class_docstr: Scale prior distributions parameters.
class_docstr_tok: ["Scale","prior","distributions","parameters","."]
code: def scale_intercept(self, term):
      if term.prior.name != "Normal":
          return
      mu, sigma = self.get_intercept_stats()
      term.prior.update(mu=mu, sigma=sigma)
  
file_path: bambi/bambi/priors/scaler.py
imports: import numpy
  import pymc
  from bambi.families.univariate import Cumulative, Gaussian, StoppingRatio, StudentT, VonMises
  from bambi.model_components import ConstantComponent
  from bambi.priors.prior import Prior
label_desc: Use image node_id 5 for calling the PriorScaler obj's underlying member method code with example usage: obj.scale_intercept(term) without return types