docs: def qnwlogn(n, mu=None, sig2=None):
      """
      Computes nodes and weights for multivariate lognormal distribution
  
      Parameters
      ----------
      n : int or array_like(float)
          A length-d iterable of the number of nodes in each dimension
  
      mu : scalar or array_like(float), optional(default=zeros(d))
          The means of each dimension of the random variable. If a scalar
          is given, that constant is repeated d times, where d is the
          number of dimensions
  
      sig2 : array_like(float), optional(default=eye(d))
          A d x d array representing the variance-covariance matrix of the
          multivariate normal distribution.
  
      Returns
      -------
      nodes : np.ndarray(dtype=float)
          Quadrature nodes
  
      weights : np.ndarray(dtype=float)
          Weights for quadrature nodes
  
      Notes
      -----
      Based of original function ``qnwlogn`` in CompEcon toolbox by
      Miranda and Fackler
  
      References
      ----------
      Miranda, Mario J, and Paul L Fackler. Applied Computational
      Economics and Finance, MIT Press, 2002.
  
      """
      nodes, weights = qnwnorm(n, mu, sig2)
      return np.exp(nodes), weights