code: def copy_index_vector(a, b, index, inplace=False, prefix=None):
      """
      Reorder the elements of a time-varying vector where all non-index
      values are in the first elements of the vector.
  
      Parameters
      ----------
      a : array_like
          The vector from which to copy. Must have shape (n, nobs) or (n, 1).
      b : array_like
          The vector to copy to. Must have shape (n, nobs).
      index : array_like of bool
          The vector of index indices. Must have shape (n, nobs).
      inplace : bool, optional
          Whether or not to copy to b in-place. Default is False.
      prefix : {'s', 'd', 'c', 'z'}, optional
          The Fortran prefix of the vector. Default is to automatically detect
          the dtype. This parameter should only be used with caution.
  
      Returns
      -------
      copied_vector : array_like
          The vector b with the non-index subvector of b copied onto it.
      """
      if prefix is None:
          prefix = find_best_blas_type((a, b))[0]
      copy = prefix_copy_index_vector_map[prefix]
  
      if not inplace:
          b = np.copy(b, order="F")
  
      # We may have been given an F-contiguous memoryview; in that case, we do
      # not want to alter it or convert it to a numpy array
      try:
          if not a.is_f_contig():
              raise ValueError()
      except (AttributeError, ValueError):
          a = np.asfortranarray(a)
  
      copy(a, b, np.asfortranarray(index))
  
      return b
  
imports: import numpy
  from scipy.linalg import solve_sylvester
  import pandas
  from statsmodels.compat.pandas import Appender
  from statsmodels.tools.data import _is_using_pandas
  from scipy.linalg.blas import find_best_blas_type
  from .None import _initialization, _representation, _kalman_filter, _kalman_smoother, _simulation_smoother, _cfa_simulation_smoother, _tools
label_desc: Use image node_id 27 for calling a global function with example usage: copy_index_vector(a, b, index, inplace, prefix) and returns: b