code: def norm_lls(y, params):
      """normal loglikelihood given observations and mean mu and variance sigma2
  
      Parameters
      ----------
      y : ndarray, 1d
          normally distributed random variable
      params : ndarray, (nobs, 2)
          array of mean, variance (mu, sigma2) with observations in rows
  
      Returns
      -------
      lls : ndarray
          contribution to loglikelihood for each observation
      """
  
      mu, sigma2 = params.T
      lls = -0.5 * (
          np.log(2 * np.pi) + np.log(sigma2) + (y - mu) ** 2 / sigma2
      )
      return lls
  
file_path: statsmodels/statsmodels/sandbox/regression/tools.py
imports: import numpy
  from scipy import special
  from scipy.special import gammaln
label_desc: Use image node_id 1 for calling a global function with example usage: norm_lls(y, params) and returns: lls