Seasonal
- Freq Seasonal
- Cycle
- Autoregressive
Specific subplots will be removed if the component is not present in the estimated model or if the corresponding keywork argument is set to False.
All plots contain (1 - alpha
) % confidence intervals.