Update the hyper-parameters for unknown mean and unknown variance.

UnknownMeanUnknownVarianceUpdate.py

def update(self,x):        
  ''' increase the number of times this socket has been used and improve the estimate of the 
      mean and variance by combining the single new value 'x' with the current estimate '''
  n = 1
  v = self.n

  self.α = self.α + n/2     
  self.β = self.β + ((n*v/(v + n)) * (((x - self.μ_0)**2)/2))

  # estimate the variance - calculate the mean from the gamma hyper-parameters
  self.v_0 = self.β / (self.α + 1)      

  self.x.append(x)  # append the new value to the list of samples 
  self.n += 1
  self.μ_0 = np.array(self.x).mean()