code: def _cross_section(
      y: ArrayLike1D | ArrayLike2D, x: ArrayLike2D, trend: UnitRootTrend
  ) -> RegressionResults:
      if trend not in ("n", "c", "ct", "ctt"):
          raise ValueError(
              'trend must be one of "n", "c", "ct" or "ctt"'
          )
      y = ensure1d(y, "y", True)
      x = ensure2d(x, "x")
  
      if not isinstance(x, pd.DataFrame):
          cols = [f"x{i}" for i in range(1, x.shape[1] + 1)]
          assert isinstance(y, pd.Series)
          x = pd.DataFrame(x, columns=cols, index=y.index)
      x = add_trend(x, trend)
      res = OLS(y, x).fit()
      return res
  
imports: from __future__ import annotations
  from typing import Any, NamedTuple, cast
  import pandas
  from statsmodels.iolib.summary import Summary
  from statsmodels.regression.linear_model import OLS, RegressionResults
  import arch.covariance.kernel
  from arch.typing import ArrayLike1D, ArrayLike2D, UnitRootTrend
  from arch.utility.array import ensure1d, ensure2d
  from arch.utility.timeseries import add_trend
label_desc: Use image node_id 3 for calling a global function with example usage: _cross_section(y, x, trend) and returns: res