class_docstr: Results from rolling regressions
  
  Parameters
  ----------
  model : RollingWLS
      Model instance
  store : RollingStore
      Container for raw moving window results
  k_constant : bool
      Flag indicating that the model contains a constant
  use_t : bool
      Flag indicating to use the Student's t distribution when computing
      p-values.
  cov_type : str
      Name of covariance estimator
code: def info_criteria(self, crit, dk_params=0):
      return self._wrap(
          RegressionResults.info_criteria(
              self, crit, dk_params=dk_params
          )
      )
  
imports: from statsmodels.compat.numpy import lstsq
  from statsmodels.compat.pandas import Appender, Substitution, cache_readonly, call_cached_func, get_cached_doc
  from collections import namedtuple
  import numpy
  from pandas import DataFrame, MultiIndex, Series
  from scipy import stats
  from statsmodels.base import model
  from statsmodels.base.model import LikelihoodModelResults, Model
  from statsmodels.regression.linear_model import RegressionModel, RegressionResults
  from statsmodels.tools.validation import array_like, int_like, string_like
label_desc: Use image node_id 5 for calling the RollingRegressionResults obj's underlying member method code with example usage: obj.info_criteria(crit, dk_params) and returns: self