class_docstr: Negative binomial variance function
  
  Parameters
  ----------
  alpha : float
      The ancillary parameter for the negative binomial variance function.
      `alpha` is assumed to be nonstochastic.  The default is 1.
  
  Methods
  -------
  call
      Returns the negative binomial variance
  
  Notes
  -----
  Formulas :
  
     V(mu) = mu + alpha*mu**2
  
  Alias for NegativeBinomial:
  nbinom = NegativeBinomial()
  
  A private method _clean trims the data by machine epsilon so that p is
  in (0,inf)
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docstr: Negative binomial variance function
  
  Parameters
  ----------
  mu : array_like
      mean parameters
  
  Returns
  -------
  variance : ndarray
      variance = mu + alpha*mu**2
docstr_tok: ["Negative","binomial","variance","function","Parameters","--","--","--","--","--","mu",":","array_like","mean","parameters","Returns","--","--","--","-","variance",":","ndarray","variance","=","mu","+","alpha","*","mu","*","*","2"]
code: def __call__(self, mu):
      """
      Negative binomial variance function
  
      Parameters
      ----------
      mu : array_like
          mean parameters
  
      Returns
      -------
      variance : ndarray
          variance = mu + alpha*mu**2
      """
      p = self._clean(mu)
      return p + self.alpha * p**2
  
file_path: statsmodels/statsmodels/genmod/families/varfuncs.py
imports: import numpy
label_desc: Use image node_id 3 for calling the NegativeBinomial obj's underlying member method code with example usage: obj.__call__(mu) and returns: unknown