class_docstr: Results class for a dimension reduction regression.
  
  Notes
  -----
  The `params` attribute is a matrix whose columns span
  the effective dimension reduction (EDR) space.  Some
  methods produce a corresponding set of eigenvalues
  (`eigs`) that indicate how much information is contained
  in each basis direction.
class_docstr_tok: ["Results","class","for","a","dimension","reduction","regression",".","Notes","--","--","-","The","`","params","`","attribute","is","a","matrix","whose","columns","span","the","effective","dimension","reduction","(","EDR",")","space",".","Some","methods","produce","a","corresponding","set","of","eigenvalues","(","`","eigs","`",")","that","indicate","how","much","information","is","contained","in","each","basis","direction","."]
code: def __init__(self, model, params, eigs):
      super().__init__(model, params)
      self.eigs = eigs
  
imports: import warnings
  import numpy
  import pandas
  from statsmodels.base import model
  import statsmodels.base.wrapper
  from statsmodels.tools.sm_exceptions import ConvergenceWarning
label_desc: Use image node_id 1 to create a new DimReductionResults object from inherited base classes: model with example: obj = DimReductionResults(model, params, eigs)