from typing import Dict
from etna.distributions import BaseDistribution
from etna.models.seasonal_ma import SeasonalMovingAverageModel
[docs]class NaiveModel(SeasonalMovingAverageModel):
"""Naive model predicts t-th value of series with its (t - lag) value.
.. math::
y_{t} = y_{t-s},
where :math:`s` is lag.
Notes
-----
This model supports in-sample and out-of-sample prediction decomposition.
Prediction component here is the corresponding target lag.
"""
def __init__(self, lag: int = 1):
"""
Init NaiveModel.
Parameters
----------
lag: int
lag for new value prediction
"""
self.lag = lag
super().__init__(window=1, seasonality=lag)
[docs] def params_to_tune(self) -> Dict[str, BaseDistribution]:
"""Get default grid for tuning hyperparameters.
This grid is empty.
Returns
-------
:
Grid to tune.
"""
return {}
__all__ = ["NaiveModel"]