class_docstr: Class responsible for handling input data and extracting metadata into the
  appropriate form
class_docstr_tok: ["Class","responsible","for","handling","input","data","and","extracting","metadata","into","the","appropriate","form"]
docstr: Labels for covariance matrices
  
  In multidimensional models, each dimension of a covariance matrix
  differs from the number of param_names.
  
  If not set, returns param_names
docstr_tok: ["Labels","for","covariance","matrices","In","multidimensional","models",",","each","dimension","of","a","covariance","matrix","differs","from","the","number","of","param_names",".","If","not","set",",","returns","param_names"]
code: def cov_names(self):
      """
      Labels for covariance matrices
  
      In multidimensional models, each dimension of a covariance matrix
      differs from the number of param_names.
  
      If not set, returns param_names
      """
      # for handling names of covariance names in multidimensional models
      if self._cov_names is not None:
          return self._cov_names
      return self.param_names
  
imports: from __future__ import annotations
  from statsmodels.compat.python import lmap
  from functools import reduce
  import numpy
  from pandas import DataFrame, Series, isnull, MultiIndex
  import statsmodels.tools.data
  from statsmodels.tools.decorators import cache_readonly, cache_writable
  from statsmodels.tools.sm_exceptions import MissingDataError
label_desc: Use image node_id 13 for calling the ModelData obj's underlying member method code with example usage: obj.cov_names() and returns: self, self