class_docstr: Wrapper class for estimators from the EconML library.
  
  Supports additional parameters as listed below. For init and fit
  parameters of each estimator, refer to the EconML docs.
docstr: Returns None if the confidence interval has not been calculated.
docstr_tok: ["Returns","None","if","the","confidence","interval","has","not","been","calculated","."]
code: def _estimate_confidence_intervals(
      self, confidence_level=None, method=None
  ):
      """Returns None if the confidence interval has not been calculated."""
      return self.effect_intervals
  
imports: import inspect
  from importlib import import_module
  from typing import Any, Callable, List, Optional, Protocol, Union
  from warnings import warn
  import numpy
  import pandas
  from numpy.distutils.misc_util import is_sequence
  from dowhy.causal_estimator import CausalEstimate, CausalEstimator
  from dowhy.causal_identifier import IdentifiedEstimand
  from dowhy.utils.api import parse_state
label_desc: Use image node_id 5 for calling the Econml obj's underlying member method code with example usage: obj._estimate_confidence_intervals(confidence_level, method) and returns: self