class_docstr: Scale prior distributions parameters.
class_docstr_tok: ["Scale","prior","distributions","parameters","."]
code: def scale_response(self):
      # Here we would add cases for other families if we wanted
      if isinstance(self.model.family, (Gaussian, StudentT)):
          sigma = self.model.components["sigma"]
          if (
              isinstance(sigma, ConstantComponent)
              and sigma.prior.auto_scale
          ):
              sigma.prior = Prior(
                  "HalfStudentT", nu=4, sigma=self.response_std
              )
      elif isinstance(self.model.family, VonMises):
          kappa = self.model.components["kappa"]
          if (
              isinstance(kappa, ConstantComponent)
              and kappa.prior.auto_scale
          ):
              kappa.prior = Prior(
                  "HalfStudentT", nu=4, sigma=self.response_std
              )
  
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 4 for calling the PriorScaler obj's underlying member method code with example usage: obj.scale_response() without return types