class_docstr: Statsforecast AutoTheta estimator.
  
  Direct interface to ``statsforecast.models.AutoTheta`` by Nixtla.
  
  This estimator directly interfaces ``AutoTheta``,
  from ``statsforecast`` [1]_ by Nixtla.
  
  AutoTheta model automatically selects the best Theta (Standard Theta Model ("STM"),
  Optimized Theta Model ("OTM"), Dynamic Standard Theta Model ("DSTM"), Dynamic
  Optimized Theta Model ("DOTM")) model using mse.
  
  Parameters
  ----------
  season_length : int, optional, default=1
      number of observations per unit of time (e.g. 24 for hourly data), by default 1
  
  decomposition_type : str, optional, default="multipliciative"
      possible values: "additive", "multiplicative"
      type of seasonal decomposition, by default "multiplicative"
  
  model : Optional[str], optional
      controlling Theta Model, by default searches the best model
  
  References
  ----------
  .. [1] https://nixtla.github.io/statsforecast/models.html#autotheta
  
  See Also
  --------
  ThetaForecaster
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code: def _get_statsforecast_params(self):
      return {
          "season_length": self.season_length,
          "decomposition_type": self.decomposition_type,
          "model": self.model,
      }
  
imports: from typing import Dict, List, Optional, Union
  from sktime.forecasting.base import BaseForecaster
  from sktime.forecasting.base.adapters._generalised_statsforecast import StatsForecastBackAdapter, _GeneralisedStatsForecastAdapter
  from sktime.utils.validation._dependencies import _check_soft_dependencies
label_desc: Use image node_id 3 for calling the StatsForecastAutoTheta obj's underlying member method code with example usage: obj._get_statsforecast_params() and returns: dict