code: def ff_target(
      H, L=None, A=None, T=None, rotation_method="orthogonal"
  ):
      r"""
      Subroutine for the value of f using (orthogonal or oblique) rotation
      towards a target matrix, i.e., we minimize:
  
      .. math::
          \phi(L) =\frac{1}{2}\|L-H\|^2.
  
      Either :math:`L` should be provided or :math:`A` and :math:`T` should be
      provided. For orthogonal rotations :math:`L` satisfies
  
      .. math::
          L =  AT,
  
      where :math:`T` is an orthogonal matrix. For oblique rotations
      :math:`L` satisfies
  
      .. math::
          L =  A(T^*)^{-1},
  
      where :math:`T` is a normal matrix.
  
      Parameters
      ----------
      H : numpy matrix
          target matrix
      L : numpy matrix (default None)
          rotated factors, i.e., :math:`L=A(T^*)^{-1}=AT`
      A : numpy matrix (default None)
          non rotated factors
      T : numpy matrix (default None)
          rotation matrix
      rotation_method : str
          should be one of {orthogonal, oblique}
      """
      if L is None:
          assert A is not None and T is not None
          L = rotateA(A, T, rotation_method=rotation_method)
      return np.linalg.norm(L - H, "fro") ** 2
  
file_path: statsmodels/statsmodels/multivariate/factor_rotation/_gpa_rotation.py
imports: import numpy
label_desc: Use image node_id 8 for calling a global function with example usage: ff_target(H, L, A, T, rotation_method) and returns: unknown