class_docstr: Scale prior distributions parameters.
class_docstr_tok: ["Scale","prior","distributions","parameters","."]
code: def scale(self):
      # Scale response
      self.scale_response()
  
      # Scale common terms
      for term in self.response_component.common_terms.values():
          if (
              hasattr(term.prior, "auto_scale")
              and term.prior.auto_scale
          ):
              self.scale_common(term)
  
      # Scale intercept
      if self.has_intercept:
          term = self.response_component.intercept_term
          if term.prior.auto_scale:
              self.scale_intercept(term)
  
      # Scale group-specific terms
      for term in self.response_component.group_specific_terms.values():
          if term.prior.auto_scale:
              self.scale_group_specific(term)
  
      # Scale threshold parameters in ordinal families
      self.scale_threshold()
  
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 9 for calling the PriorScaler obj's underlying member method code with example usage: obj.scale() without return types