code: def S_nw_panel(xw, weights, groupidx):
      """inner covariance matrix for HAC for panel data
  
      no denominator nobs used
  
      no reference for this, just accounting for time indices
      """
      nlags = len(weights) - 1
  
      S = weights[0] * np.dot(xw.T, xw)  # weights just for completeness
      for lag in range(1, nlags + 1):
          xw0, xwlag = lagged_groups(xw, lag, groupidx)
          s = np.dot(xw0.T, xwlag)
          S += weights[lag] * (s + s.T)
      return S
  
imports: import numpy
  from statsmodels.tools.grouputils import combine_indices, group_sums
  from statsmodels.stats.moment_helpers import se_cov
label_desc: Use image node_id 21 for calling a global function with example usage: S_nw_panel(xw, weights, groupidx) and returns: S