class_docstr: Estimates a mean using outside information.
  
  Parameters
  ----------
  prior
  prior_weight
  
  References
  ----------
  [^1]: [Additive smoothing](https://www.wikiwand.com/en/Additive_smoothing)
  [^2]: [Bayesian average](https://www.wikiwand.com/en/Bayesian_average)
  [^3]: [Practical example of Bayes estimators](https://www.wikiwand.com/en/Bayes_estimator#/Practical_example_of_Bayes_estimators)
code: def __init__(self, prior: float, prior_weight: float):
      self.prior = prior
      self.prior_weight = prior_weight
      self._mean = Mean()
  
imports: from __future__ import annotations
  import copy
  import numpy
  from river import stats
label_desc: Use image node_id 1 to create a new BayesianMean object from inherited base classes: stats.base with example: obj = BayesianMean(prior, prior_weight)