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: Check whether parameters of the bootstrap have changed.
  
  This is an efficiency method that checks if fresh resampling of the bootstrap samples is required.
  Returns True if parameters have changed and resampling should be done again.
  
  :param bootstrap_estimates_params: A dictionary of parameters for the current bootstrap samples
  :param given_params: A dictionary of parameters passed by the user
  :returns: A binary flag denoting whether the parameters are different.
code: def is_bootstrap_parameter_changed(
      bootstrap_estimates_params, given_params
  ):
      """Check whether parameters of the bootstrap have changed.
  
      This is an efficiency method that checks if fresh resampling of the bootstrap samples is required.
      Returns True if parameters have changed and resampling should be done again.
  
      :param bootstrap_estimates_params: A dictionary of parameters for the current bootstrap samples
      :param given_params: A dictionary of parameters passed by the user
      :returns: A binary flag denoting whether the parameters are different.
      """
      is_any_parameter_changed = False
      for prm, val in bootstrap_estimates_params.items():
          given_val = given_params.get(prm, None)
          if given_val is not None and given_val != val:
              is_any_parameter_changed = True
              break
      return is_any_parameter_changed
  
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 24 for calling the CausalEstimator obj's underlying member method code with example usage: obj.is_bootstrap_parameter_changed(bootstrap_estimates_params, given_params) and returns: is_any_parameter_changed