class_docstr: StatsForecast ARCH estimator.
  
  Direct interface to ``statsforecast.models.ARCH``.
  
  This implements the Autoregressive Conditional
  Heteroskedasticity (ARCH) model.
  
  Constructs an ARCH(p) model.
  
  Parameters
  ----------
  p: int (default 1)
      AR parameter - number of auto-regressive lags.
class_docstr_tok: ["StatsForecast","ARCH","estimator",".","Direct","interface","to","``","statsforecast.models.ARCH","``",".","This","implements","the","Autoregressive","Conditional","Heteroskedasticity","(","ARCH",")","model",".","Constructs","an","ARCH","(","p",")","model",".","Parameters","--","--","--","--","--","p",":","int","(","default","1",")","AR","parameter","-","number","of","auto-regressive","lags","."]
code: def _get_statsforecast_params(self):
      return {"p": self.p}
  
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 3 for calling the StatsForecastARCH obj's underlying member method code with example usage: obj._get_statsforecast_params() and returns: dict