class_docstr: A specification of model family.
  
  Parameters
  ----------
  name : str
      The name of the family. It can be any string.
  likelihood : Likelihood
      A ``bambi.families.Likelihood`` instance specifying the model likelihood function.
  link : Union[str, Dict[str, Union[str, Link]]]
      The link function that's used for every parameter in the likelihood function.
      Keys are the names of the parameters and values are the link functions.
      These can be a ``str`` with a name or a ``bambi.families.Link`` instance.
      The link function transforms the linear predictors.
  
  Examples
  --------
  >>> import bambi as bmb
  
  Replicate the Gaussian built-in family.
  
  >>> sigma_prior = bmb.Prior("HalfNormal", sigma=1)
  >>> likelihood = bmb.Likelihood("Gaussian", params=["mu", "sigma"], parent="mu")
  >>> family = bmb.Family("gaussian", likelihood, "identity")
  >>> bmb.Model("y ~ x", data, family=family, priors={"sigma": sigma_prior})
  
  Replicate the Bernoulli built-in family.
  
  >>> likelihood = bmb.Likelihood("Bernoulli", parent="p")
  >>> family = bmb.Family("bernoulli", likelihood, "logit")
  >>> bmb.Model("y ~ x", data, family=family)
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code: def __init__(
      self,
      name,
      likelihood,
      link: Union[str, Dict[str, Union[str, Link]]],
  ):
      self.name = name
      self.likelihood = likelihood
      self.link = link
      self.default_priors = {}
  
file_path: bambi/bambi/families/family.py
imports: from typing import Dict, Union
  import numpy
  import pymc
  import xarray
  from bambi.families.link import Link
  from bambi.utils import get_auxiliary_parameters, get_aliased_name
label_desc: Use image node_id 1 to create a new Family object  with example: obj = Family(name, likelihood, link)