code: def _compute_multivariate_sample_acovf(endog, maxlag):
      r"""
      Computer multivariate sample autocovariances
  
      Parameters
      ----------
      endog : array_like
          Sample data on which to compute sample autocovariances. Shaped
          `nobs` x `k_endog`.
      maxlag : int
          Maximum lag to use when computing the sample autocovariances.
  
      Returns
      -------
      sample_autocovariances : list
          A list of the first `maxlag` sample autocovariance matrices. Each
          matrix is shaped `k_endog` x `k_endog`.
  
      Notes
      -----
      This function computes the forward sample autocovariances:
  
      .. math::
  
          \hat \Gamma(s) = \frac{1}{n} \sum_{t=1}^{n-s}
          (Z_t - \bar Z) (Z_{t+s} - \bar Z)'
  
      See page 353 of Wei (1990). This function is primarily implemented for
      checking the partial autocorrelation functions below, and so is quite slow.
  
      References
      ----------
      .. [*] Wei, William. 1990.
         Time Series Analysis : Univariate and Multivariate Methods. Boston:
         Pearson.
      """
      # Get the (demeaned) data as an array
      endog = np.array(endog)
      if endog.ndim == 1:
          endog = endog[:, np.newaxis]
      endog -= np.mean(endog, axis=0)
  
      # Dimensions
      nobs, k_endog = endog.shape
  
      sample_autocovariances = []
      for s in range(maxlag + 1):
          sample_autocovariances.append(np.zeros((k_endog, k_endog)))
          for t in range(nobs - s):
              sample_autocovariances[s] += np.outer(
                  endog[t], endog[t + s]
              )
          sample_autocovariances[s] /= nobs
  
      return sample_autocovariances
  
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 14 for calling a global function with example usage: _compute_multivariate_sample_acovf(endog, maxlag) and returns: sample_autocovariances