docs: def linreg_ols_lu(y, X):
      """Linear Regression, OLS, by solving linear equations and LU decomposition
  
      Properties
      ----------
      * based on LAPACK's _gesv what applies LU decomposition
      * avoids using python's inverse functions
      * should be stable
      * no overhead or other computations
  
      Example:
      --------
          beta = linreg_ols_lu(y,X)
  
      Links:
      ------
      * http://oxyba.de/docs/linreg_ols_lu
  
      """
      import numpy as np
      try:  # solve OLS formula
          return np.linalg.solve(np.dot(X.T, X), np.dot(X.T, y))
      except np.linalg.LinAlgError:
          print("LinAlgError: X*X' is singular or not square.")
          return None