code: def test_rm2006_forecast(self):
      vol = RiskMetrics2006()
      params = np.array([])
      resids = self.resid
      backcast = vol.backcast(resids)
      var_bounds = vol.variance_bounds(resids)
      forecasts = vol.forecast(
          params, resids, backcast, var_bounds, horizon=10, start=0
      )
      _resids = np.array(resids.tolist() + [0])
      _sigma2 = np.empty_like(_resids)
      _var_bounds = np.array(var_bounds.tolist() + [[0, np.inf]])
      vol.compute_variance(
          params, _resids, _sigma2, backcast, _var_bounds
      )
      assert forecasts.forecast_paths is None
      assert forecasts.shocks is None
      one_step = _sigma2[1:]
      for i in range(10):
          assert_allclose(
              forecasts.forecasts[:, i], one_step, rtol=1e-4
          )
  
      alt_forecasts = vol.forecast(
          params, resids, backcast, var_bounds, horizon=10, start=500
      )
      _compare_truncated_forecasts(forecasts, alt_forecasts, 500)
  
imports: import numpy
  from numpy.random import RandomState
  from numpy.testing import assert_allclose
  import pandas
  import pytest
  from arch.univariate import arch_model
  from arch.univariate.distribution import Normal, StudentsT
  from arch.univariate.mean import ConstantMean
  from arch.univariate.volatility import APARCH, EGARCH, FIGARCH, GARCH, HARCH, BootstrapRng, ConstantVariance, EWMAVariance, FixedVariance, MIDASHyperbolic, RiskMetrics2006
label_desc: Use image node_id 30 for calling the TestVarianceForecasts obj's underlying member method code with example usage: obj.test_rm2006_forecast() without return types