class_docstr: Summarize the fit of a linear regression model.
  
  It handles the output of contrasts, estimates of covariance, etc.
docstr: Proportion of explained variance.
  
  If not from an OLS model this is "pseudo"-R2.
docstr_tok: ["Proportion","of","explained","variance",".","If","not","from","an","OLS","model","this","is","``","pseudo","''","-R2","."]
code: def r_square(self):
      """Proportion of explained variance.
  
      If not from an OLS model this is "pseudo"-R2.
      """
      return np.var(self.predicted, 0) / np.var(self.whitened_Y, 0)
  
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 6 for calling the RegressionResults obj's underlying member method code with example usage: obj.r_square() and returns: unknown