class_docstr: Base class for an estimator of causal effect.
  
  Subclasses implement different estimation methods. All estimation methods are in the package "dowhy.causal_estimators"
class_docstr_tok: ["Base","class","for","an","estimator","of","causal","effect",".","Subclasses","implement","different","estimation","methods",".","All","estimation","methods","are","in","the","package","``","dowhy.causal_estimators","''"]
docstr: Compute standard error of an obtained causal estimate.
  
  :param method: Method for computing the standard error.
  :param kwargs: Other optional parameters to be passed to the estimating method.
  :returns: Standard error of the causal estimate.
code: def estimate_std_error(
      self, data: pd.DataFrame, method=None, **kwargs
  ):
      """Compute standard error of an obtained causal estimate.
  
      :param method: Method for computing the standard error.
      :param kwargs: Other optional parameters to be passed to the estimating method.
      :returns: Standard error of the causal estimate.
      """
      if method is None:
          if self._confidence_intervals:
              method = self._confidence_intervals
          else:
              method = "default"
      std_error = None
      if (
          method == "default" or method is True
      ):  # user has not provided any method
          try:
              std_error = self._estimate_std_error(method, **kwargs)
          except NotImplementedError:
              std_error = self._estimate_std_error_with_bootstrap(
                  data, **kwargs
              )
      else:
          if method == "bootstrap":
              std_error = self._estimate_std_error_with_bootstrap(
                  data, **kwargs
              )
          else:
              std_error = self._estimate_std_error(method, **kwargs)
      return std_error
  
imports: import copy
  import logging
  from collections import namedtuple
  from typing import Dict, List, Optional, Union
  import numpy
  import pandas
  import sympy
  from sklearn.utils import resample
  import dowhy.interpreters
  from dowhy.causal_identifier.identified_estimand import IdentifiedEstimand
  from dowhy.utils.api import parse_state
label_desc: Use image node_id 17 for calling the CausalEstimator obj's underlying member method code with example usage: obj.estimate_std_error(data, method) and returns: std_error