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 __str__(self):
      args = [
          ("name", self.name),
          ("params", self.params),
          ("parent", self.parent),
          ("dist", self.dist),
      ]
      args = [f"{arg[0]}: {arg[1]}" for arg in args]
      return (
          f"{self.__class__.__name__}({indentify(multilinify(args))}\n)"
      )
  
file_path: bambi/bambi/families/likelihood.py
imports: from collections import namedtuple
  from bambi.utils import multilinify, indentify
label_desc: Use image node_id 6 for calling the Likelihood obj's underlying member method code with example usage: obj.__str__() and returns: self, str, indentify, str