class_docstr: Contain only information of the model fit necessary     for :term:`contrast` computation.
  
  Its intended to save memory when details of the model are unnecessary.
docstr: See LikelihoodModelResults constructor.
  
  The only difference is that the whitened Y and residual values
  are stored for a regression model.
docstr_tok: ["See","LikelihoodModelResults","constructor",".","The","only","difference","is","that","the","whitened","Y","and","residual","values","are","stored","for","a","regression","model","."]
code: def __init__(self, results):
      """See LikelihoodModelResults constructor.
  
      The only difference is that the whitened Y and residual values
      are stored for a regression model.
      """
      self.theta = results.theta
      self.cov = results.cov
      self.dispersion = results.dispersion
      self.nuisance = results.nuisance
  
      self.df_total = results.Y.shape[0]
      self.df_model = results.model.df_model
      # put this as a parameter of LikelihoodModel
      self.df_residuals = self.df_total - self.df_model
  
imports: import numpy
  import scipy.linalg
  from nibabel.onetime import auto_attr
  from numpy.linalg import matrix_rank
  from nilearn.glm._utils import positive_reciprocal
  from nilearn.glm.model import LikelihoodModelResults
label_desc: Use image node_id 1 to create a new SimpleRegressionResults object from inherited base classes: LikelihoodModelResults with example: obj = SimpleRegressionResults(results)