class_docstr: Class representing a simple nonlinear least squares model.
docstr: Sum of squares error.
  
  Returns
  -------
  sse: float
      sum of squared residuals
docstr_tok: ["Sum","of","squares","error",".","Returns","--","--","--","-","sse",":","float","sum","of","squared","residuals"]
code: def SSE(self):
      """Sum of squares error.
  
      Returns
      -------
      sse: float
          sum of squared residuals
      """
      return sum((self.Y - self.predict()) ** 2)
  
file_path: nipy/nipy/algorithms/statistics/models/nlsmodel.py
imports: import numpy
  import numpy.linalg
  from .model import Model
label_desc: Use image node_id 7 for calling the NLSModel obj's underlying member method code with example usage: obj.SSE() and returns: sum