class_docstr: Gaussian exponential family.
  
  INPUTS:
     link      -- a Link instance
class_docstr_tok: ["Gaussian","exponential","family",".","INPUTS",":","link","--","a","Link","instance"]
docstr: Gaussian deviance residual
  
  INPUTS:
     Y     -- response variable
     mu    -- mean parameter
     scale -- optional scale in denominator (after taking sqrt)
  
  OUTPUTS: resid
     resid -- deviance residuals
docstr_tok: ["Gaussian","deviance","residual","INPUTS",":","Y","--","response","variable","mu","--","mean","parameter","scale","--","optional","scale","in","denominator","(","after","taking","sqrt",")","OUTPUTS",":","resid","resid","--","deviance","residuals"]
code: def devresid(self, Y, mu, scale=1.0):
      """
      Gaussian deviance residual
  
      INPUTS:
         Y     -- response variable
         mu    -- mean parameter
         scale -- optional scale in denominator (after taking sqrt)
  
      OUTPUTS: resid
         resid -- deviance residuals
      """
  
      return (Y - mu) / np.sqrt(self.variance(mu) * scale)
  
imports: import numpy
  from .None import links
  from .None import varfuncs
label_desc: Use image node_id 2 for calling the Gaussian obj's underlying member method code with example usage: obj.devresid(Y, mu, scale) and returns: unknown