class_docstr: Results class for Engle-Granger cointegration tests.
  
  Parameters
  ----------
  stat : float
      The Engle-Granger test statistic.
  pvalue : float
      The pvalue of the Engle-Granger test statistic.
  crit_vals : Series
      The critical values of the Engle-Granger specific to the sample size
      and model dimension.
  null : str
      The null hypothesis.
  alternative : str
      The alternative hypothesis.
  trend : str
      The model's trend description.
  order : int
      The number of stochastic trends in the null distribution.
  adf : ADF
      The ADF instance used to perform the test and lag selection.
  xsection : RegressionResults
      The OLS results used in the cross-sectional regression.
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code: def __init__(
      self,
      stat: float,
      pvalue: float,
      crit_vals: pd.Series,
      null: str = "No Cointegration",
      alternative: str = "Cointegration",
      trend: str = "c",
      order: int = 2,
      adf: ADF | None = None,
      xsection: RegressionResults | None = None,
  ) -> None:
      super().__init__(
          stat,
          pvalue,
          crit_vals,
          null,
          alternative,
          trend,
          order,
          xsection,
      )
      self.name = "Engle-Granger Cointegration Test"
      assert adf is not None
      self._adf = adf
      self._additional_info.update(
          {
              "ADF Lag length": self.lags,
              "Trend": self.trend,
              "Estimated Root ρ (γ+1)": self.rho,
              "Distribution Order": self.distribution_order,
          }
      )
  
imports: from __future__ import annotations
  import numpy
  import pandas
  from scipy import stats
  from statsmodels.iolib.summary import Summary
  from statsmodels.iolib.table import SimpleTable
  from statsmodels.regression.linear_model import RegressionResults
  from arch.typing import ArrayLike1D, ArrayLike2D, Literal, UnitRootTrend
  from arch.unitroot._shared import ResidualCointegrationTestResult, _check_cointegrating_regression, _cross_section
  from arch.unitroot.critical_values.engle_granger import CV_PARAMETERS, LARGE_PARAMETERS, SMALL_PARAMETERS, TAU_MAX, TAU_MIN, TAU_STAR
  from arch.unitroot.unitroot import ADF, TREND_DESCRIPTION
label_desc: Use image node_id 1 to create a new EngleGrangerTestResults object from inherited base classes: ResidualCointegrationTestResult with example: obj = EngleGrangerTestResults(stat, pvalue, crit_vals, null, alternative, trend, order, adf, xsection)