class_docstr: Handles parameter management for estimators composed of named estimators.
  
  Partly adapted from sklearn utils.metaestimator.py.
code: def _replace_estimator(self, attr, name, new_val):
      # assumes `name` is a valid estimator name
      new_estimators = list(getattr(self, attr))
      for i, est_tpl in enumerate(new_estimators):
          estimator_name = est_tpl[0]
          if estimator_name == name:
              new_tpl = list(est_tpl)
              new_tpl[1] = new_val
              new_estimators[i] = tuple(new_tpl)
              break
      setattr(self, attr, new_estimators)
  
imports: from inspect import isclass
  import numpy
  import pandas
  from sktime.base import BaseEstimator
label_desc: Use image node_id 7 for calling the _HeterogenousMetaEstimator obj's underlying member method code with example usage: obj._replace_estimator(attr, name, new_val) without return types