MovingAverageModel

class MovingAverageModel(window: int = 5)

Bases: etna.models.seasonal_ma.SeasonalMovingAverageModel

MovingAverageModel averages previous series values to forecast future one.

\[y_{t} = \frac{\sum_{i=1}^{n} y_{t-i} }{n},\]

where \(n\) is window size.

Notes

This model supports in-sample and out-of-sample prediction decomposition. Prediction components are corresponding target lags with weights of \(1/window\).

Init MovingAverageModel.

Parameters

window (int) – number of history points to average

Inherited-members

Methods

fit(ts)	Fit model.
forecast(ts, prediction_size[, ...])	Make autoregressive forecasts.
get_model()	Get internal model.
load(path)	Load an object.
params_to_tune()	Get default grid for tuning hyperparameters.
predict(ts, prediction_size[, return_components])	Make predictions using true values as autoregression context (teacher forcing).
save(path)	Save the object.
set_params(**params)	Return new object instance with modified parameters.
to_dict()	Collect all information about etna object in dict.

Attributes

context_size

Context size of the model.