class_docstr: Class to contain results from likelihood models.
  
  This is the class in which things like AIC, BIC, llf
  can be implemented as methods, not computed in, say,
  the fit method of OLSModel.
class_docstr_tok: ["Class","to","contain","results","from","likelihood","models",".","This","is","the","class","in","which","things","like","AIC",",","BIC",",","llf","can","be","implemented","as","methods",",","not","computed","in",",","say",",","the","fit","method","of","OLSModel","."]
docstr: Return the maximized log-likelihood.
docstr_tok: ["Return","the","maximized","log-likelihood","."]
code: def logL(self):
      """Return the maximized log-likelihood."""
      return self.model.logL(self.theta, self.Y, nuisance=self.nuisance)
  
imports: import numpy
  from nibabel.onetime import auto_attr
  from scipy.linalg import inv
  from scipy.stats import t
  from nilearn.glm._utils import pad_contrast, positive_reciprocal
label_desc: Use image node_id 2 for calling the LikelihoodModelResults obj's underlying member method code with example usage: obj.logL() and returns: self