class_docstr: StatsForecast GARCH estimator.
  
  Direct interface to ``statsforecast.models.GARCH``.
  
  This implements the Generalized Autoregressive Conditional
  Heteroskedasticity (GARCH) model.
  
  Constructs a GARCH(p, q) model.
  
  Parameters
  ----------
  p: int (default 1)
      AR parameter - number of auto-regressive lags.
  q: int (default 1)
      GARCH heteroskedasticity lag parameter - number of lags for variance term.
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code: def _get_statsforecast_class(self):
      from statsforecast.models import GARCH as _GARCH
  
      return _GARCH
  
file_path: sktime/sktime/forecasting/arch/_statsforecast_arch.py
imports: from sktime.forecasting.base.adapters._generalised_statsforecast import _GeneralisedStatsForecastAdapter
label_desc: Use image node_id 2 for calling the StatsForecastGARCH obj's underlying member method code with example usage: obj._get_statsforecast_class() and returns: _GARCH