class_docstr: Class to hold results from fitting a state space model.
  
  Parameters
  ----------
  model : MLEModel instance
      The fitted model instance
  params : ndarray
      Fitted parameters
  
  Attributes
  ----------
  model : Model instance
      A reference to the model that was fit.
  nobs : float
      The number of observations used to fit the model.
  params : ndarray
      The parameters of the model.
class_docstr_tok: ["Class","to","hold","results","from","fitting","a","state","space","model",".","Parameters","--","--","--","--","--","model",":","MLEModel","instance","The","fitted","model","instance","params",":","ndarray","Fitted","parameters","Attributes","--","--","--","--","--","model",":","Model","instance","A","reference","to","the","model","that","was","fit",".","nobs",":","float","The","number","of","observations","used","to","fit","the","model",".","params",":","ndarray","The","parameters","of","the","model","."]
code: def df_resid(self):
      return self.nobs_effective - self.df_model
  
imports: from collections import OrderedDict
  import contextlib
  import warnings
  import numpy
  import pandas
  from scipy.stats import norm
  from statsmodels.base.data import PandasData
  from statsmodels.tools.decorators import cache_readonly
  from statsmodels.tools.eval_measures import aic, aicc, bic, hqic
  from statsmodels.tools.sm_exceptions import PrecisionWarning
  from statsmodels.tools.numdiff import _get_epsilon, approx_fprime, approx_fprime_cs, approx_hess_cs
  from statsmodels.tools.tools import pinv_extended
  import statsmodels.tsa.base.tsa_model
  from statsmodels.tsa.statespace.tools import _safe_cond
label_desc: Use image node_id 3 for calling the StateSpaceMLEResults obj's underlying member method code with example usage: obj.df_resid() and returns: unknown