code: def corr2cov(corr, std):
      """
      convert correlation matrix to covariance matrix given standard deviation
  
      Parameters
      ----------
      corr : array_like, 2d
          correlation matrix, see Notes
      std : array_like, 1d
          standard deviation
  
      Returns
      -------
      cov : ndarray (subclass)
          covariance matrix
  
      Notes
      -----
      This function does not convert subclasses of ndarrays. This requires
      that multiplication is defined elementwise. np.ma.array are allowed, but
      not matrices.
      """
      corr = np.asanyarray(corr)
      std_ = np.asanyarray(std)
      cov = corr * np.outer(std_, std_)
      return cov
  
file_path: statsmodels/statsmodels/stats/moment_helpers.py
imports: import numpy
  from scipy.special import comb
label_desc: Use image node_id 13 for calling a global function with example usage: corr2cov(corr, std) and returns: cov