class_docstr: Class for the estimate object that every causal estimator returns
class_docstr_tok: ["Class","for","the","estimate","object","that","every","causal","estimator","returns"]
docstr: Get standard error of the obtained estimate.
  
  By default, this is done with the help of bootstrapped standard errors
  but can be overridden if the specific estimator implements other methods of estimating standard error.
  
  If the method provided is not bootstrap, this function calls the implementation of the specific estimator.
  
  :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 get_standard_error(self, method=None, **kwargs):
      """Get standard error of the obtained estimate.
  
      By default, this is done with the help of bootstrapped standard errors
      but can be overridden if the specific estimator implements other methods of estimating standard error.
  
      If the method provided is not bootstrap, this function calls the implementation of the specific estimator.
  
      :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.
  
      """
      std_error = self.estimator.estimate_std_error(
          self._data, method=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 6 for calling the CausalEstimate obj's underlying member method code with example usage: obj.get_standard_error(method) and returns: std_error