docstr: Derivatives of loglikelihood function w.r.t. linear predictors.
          
docstr_tok: ["Derivatives","of","loglikelihood","function","w.r.t",".","linear","predictors","."]
code: def hessian_factor(self, params, observed=True):
      """Derivatives of loglikelihood function w.r.t. linear predictors."""
      _, hf = self.score_hessian_factor(
          params, return_hessian=True, observed=observed
      )
      return hf
  
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 15 for calling the BetaModel obj's underlying member method code with example usage: obj.hessian_factor(params, observed) and returns: hf