class_docstr: Representation of a Likelihood function for a Bambi model.
  
  Notes:
  * ``parent`` must be in ``params``
  * ``parent`` is inferred from the ``name`` if it is a known name
  
  Parameters
  ----------
  name : str
      Name of the likelihood function. Must be a valid PyMC distribution name.
  params : Sequence[str]
      The name of the parameters the likelihood function accepts.
  parent : str
      Optional specification of the name of the mean parameter in the likelihood.
      This is the parameter whose transformation is modeled by the linear predictor.
  dist : pymc.distributions.distribution.DistributionMeta or callable
      Optional custom PyMC distribution that will be used to compute the likelihood.
code: def params(self, value):
      if self.name in self.DISTRIBUTIONS:
          if value is None:
              value = self.DISTRIBUTIONS[self.name].params
          elif set(value) != set(self.DISTRIBUTIONS[self.name].params):
              raise ValueError(
                  f"'{value}' does not match the parameters of '{self.name}'"
              )
      # Otherwise, no check is done. At your own risk!
      self._params = value
  
file_path: bambi/bambi/families/likelihood.py
imports: from collections import namedtuple
  from bambi.utils import multilinify, indentify
label_desc: Use image node_id 3 for calling the Likelihood obj's underlying member method code with example usage: obj.params(value) without return types