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: Overall goodness of fit F test,
  comparing model to a model with just an intercept.
  If not an OLS model this is a pseudo-F.
code: def F_overall(self):
      """Overall goodness of fit F test,
      comparing model to a model with just an intercept.
      If not an OLS model this is a pseudo-F.
      """
      F = self.MSR / self.MSE
      Fp = stats.f.sf(F, self.df_model - 1, self.df_resid)
      return {
          "F": F,
          "p_value": Fp,
          "df_num": self.df_model - 1,
          "df_den": self.df_resid,
      }
  
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 13 for calling the RegressionResults obj's underlying member method code with example usage: obj.F_overall() and returns: dict