code: def test_raise(data):
      y, x, w = data
  
      mod = RollingWLS(y, x, window=100, missing="drop", weights=w)
      res = mod.fit()
      params = np.asarray(res.params)
      assert np.all(np.isfinite(params[99:]))
  
      if not np.any(np.isnan(y)):
          return
      mod = RollingWLS(y, x, window=100, missing="skip")
      res = mod.fit()
      params = np.asarray(res.params)
      assert np.any(np.isnan(params[100:]))
  
imports: from io import BytesIO
  from itertools import product
  import warnings
  import numpy
  import pandas
  import pytest
  from numpy.testing import assert_allclose, assert_array_equal
  from statsmodels import tools
  from statsmodels.regression.linear_model import WLS
  from statsmodels.regression.rolling import RollingWLS, RollingOLS
label_desc: Use image node_id 10 for calling a global function with example usage: test_raise(data) without return types