class_docstr: The logit transform as a link function:
  
  g'(x) = 1 / (x * (1 - x))
  g^(-1)(x) = exp(x)/(1 + exp(x))
docstr: Derivative of logit transform
  
  g(p) = 1 / (p * (1 - p))
  
  INPUTS:
     p   -- probabilities
  
  OUTPUTS: y
     y   -- derivative of logit transform of p
docstr_tok: ["Derivative","of","logit","transform","g","(","p",")","=","1","\/","(","p","*","(","1","-","p",")",")","INPUTS",":","p","--","probabilities","OUTPUTS",":","y","y","--","derivative","of","logit","transform","of","p"]
code: def deriv(self, p):
      """
      Derivative of logit transform
  
      g(p) = 1 / (p * (1 - p))
  
      INPUTS:
         p   -- probabilities
  
      OUTPUTS: y
         y   -- derivative of logit transform of p
  
      """
      p = self.clean(p)
      return 1.0 / (p * (1 - p))
  
imports: import numpy
  import scipy.stats
label_desc: Use image node_id 4 for calling the Logit obj's underlying member method code with example usage: obj.deriv(p) and returns: unknown