class_docstr: This class summarizes the fit of a linear regression model.
  
  It handles the output of contrasts, estimates of covariance, etc.
class_docstr_tok: ["This","class","summarizes","the","fit","of","a","linear","regression","model",".","It","handles","the","output","of","contrasts",",","estimates","of","covariance",",","etc","."]
docstr: See LikelihoodModelResults constructor.
  
  The only difference is that the whitened Y and residual values
  are stored for a regression model.
code: def __init__(
      self,
      theta,
      Y,
      model,
      wY,
      wresid,
      cov=None,
      dispersion=1.0,
      nuisance=None,
  ):
      """See LikelihoodModelResults constructor.
  
      The only difference is that the whitened Y and residual values
      are stored for a regression model.
      """
      LikelihoodModelResults.__init__(
          self, theta, Y, model, cov, dispersion, nuisance
      )
      self.wY = wY
      self.wresid = wresid
  
imports: import warnings
  import numpy
  import numpy.linalg
  import scipy.linalg
  from nibabel.onetime import auto_attr
  from scipy import stats
  from nipy.algorithms.utils.matrices import matrix_rank, pos_recipr
  from .model import LikelihoodModel, LikelihoodModelResults
label_desc: Use image node_id 1 to create a new RegressionResults object from inherited base classes: LikelihoodModelResults with example: obj = RegressionResults(theta, Y, model, wY, wresid, cov, dispersion, nuisance)