class_docstr: Results class for Beta regression
  
  This class inherits from GenericLikelihoodModelResults and not all
  inherited methods might be appropriate in this case.
class_docstr_tok: ["Results","class","for","Beta","regression","This","class","inherits","from","GenericLikelihoodModelResults","and","not","all","inherited","methods","might","be","appropriate","in","this","case","."]
docstr: Return distribution parameters converted from model prediction.
  
  Parameters
  ----------
  params : array_like
      The model parameters.
  exog : array_like
      Array of predictor variables for mean.
  transform : bool
      If transform is True and formulas have been used, then predictor
      ``exog`` is passed through the formula processing. Default is True.
  
  Returns
  -------
  (alpha, beta) : tuple of ndarrays
      Parameters for the scipy distribution to evaluate predictive
      distribution.
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code: def get_distribution_params(
      self, exog=None, exog_precision=None, transform=True
  ):
      """
      Return distribution parameters converted from model prediction.
  
      Parameters
      ----------
      params : array_like
          The model parameters.
      exog : array_like
          Array of predictor variables for mean.
      transform : bool
          If transform is True and formulas have been used, then predictor
          ``exog`` is passed through the formula processing. Default is True.
  
      Returns
      -------
      (alpha, beta) : tuple of ndarrays
          Parameters for the scipy distribution to evaluate predictive
          distribution.
      """
      mean = self.predict(exog=exog, transform=transform)
      precision = self.predict(
          exog_precision=exog_precision,
          which="precision",
          transform=transform,
      )
      return precision * mean, precision * (1 - mean)
  
imports: import numpy
  from scipy.special import gammaln
  import patsy
  import statsmodels.base.wrapper
  import statsmodels.regression.linear_model
  from statsmodels.tools.decorators import cache_readonly
  from statsmodels.base.model import GenericLikelihoodModel, GenericLikelihoodModelResults, _LLRMixin
  from statsmodels.genmod import families
label_desc: Use image node_id 6 for calling the BetaResults obj's underlying member method code with example usage: obj.get_distribution_params(exog, exog_precision, transform) and returns: unknown,  unknown